This study explores the evolving landscape of embodied intelligence, and presents a comprehensive survey on leveraging reinforcement learning (RL) to enhance embodied intelligence, systematically addressing the evolution from single-task performance in controlled settings to sophisticated cross-environment and cross-ta...
BICPO-VLA addresses the request-to-handoff gap by reducing iterative refinement in the original action space and applies reference-relative Flow-DPO among behaviorally matched candidates, adapting the generated chunk to the remaining request-to-handoff mismatch without changing its intended behavior.
Ming Shang, Yuchen Huang, Jiaoyang Chen et al.· 1 citation
PBD-AG is presented, a persistent baseline-delta active graph framework that decouples robot-verified stable fixtures from revisable dynamic object events, and maintains reliability-weighted object states over geometry, semantics, identity, existence, and support relations.
Shuo Bao, Wei Dong, Shu-Yue Zhang et al.· 0 citations
This work proposes Transition Occupancy Matching as a unifying principle to resolve policy and dynamics shifts within a single mathematical framework and introduces Occupancy-Matching Policy Optimization (OMPO), a novel algorithm that optimizes a surrogate objective explicitly correcting for transition discrepancies.
Yu Luo, Lei Lv, Fu-Chun Sun et al.· National Science Review· 0 citations
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