81 citations · 96 across the 14 of their papers we have counts for
12 papers · 1 filter
RoboWheel: A Data Engine from Real-World Human Demonstrations for Cross-Embodiment Robotic Learning
Yuhong Zhang, Zihan Gao, Shengpeng Li +12
We introduce Robowheel, a data engine that converts human hand object interaction (HOI) videos into training-ready supervision for cross morphology robotic learning. From monocular…
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…
Learning Goal-oriented Bimanual Dough Rolling Using Dynamic Heterogeneous Graph Based on Human Demonstration
Junjia Liu, Chenzui Li, Shixiong Wang +4
Soft object manipulation poses significant challenges for robots, requiring effective techniques for state representation and manipulation policy learning. State representation inv…
BiRP: Learning Robot Generalized Bimanual Coordination using Relative Parameterization Method on Human Demonstration
Junjia Liu, Hengyi Sim, Chenzui Li +1
Human bimanual manipulation can perform more complex tasks than a simple combination of two single arms, which is credited to the spatio-temporal coordination between the arms. How…
SoftGPT: Learn Goal-oriented Soft Object Manipulation Skills by Generative Pre-trained Heterogeneous Graph Transformer
Junjia Liu, Zhihao Li, Wanyu Lin +3
Soft object manipulation tasks in domestic scenes pose a significant challenge for existing robotic skill learning techniques due to their complex dynamics and variable shape chara…
ReVoLT: Relational Reasoning and Voronoi Local Graph Planning for Target-driven Navigation
Junjia Liu, Jianfei Guo, Zehui Meng +1
Embodied AI is an inevitable trend that emphasizes the interaction between intelligent entities and the real world, with broad applications in Robotics, especially target-driven na…
Mixline: A Hybrid Reinforcement Learning Framework for Long-horizon Bimanual Coffee Stirring Task
Zheng Sun, Zhiqi Wang, Junjia Liu +2
Bimanual activities like coffee stirring, which require coordination of dual arms, are common in daily life and intractable to learn by robots. Adopting reinforcement learning to l…
Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects
Junjia Liu, Yiting Chen, Zhipeng Dong +4
This letter describes an approach to achieve well-known Chinese cooking art stir-fry on a bimanual robot system. Stir-fry requires a sequence of highly dynamic coordinated movement…
Efficient reinforcement learning control for continuum robots based on Inexplicit Prior Knowledge
Junjia Liu, Jiaying Shou, Zhuang Fu +5
Compared to rigid robots that are generally studied in reinforcement learning, the physical characteristics of some sophisticated robots such as soft or continuum robots are higher…