Robotics Papers — 2026

3D Euler-Angle Orientation Control for Two-Ray Fading Mitigation in Maritime Air-to-Sea Communications

Mohammed Bajja, Abdoul Karim A. H. Saliah, Hajar El Hammouti et al. · arXiv preprint · Sep 2026

Maritime Air-to-Sea links are dominated by a line-of-sight ray and a sea-surface reflected ray whose destructive combination produces deep fades. Existing mitigation strategies optimize Unmanned Aerial Vehicle position or trajectory but leave attitude unexploited. This paper treats the full three...

control benchmark

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No code repo Sep 2026

A Confidence-Aware Multimodal Fusion Framework for Industrial Human-Robot Collaboration

Xinyu Liu, Qiqi Dong, Boya Jia et al. · arXiv preprint · Sep 2026

A confidence-aware multimodal fusion framework (CAMF) is proposed to realize reliable human intention prediction for industrial human-robot collaboration. This framework fuses four heterogeneous modalities including object 6D pose, gaze, skeletal motion and IMU-based hand motion. It embeds a conf...

human-robot-interaction

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No code repo Sep 2026

A Low-Cost, Open Platform for End-to-End Autonomous Driving on a Miniature Ackermann Vehicle

Gustavo Claudio Karl Couto, Eric Aislan Antonelo, Gabriel George Zipperer · arXiv preprint · Sep 2026

This paper presents a low-cost, open experimental platform for research in end-to-end autonomous driving with miniature Ackermann vehicles. The platform combines a physical vehicle, a printed urban track, data collection tools, trajectory registration, and a Webots digital twin, enabling controll...

vision reinforcement-learning sim-to-real planning control learning-from-demonstration

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No code repo Sep 2026

Adaptation Needs in Robotic Systems: Assessing Behavior Trees and Their Enhancement

Mehran Rostamnia, Gianluca Filippone, Ricardo Caldas et al. · arXiv preprint · Sep 2026

Robotic systems increasingly operate in dynamic, uncertain, and open-ended environments, where design-time assumptions may no longer hold, and adaptation becomes necessary to maintain effective and safe operation. Behavior Trees (BTs) are widely used in robotic control architectures due to their ...

vision planning control

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No code repo Sep 2026

Adaptive Vision-Language Grasping via Composable Foundation Priors and Generalizable Grasp Synthesis

Sixu Yan, Shikang Wang, Binhua Huang et al. · arXiv preprint · Sep 2026

This paper proposes AdaRoboVLG, a task-adaptive Vision-Language-Grasp (VLG) framework that supports generalizable grasp synthesis across different robotic hands. Unlike existing VLG methods that tightly couple foundation models with end-to-end grasp policies, AdaRoboVLG learns an efficient genera...

manipulation vision reinforcement-learning

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GitHub ★ — Sep 2026

Can People Distinguish Human and AI Agency in Humanoid Teleoperation? A Preliminary Study of Agency Perception

Xiang Li, Koya Dendo, Keigo Minamida et al. · arXiv preprint · Sep 2026

Can people distinguish between human and AI agency in humanoid teleoperation? To explore this question, we developed \textit{Ghost-in-the-Loop}, a teleoperation framework that supports both human-operated and AI-generated control of a robot's voice, facial expressions, and gestures while maintain...

vision reinforcement-learning control learning-from-demonstration

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No code repo Sep 2026

CAP: Continuously Adaptive Perception-Blind Humanoid Locomotion via Learned Denoising

Hongjin Chen, Zijun Xu, Shihao Ma et al. · arXiv preprint · Sep 2026

Humanoid locomotion across complex terrain demands forward-looking exteroception to anticipate obstacles, yet this signal is unreliable in real-world deployment, failing partially and intermittently. Existing perceptive policies often assume that depth observations remain clean and in-distributio...

locomotion vision reinforcement-learning control

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No code repo Sep 2026

CARLAverse: A Highly Modular, Distributed, and Multimodal Framework for Human-in-the-Loop Simulation

Patrick Rebling, Philipp Nenninger, Reiner Kriesten · arXiv preprint · Sep 2026

The development of autonomous driving demands comprehensive testing in mixed-traffic scenarios involving vulnerable road users (VRUs), where purely artificial agents often fail to capture authentic human social negotiations. While human-in-the-loop (HITL) simulators enable safe investigation of t...

reinforcement-learning control tactile

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No code repo Sep 2026

Catalogue Photography as a Cold Start: Toward Deployable Carbide Burr Recognition

Abilash Philip Madavath, Chandra Yuvesh Aubeeluck, Augustin Raju et al. · arXiv preprint · Sep 2026

Verifying that manufactured batches of milling tools or carbide rotary burrs conform to production order sheets remains a largely manual and error-prone quality assurance task. Automating this process with computer vision faces a critical cold-start constraint since no labelled imagery is availab...

vision reinforcement-learning benchmark

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No code repo Sep 2026

Collision Snapshot Guided Time-Reversed Safety-Critical Scenario Generation

Taehyung Kim, Jongeun Choi · arXiv preprint · Sep 2026

The generation of safety-critical traffic scenarios is essential for training and evaluating autonomous vehicles. Prior approaches typically perturb the trajectories of existing agents in a traffic scenario using simplified adversarial objectives to induce safety-critical interactions, which can ...

reinforcement-learning benchmark

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GitHub ★ — Sep 2026

Continuous Actions from Discrete Minds: Latent-Aligned Planning for End-to-End Autonomous Driving

Ruoyu Yao, Yusen Xie, Qingzhao Liu et al. · arXiv preprint · Sep 2026

Bridging the gap between the discrete reasoning of Vision-Language Models and the continuous, physics-constrained nature of autonomous driving remains a significant challenge. In this work, we introduce LaPla, a unified Vision-Language-Action (VLA) framework featuring latent-aligned planning to s...

vision vla planning benchmark

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No code repo Sep 2026

Corner Cases: Headland Coverage Path Planning for Autonomous Driving in Arable Farming

Riikka Soitinaho, Timo Oksanen · arXiv preprint · Sep 2026

This paper presents a new method for headland coverage path planning for arable fields. Several earlier approaches suggest covering the headland with nested polygons and smooth turns, however, covering the field corners entirely requires manoeuvres with reversing. In the new method, the polygon c...

reinforcement-learning planning

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No code repo Sep 2026

CougarTail & CUB: A General-Purpose Mast and Central Utility Board for Cylindrical Underwater Enclosures

Ben Washburn, Clayton Smith, Eli Gaskin et al. · arXiv preprint · Sep 2026

Cylindrical watertight enclosures are widely used across various underwater systems, from unmanned underwater vehicles (UUVs), to remotely operated vehicles (ROVs), to various sensor platforms. However, electronics are typically built on rectangular PCBs arranged in horizontal stacks, which ineff...

control

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No code repo Sep 2026

CrossDepth: Geometry-Constrained Attention for Generalizable Multi-View Surround Depth Estimation

Samer Abualhanud, Max Mehltretter · arXiv preprint · Sep 2026

Reliable 3D understanding of the surrounding environment is a core requirement for autonomous driving. Multi-view surround camera rigs provide broad scene coverage, but the spatially adjacent images typically overlap only minimally. Consequently, the depth of most pixels must be inferred from mon...

vision reinforcement-learning benchmark

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GitHub ★ — Sep 2026

Deformable Object Manipulation under Partial Observability via Real-Time Full-Shape Estimation

Kosar Behnia, Ville Kyrki, Gokhan Alcan · arXiv preprint · Sep 2026

Manipulating deformable objects (DOs) is challenging due to their high-dimensional state space, underactuated dynamics, and partial observability. In this paper, we propose cRVAE, a lightweight conditional recurrent variational autoencoder that estimates the full DO state from only partial corner...

manipulation planning control

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No code repo Sep 2026

Development of a Humanoid Robot Prototype for Multimodal Human-Robot Interaction

Thang Tran Viet, Thanh Nguyen Canh, Huy Uong Gia et al. · arXiv preprint · Sep 2026

Human-robot interaction (HRI) enables intuitive and intelligent collaboration between humans and robots in real-world environments. This paper introduces a humanoid robot prototype designed as a flexible testbed for developing and integrating artificial intelligence (AI) modules in HRI tasks. The...

manipulation vision vla reinforcement-learning control human-robot-interaction

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GitHub ★ — Sep 2026

Dynamic System Emulation: Fixed Wing Dynamics on a Multicopter

Abdelhakim Amer, Andriy Sarabakha · arXiv preprint · Sep 2026

This work presents a control framework that enables a multicopter equipped with a two-axis gimbal to emulate the flight dynamics of a fixed-wing aircraft. The goal is to provide an operationally simple platform for training and simulation that avoids the aerodynamic constraints of fixed-wing vehi...

control benchmark

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No code repo Sep 2026

EVPeriscope: Extended Perception across Aerial and Ground Vehicles with Event-based Propeller Tracking

Dexter Ong, Vijay Kumar, Pratik Chaudhari · arXiv preprint · Sep 2026

Reliable relative localization between aerial and ground robots is a key requirement for tightly coordinated heterogeneous teams. This can be difficult to do using conventional frame-based cameras and fiducial markers because they are sensitive to motion blur, lighting variations, and payload con...

vision reinforcement-learning planning control

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GitHub ★ — Sep 2026

FARM: Reading Failure Signals from the Internal Predictive States of a Frozen Robotic World Model

Haoran Pei, Mingrui Luo, Senbao Wang et al. · arXiv preprint · Sep 2026

Reliable robot deployment requires online failure monitoring, yet existing monitors mainly derive risk from proxy signals or train dedicated monitoring components. We ask whether the internal predictive states of a frozen pretrained robotic world model already contain directly decodable failure i...

vla reinforcement-learning benchmark

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No code repo Sep 2026

FIRE-LIVWO: Robust LiDAR-Inertial-Visual-Wheel Odometry via Failure-Immune mmWave Radar Enhancement

Kun Hu, Menggang Li, Kaidi Wu et al. · arXiv preprint · Sep 2026

Achieving robust SLAM in large-scale underground coal mines with complex structures and severe degeneracies remains highly challenging. Dense smoke and dust cause substantial loss of visual information and degrade LiDAR point-cloud features, while long, self-similar corridors induce geometric deg...

vision reinforcement-learning planning

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GitHub ★ — Sep 2026

FolDeX: A Physical-World Benchmark for Long-Horizon Robotic Manipulation of Deformable Objects

Chenhuan Liu, Yi Xu, Feng Wu et al. · arXiv preprint · Sep 2026

Embodied AI, including vision-language-action and world-action models, must operate reliably in the physical world. Yet methods that perform well in simulation can degrade substantially on real robots, especially in long-horizon deformable-object manipulation, where policies must track changing s...

manipulation vision vla reinforcement-learning control benchmark

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No code repo Sep 2026

Formation Matrix and Energy-based Control of Multi-Agent Systems

Martín Crespo, Sergio Junco, Matías Nacusse · arXiv preprint · Sep 2026

This paper presents an energy-based controller for a multiagent robotic system designed to achieve and maintain a specific formation while moving on a plane and avoiding collisions between agents. The controller emulates a network of elementary spring-damper modules connecting pairs of agents. Th...

control

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No code repo Sep 2026

Frame-Coded Legged Locomotion over Noisy Terrain

Lav R. Varshney · arXiv preprint · Sep 2026

Open-loop multilegged locomotion over rough terrain has been interpreted as matter transport over a noisy channel: leg-ground interactions are discrete basic active contacts, terrain deletes or perturbs those contacts, and spatial redundancy concentrates the resulting thrust and arrival time. Tha...

locomotion

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No code repo Sep 2026

GIFT: Guided Intermediate Feature Training via Action-Oriented Structural Supervision for Robotic Manipulation

Yupeng Zheng, Xiang Li, Songen Gu et al. · arXiv preprint · Sep 2026

Vision-language pre-training and predictive world modeling provide robot policies with rich semantic and dynamic visual features, but their native action and visual-prediction objectives may omit critical physical and task structure while retaining control-irrelevant visual redundancy. We call th...

manipulation vision vla reinforcement-learning control

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No code repo Sep 2026

HaWMPO: Hallucination-Aware World Model-based Policy Optimization for Generalist Robot Policy

Zengjue Chen, Peidong Liu, Jiawei Li et al. · arXiv preprint · Sep 2026

Generalist robot policies have demonstrated strong generalization across robotic manipulation tasks, yet their success rates remain limited in com- plex long-horizon scenarios. Recent methods improve Visual-Language-Action (VLA) policies through online reinforcement learning on real robots, but s...

