10 papers
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…
Semantically Structured Mixture-of-Experts for Compositional Robotic Manipulation
Chengyu Deng, Guanqi Chen, Yizhou Chen +4
Diffusion-based policies have established a new standard for precise robotic manipulation but face a critical scalability bottleneck: high-performance models are computationally ex…
Beyond Pixels: Learning Invariant Rewards for Real-World Robotics From a Few Demonstrations
Tengye Xu, Yangting Sun, Ziju Shen +5
Designing reward functions that generalize beyond controlled laboratory settings remains a fundamental challenge in reinforcement learning for robotics. In open-world manipulation…
BiKC+: Bimanual Hierarchical Imitation with Keypose-Conditioned Coordination-Aware Consistency Policies
Hang Xu, Yizhou Chen, Dongjie Yu +2
Robots are essential in industrial manufacturing due to their reliability and efficiency. They excel in performing simple and repetitive unimanual tasks but still face challenges w…
BagIt! An Adaptive Dual-Arm Manipulation of Fabric Bags for Object Bagging
Peng Zhou, Jiaming Qi, Hongmin Wu +3
Bagging tasks, commonly found in industrial scenarios, are challenging considering deformable bags' complicated and unpredictable nature. This paper presents an automated bagging s…
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.…
Signage-Aware Exploration in Open World using Venue Maps
Chang Chen, Liang Lu, Lei Yang +4
Current exploration methods struggle to search for shops or restaurants in unknown open-world environments due to the lack of prior knowledge. Humans can leverage venue maps that o…
Language-Augmented Symbolic Planner for Open-World Task Planning
Guanqi Chen, Lei Yang, Ruixing Jia +5
Enabling robotic agents to perform complex long-horizon tasks has been a long-standing goal in robotics and artificial intelligence (AI). Despite the potential shown by large langu…
BiKC: Keypose-Conditioned Consistency Policy for Bimanual Robotic Manipulation
Dongjie Yu, Hang Xu, Yizhou Chen +2
Bimanual manipulation tasks typically involve multiple stages which require efficient interactions between two arms, posing step-wise and stage-wise challenges for imitation learni…