7 papers
SSC: A Verifiable Structured Representation for Bimanual Manipulation Labelling
Yupu Lu, Shuang Wu, Sihan Chen +4
Subtask labels decompose a long-horizon manipulation demonstration into shorter semantic segments for policy training and evaluation. Natural language descriptions are easy to read…
Decompose and Reorganize: Planning with Primitives and Visuomotor Policies Learned from Demonstrations
Yizhou Chen, Hang Xu, Dongjie Yu +7
Successfully automating dexterous, long-horizon robotic manipulation requires frameworks capable of both high-level reasoning and fine-grained execution. Traditional task and motio…
Keypose Exploration: Efficient Automatic Trajectory Labelling and Cross-Embodiment Policy Transfer
Yupu Lu, Hang Xu, Yizhou Chen +1
Keypose-based manipulation decomposes tasks into critical waypoints to simplify policy learning for long-horizon tasks, but existing approaches rely on task-specific heuristics or…
Shared Autonomy Assisted by Impedance-Driven Anisotropic Guidance Field
Sihan Chen, Hang Xu, Yupu Lu +4
Shared autonomy (SA) enables robots to infer human intent and assist in its achievement. While most research focuses on improving intent inference, it overlooks whether humans can…
RichMap: A Reachability Map Balancing Precision, Efficiency, and Flexibility for Rich Robot Manipulation Tasks
Yupu Lu, Yuxiang Ma, Jia Pan
This paper presents RichMap, a high-precision reachability map representation designed to balance efficiency and flexibility for versatile robot manipulation tasks. By refining the…
SViP: Sequencing Bimanual Visuomotor Policies with Object-Centric Motion Primitives
Yizhou Chen, Hang Xu, Dongjie Yu +3
Imitation learning (IL), particularly when leveraging high-dimensional visual inputs for policy training, has proven intuitive and effective in complex bimanual manipulation tasks.…