manipulation vision vla reinforcement-learning benchmark

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No code repo Sep 2026

JEPA Policy: Diffusion-Free Imitation Learning via Paired Action and Future Representation Prediction

Jie Xu, Kangjin Yu, Ziyi Jin et al. · arXiv preprint · Sep 2026

Standard behavior cloning supervises actions without explicitly constraining the future representation paired with each demonstrated action chunk. We introduce JEPA Policy, a diffusion-free framework that uses the action chunk and its observed future representation as paired training targets. Act...

vision reinforcement-learning control learning-from-demonstration

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GitHub ★ — Sep 2026

Knowledge-Guided Hierarchical Policy Learning for High-Precision Cylindrical Assembly under Tight Tolerances

Binbin Lian, Xinyu Liu, Tao Sun · arXiv preprint · Sep 2026

A hybrid hierarchical learning framework is proposed to achieve high-precision assembly of 170mm cylindrical components with tolerance of 0.1mm. The lower-level network integrates expert experience through Behavior Cloning (BC), giving the robot human-like intuition, and incorporates the Twin Del...

reinforcement-learning learning-from-demonstration

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No code repo Sep 2026

LANTERN: A Closed-Loop Benchmark for VLM-Based Cooperative Driving with Temporally Grounded Warnings

Yongshuo Liu, Xu Gao, Morui Zhu et al. · arXiv preprint · Sep 2026

We present LANTERN, a closed-loop benchmark for temporally grounded cooperative warnings. LANTERN separates warning onset, hazard onset, warning termination, and post-hazard recovery, and evaluates each physical event under matched warning and no-warning executions so that the warning's contribut...

vision vla control benchmark

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No code repo Sep 2026

Learning Agent-based Model Predictive Control for Holistic Vehicle Performance

Jiaming Zhong, Reza Valiollahi Mehrizi, Mohammad Pirani et al. · arXiv preprint · Sep 2026

Agent-based model predictive control (AMPC) has recently been proposed as a distributed scheme that collaborates with all agents to achieve optimal holistic performance. However, its optimality highly depends on the prediction accuracy that requires all agents or their contributions to be known, ...

control

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No code repo Sep 2026

Learning Terrain-Adaptive Humanoid Locomotion on Granular Terrain

Junnosuke Kamohara, Feiyang Wu, Andy Ningan Zong et al. · arXiv preprint · Sep 2026

Humanoid locomotion on granular terrain remains a significant challenge due to its complex foot-terrain interaction dynamics that are difficult to model. Existing approaches either ignore granular contact dynamics or incorporate simplified normal force models with heuristic tangential components....

locomotion reinforcement-learning control learning-from-demonstration

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No code repo Sep 2026

Memory as Plans: World-Action Modeling with Memory-Grounded Planning

Sizhe Zhao, Haozhe Xie, Weiyu Zhao et al. · arXiv preprint · Sep 2026

Mainstream robotic policies often adopt a Markovian formulation, but many complex real-world manipulation tasks are inherently non-Markovian, requiring long-horizon memory beyond the current observation. Existing memory mechanisms often rely on language summaries, growing visual windows, or their...

manipulation vision reinforcement-learning planning

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No code repo Sep 2026

Odometer-Agnostic Drift Correction Using OpenStreetMap Lane Geometry

Joaquin Caballero, Emilio Garcia-Fidalgo, Alberto Ortiz et al. · arXiv preprint · Sep 2026

Despite significant progress in odometry estimation, long-term drift remains a fundamental limitation of incremental pose integration, especially in large-scale or loop-free environments. Existing map-assisted methods can reduce drift, but often depend on dense maps, sensor-specific processing, o...

vision reinforcement-learning

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No code repo Sep 2026

ORCH: Organizational Principles Enable Collective Intelligence in Embodied AI

Zhengran Ji, Jonathan Hyun, Boyuan Chen · arXiv preprint · Sep 2026

Collective intelligence depends not only on the capabilities of individual members, but also on how those members are organized. Yet artificial multi-agent systems are typically assembled using fixed organizational structures, even when the physical tasks they perform impose fundamentally differe...

reinforcement-learning

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No code repo Sep 2026

OVMAN: A Task and Benchmark for Open-Vocabulary Motion-Aware Navigation

Dibyendu Ghosh · arXiv preprint · Sep 2026

Homes change between a robot's visits. Navigation benchmarks pose their goals in the world the agent currently sees, and the two-visit benchmarks that exist score recall or rearrangement rather than navigation. None of them can express go to the chair that was moved or go to where the vase used t...

reinforcement-learning planning benchmark

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No code repo Sep 2026

Quasi-static analysis of passive stability in a novel underactuated multi-finger hand

Léonie Plancoulaine, Sylvain Guégan, Franck Plestan et al. · arXiv preprint · Sep 2026

Underactuated robotic hands achieve adaptive and robust grasping with a reduced number of actuators, but predicting the stable equilibrium pose of the grasped object remains a significant challenge. This paper introduces a quasi-static analytical approach to assess passive stability in underactua...

manipulation

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No code repo Sep 2026

Rapid Learning of Dexterous In-Hand Pen Writing through Real-Time Jacobian Estimation

Kai Stewart, Yasunori Toshimitsu, Robert K. Katzschmann · arXiv preprint · Sep 2026

Dexterous in-hand manipulation of a grasped object with an anthropomorphic hand is an unsolved frontier for robot dexterity. The contact-richness and highly dynamic nature of object-hand interactions tend to require extensive modeling or data-collection efforts for learning-based approaches. Mode...

manipulation reinforcement-learning control learning-from-demonstration

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GitHub ★ — Sep 2026

Reflex-Informed Neuromuscular Reinforcement Learning for Muscle-Driven Locomotion

Jian Zhou, Xingyu Zhang, Rui Ma et al. · arXiv preprint · Sep 2026

Muscle-driven locomotion provides a physically grounded approach to generating realistic human movement. However, achieving both physiological plausibility and adaptability to changes in musculoskeletal capacity and external disturbances remains a fundamental challenge. To address this limitation...

locomotion reinforcement-learning control

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No code repo Sep 2026

RoboSPA: Can VLA Models Go Beyond Simple Scenes and Short-Horizon Tasks?

Zhenxuan Fan, Bo Zhang, Yutong Lin et al. · arXiv preprint · Sep 2026

Vision-Language-Action (VLA) models have shown promising progress in language-conditioned robotic manipulation. However, existing datasets and benchmarks mainly evaluate task completion under predefined settings, offering limited insight into model reasoning under increasing spatial and procedura...

manipulation vision vla planning benchmark

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GitHub ★ — Sep 2026

Safety-aware Skill Adaptation for Reinforcement Learning in Dynamic Environments

A K M Nadimul Haque, Sheila Sutjipto, Marc G. Carmichael et al. · arXiv preprint · Sep 2026

Skill adaptation frameworks based on reinforcement learning often require restrictive assumptions to maintain stability, such as fixed observations or tightly controlled exploration schedules. In cluttered and dynamic environments, however, unrestricted exploration can lead to unsafe behaviour an...

manipulation reinforcement-learning control

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No code repo Sep 2026

Same Trajectory, Contradictory Rewards (ROBORMBENCH): Paraphrase Fragility in Vision Language Reward Models

Wonje Jeung, Sangyeon Yoon, Hyesoo Hong et al. · arXiv preprint · Sep 2026

Vision-language models are increasingly used as reward functions for robotic learning, but this role requires paraphrase invariance: the same trajectory should receive the same reward under semantically equivalent goal descriptions. We show that current VLM reward models often violate this proper...

vision vla benchmark

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No code repo Sep 2026

SEED-UMI: Sharing the Exoskeleton between human and robot for onE-to-one Dexterous demonstration

Tengbo Yu, Jiahao Wu, Daohan Li et al. · arXiv preprint · Sep 2026

Imitation learning for dexterous hands is bottlenecked by the difficulty of collecting contact-rich demonstrations that transfer faithfully to the robot. Prior wearable-exoskeleton systems record only on the human side and retarget via open-loop mappings calibrated in free space, which degrade un...

manipulation vision reinforcement-learning learning-from-demonstration

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GitHub ★ — Sep 2026

Subspace Inference Enables Efficient Active Reward Learning from Preferences

Yutai Zhou, Erdem Bıyık · arXiv preprint · Sep 2026

Reinforcement learning from human feedback (RLHF) has emerged as a powerful yet sample-inefficient approach for learning reward models from human preferences, making active learning a critical component in synthesizing informative preference queries. However, effective uncertainty quantification ...

reinforcement-learning benchmark

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GitHub ★ — Sep 2026

SwingBot: Learning Whole-Body Brachiation for Humanoid Robots

Yujie Xiong, Peng Zhai, Taixian Hou et al. · arXiv preprint · Sep 2026

Brachiation enables primates to move across overhead supports when ground paths are blocked, suggesting a complementary locomotion mode for robots operating in cluttered or hazardous environments. Bringing this capabil?ity to high-DoF humanoid robots is difficult because the controller must disco...

locomotion reinforcement-learning control

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No code repo Sep 2026

\textbf{PLATO}: \emph{Preintegration Learning from Accurate Trajectory Observations} for Neural Inertial Odometry

Haoying Li, Qihang Liu, Yifan Peng et al. · arXiv preprint · Sep 2026

Neural inertial odometry has demonstrated strong potential for motion estimation in challenging environments, yet inertial-only preintegration remains sensitive to IMU bias and uncertainty. To this end, this paper introduces \textbf{PLATO}:~\emph{Preintegration Learning from Accurate Trajectory O...

vision

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No code repo Sep 2026

Towards Neuro-Symbolic Procedural Reasoning for Long-Horizon Vision-Language-Action Manipulation

Vivek Chavan, Yahuan Shi, Oliver Heimann et al. · arXiv preprint · Sep 2026

Vision-language-action (VLA) models can execute short manipulation skills, but remain brittle in long-horizon procedures requiring persistent task state, dependency-aware reasoning, conditional decisions, and reliable grounding. We investigate a neuro-symbolic framework that combines learned VLA ...

manipulation vision vla reinforcement-learning control learning-from-demonstration

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No code repo Sep 2026

UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modeling

Wei Li, Rui Shao, Jie He et al. · arXiv preprint · Sep 2026

Recent advances in Vision-Language-Action (VLA) models have improved robotic manipulation, yet observation-to-action learning remains limited by a fundamental transition realizability gap, manifested in three tightly coupled problems: (i) Transition ambiguity. Visually similar current observation...

manipulation vision vla reinforcement-learning

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GitHub ★ — Sep 2026

Using Automated Vehicles Operational Data to Confirm Safety and Anticipate Threats

Riccardo Donà, Espedito Rusciano, Germana Trentadue et al. · arXiv preprint · Sep 2026

European Union (EU) policymakers adopted revolutionary data collection provisions for Automated Driving Systems (ADS) in the recently approved regulation that allows driverless vehicles to be operated on public roads. The framework is inspired by best practices developed at the United Nations Eco...

vision reinforcement-learning

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No code repo Sep 2026

Visual-SLAM for the detection of hidden tomatoes in greenhouses by Hierarchical Localization and GLOMAPfor robotized harvesting

Fernando Cañadas-Aránega, José C. Moreno, José L. Blanco-Claraco et al. · arXiv preprint · Sep 2026

Advanced crop monitoring inside greenhouses is becoming one of the primary objectives of research centers. High-performance sensors, such as LiDAR or stereo cameras, have traditionally been employed for this purpose, though these often have a high cost. This work proposes a Visual-SLAM system usi...

vision planning

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GitHub ★ — Sep 2026

VLA-Corrector: Stage-Aware Observable State Understanding for Prompt-Based Closed-Loop Recovery of Vision-Language-Action Policies

Chang Song, Bin Qian, Yan Feng et al. · arXiv preprint · Sep 2026

Long-horizon robot manipulation with Vision-Language-Action (VLA) policies remains vulnerable to execution-time deviations, as final task success provides little information for diagnosing and correcting failures caused by action noise, object displacement, or goal misalignment. We introduce a st...

manipulation vision vla reinforcement-learning benchmark

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No code repo Sep 2026

What Matters, When? Diagnosing and Improving Conditional Visual Grounding in Visuomotor Imitation Policies

Vivek Chavan, Pengtao Xie, Yahuan Shi et al. · arXiv preprint · Sep 2026

Visuomotor imitation policies can achieve high performance under in-distribution visual conditions yet fail when visually similar objects or receptacles are introduced. We study this behavior as a problem of conditional visual grounding: the visual target required for successful control changes w...

