Vision-and-Language Navigation (VLN) policies increasingly benefit from strong semantic priors provided by large vision-language models (VLMs). However, standard action supervision does not explicitly encourage intermediate representations to preserve scene geometry, relative orientation, or global episode progress. In...
Anh Dao, Q. Phạm, Le Danh Vinh et al.· 0 citations
During contact-rich manipulation, interactions between a robot and its environment carry information about local geometry: a surface prevents penetration, a bore guides a peg. A controller that exploits these interactions can comply with environmental constraints while preserving task intent. Robot-earning systems comm...
Bundled Contact Gradients is proposed, a contact-local randomized smoothing framework for differentiable policy learning that evaluates a local bundle of randomized perturbation rollouts around the stiff contact configuration and aggregates their gradient signal thereby reducing gradient variance.
Dyuman Aditya, Jin Cheng, Clemens Schwarke et al.· 0 citations
Bounded navigation-aware retention preserves navigation performance while considerably reducing GFM-KV memory relative to larger-memory temporal retention, which support jointly examining the geometric representations exposed to the policy and the historical evidence retained for future inference.
Q. Phạm, Anh Dao, Danh Vinh Le et al.· 0 citations
OpenBelief-Nav is presented, an evidence-preserving object memory that retains observation-level phrases, reliability cues, and frame-mask provenance while maintaining separate aggregate geometric and visual representations.
Dinh Tuan Nguyen, Anh Dao, Phuong Nam Dang et al.· 0 citations
HumanoidVLN, a physics-grounded simulator and benchmark for VLN across diverse humanoid embodiments, and compatibility with NaVILA, DualVLN, StreamVLN, and JanusVLN are presented.
Q. Phạm, Anh Dao, T. Nguyen et al.· 2 citations
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