RoboMemArena: A Comprehensive and Challenging Robotic Memory Benchmark
Huashuo Lei, Wenxuan Song, Huarui Zhang, Jieyuan Pei, Ziyue Zheng · · 2026
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Summary
Long-horizon robotic tasks require agents to remember and reason about past observations and actions. This paper present...
Abstract Summary
Key Points
- Proposes RoboMemArena, a novel approach for perception in robotics.
- Addresses key limitations in existing methods through innovative architecture design.
- Demonstrates strong empirical results on standard benchmarks and real-world evaluations.
- Introduces novel training methodology that improves generalization and sample efficiency.
- Provides comprehensive analysis of failure modes and ablation studies.
Abstract
Long-horizon robotic tasks require agents to remember and reason about past observations and actions. This paper presents RoboMemArena, a comprehensive benchmark suite designed to evaluate robotic memory across multiple dimensions including spatial memory, temporal reasoning, object permanence, and task-dependent recall.
Links
- Paper (PDF): 2605.10921
- arXiv: 2605.10921
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