manipulation vision vla reinforcement-learning control

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No code repo Sep 2026

A Browser-Native Digital Test Range for Benchmarking 4D Ocean-Glider Planning Algorithms

Edward Holmberg, Elias Ioup, Mahdi Abdelguerfi · arXiv preprint · Aug 2026

Repeated in-situ evaluation of ocean-glider planners requires scarce vehicles, operators, deployment and recovery resources, and ocean conditions that cannot be reset for competing algorithms. We present a guided, installation-free browser-native digital test range that transforms a selected regi...

reinforcement-learning planning control benchmark

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No code repo Aug 2026

A Master-Salve Robot Manipulator for Needle-Based Teleoperation in MRI Chamber

Omar Curiel, Jing-Yuan Huang, Po-Chih Chen et al. · arXiv preprint · Aug 2026

We present a MR safe, master-slave robot manipulator for abdominal interventions in the MRI chamber. A human operated 2+1-DoF master controller manipulator transmits motion and force to a 2+1-DoF slave manipulator via fluid transmission. Jointly, a digital master controller provides multimodal co...

control learning-from-demonstration

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No code repo Aug 2026

Attention from Action, for Action: Emergent Visual Bottlenecks for Policy Learning

Zheyu Zhuang, Ruiyu Wang, Nick Heppert et al. · arXiv preprint · Aug 2026

Visual bottlenecks that focus policy inputs on regions of interest (ROIs) can improve data-efficient visuomotor learning by separating where to look from how to act. Many ROI interfaces rely on external spatial labels, such as gaze, object classes, or affordance annotations. Label-free alternativ...

vision reinforcement-learning control

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No code repo Aug 2026

CLAP: Cross-Embodiment Video World Models are Zero-Shot Physical Simulators

Kechen Liu, Ola Shorinwa · arXiv preprint · Aug 2026

State-of-the-art action-conditioned video models are typically restricted to a single robot embodiment, preventing them from leveraging the vast corpus of heterogeneous video data that contains rich signals for learning generalizable physics. To bridge this gap, we introduce CLAP, a framework for...

reinforcement-learning

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GitHub ★ — Aug 2026

ContactGuard: Pre-Contact Execution Monitoring with Action-Conditioned Latent World Models

Gehan Zheng, Matthew Johnson-Roberson, Weiming Zhi · arXiv preprint · Aug 2026

Contact-rich manipulation failures are often detected only after the robot has committed to contact. This is especially limiting in wrist-camera setups: close gripper--object views help observe contact, but a poor approach may already push, miss, slip, or disturb the object before conventional de...

manipulation vision reinforcement-learning

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No code repo Aug 2026

Control-Informed Constraint Adaptation in Minimum-Time Trajectory Planning for Autonomous Racing

Ann-Kathrin Schwehn, Alexander Langmann, Mattia Piccinini et al. · arXiv preprint · Aug 2026

Autonomous racecars operate at the limits of vehicle dynamics, where small control errors translate into safety-critical behavior and lost performance. Trajectory planners assume perfect tracking and remain blind to execution errors. To guarantee safety, trajectory planners therefore restrict the...

planning control

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No code repo Aug 2026

CORAL: Curriculum-Optimized Reward Adaptation for LiDAR-Based Goal-Directed Urban Driving

Anisa Saleem, Duksu Kim · arXiv preprint · Aug 2026

Reinforcement learning is promising for autonomous urban driving, but long-horizon goal-directed navigation asks a policy to acquire several competing behaviors at once--reaching a distant goal, tracking a route, avoiding obstacles, obeying signals--and a fixed objective gives no order in which t...

reinforcement-learning planning benchmark

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No code repo Aug 2026

DART-S: Reachability-Audited Active-Suspension Preconditioning for Off-Road Vehicle Jumps

Yu Hu, Fangzhou Zhao, Liang Chen et al. · arXiv preprint · Aug 2026

Airborne torque reaction cannot recover takeoff errors beyond the wheel angular-momentum budget. DART-S applies ramp-face suspension preconditioning to change pitch, pitch rate, and wheel spin before liftoff, thereby shifting the queried state and altering the remaining authority budget. To predi...

reinforcement-learning tactile

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GitHub ★ — Aug 2026

Decoding Task Progress from VLA Representations

Atiksh Bhardwaj, Edward Weiyi Duan, Prithwish Dan et al. · arXiv preprint · Aug 2026

Vision-language-action models (VLAs) are moving rapidly towards deployment as general-purpose manipulation policies, but we currently lack basic tools for understanding what these models represent internally or for monitoring them at runtime. Leveraging ideas from mechanistic interpretability, we...

manipulation vision vla reinforcement-learning control

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No code repo Aug 2026

DECOWAM: Decoupled Whole-Body World-Action Model for Legged Mobile Manipulation

Siyuan Ma, Boshi Zhang, Yutian Zhang et al. · arXiv preprint · Aug 2026

Mobile manipulation requires a robot to predict how locomotion and arm motion jointly alter future observations and control. Existing world-action models, developed largely for fixed-base platforms, do not explicitly distinguish camera ego-motion from base and arm actions. Here we introduce DECOW...

manipulation locomotion vision reinforcement-learning control benchmark

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No code repo Aug 2026

Deliberate Practice: Learning Robot Skills under a Budget

Shivam Vats, Sudarshan Harithas, Mete Tuluhan Akbulut et al. · arXiv preprint · Aug 2026

We consider the problem of autonomously learning robot skills under a limited practice budget for sequential tasks. We propose an active skill learning algorithm, \emph{Deliberate Practice (DP)}, that computes a provably \emph{budget-optimal} allocation---practicing skills that maximize expected ...

manipulation reinforcement-learning planning

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No code repo Aug 2026

Design and Evaluation of a Touchscreen-Based Teleoperation Interface for Robotic Manipulators

Juan José García Cárdenas, Alperen Kenan, Hamidreza Raei et al. · arXiv preprint · Aug 2026

Intuitive teleoperation interfaces are crucial for the safe and effective operation of robotic manipulators in challenging environments. In the nuclear industry, surface contact tasks such as swab sampling require precise path and force tracking, obstacle avoidance, and sustained operator attenti...

manipulation vision reinforcement-learning control learning-from-demonstration tactile benchmark

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No code repo Aug 2026

DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation

DreamX Team, Rui Chen, Xiangxiang Chu et al. · arXiv preprint · Aug 2026

We present \textbf{DreamX-Phi 1.0}, an action-conditioned video world model for robotic manipulation that, given an observed frame, a language instruction, and a prescribed action sequence comprising end-effector poses and gripper states, predicts the resulting future observations. Yet realism al...

manipulation reinforcement-learning control

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No code repo Aug 2026

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation

Junfeng Li, Junjie He, Zhide Zhong et al. · arXiv preprint · Aug 2026

Vision-Language-Action (VLA) models have become a powerful paradigm for robot manipulation, but training a single generalist policy for heterogeneous robot embodiments remains an open problem. Existing methods have two main limitations. First, they underuse dynamics priors shared across diverse v...

manipulation vision vla reinforcement-learning control benchmark

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No code repo Aug 2026

Effect of Twisted-Yarn Architecture on Pressure and Proximity Sensing Characteristics of Textile Capacitive Sensors for Robotic Skin

Ishtia Zahir, Eslam Saleh, Maryam Rezayati et al. · arXiv preprint · Aug 2026

Textile-integrated capacitive sensors offer flexible and conformable tactile sensing for wearable electronics and human-robot interaction; however, the influence of yarn-level architecture on capacitive transduction characteristics remains insufficiently quantified. This work presents a textile c...

vision reinforcement-learning human-robot-interaction tactile

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No code repo Aug 2026

Embodied Scene Rearrangement Planning

Canzhi Chen, Zan Wang, Siqi Zhu et al. · arXiv preprint · Aug 2026

This paper introduces Embodied Scene Rearrangement Planning (ESRP), a novel task requiring embodied agents to rearrange furniture in 3D scenes to match a target configuration using only egocentric observations and a top-down target layout. Unlike prior rearrangement tasks, ESRP precludes global s...

vision reinforcement-learning planning benchmark

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GitHub ★ — Aug 2026

Ensuring Safe Physical AI in Urban Mobility via Hazard-Informed Synthesized Envelopes

Alexei Odinokov, Rostislav Yavorskiy · arXiv preprint · Aug 2026

As heterogeneous robotic systems deploy across diverse urban zones, maintaining safety amid complex human-robot interactions remains a critical challenge. We present a unified framework that bridges systematic hazard analysis and runtime enforcement using hazard-informed safety envelopes. Rather ...

reinforcement-learning human-robot-interaction

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No code repo Aug 2026

ErgoSurf: Ergodic Control for the Coverage of Unknown Surfaces

Stefan Schneyer, Timo Bachmann, Maged Iskandar et al. · arXiv preprint · Aug 2026

Contact-centric tasks on surfaces, ranging from inspection and cleaning to sanding and polishing, require robots to systematically cover the surface while maintaining stable contact. Ergodic control generates trajectories that spend time at a location proportional to a desired, task-specific spat...

vision reinforcement-learning planning control tactile

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No code repo Aug 2026

Evidence-Gated Task and Motion Planning with Vision-Language Models

Tsunehiko Tanaka, Matthew Stephenson, Alistair Macvicar et al. · arXiv preprint · Aug 2026

Robots executing long-horizon manipulation tasks from natural-language instructions must reason about both semantic task structure and geometric feasibility. However, under partial observability, the availability of goal-relevant objects may be uncertain. In such cases, approaches that combine Vi...

manipulation vision vla reinforcement-learning planning

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No code repo Aug 2026

Expected Free Energy-based Informative Path Planning for Robotic Mars Exploration

Ajith Anil Meera, Pablo Lanillos, Wouter Kouw · arXiv preprint · Aug 2026

An autonomous robot efficiently exploring an unknown environment, such as looking for water sources on Mars, faces two simultaneous demands: building an accurate information map while quickly finding the regions of greatest value, and paying for every meter of travel and the cost of every measure...

planning

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No code repo Aug 2026

FlashVLA: Streaming Action Decoding for Fast and Asynchronous VLA Inference

Zekai Li, Jiaming Tang, Zhijian Liu · arXiv preprint · Aug 2026

Vision-Language-Action (VLA) models are increasingly promising for robotic manipulation, yet their real-world deployment remains bottlenecked by high inference latency and unstable asynchronous execution. This challenge is particularly pronounced in flow-matching-based VLA models, where action de...

manipulation vision vla reinforcement-learning control

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GitHub ★ — Aug 2026

GeniWorld: A Generalizable Interactive World Model for Robotic Manipulation via Visual Actions

Chenghao Gu, Hanyang Yu, Jingbo Zhang et al. · arXiv preprint · Aug 2026

Generalist robot policies exhibit strong capabilities, but their robustness in complex and unseen environments remains limited. Scaling robot learning and evaluation in diverse real-world environments remains costly and challenging. Action-conditioned world models offer a promising alternative, b...

manipulation vision reinforcement-learning control learning-from-demonstration benchmark

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No code repo Aug 2026

HumanTracker: Towards Comprehensive and Human-Aligned Motion Tracking Benchmark

Dairu Liu, Zekun Qi, Jiayu Zeng et al. · arXiv preprint · Aug 2026

Humanoid motion tracking is central to teleoperation and whole-body imitation, yet evaluation often disagrees with what people perceive in videos. Kinematic errors average per-frame pose differences but miss the physical artifacts that matter most, particularly unstable support and incorrect cont...

reinforcement-learning learning-from-demonstration tactile benchmark

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GitHub ★ — Aug 2026

Marine Autonomous Vehicle Fleet Scheduling to Maximise Scientific Impact

Mehdi El Krari, Jonathan Smith, Maria Fox · arXiv preprint · Aug 2026

The marine science community increasingly relies on Marine Autonomous Vehicles (MAVs) to collect the critical environmental data required to understand global ocean systems. However, as these operations scale, manually routing and planning large autonomous fleets becomes exponentially complex and...

vision reinforcement-learning planning

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No code repo Aug 2026

Mind the Context: Continual Learning of Socially Appropriate Robot Actions via Environmental-Social Disentanglement

Rafal Robert Karpinski, Fethiye Irmak Dogan, Nikhil Churamani et al. · arXiv preprint · Aug 2026

Social robots are expected to operate across diverse environments, where similar arrangements can imply different socially appropriate actions, e.g., starting a conversation may be acceptable in a crowded home but disruptive in an office meeting. Because such norms and environments cannot all be ...

human-robot-interaction

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GitHub ★ — Aug 2026

Planning-Oriented End-to-End Autonomous Driving: Architectures, Evaluation, and Emerging Paradigms

