7 papers
Towards Deploying VLA without Fine-Tuning: Plug-and-Play Inference-Time VLA Policy Steering via Embodied Evolutionary Diffusion
Zhuo Li, Junjia Liu, Zhipeng Dong +4
Vision-Language-Action (VLA) models have demonstrated significant potential in real-world robotic manipulation. However, pre-trained VLA policies still suffer from substantial perf…
Adapt as You Say: Online Interactive Bimanual Skill Adaptation via Human Language Feedback
Zhuo Li, Dianxi Li, Tao Teng +5
Developing general-purpose robots capable of autonomously operating in human living environments requires the ability to adapt to continuously evolving task conditions. However, ad…
Disentangling perception and reasoning for improving data efficiency in learning cloth manipulation without demonstrations
Donatien Delehelle, Fei Chen, Darwin Caldwell
Cloth manipulation is a ubiquitous task in everyday life, but it remains an open challenge for robotics. The difficulties in developing cloth manipulation policies are attributed t…
Interactive Motion Planning for Human-Robot Collaboration Based on Human-Centric Configuration Space Ergonomic Field
Chenzui Li, Yiming Chen, Xi Wu +4
Industrial human-robot collaboration requires motion planning that is collision-free, responsive, and ergonomically safe to reduce fatigue and musculoskeletal risk. We propose the…
Human-Like Robot Impedance Regulation Skill Learning from Human-Human Demonstrations
Chenzui Li, Xi Wu, Yiming Chen +5
Humans are experts in physical collaboration by leveraging cognitive abilities such as perception, reasoning, and decision-making to regulate compliance behaviors based on their pa…
ManiDP: Manipulability-Aware Diffusion Policy for Posture-Dependent Bimanual Manipulation
Zhuo Li, Junjia Liu, Dianxi Li +5
Recent work has demonstrated the potential of diffusion models in robot bimanual skill learning. However, existing methods ignore the learning of posture-dependent task features, w…