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Dream2Reward: Transition-Alignment Reward Models from Positive Demonstrations for Robotic Manipulation
Haoyu Zhang, Zecui Zeng, Bin Wang +3
Learning robotic policies requires dense rewards that remain informative when behavior departs from successful demonstrations. Progress-based rewards estimate how far an observatio…
A Neuromorphic Reinforcement Learning Framework for Efficient Pathfinding in Robotic Mobile Fulfillment Systems
Junzhe Xu, Zecui Zeng, Lusong Li +2
Dynamic environmental changes, confined workspaces, and stringent real-time constraints make pathfinding in Robotic Mobile Fulfillment Systems (RMFS) a challenging problem for conv…
HumanoidArena: Benchmarking Egocentric Hierarchical Whole-body Learning
Taowen Wang, Zikang Xie, Bin Yang +13
Humanoid robots promise whole-body interaction in human-centered environments, but scalable policy learning remains difficult because task-level decision-making and whole-body dyna…
What Limits Vision-and-Language Navigation ?
Yunheng Wang, Yuetong Fang, Taowen Wang +9
Vision-and-Language Navigation (VLN) is a cornerstone of embodied intelligence. However, current agents often suffer from significant performance degradation when transitioning fro…
AdaMorph: Unified Motion Retargeting via Embodiment-Aware Adaptive Transformers
Haoyu Zhang, Shibo Jin, Lusong Li +4
Retargeting human motion to heterogeneous robots is a fundamental challenge in robotics, primarily due to the severe kinematic and dynamic discrepancies between varying embodiments…
Embodied Tree of Thoughts: Deliberate Manipulation Planning with Embodied World Model
Wenjiang Xu, Cindy Wang, Rui Fang +6
World models have emerged as a pivotal component in robot manipulation planning, enabling agents to predict future environmental states and reason about the consequences of actions…