Yanchen Guan, Xingcheng Liu, Bin Rao et al. · arXiv preprint · Aug 2026

End-to-end autonomous driving has evolved from camera-to-control regression toward planning-oriented systems that use structured representations, trajectory-level outputs, and increasingly realistic evaluation protocols. This survey reviews this transition across behavior cloning, conditional imi...

vision vla reinforcement-learning planning control learning-from-demonstration benchmark

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Reflex: Enabling Fast and Predictive Vision-Language-Action Models for Reaction-Critical Manipulation

Yuxuan Chen, Wanruo Zhang, Xiao Li · arXiv preprint · Aug 2026

Vision-Language-Action (VLA) models have recently achieved promising performance in robotic manipulation. However, existing benchmarks mainly evaluate generalization on static manipulation tasks and largely overlook dynamic interaction scenarios. To address this gap, we present ReflexBench, a ben...

manipulation vision vla reinforcement-learning control benchmark

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GitHub ★ — Aug 2026

Robot Learning from Human Demonstrations: Handwritten Alphabet Trajectories and Human-Likeness Evaluation

Alperen Kenan, Paul Bremner, Manuel Giuliani · arXiv preprint · Aug 2026

Learning from demonstration (LfD) provides a developmental framework through which robots can develop motor skills by observing and imitating human dynamics, reducing reliance on explicit programming to teach a skill to a robot. The resulting human-like robot motion is recognised as a key factor ...

human-robot-interaction learning-from-demonstration tactile benchmark

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GitHub ★ — Aug 2026

Spatiotemporal Tube-Based Safety-Certificate for Autonomous Navigation of Articulated Vehicles

Mohd. Faizuddin Faruqui, Ratnangshu Das, Ravi Kumar L et al. · arXiv preprint · Aug 2026

Articulated vehicles are the workhorses of freight transportation, and their autonomous navigation is challenging. Their physical characteristics and motion constraints pose significant challenges in manoeuvring these vehicles on narrow routes. This paper presents a spatiotemporal tube-based appr...

planning

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STEP: State-Aware Task Estimation and Planning with Multi-Modal LLMs for Human-Robot Collaboration

Maitrey Gramopadhye, Prakash Baskaran, Xiao Liu et al. · arXiv preprint · Aug 2026

Effective human-robot collaboration in industrial settings requires robots to understand human intentions and assist with task planning, reducing workload. Recent works have explored the use of Multi-modal Large Language Models (MM-LLMs) for task planning in such data-scarce scenarios, leveraging...

vla planning

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No code repo Aug 2026

TADP: Task-Aware Deformable Prediction for Single-Stage 3D Object Detection

Su Wang, Yaochen Li, Min Yang et al. · arXiv preprint · Aug 2026

Most single-stage 3D object detectors complete different tasks with the same extracted features. Nevertheless, it is impossible to project features into a common space that is adaptive for all the tasks. We present a novel task-aware deformable prediction (TADP) method for single-stage 3D object ...

vision benchmark

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No code repo Aug 2026

Task-space model-based control of pneumatic soft actuators

Nithin S. Kumar, Joshua Gaston, D. Caleb Rucker et al. · arXiv preprint · Aug 2026

Soft actuators enable dexterous and compliant interaction, but closed-loop task-space control remains challenging due to strong nonlinearities, distributed deformation, and uncertainty in their dynamics. This paper presents a real-time dynamic-model-based task-space feedback and estimation framew...

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Tensegrity Continuum Robots Enable Task-Adaptive Morphologies for Cooperative Behaviors

Mahmud Hasan Saikot, Sydney Spiegel, Sudheera Akalanka Kariyawasam et al. · arXiv preprint · Aug 2026

Robots that can change their morphologies and behaviors for different tasks and environments hold great promise for adaptable, multifunctional systems. Modular reconfigurable robots (MRRs) can achieve such functionalities by docking and rearranging individual units, but most rely on rigid modules...

manipulation locomotion reinforcement-learning

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No code repo Aug 2026

THRIVE: Therapeutic Humanoid Robot In Virtual Environment

Jin Xu, Yu-Ping Chen, Ayanna Howard · arXiv preprint · Aug 2026

This paper presents THRIVE (Therapeutic Humanoid Robot In Virtual Environment), an at-home rehabilitation platform that integrates a suite of virtual-reality upper-body rehabilitation games, a real-time camera-based motion-tracking system, and a socially interactive robot therapist. The system is...

manipulation vision reinforcement-learning human-robot-interaction

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No code repo Aug 2026

Towards Professional Tennis Styles for Humanoid Robots with Adaptive Motion Planning and Tracking

Tao Huang, Ruofei Liu, Xuchen Tang et al. · arXiv preprint · Aug 2026

Humanoid robots have recently demonstrated promising capabilities in real-world ball sports. However, achieving professional motion styles while maintaining strong task performance remains challenging. In this work, we propose AdaPT, an Adaptive Motion Planning and Tracking framework that learns ...

vision reinforcement-learning sim-to-real planning

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GitHub ★ — Aug 2026

Towards Surgical World-Action Modeling: A Preliminary Joint Visual-Trajectory Forecasting for Surgical Motion Planning

Weiliang Huang, Huanrong Liu, Bob Zhang et al. · arXiv preprint · Aug 2026

Reliable surgical planning requires models to anticipate not only how instruments will move, but also how the operative visual state will evolve together with such motion. Existing approaches typically treat future scene generation and instrument trajectory prediction as two separate tasks. Scene...

vision reinforcement-learning planning benchmark

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GitHub ★ — Aug 2026

Video2DoorTraversal: Push Door Traversal via Simulated Door Twins

Xincheng Tang, Yiji Chen, Youhan Xie et al. · arXiv preprint · Aug 2026

Door opening and traversal is a long-horizon loco-manipulation task that requires precise handle interaction and coordinated base-arm control. We present Video2DoorTraversal, a single-video real-to-sim-to-real framework for wheel-legged mobile manipulators. Given one RGB video of a real door, Doo...

manipulation locomotion vision reinforcement-learning sim-to-real control learning-from-demonstration

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No code repo Aug 2026

VIDP: Variable Impedance Diffusion Policy for Compliant Robot Manipulation from Diverse Demonstrations

Hisham Khalil, Neil Fernandes, Thomas M. Kwok et al. · arXiv preprint · Aug 2026

Contact-rich manipulation requires precise tracking and mechanical compliance, where variable impedance control can improve robustness in task success, whereas static compliance cannot adapt to varying contact constraints. Variable impedance skills can be learned from demonstrations, avoiding com...

manipulation reinforcement-learning control learning-from-demonstration

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Wave-Based Bilateral Teleoperation between Nonlinear Manipulators with Direct Contact Force Feedback

G. Q. Bao Tran, Takanori Miyoshi, Ho Duc Tho · arXiv preprint · Aug 2026

We study bilateral teleoperation between nonlinear, multi-DOF robotic manipulators in the presence of constant communication delays. Unlike classical wave-transformation architectures that transmit a coordinating force, we consider the case where the environmental force is reflected to the master...

learning-from-demonstration

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No code repo Aug 2026

$ω$-0: A Latent Predictive World Action Model for Concurrent Humanoid Loco-Manipulation

Zhe Li, Zhenzhe Zhang, Yangyang Wei et al. · arXiv preprint · Aug 2026

Humanoid household tasks often require concurrent loco-manipulation, where the robot must move, adjust posture, maintain balance, and manipulate objects as a single coordinated behavior. Yet existing humanoid policies typically decompose locomotion and manipulation, while recent world-action mode...

manipulation locomotion vision vla reinforcement-learning control learning-from-demonstration benchmark

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A New Human-Likeness and Comfort Index for Robot Movements Along Prescribed Paths

Rosanna Coccaro, Enrico Ferrentino, Antonio Parziale et al. · arXiv preprint · Jul 2026

As human-robot interaction rapidly spreads in numerous fields, the subject of robot acceptance gains increasing importance. Visual similarity to the human body, as occurs for humanoids, is generally not enough to ensure acceptance in physical interaction, as acceptance directly links to comfort a...

vision control human-robot-interaction

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No code repo Jul 2026

Actuator Reality Shaping for Zero-Shot Sim-to-Real Robot Learning

Satoshi Yamamori, Koji Ishihara, Kentaro Minamikawa et al. · arXiv preprint · Jul 2026

Sim-to-real transfer in robot learning is often limited by discrepancies between the ideal actuator dynamics assumed during policy training and the nonlinear, hardware-dependent be...

ar-vr humanoid locomotion

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No code repo Jul 2026

AHEAD: Anticipatory Hand-Driven Teleoperation via Human Intent Prediction

Seok Joon Kim, Junho Lee, Federica Spinola et al. · arXiv preprint · Jul 2026

Direct hand-driven teleoperation maps an operator's hand motion to robot end-effector commands at every frame, enabling precise control, but it requires constant monitoring and correction during approach, grasp, and placement, which can be slow and fatiguing. For repetitive pick-and-place tasks, ...

manipulation reinforcement-learning planning control learning-from-demonstration

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No code repo Jul 2026

ARDY: Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation

Kaifeng Zhao, Mathis Petrovich, Haotian Zhang et al. · arXiv preprint · Jul 2026

Generating realistic 3D human motions in real-time within interactive applications is key for animation, simulation, and humanoid robotics. While recent offline motion generation approaches offer precise control via text and kinematic constraints, they lack the inference speed required for intera...

locomotion reinforcement-learning control benchmark

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No code repo Jul 2026

Assessing Physical Frailty and Fall-Risk Indicators with Social Robots: An in situ Evaluation with Older Adults

Aniol Civit, Antonio Andriella, Alba Martínez et al. · arXiv preprint · Jul 2026

Frailty assessments are crucial to evaluate the risk of adverse events and the health and social care needs of older adults, yet their administration remains resource-intensive and typically relies on coarse clinical outcomes, such as task completion times, which may overlook biomechanical indica...

vision reinforcement-learning human-robot-interaction benchmark

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No code repo Jul 2026

AXIS: A Growable Community-Driven Data Engine for Scalable Robot Manipulation

Mengfei Zhao, Dihong Huang, Yikai Tang et al. · arXiv preprint · Jul 2026

Learning effective robot manipulation policies requires diverse, high-quality demonstrations, yet existing data pipelines are often difficult to scale because they rely on specialized hardware, centralized operators, or fixed task suites. We present AXIS, a growable community-driven data engine a...

manipulation vision vla learning-from-demonstration benchmark

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No code repo Jul 2026

BadWAM: When World-Action Models Dream Right but Act Wrong

Qi Li, Xingyi Yang, Xinchao Wang · arXiv preprint · Jul 2026

World-action models (WAMs) are emerging as a promising foundation for embodied control: rather than predicting actions alone, they learn representations that couple action generation with future world prediction. This coupling is often viewed as a source of robustness, interpretability, and safet...

vision reinforcement-learning control

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No code repo Jul 2026

Beyond Episodic Evaluation: Memory Architectural Bottlenecks in Sequential Embodied Question Answering

Zikui Cai, Kaushal Janga, Tan Dat Dao et al. · arXiv preprint · Jul 2026

Embodied question answering (EQA) is traditionally evaluated under an episodic formulation, where agents solve each task independently and reset internal state between episodes. However, real-world robots operate continuously and must accumulate, retain, and selectively reuse information acquired...

vision reinforcement-learning planning benchmark

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No code repo Jul 2026

Catch, Throw, Repeat: Planning for Human-Robot Partner Juggling

Jonathan Rainer Lippert, Kai Ploeger, Abir Chowdhury et al. · arXiv preprint · Jul 2026

Dynamic object exchange between humans and robots remains a challenging problem due to uncertainty in perception, timing, and contact-rich interaction. Human-robot juggling represents a particularly demanding instance of this problem, requiring precise real-time coordination, predictive motion pl...

vision reinforcement-learning planning control human-robot-interaction

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No code repo Jul 2026

Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections

Gil Lifshits, Igal Bilik, Gilad Katz · arXiv preprint · Jul 2026

Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, which typically struggle with combinatorial action spaces, reliance on privileged information, or rigid agent designs. We propose Master-Agent Proto-p...

reinforcement-learning planning control benchmark

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No code repo Jul 2026

ContactMimic: Humanoid Object Interaction via Contact Control

Xinyao Li, Xialin He, Runpei Dong et al. · arXiv preprint · Jul 2026

Keypoint tracking alone is insufficient for object interaction tasks such as sitting on a chair, wiping a board, or pushing furniture, where the robot can reach the correct pose without making meaningful physical contact with the object. We present CONTACTMIMIC, a learning framework that tracks e...

