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Learning to Absorb Corrections: Critic-Weighted Residual Flow for Vision-Based Insertion
Yiqing Yuan, Zhi Li, Jinrong Yang +5
Vision-based insertion requires correcting alignment errors while retaining useful behavior learned from demonstrations. We present ACT--Flow, an online learning framework that cou…
Unordered Landmark Visual Navigation
Hao Ren, Junzhe Zhu, Yihan Li +8
Image-goal navigation is a fundamental capability for embodied AI, yet its practical deployment is strained by strong prior assumptions. Existing methods predominantly rely on temp…
Fisher-Preserving Guidance: Training-Free Manifold Constraints for Safe Diffusion Control
Hao Ren, Zetong Bi, Yiming Zeng +5
Diffusion models are effective for waypoint prediction in visual navigation, but standard sampling and test time guidance can produce unreliable or inefficient trajectories when up…
Human-in-the-Loop Failure Recovery with Adaptive Task Allocation
Lorena Maria Genua, Nikita Boguslavskii, Zhi Li
Since the recent Covid-19 pandemic, mobile manipulators and humanoid assistive robots with higher levels of autonomy have increasingly been adopted for patient care and living assi…
Reactive Multi-Robot Navigation in Outdoor Environments Through Uncertainty-Aware Active Learning of Human Preference Landscape
Chao Huang, Wenshuo Zang, Carlo Pinciroli +4
Compared with single robots, Multi-Robot Systems (MRS) can perform missions more efficiently due to the presence of multiple members with diverse capabilities. However, deploying a…