2 citations · 3 across the 13 of their papers we have counts for
11 papers · 1 filter
Translating Flow to Policy via Hindsight Online Imitation
Yitian Zheng, Zhangchen Ye, Weijun Dong +5
Recent advances in hierarchical robot systems leverage a high-level planner to propose task plans and a low-level policy to generate robot actions. This design allows training the…
Do You Need Proprioceptive States in Visuomotor Policies?
Juntu Zhao, Wenbo Lu, Di Zhang +10
Imitation-learning-based visuomotor policies have been widely used in robot manipulation, where both visual observations and proprioceptive states are typically adopted together fo…
MotionTrans: Human VR Data Enable Motion-Level Learning for Robotic Manipulation Policies
Chengbo Yuan, Rui Zhou, Mengzhen Liu +6
Scaling real robot data is a key bottleneck in imitation learning, leading to the use of auxiliary data for policy training. While other aspects of robotic manipulation such as ima…
Prior Reinforce: Goal-Conditioned Dynamic Manipulation with Limited Trials
Yihang Hu, Pingyue Sheng, Yuyang Liu +2
Embodied robots have achieved strong performance in many real-world manipulation tasks, yet agile dynamic manipulation remains challenging due to high sensitivity to motion paramet…
EasyInsert: A Data-Efficient and Generalizable Insertion Policy
Guanghe Li, Junming Zhao, Shengjie Wang +1
Robotic insertion is a highly challenging task that requires exceptional precision in cluttered environments. Existing methods often have poor generalization capabilities. They typ…
SKIL: Semantic Keypoint Imitation Learning for Generalizable Data-efficient Manipulation
Shengjie Wang, Jiacheng You, Yihang Hu +2
Real-world tasks such as garment manipulation and table rearrangement demand robots to perform generalizable, highly precise, and long-horizon actions. Although imitation learning…
Navi2Gaze: Leveraging Foundation Models for Navigation and Target Gazing
Jun Zhu, Zihao Du, Haotian Xu +5
Task-aware navigation continues to be a challenging area of research, especially in scenarios involving open vocabulary. Previous studies primarily focus on finding suitable locati…
CoPa: General Robotic Manipulation through Spatial Constraints of Parts with Foundation Models
Haoxu Huang, Fanqi Lin, Yingdong Hu +2
Foundation models pre-trained on web-scale data are shown to encapsulate extensive world knowledge beneficial for robotic manipulation in the form of task planning. However, the ac…
SpaceOctopus: An Octopus-inspired Motion Planning Framework for Multi-arm Space Robot
Wenbo Zhao, Shengjie Wang, Yixuan Fan +2
Space robots have played a critical role in autonomous maintenance and space junk removal. Multi-arm space robots can efficiently complete the target capture and base reorientation…
DexCatch: Learning to Catch Arbitrary Objects with Dexterous Hands
Fengbo Lan, Shengjie Wang, Yunzhe Zhang +5
Achieving human-like dexterous manipulation remains a crucial area of research in robotics. Current research focuses on improving the success rate of pick-and-place tasks. Compared…
Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own
Weirui Ye, Yunsheng Zhang, Haoyang Weng +6
Reinforcement learning (RL) is a promising approach for solving robotic manipulation tasks. However, it is challenging to apply the RL algorithms directly in the real world. For on…