manipulation reinforcement-learning control

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No code repo Jul 2026

CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning

Hexian Ni, Tao Lu, Yinghao Cai · ICML 2026 · Jul 2026

Reward design remains a central challenge in reinforcement learning (RL). Hand-crafted rewards are often difficult to specify and may lead to suboptimal policies, while learned rew...

ar-vr manipulation rl

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No code repo Jul 2026

DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation

Yunchao Yao, Zhuxiu Xu, Tianqi Zhang et al. · arXiv preprint · Jul 2026

Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sensory conditions, and robot embodiments. However, existing benchmarks remain limited in task and data diversity, embod...

manipulation vision vla reinforcement-learning control learning-from-demonstration benchmark

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No code repo Jul 2026

FA-RDP: A Frequency-Adaptive Reactive Diffusion Policy for Contact-Rich Manipulation

Lifeng Zhuo, Wendi Chen, Han Xue et al. · arXiv preprint · Jul 2026

In contact-rich manipulation, action multimodality and reactivity dominate different stages of a single episode. Before contact, multiple trajectories might be equally valid, making it important to preserve diverse action modes. After contact, geometric constraints and force limits narrow the sol...

manipulation vision reinforcement-learning control

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GitHub ★ — Jul 2026

FabriVLA: A Lightweight Vision-Language-Action Model for Precise Multi-Task Manipulation

Shiyuan Yang, Borong Zhang, Jizheng Zhang et al. · arXiv preprint · Jul 2026

We present FabriVLA, a lightweight Vision-Language-Action model for Precise Multi-Task Manipulation. FabriVLA combines an InternVL3.5 vision-language backbone with a flow-matching action head featuring gated self-attention across action tokens and shallow VLM layer fusion for enriched spatial con...

manipulation vision vla reinforcement-learning benchmark

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No code repo Jul 2026

FasTac: A Curved Multispectral Vision-Based Tactile Sensor for High-Speed High-Precision 3D Shape and Force Perception

Xiaofan Lu, Kaiji Huang, Jiahui Chen et al. · arXiv preprint · Jul 2026

Curved tactile fingertips for dexterous manipulation must resolve fine contact geometry, distinguish normal and tangential loads, and capture transient signals. Existing curved vision-based tactile sensors struggle to combine accurate 3D reconstruction, three-axis force estimation, and high-speed...

manipulation vision tactile

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No code repo Jul 2026

FurnitureVLA: Learning Long-Horizon Bimanual Furniture Assembly with Vision-Language-Action Model

Chenyang Ma, Yue Yang, Radu Corcodel et al. · arXiv preprint · Jul 2026

Current work on robot furniture assembly mostly focuses on toy-scale settings or single-arm manipulation. We introduce FurnitureVLA, the first systematic study of real-scale bimanu...

ar-vr assembly evaluation

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No code repo Jul 2026

GLAM-SLAM: Real-time Gaussian Large-scale Mapping via Flow Densification and Spatial Decomposition

Panagiotis Mermigkas, Argyris Manetas, Petros Maragos · arXiv preprint · Jul 2026

Existing Gaussian-splatting-based monocular Simultaneous Localization and Mapping (SLAM) systems are either tailored to short sequences, are not real-time, or suffer from prohibitive GPU memory requirements, limiting their applicability in realistic, long-horizon scenarios. To address this, we pr...

planning benchmark

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GitHub ★ — Jul 2026

Goal-Oriented Semantic Communication for Distributed ISAC-Enabled Vehicle Coordination

Wenjie Liu, Yansha Deng · arXiv preprint · Jul 2026

Vehicle coordination at unsignalized intersections relies on accurate real-time vehicle state acquisition and reliable command-and-control (C&C) signal delivery. However, existing studies typically treat sensing, communication, and control separately, which may lead to redundant transmissions, ou...

vision reinforcement-learning control

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No code repo Jul 2026

Grasp, Handover, Rotate: Bimanual Object Reorientation via Compositional Diffusion and Energy-Based Optimization

Wun Lam Yeung, Wenjun Liu, Yui Cheung Yu et al. · arXiv preprint · Jul 2026

Bimanual object reorientation - picking an object, handing it over between two arms, and placing it in a desired target pose - is valuable when direct placement from the initial grasp is infeasible due to collisions, kinematic constraints, or poor final orientation. However, achieving this under ...

manipulation reinforcement-learning sim-to-real planning

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No code repo Jul 2026

GS-Agent: Creating 4D Physical Worlds With Generative Simulation

Hongxin Zhang, Chunru Lin, Junyan Li et al. · arXiv preprint · Jul 2026

Creating dynamic and physically realistic 4D worlds from natural language descriptions is both fascinating and challenging. Traditional computer graphics methods rely on manual creation, requiring extensive human effort to fine-tune materials, motions, and visual fidelity. Recent advances in gene...

manipulation vision reinforcement-learning control

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GitHub ★ — Jul 2026

Human-Centric Transferable Tactile Pre-Training for Dexterous Robotic Manipulation

Chi Zhang, Penglin Cai, Ziheng Xi et al. · arXiv preprint · Jul 2026

As an essential modality for dexterous and contact-rich tasks, tactile sensing provides precise force feedback that cannot be reliably inferred from vision. However, limited by har...

ar-vr manipulation simulation

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No code repo Jul 2026

Latent Memory Palace: Reasoning for Control as Autoregressive Variational Inference

Chuning Zhu, Eva Xu, Jose Barreiros et al. · arXiv preprint · Jul 2026

Human decision-making is highly flexible -- some actions are taken immediately; others require longer deliberation. Language models have exhibited a similar capacity for adaptive "reasoning." However, transferring this capability to continuous control policies has been challenging, as directly re...

reinforcement-learning control

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No code repo Jul 2026

Learning Adaptive Solvers for Distributed Factor Graph Optimization on Matrix Lie Groups

Jaeho Shin, Maani Ghaffari, Yulun Tian · arXiv preprint · Jul 2026

Modern robotic perception increasingly involves large-scale geometric optimization problems distributed across multiple robots or sessions. However, existing distributed solvers often depend on brittle hand tuning and primarily target rigid body pose graphs. To address this, we present DeepCORD, ...

vision reinforcement-learning benchmark

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No code repo Jul 2026

Machines that know they are aging: a framework for hardware-aware autonomous intelligence

Cheng Siong Chin, Jianhua Zhang, Mohan Venkateshkumar · arXiv preprint · Jul 2026

Autonomous systems inevitably age, yet their artificial intelligence typically assumes hardware remains in its original condition. Batteries degrade, sensors drift, processors accumulate timing errors, and memory reliability declines, creating a growing mismatch between assumed and actual capabil...

reinforcement-learning planning

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No code repo Jul 2026

Native Video-Action Pretraining for Generalizable Robot Control

Qihang Zhang, Lin Li, Luyao Zhang et al. · arXiv preprint · Jul 2026

The advent of video-action models offers a promising path for robot control. Nevertheless, we argue that repurposing video generative models designed for digital content creation is inherently inadequate for physical environments. To bridge this gap, we present LingBot-VA 2.0, a video-action foun...

manipulation vision reinforcement-learning control

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No code repo Jul 2026

Neuro-Symbolic Safety Guidance for Vision-Language-Action Models via Constrained Flow Matching

William English, Hao Zheng, Rickard Ewetz · arXiv preprint · Jul 2026

Vision-Language-Action (VLA) models have demonstrated promising generalization capabilities across robotic manipulation tasks, yet their real-world deployment remains limited by th...

ar-vr evaluation generation

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No code repo Jul 2026

One Demonstration Is Enough for Real-World Robotic Reinforcement Learning

Yuwan Liu, Hongze Yu, Song Liu et al. · arXiv preprint · Jul 2026

Learning effective robot control policies on physical hardware is challenging due to costly data collection and the difficulty of reward specification. Prior work has incorporated ...

ar-vr behavior-cloning imitation-learning

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No code repo Jul 2026

One Future, Every Robot: Label-Efficient Collective-State Prediction with Decentralized JEPA

Alan-Barsag Gazzaev, Alexey Garvilov, Sergey Muravyov · arXiv preprint · Jul 2026

Can every robot in a swarm predict the same future collective state from only local observations and bandwidth-limited messages? We formulate this as decentralized shared-state prediction and introduce Collective-State JEPA (CS-JEPA), a recurrent joint-embedding predictive architecture whose outp...

reinforcement-learning planning

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No code repo Jul 2026

PAC-MAN: Perception-Aware CBF-RL for Whole-Body Safety in Humanoid Dodgeball

Lizhi Yang, Junheng Li, Aaron D. Ames · arXiv preprint · Jul 2026

We present PAC-MAN, a perception-aware CBF-RL framework that couples control-barrier safety with deployment-realistic onboard sensing for whole-body humanoid dodgeball. The deployed policy sees the ball only as segmentation-masked depth from a head-mounted camera, while training-time CBF guidance...

vision reinforcement-learning control benchmark

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GitHub ★ — Jul 2026

QQWorld: Quantile-Quantile Matching for World Model Regularization

Zhoushun Yu, Xiaoyu Hu, Xiangyu Xu · arXiv preprint · Jul 2026

Latent world models enable efficient planning by predicting future states in a compact representation space, but their performance depends critically on the quality of the learned latent distribution. LeWorldModel (LeWM) regularizes its latents toward an isotropic Gaussian using the Epps-Pulley (...

reinforcement-learning planning control

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No code repo Jul 2026

RoboTTT: Context Scaling for Robot Policies

Yunfan Jiang, Yevgen Chebotar, Ruijie Zheng et al. · arXiv preprint · Jul 2026

Recent robot foundation models operate with single-step or short-history visuomotor context. We introduce Test-Time-Training Robot Policies (RoboTTT), a robot model and training recipe that scale visuomotor context to 8K timesteps, three orders of magnitude beyond state-of-the-art policies, witho...

manipulation vision vla reinforcement-learning learning-from-demonstration

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GitHub ★ — Jul 2026

Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation

Yu Qi, Zhang Ye, Xinyi Xu et al. · arXiv preprint · Jul 2026

Compositional generalization is essential for robot to follow diverse instructions. However, pretrained policies are known to take shortcuts, deferring to salient cues rather than grounding language. We introduce a diagnostic framework that localizes this failure to individual \textit{instruction...

manipulation reinforcement-learning learning-from-demonstration benchmark

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No code repo Jul 2026

Scaling Behavior Foundation Model for Humanoid Robots

Weishuai Zeng, Kangning Yin, Xiaojie Niu et al. · arXiv preprint · Jul 2026

Humanoid control requires natural whole-body coordination, precise real-time responses to control signals, and robust generalization across diverse environmental contexts, making it a cornerstone for generalist embodied agents. Behavior Foundation Models (BFMs) have recently emerged as a promisin...

reinforcement-learning control

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GitHub ★ — Jul 2026

Stigmergic Graph Memory: An Environment-Aware Approach for Many-to-Many Multi-Agent Pickup and Delivery

Aditya Dutta, Joon-Seok Kim · arXiv preprint · Jul 2026

Automated fulfillment warehouses must continuously assign and execute pickup-and-delivery work while avoiding congestion. In many-to-many Multi-Agent Pickup and Delivery (MAPD), a request specifies a stock-keeping unit rather than fixed endpoints, requiring the controller to select an agent, sour...

vla planning control

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No code repo Jul 2026

TEA-AgriVLN: Traversability Estimation Alarm for Agricultural Vision-and-Language Navigation

Xiaobei Zhao, Xingqi Lyu, Xin Chen et al. · arXiv preprint · Jul 2026

Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires an agent to follow a natural language instruction, predicting a sequence of low-level actions to navigate a robot from a starting point to a target location. The A2A benchmark and the AgriVLN method pioneeringly extended ...

vision planning benchmark

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GitHub ★ — Jul 2026

VoLN: Vision-Only Long-Horizon Navigation---Paradigm, Benchmark, and Method

Jiabin Lou, Haopeng Wang, Yuanshuai Wang et al. · arXiv preprint · Jul 2026

Vision-and-Language Navigation (VLN) enables embodied agents to follow natural-language instructions. However, route-level instructions commonly encode spatial priors, such as orientation, distance, and layout, that are not explicitly available from onboard sensing at deployment in open, GPS-deni...

vision vla planning benchmark

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GitHub ★ — Jul 2026

WorldSample: Closed-loop Real-robot RL with World Modelling

Yuquan Xue, Le Xu, Zeyi Liu et al. · arXiv preprint · Jul 2026

Reinforcement learning (RL) can overcome the demonstration-coverage limitation of imitation learning (IL) by allowing robots to improve through trial-and-error interaction beyond t...

ar-vr generation imitation-learning

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No code repo Jul 2026

X-NavDP: Generalizing Navigation Diffusion Policy to Novel Behavior and Embodiments with Group Q-score Reweighted Matching

Tianyu Yang, Yiming Zeng, Wenzhe Cai et al. · arXiv preprint · Jul 2026

Pretraining navigation diffusion policies rely on large-scale expert demonstrations. These data are typically generated by a fully-informed oracle planner suited to a single nominal robot. This limits the policy's generalization to diverse embodiments and challenging scenarios (e.g., escaping dea...

vision reinforcement-learning planning learning-from-demonstration

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GitHub ★ — Jul 2026

3DThinkVLA: Endowing Vision-Language-Action Models with Latent 3D Priors via 3D-Thinking-Guided Co-training

Jiaxin Shi, Xidong Zhang, Fucai Zhu et al. · arXiv preprint · Jun 2026

We propose a 3D-thinking-guided co-training framework that enables vision-language-action (VLA) models to perform 3D spatial reasoning implicitly during action prediction. Our core insight is that 3D geometry perception and 3D spatial reasoning are distinct capabilities that can be disentangled and ...

sim-to-real reinforcement-learning vision vla manipulation

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No code repo Jun 2026

Scalable Behavior Cloning with Open Data, Training, and Evaluation

Arthur Allshire, Himanshu Gaurav Singh, Ritvik Singh et al. · arXiv · Jun 2026

We introduce ABC, a fully open-source stack for manipulation with behavior cloning. At its core is ABC-130K: the largest open-source teleoperation dataset to date, featuring 3,500 hours of data spanning over 130K episodes across 195 diverse tasks. Furthermore, we open-source o...

