Foothold-constrained terrain is characterized by sparse, discontinuous, or geometrically restricted feasible foot contacts, as encountered on stepping stones, across gaps, and on narrow stair treads. On such terrain, a single misstep often leaves little room to recover, so policies that base foot-placement decisions pr...
Yu-Xi Liu, Lijun Han, Zi-Ming Wang et al.· 1 citation
This work presents Uranus, a data-driven robot simulator built around a joint-trajectory-conditioned autoregressive diffusion model, providing a unified interface for synchronized multi-view generation across diverse robot embodiments and camera configurations.
Wen-Kang Qin, Yu-Kun Zhou, Noah Shen et al.· 0 citations
Cross-embodiment navigation is a key challenge in embodied intelligence. Due to differences in embodiment, the same visual observation may imply different actions for different agents, making prediction ambiguous when relying solely on vision. Existing studies mainly rely on reinforcement learning, which requires large...
Jialu Zhang, Yong Du, Xianda Guo et al.· arXiv.org· 0 citations
Vision-Language Model (VLM) agents have advanced zero-shot object-goal navigation, yet single-frame reasoning leaves them without the cross-step behavioral awareness an embodied navigator requires, producing recurring failures such as dead-end stalls, in-room loops, and circuitous approaches to detected targets. Prompt...
Rui Sang, Yiqun Duan, Pinhan Fu et al.· arXiv.org· 0 citations
TrustVLA is introduced, a mechanism-guided inference-time defense that adapts the Dirichlet evidence framework from trusted classification to monitor per-token, per-layer epistemic uncertainty in VLA policies, providing a retraining-free, mechanism-guided defense for visual-triggered VLA backdoors.
Pin-Han Fu, Xian-Da Guo, Xue-Tao Li et al.· arXiv.org· 0 citations
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