123 citations · 126 across the 9 of their papers we have counts for
10 papers
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…
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…
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…
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…
Human-Humanoid Robots Cross-Embodiment Behavior-Skill Transfer Using Decomposed Adversarial Learning from Demonstration
Junjia Liu, Zhuo Li, Minghao Yu +4
Humanoid robots are envisioned as embodied intelligent agents capable of performing a wide range of human-level loco-manipulation tasks, particularly in scenarios requiring strenuo…
Towards Precise Pruning Points Detection using Semantic-Instance-Aware Plant Models for Grapevine Winter Pruning Automation
Miguel Fernandes, Antonello Scaldaferri, Paolo Guadagna +7
Grapevine winter pruning is a complex task, that requires skilled workers to execute it correctly. The complexity makes it time consuming. It is an operation that requires about 80…
MPC-based Controller with Terrain Insight for Dynamic Legged Locomotion
Octavio Villarreal, Victor Barasuol, Patrick M. Wensing +2
We present a novel control strategy for dynamic legged locomotion in complex scenarios, that considers information about the morphology of the terrain in contexts when only on-boar…
Simultaneous Contact, Gait and Motion Planning for Robust Multi-Legged Locomotion via Mixed-Integer Convex Optimization
Bernardo Aceituno-Cabezas, Carlos Mastalli, Hongkai Dai +7
Traditional motion planning approaches for multi-legged locomotion divide the problem into several stages, such as contact search and trajectory generation. However, reasoning abou…