Manipulation VLA Models Reinforcement Learning Imitation Learning Sensing & Perception

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GitHub ★ 200 Code updated: Jun 2026

Accelerating and Scaling MPC-Guided Reinforcement Learning for Humanoid Locomotion and Manipulation

Junheng Li, Liang Wu, Sergio A. Esteban et al. · arXiv preprint · Jun 2026

In humanoid motion control, model predictive control (MPC) offers physically grounded prediction and constraint handling, while reinforcement learning (RL) enables robust whole-body skills through large-scale simulation. However, using MPC inside RL often requires time-consuming problem construction or excessive training overhead, making such frameworks difficult to justify in practice. This work studies efficient training-time MPC guidance for humanoid locomotion and manipulation, termed MPC-RL. We introduce a centroidal-dynamics MPC reward formulation that leverages guidance from MPC trajectories in training time. To make this practical in massively parallel RL, we develop π^nMPC, a parallel-in-horizon and construction-free batched GPU MPC solver that operates directly on time-varying dynamics to avoid high memory usage and pre-compilation. Through a variety of comparative studies and hardware validations, we have found that MPC-RL achieves superior performance in locomotion and manipulation skills.

humanoid reinforcement-learning model-predictive-control locomotion manipulation

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GitHub ★ — Jun 2026

AIR-VLA+: Decoupling Movement and Manipulation via Cascaded Dual-Action Decoders with Asymmetric MoE for Aerial Robots

Jianli Sun, Bin Tian, Qiyao Zhang et al. · arXiv preprint · Jun 2026

Aerial manipulation systems have long suffered from representation coupling in end-to-end control, as platform-level Unmanned Aerial Vehicle (UAV) movement and end-effector-level arm manipulation differ substantially in action scale, dynamics, and control objectives. In this paper, we propose AIR-VL...

uav vla manipulation

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No code repo Jun 2026

Bridging Performance and Generalization in Reinforcement Learning for Agile Flight

Jonathan Green, Jiaxu Xing, Nico Messikommer et al. · arXiv · Jun 2026

Autonomous drone racing is a fundamentally challenging regime for autonomous aerial robots, requiring time-optimal control while operating under persistent actuation saturation. While reinforcement learning (RL) has achieved human-level performance in this domain, current meth...

Reinforcement Learning Aerial Robotics Sensing & Perception

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No code repo Code updated: Jun 2026

Co-VLA: Coordination-Aware Structured Action Modeling for Dual-Arm Vision-Language-Action Systems

Yandong Wang, Jiaqian Yu, Xiongfeng Peng et al. · arXiv preprint · Jun 2026

Vision-language-action (VLA) models show strong capabilities in single and dual-arm robotic manipulation. Prior works show coordinated bimanual behaviors can emerge from end-to-end...

ar-vr evaluation generation

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No code repo Jun 2026

Co-VLA: Coordination-Aware Structured Action Modeling for Dual-Arm Vision-Language-Action Systems

Yandong Wang, Jiaqian Yu, Xiongfeng Peng et al. · arXiv preprint · Jun 2026

Vision-language-action (VLA) models show strong capabilities in single and dual-arm robotic manipulation. Prior works show coordinated bimanual behaviors can emerge from end-to-end...

ar-vr evaluation generation

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No code repo Jun 2026

Critic Architecture Matters: Dual vs. Unified Critics for Humanoid Loco-Manipulation

Mehmet Turan Yardımcı · arXiv preprint · Jun 2026

Multi-objective reinforcement learning for humanoid robots must coordinate locomotion and manipulation within a single policy. A natural design choice is whether to use a single (unified) critic that estimates the combined value of all objectives, or separate (dual) critics with disjoint reward sign...

humanoid reinforcement-learning manipulation

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No code repo Jun 2026

Dual Advantage Fields

Alexey Zemtsov, Maxim Bobrin, Alexander Nikulin et al. · ICML 2026 · Jun 2026

Offline goal-conditioned reinforcement learning requires both long-horizon reachability estimates and local action comparisons. Dual goal representations provide value fields that capture global goal reachability, but they do not directly specify which action should be preferred at a given state. We...

reinforcement-learning manipulation locomotion

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No code repo Jun 2026

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation

Wen Ye, Peiyan Li, Tingyu Yuan et al. · arXiv · Jun 2026

Recently, a few works have made early attempts to study test-time scaling for embodied tasks. However, two major challenges remain unsolved: (1) reasoning can effectively improve the performance of the policy, but its scaling mechanism has seldom been studied; (2) historical i...

Manipulation VLA Models Reinforcement Learning Sensing & Perception

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No code repo Code updated: Jun 2026

Finetuning Vision-Language-Action Models Requires Fewer Layers Than You Think

Gia-Binh Nguyen, Trong-Bao Ho, Thien-Loc Ha et al. · arXiv preprint · Jun 2026

Vision-Language-Action (VLA) models pre-trained on massive video-robot datasets have revolutionized robotic manipulation, yet their multi-billion parameter architectures impose pro...

ar-vr evaluation manipulation

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No code repo Jun 2026

Finetuning Vision-Language-Action Models Requires Fewer Layers Than You Think

Gia-Binh Nguyen, Trong-Bao Ho, Thien-Loc Ha et al. · arXiv preprint · Jun 2026

Vision-Language-Action (VLA) models pre-trained on massive video-robot datasets have revolutionized robotic manipulation, yet their multi-billion parameter architectures impose pro...

ar-vr evaluation manipulation

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No code repo Jun 2026

Flash-WAM: Modality-Aware Distillation for World Action Models

Arman Akbari, Ci Zhang, Arash Akbari et al. · arXiv preprint · Jun 2026

World-action models (WAMs) jointly generate future video and robot actions through iterative diffusion, achieving strong performance on manipulation benchmarks but requiring tens of denoising steps, a cost that precludes real-time control. Step distillation has emerged as the natural remedy, but off...

sim-to-real reinforcement-learning diffusion-policy manipulation humanoid

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No code repo Jun 2026

Frequency-Aware Flow Matching for Continuous and Consistent Robotic Action Generation

Jianing Guo, Fangzheng Chen, Zihao Mao et al. · arXiv preprint · Jun 2026

Flow matching has emerged as a standard paradigm for robotic manipulation owing to its strong expressive power for modelling complex, multimodal action distributions, alongside sim...

ar-vr diffusion-policy evaluation

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No code repo Jun 2026

Frequency-Aware Flow Matching for Continuous and Consistent Robotic Action Generation

Jianing Guo, Fangzheng Chen, Zihao Mao et al. · arXiv preprint · Jun 2026

Flow matching has emerged as a standard paradigm for robotic manipulation owing to its strong expressive power for modelling complex, multimodal action distributions, alongside sim...

ar-vr diffusion-policy evaluation

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No code repo Jun 2026

Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

Luca Zanatta, Grzegorz Malczyk, Kostas Alexis · arXiv preprint · Jun 2026

World models, learned generative models that predict how an environment evolves, have become a promising tool for sample-efficient robot learning. Yet how robust they are to environmental variability remains poorly understood. To address this, we conduct a systematic study using vision-based quadrot...

sim-to-real reinforcement-learning navigation vision world-models

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No code repo Jun 2026

GenHOI: Contact-Aware Humanoid-Object Interaction by Imitating Generated Videos without Task-Specific Training

Zhihai Bi, Qiang Zhang, Guoyang Zhao et al. · arXiv preprint · Jun 2026

Humanoid-Object Interaction (HOI) is a fundamental capability for humanoid robots, yet it remains challenging due to the tight coupling between dynamic balance and stable interaction with diverse objects. Existing methods often require time-consuming task-specific policy training or rely on rigid tr...

humanoid manipulation vision

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No code repo Jun 2026

GRAIL: Generating Humanoid Loco-Manipulation from 3D Assets and Video Priors

Tianyi Xie, Haotian Zhang, Jinhyung Park et al. · arXiv preprint · Jun 2026

Scaling humanoid loco-manipulation requires robot-compatible demonstrations across diverse objects, whole-body motions, and scene geometries, but teleoperation and motion capture are difficult to scale because each collection depends on physical setups, instrumented actors, and robot operation. We p...

sim-to-real reinforcement-learning vision manipulation humanoid

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GitHub ★ 275 Code updated: Jun 2026

GuideWalk: Learning Unified Autonomous Navigation and Locomotion for Humanoid Robots across Versatile Terrains

Haoxuan Han, Chen Chen, Linao Gong et al. · arXiv preprint · Jun 2026

Humanoid robots have achieved strong locomotion capabilities, but reliable navigation on versatile terrains remains challenging because obstacle avoidance must be coordinated with dynamically feasible motion. In this work, we present GuideWalk, a unified end-to-end framework that integrates traversa...

humanoid navigation locomotion

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No code repo Jun 2026

HumanoidUMI: Bridging Robot-Free Demonstrations and Humanoid Whole-Body Manipulation

Hongwu Wang, Chenhao Yu, Youhao Hu et al. · arXiv · Jun 2026

High-quality demonstration data are essential for humanoid robot skill learning, especially for whole-body behaviors that require coordinated perception, locomotion, and manipulation. Existing data-collection methods largely rely on robot teleoperation, which is constrained by...

Humanoids Manipulation Reinforcement Learning Imitation Learning Locomotion & Navigation Sensing & Perception

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GitHub ★ 0 Code updated: Jun 2026

Improving Robotic Generalist Policies via Flow Reversal Steering

Andy Tang, William Chen, Andrew Wagenmaker et al. · arXiv preprint · Jun 2026

Generalist policies can learn a wide range of skills from diverse robot datasets. In order to solve or improve on challenging news tasks, we need a way to infer and invoke the appropriate actions from the policy's rich behavioral prior, especially when directly commanding the policy fails. We focus ...

manipulation vla world-models

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No code repo Jun 2026

Invertible Neural Network Adapter for One-Step Flow Matching in Robot Manipulation

Yu Zhang, Kangyi Ji, Yongxiang Zou et al. · arXiv preprint · Jun 2026

This paper presents an invertible neural network adapter for general robotic manipulation, designed to generate precise high-dimensional actions conditioned on multimodal observati...

ar-vr evaluation generation

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No code repo Jun 2026

Invertible Neural Network Adapter for One-Step Flow Matching in Robot Manipulation

Yu Zhang, Kangyi Ji, Yongxiang Zou et al. · arXiv preprint · Jun 2026

This paper presents an invertible neural network adapter for general robotic manipulation, designed to generate precise high-dimensional actions conditioned on multimodal observati...

ar-vr evaluation generation

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No code repo Jun 2026

LA4VLA: Learning to Act without Seeing via Language-Action Pretraining

Tao Lin, Yuxin Du, Yiran Mao et al. · arXiv · Jun 2026

Vision-Language-Action (VLA) models are commonly pretrained on robot demonstrations by jointly mapping visual observations and language instructions to actions. However, dense visual-action supervision can dominate the comparatively sparse language-action signal. As a result, ...

