Simulation enables large-scale, low-cost robot data generation, but policies trained in simulation often fail to transfer to the real world due to the sim-to-real visual discrepancies. Existing approaches often rely on intermediate representations, which can discard rich semantic information or require additional perce...
Huang Huang, Wen-Si Ai, Zi-Yu Chen et al.· 0 citations
Existing chunk-based Vision-Language-Action (VLA) models execute a fixed number of actions (i.e., execution horizon) before replanning, turning replanning into a task-agnostic periodic schedule that is independent of task progress. As a result, when no replanning boundary falls before a critical manipulation stage, it...
Weichen Xu, Zhenhua Liu, Lin Luo et al.· 1 citation
FM-VLA is proposed, a VLA model with force-based memory, enabling temporal context reasoning for non-Markovian, contact-rich manipulation, and achieves over 80% success rate with minimal inference overhead, significantly outperforming baseline approaches.
Ruicheng Li, Qi-Xiu Li, Ruichun Ma et al.· arXiv.org· 1 citation
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