Robotics Research Hub

World Models

2 papers

Learned predictive models of environment dynamics.

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

Papers

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

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
Improving Robotic Generalist Policies via Flow Reversal Steering

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 ...

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No code repo Jun 2026

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Read these papers in order to build expertise in World Models.

  1. 1
    Generalization of World Models under Environmental Variability for Vision-based Quadrotor Navigation

    Luca Zanatta, Grzegorz Malczyk et al. · 2026

  2. 2
    Improving Robotic Generalist Policies via Flow Reversal Steering

    Andy Tang, William Chen et al. · 2026