Manipulation VLA Models Reinforcement Learning Imitation Learning Sensing & Perception

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No code repo Code updated: Jun 2026

LadderMan: Learning Humanoid Perceptive Ladder Climbing

Siheng Zhao, Yuanhang Zhang, Ziqi Lu et al. · arXiv preprint · Jun 2026

Humanoid robots hold great promise for operating in human-centered environments, yet ladder climbing remains one of the most challenging tasks due to sparse footholds and handholds, complex whole-body coordination, and sensitivity to perception and control errors. We present extbf{LadderMan}, a un...

sim-to-real reinforcement-learning vision manipulation humanoid

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No code repo Jun 2026

Learning to Fold: prizewinning solution at LeHome Challenge 2026 (1st place online, 2nd offline)

Ilia Larchenko · arXiv · Jun 2026

I describe my solution to the LeHome Challenge 2026, an ICRA 2026 competition on bimanual garment folding. The system placed 1st of 62 teams in the online (simulation) round and 2nd in the real-world final. It improves a vision-language-action (VLA) policy with a reinforcement...

Manipulation VLA Models Reinforcement Learning Sensing & Perception Sim-to-Real Transfer

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No code repo Code updated: Jun 2026

M3imic: Learning a Versatile Whole-Body Controller for Multimodal Motion Mimicking

Zuxing Lu, Ziang Zheng, Yao Lyu et al. · arXiv preprint · Jun 2026

Building a general-purpose whole-body controller is essential for enabling diverse motion capabilities in humanoid robots across a wide range of downstream tasks, including locomotion and loco-manipulation. Different tasks rely on distinct motion reference modalities: locomotion primarily depends on...

sim-to-real reinforcement-learning locomotion manipulation humanoid

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GitHub ★ — Jun 2026

MemoryWAM: Efficient World Action Modeling with Persistent Memory

Sizhe Yang, Juncheng Mu, Tianming Wei et al. · arXiv preprint · Jun 2026

Robust robotic manipulation in the real world requires not only an understanding of the current observation, but also memory and dynamics modeling. World action models (WAMs) posse...

ar-vr gpu-acceleration manipulation

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No code repo Jun 2026

MemoryWAM: Efficient World Action Modeling with Persistent Memory

Sizhe Yang, Juncheng Mu, Tianming Wei et al. · arXiv preprint · Jun 2026

Robust robotic manipulation in the real world requires not only an understanding of the current observation, but also memory and dynamics modeling. World action models (WAMs) posse...

ar-vr gpu-acceleration manipulation

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No code repo Jun 2026

Video

MOCHI: Motion Enhancement of Collaborative Human-object Interactions

Jiye Lee, Yonghun Choi, Jungdam Won · SIGGRAPH 2026 (Journal Track) · Jun 2026

Two-stage framework that enhances noisy multi-human object interaction (MHOI) data by generating plausible hand grasps and refining full-body motion via diffusion-based optimization.

manipulation hand-tracking foundation-models simulation

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GitHub ★ — Jun 2026

Object-Centric Residual RL for Zero-Shot Sim-to-Real VLA Enhancement

Kinam Kim, Namiko Saito, Heecheol Kim et al. · arXiv preprint · Jun 2026

Vision-Language-Action (VLA) models can generalize across diverse manipulation tasks, but their imitation-learning-based policies remain brittle in precise physical interactions du...

ar-vr manipulation rl

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No code repo Jun 2026

Object-Centric Residual RL for Zero-Shot Sim-to-Real VLA Enhancement

Kinam Kim, Namiko Saito, Heecheol Kim et al. · arXiv preprint · Jun 2026

Vision-Language-Action (VLA) models can generalize across diverse manipulation tasks, but their imitation-learning-based policies remain brittle in precise physical interactions du...

ar-vr manipulation rl

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No code repo Jun 2026

OMG: Omni-Modal Motion Generation for Generalist Humanoid Control

Siqiao Huang, Kun-Ying Lee, Dongming Qiao et al. · arXiv preprint · Jun 2026

Humanoid whole-body control has made significant progress in recent years, yet existing approaches remain limited to few-skill policies with heavy reward engineering, or motion trackers that are difficult to extend to new input modalities. We argue that the key to general-purpose humanoid control is...

humanoid diffusion-models generation

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No code repo Jun 2026

Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy

Junhao Shi, Zezheng Huai, Siyin Wang et al. · arXiv · Jun 2026

Building persistent embodied agents in unstructured environments demands unified orchestration of heterogeneous tools spanning both cyber (APIs, IoT) and physical (manipulation, navigation) domains, coupled with autonomous recovery from physical failures that inevitably arise ...

Manipulation VLA Models Reinforcement Learning Locomotion & Navigation

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GitHub ★ 1 Code updated: Jun 2026

OopsieVerse: A Safety Benchmark with Damage-Aware Simulation for Robot Manipulation

Arnav Balaji, Arpit Bahety, Sriniket Ambatipudi et al. · RSS 2026 · Jun 2026

While robotic manipulation capabilities have advanced rapidly, physical safety remains a major barrier to deploying household robots: task success is insufficient if the robot dama...

ar-vr evaluation imitation-learning

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No code repo Jun 2026

Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation

Jonghoon Lee, Seong Hyeon Park, Byungwoo Jeon et al. · arXiv preprint · Jun 2026

Vision-language-action (VLA) policies have shown strong potential for general-purpose manipulation, yet they often fail on novel, out-of-distribution objects whose appearance or ge...

ar-vr manipulation rl

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No code repo Jun 2026

Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation

Jonghoon Lee, Seong Hyeon Park, Byungwoo Jeon et al. · arXiv preprint · Jun 2026

Vision-language-action (VLA) policies have shown strong potential for general-purpose manipulation, yet they often fail on novel, out-of-distribution objects whose appearance or ge...

ar-vr manipulation rl

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No code repo Jun 2026

Stubborn: A Streamlined and Unified Reinforcement Learning Framework for Robust Motion Tracking and Fall Recovery for Humanoids

Xiao Ren, Yuhui Yang, Zongbiao Weng et al. · arXiv preprint · Jun 2026

Recent reinforcement learning approaches have shown great promise in improving humanoid motion tracking performance and achieving fall recovery under disturbances. However, most existing works treat motion tracking and fall recovery as different tasks and require multi-stage training with specialize...

humanoid reinforcement-learning locomotion

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No code repo Jun 2026

Synthetic Data Generation and Vision-based Wrinkle and Keypoint Detection for Bimanual Cloth Manipulation

Ariel Herrera, Xueyang Kang, Atal Anil Kumar · arXiv preprint · Jun 2026

Robotic manipulation of textiles remains challenging because continuous deformation and self-occlusions hinder the robust visual perception required to estimate the cloth's state. To address the lack of annotated real-world data, we developed a Blender-based synthetic pipeline exporting auto-annotat...

vision manipulation reinforcement-learning

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No code repo Jun 2026

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer

Arunim Joarder, Arjun Bhardwaj, René Zurbrügg et al. · IROS 2026 · Jun 2026

Tactile sensing provides direct measurements of contact interactions that are essential for robotic manipulation. However, current simulators lack the fidelity to faithfully model ...

ar-vr generation manipulation

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No code repo Jun 2026

TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer

Arunim Joarder, Arjun Bhardwaj, René Zurbrügg et al. · IROS 2026 · Jun 2026

Tactile sensing provides direct measurements of contact interactions that are essential for robotic manipulation. However, current simulators lack the fidelity to faithfully model ...

ar-vr generation manipulation

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No code repo Jun 2026

Uncertainty Quantification for Flow-Based Vision-Language-Action Models

Ralf Römer, Maximilian Seeliger, Saida Liu et al. · RSS 2026 — Best Paper Award · Jun 2026

Quantifies epistemic uncertainty in flow-matching VLAs using velocity-field disagreement (VFD) across a small ensemble, enabling failure detection at deployment and sample-efficient active fine-tuning (SAVE).

vla foundation-models safety manipulation

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GitHub ★ — Jun 2026

VibeAct: Vibration to Actions for Contact-Rich Reactive Robot Dexterity

Yuemin Mao, Uksang Yoo, Jean Oh et al. · arXiv · Jun 2026

Dexterous manipulation depends on contact events that are fast, local, and often visually occluded. Piezoelectric microphones offer a compact and high-bandwidth way to sense these interactions, but the resulting vibro-acoustic signals are difficult to simulate faithfully enoug...

Manipulation Reinforcement Learning Imitation Learning Sensing & Perception Sim-to-Real Transfer

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No code repo Code updated: Jun 2026

WT-UMI: Tactile-based Whole-Body Manipulation via Force-Supervised Contact-Aware Planning

Jaehwi Jang, Zhaoyuan Gu, Alfred Cueva et al. · arXiv preprint · Jun 2026

Whole-body humanoid manipulation of bulky, deformable, and shared-load objects requires distributed contact sensing and explicit force regulation, yet most imitation policies treat contact force only implicitly. On the other hand, different demonstration sources provide complementary modalities with...

humanoid manipulation tactile

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No code repo Jun 2026

A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms

Yufei Jia, Zhanxiang Cao, Mingrui Yu et al. · arXiv preprint · May 2026

Simulation-based RL for contemporary robot control is increasingly organized around GPU-resident simulation: physics, rollout collection, and learning are placed on a single GPU-centric execution path

reinforcement-learning simulation system-design locomotion

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No code repo Code updated: May 2026

ALAM: Algebraically Consistent Latent Transitions for Vision-Language-Action Models

Zuojin Tang, Haoyun Liu, Xinyuan Chang et al. · arXiv · May 2026

Vision-Language-Action (VLA) models map visual observations and language instructions to robot actions through learned l...

vla foundation-models imitation-learning

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No code repo Code updated: May 2026

AwareVLN: Reasoning with Self-awareness for Vision-Language Navigation

Wenxuan Guo, Xiuwei Xu, Yichen Liu et al. · arXiv preprint · May 2026

AwareVLN introduces selective self-aware reasoning for VLN agents, triggering explicit spatial and progress analysis only at uncertain waypoints to improve robustness and explainability.

vla foundation-models

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GitHub ★ 29 Code updated: May 2026

Beyond Binary: Sim-to-Real Dexterous Manipulation with Physics-Grounded Contact Representation

Jiahe Pan, Stelian Coros, Jitendra Malik et al. · arXiv preprint · May 2026

A primary bottleneck in contact-rich manipulation is the difficulty of collecting real-world data. Sim-to-real reinforcement learning offers a scalable alternative, but the simulation-reality gap prev

dexterous sim-to-real tactile manipulation

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No code repo Code updated: May 2026

BORA: Bridging Offline Reinforcement Learning and Online Residual Adaptation for Real-World Dexterous VLA Models

Zhongxi Chen, Yifan Han, Yanming Shao et al. · arXiv preprint · May 2026

Vision-Language-Action (VLA) models have emerged as a promising paradigm for grounding visual-language understanding into real-world robotic manipulation. However, dexterous manipulation remains chall

dexterous vla reinforcement-learning manipulation offline-rl

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No code repo Code updated: May 2026

CUBic: Coordinated Unified Bimanual Perception and Control Framework

Xingyu Wang, Pengxiang Ding, Jingkai Xu et al. · arXiv · May 2026

Recent advances in visuomotor policy learning have enabled robots to perform control directly from visual inputs. Yet, extending such end-to-end learning from single-arm to bimanual manipulation remains challenging due to the need for both independent perception and coordinated interaction between a...

Manipulation Navigation Sensing & Perception

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No code repo Code updated: May 2026

DynaFLIP: Rethinking Robotics Perception via Tri-Modal-Dynamics Guided Representation

Jusuk Lee, Seungjae Lee, Jonghun Shin et al. · arXiv preprint · May 2026

Robot manipulation critically depends on perception that preserves the action-relevant aspects of a scene. Yet most robot learning pipelines are built upon visual encoders pre-trained for static recog

foundation-models perception manipulation representation-learning vla

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No code repo Code updated: May 2026

EgoForce: Forearm-Guided Camera-Space 3D Hand Pose from a Monocular Egocentric Camera

Christen Millerdurai, Shaoxiang Wang, Yaxu Xie et al. · SIGGRAPH 2026 · May 2026

Reconstructing the absolute 3D pose and shape of the hands from the user's viewpoint using a single head-mounted camera is crucial for practical egocentric interaction in AR/VR, telepresence, and hand-centric manipulation tasks, where sensing must...

manipulation manipulation simulation

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Code ★ 0 May 2026

Energy-Efficient Quadruped Locomotion with Compliant Feet

Pramod Pal, Shishir Kolathaya, Ashitava Ghosal · arXiv · May 2026

Quadruped robots are often designed with rigid feet to simplify control and maintain stable contact during locomotion. While this approach is straightforward, it limits the ability of the legs to absorb impact forces and reuse stored elastic energy, leading to higher energy expenditure during locomo...

Locomotion Reinforcement Learning

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No code repo Code updated: May 2026

Aligning Flow Map Policies with Optimal Q-Guidance

Christos Ziakas, Alessandra Russo, Avishek Joey Bose · arXiv · May 2026

Generative policies based on expressive model classes, such as diffusion-models and flow matching, are well-suited to complex control problems with highly multimodal action distributions. Their expressivity, however, comes at a significant inference cost:...

rl diffusion-models manipulation

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No code repo May 2026

GesVLA: Gesture-Aware Vision-Language-Action Model

Wenxuan Guo, Ziyuan Li, Meng Zhang et al. · arXiv preprint · May 2026

GesVLA augments standard VLA models with gesture awareness, enabling robots to interpret verbal instructions alongside human hand gestures for disambiguated manipulation.

vla manipulation hand-tracking

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GitHub ★ 18 Code updated: May 2026

Guide, Think, Act: Interactive Embodied Reasoning in Vision-Language-Action Models

Yiran Ling, Qing Lian, Jinghang Li et al. · arXiv · May 2026

In this paper, we propose GTA-VLA(Guide, Think, Act), an interactive Vision-Language-Action (VLA) framework that enables spatially steerable embodied reasoning by allowing users to guide robot policies with explicit visual cues. Existing VLA models learn a direct "Sense-to-Act" mapping from multimod...

Navigation VLA Models Sensing & Perception

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GitHub ★ 1 Code updated: May 2026

GuidedVLA: Specifying Task-Relevant Factors via Plug-and-Play Action Attention Specialization

Xiaosong Jia, Bowen Yang, Zuhao Ge et al. · RSS 2026 · May 2026

Vision-Language-Action (VLA) models aim for general robot learning by aligning action as a modality within powerful Vision-Language Models (VLMs). Existing VLAs rely on end-to-end supervision to implicitly enable the action decoding process to learn...

vla foundation-models manipulation

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Code ★ 0 May 2026

Hand-in-the-Loop: Improving Dexterous VLA via Seamless Interventional Correction

Zhuohang Li, Liqun Huang, Wei Xu et al. · arXiv · May 2026

Vision-Language-Action (VLA) models are prone to compounding errors in dexterous manipulation, where high-dimensional action spaces and contact-rich dynamics amplify small policy deviations over long horizons. While Interactive Imitation Learning (IIL) can refine policies through human takeover data...

Manipulation Imitation Learning VLA Models Sensing & Perception

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No code repo Code updated: May 2026

HarmoWAM: Harmonizing Generalizable and Precise Manipulation via Adaptive World Action Models

Qiuxuan Feng, Jiale Yu, Jiaming Liu et al. · arXiv · May 2026

World Action Models (WAMs) have emerged as a promising paradigm for robot control by modeling physical dynamics. Current...

foundation-models manipulation

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GitHub ★ 7 Code updated: May 2026

IntentVLA: Short-Horizon Intent Modeling for Aliased Robot Manipulation

Shijie Lian, Bin Yu, Xiaopeng Lin et al. · arXiv · May 2026

Robot imitation data are often multimodal: similar visual-language observations may be followed by different action chunks because human demonstrators act with different short-horizon intents, task phases, or recent context. Existing frame-conditioned VLA policies infer each chunk from the current o...

Imitation Learning VLA Models

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GitHub ★ 8 Code updated: May 2026

MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction

Zhihao Cao, Qi Shao, Shuhao Zhai et al. · arXiv · May 2026

Multi-agent simultaneous localization and mapping (SLAM) enables collaborative 3D reconstruction. This paper introduces ...

perception simulation

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No code repo Code updated: May 2026

MDrive: Benchmarking Closed-Loop Cooperative Driving for End-to-End Multi-agent Systems

Marco Coscoy, Zewei Zhou, Seth Z. Zhao et al. · arXiv · May 2026

Multi-agent autonomous driving systems require coordination among vehicles to navigate complex traffic scenarios safely ...

navigation simulation

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GitHub ★ 17 Code updated: May 2026

From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation

Yajie Li, Bozhou Zhang, Chun Gu et al. · ICML 2026 · May 2026

Video foundation-models models offer a promising imagination mechanism for robot manipulation by predicting long-horizon future observations, but effectively exploiting these imagined futures for action execution remains challenging. Existing approaches...

vla foundation-models manipulation

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Code ★ 0 May 2026

MonoDuo: Using One Robot Arm to Learn Bimanual Policies

Sandeep Bajamahal, Lawrence Yunliang Chen, Toru Lin et al. · ICRA 2026 · May 2026

Bimanual coordination is essential for many real-world manipulation tasks, yet learning bimanual robot policies is limited by the scarcity of bimanual robots and datasets. Single-arm robots, however,

manipulation bimanual imitation-learning dataset

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No code repo Code updated: May 2026

MoSA: Motion-constrained Stress Adaptation for Mitigating Real-to-Sim Gap in Continuum Dynamics

Jiaxu Wang, Junhao He, Jingkai Sun et al. · arXiv preprint · May 2026

MoSA closes the real-to-sim gap for continuum robots by learning a residual stress field that captures anisotropic material behavior missed by standard simulators.

simulation manipulation

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PhAIL: A Real-Robot VLA Benchmark and Distributional Methodology

Sergey Arkhangelskiy · arXiv preprint · May 2026

Real-world evaluation of vision-language-action (VLA) policies still rests on binary success rate at a fixed timeout with N <= 25 rollouts per condition, almost always without confidence intervals or

benchmarking vla manipulation evaluation

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Pre-VLA: Preemptive Runtime Verification for Reliable Vision-Language-Action and World-Model Rollouts

Zhen Sun, Yongjian Guo, Haoran Sun et al. · arXiv preprint · May 2026

A lightweight runtime verification layer that preemptively prunes unsafe VLA and world-model actions before they reach robot hardware, eliminating collision and droppage failures.

vla safety foundation-models

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PriorVLA: Prior-Preserving Adaptation for Vision-Language-Action Models

Xinyu Guo, Bin Xie, Wei Chai et al. · arXiv · May 2026

Vision-Language-Action (VLA) models have shown promise for generalizable robot control but struggle when adapting to new...

vla foundation-models imitation-learning

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GitHub ★ 14 Code updated: May 2026

Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Qiuyue Wang, Mingsheng Li, Jian Guan et al. · arXiv preprint · May 2026

Embodied intelligence is often studied through specialized models for individual tasks such as manipulation or navigation, resulting in fragmented capabilities and limited generalization across tasks,

foundation-models vla manipulation navigation vision-language

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RoboMemArena: A Comprehensive and Challenging Robotic Memory Benchmark

Huashuo Lei, Wenxuan Song, Huarui Zhang et al. · arXiv · May 2026

Long-horizon robotic tasks require agents to remember and reason about past observations and actions. This paper present...

perception manipulation

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GitHub ★ 76 Code updated: May 2026

RotVLA: Rotational Latent Action for Vision-Language-Action Model

Qiwei Li, Xicheng Gong, Xinghang Li et al. · arXiv · May 2026

Latent Action Models (LAMs) have emerged as an effective paradigm for handling heterogeneous datasets during Vision-Language-Action (VLA) model pretraining, offering a unified action space across embodiments. However, existing LAMs often rely on discrete quantization encode and decode pipelines, whi...

Manipulation Reinforcement Learning VLA Models Sensing & Perception

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GitHub ★ 7 Code updated: May 2026

Safe Aerial 3D Path Planning for Autonomous UAVs using Magnetic Potential Fields

Haechan Mark Bong, Giovanni Beltrame · arXiv · May 2026

Safe autonomous navigation in three-dimensional environments remains a critical challenge for unmanned aerial vehicles (...

uav navigation

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SafeManip: A Property-Driven Benchmark for Temporal Safety Evaluation in Robotic Manipulation

Chengyue Huang, Khang Vo Huynh, Sebastian Elbaum et al. · arXiv · May 2026

Robotic manipulation is typically evaluated by task success, but successful completion does not guarantee safe execution. Many rl failures are temporal: a robot may touch a clean surface after contamination or release an object before it is...

simulation rl manipulation

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Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance

Shutong Ding, Zejia Zhong, Zhongyi Wang et al. · ICML 2026 · May 2026

Recent advances in reinforcement learning (RL) have achieved great successes by leveraging the multimodality and exploration capability of diffusion policies. Among these approaches, one representativ

diffusion-policy reinforcement-learning locomotion manipulation

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Scout-Assisted Planning for Heterogeneous Robot Teams under Partially Known Environments

Hoang-Dung Bui, Abhish Khanal, Raihan Islam Arnob et al. · arXiv preprint · May 2026

SAP pairs aerial scouts with ground robots to gather environmental information ahead of time, reducing mission time by 40% through information-theoretic POMDP planning.

rl uav

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SI-Diff: A Framework for Learning Search and High-Precision Insertion with a Force-Domain Diffusion Policy

Yibo Liu, Stanko Oparnica, Simon Shewchun-Jakaitis et al. · arXiv · May 2026

Contact-rich manipulation is fundamental in robotics but poses significant challenges due to uncertainties in relative poses, such as misalignments and small clearances in peg-in-hole tasks. Existing approaches typically address search and...

manipulation tactile manipulation

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Code ★ 0 May 2026

Slot-MPC: Goal-Conditioned Model Predictive Control with Object-Centric Representations

Jonathan Spieler, Angel Villar-Corrales, Sven Behnke · arXiv · May 2026

Predictive world models enable agents to model scene dynamics and reason about the consequences of their actions. Inspired by human perception, object-centric world models capture scene dynamics using object-level representations, which can be used for downstream applications such as action planning...

Manipulation Reinforcement Learning Sensing & Perception

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Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action

Pengteng Li, Weiyu Guo, He Zhang et al. · arXiv preprint · May 2026

SOMA introduces an explicit spatial memory framework that enables VLA models to track and manipulate objects even after they leave the camera's field of view.

vla manipulation foundation-models

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No code repo May 2026

Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning

Ismail Geles, Leonard Bauersfeld, Markus Wulfmeier et al. · arXiv preprint · May 2026

The first demonstration of superhuman, safe, multi-agent drone racing using a MARL framework trained in simulation and transferred to real Crazyflie nano-drones.

rl uav safety

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Symmetries Here and There, Combined Everywhere: Cross-space Symmetry Compositions in Robotics

Loizos Hadjiloizou, Rodrigo Pérez-Dattari, Noémie Jaquier · arXiv preprint · May 2026

Formalizes cross-space symmetry compositions in robotics and derives equivariant network architectures that exploit multiple simultaneous symmetries for improved generalization.

foundation-models rl manipulation

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TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning

Matthew M. Hong, Jesse Zhang, Anusha Nagabandi et al. · arXiv · May 2026

Fine-tuning pre-trained robot policies with reinforcement learning (RL) often inherits the bottlenecks introduced by pre-training with behavioral cloning (BC), which produces narrow action distributions that lack the coverage necessary for...

rl imitation-learning manipulation

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Unified Noise Steering for Efficient Human-Guided VLA Adaptation

Junjie Lu, Xinyao Qin, Yuhua Jiang et al. · arXiv · May 2026

Adapting Vision-Language-Action (VLA) models to specific user preferences or task requirements typically requires expens...

vla foundation-models imitation-learning

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What Limits Vision-and-Language Navigation ?

Yunheng Wang, Yuetong Fang, Taowen Wang et al. · arXiv · May 2026

Vision-and-Language Navigation (VLN) is a cornerstone of embodied intelligence. However, current agents often suffer from significant performance degradation when transitioning from simulation to real-world deployment, primarily due to perceptual instability (e.g., lighting variations and motion blu...

Navigation Reinforcement Learning VLA Models Sensing & Perception

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GitHub ★ 17 Code updated: May 2026

X-Imitator: Spatial-Aware Imitation Learning via Bidirectional Action-Pose Interaction

Kai Xiong, Hongjie Fang, Lixin Yang et al. · arXiv · May 2026

Effectively handling the interplay between spatial perception and action generation remains a critical bottleneck in robotic manipulation. Existing methods typically treat spatial perception and action execution as decoupled or strictly...

imitation-learning manipulation foundation-models

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No code repo May 2026