7 papers
Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration
Xinghao Zhu, Zixi Liu, Shalin Jain +18
Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains challenging. We present Contact…
Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video
Yunhai Han, Jianuo Qiu, Linhao Bai +14
Human manipulation videos are a convenient and intuitive source for robot learning. However, directly transferring human dexterity to robots remains challenging due to perception e…
AGILE: A Comprehensive Workflow for Humanoid Loco-Manipulation Learning
Huihua Zhao, Rafael Cathomen, Lionel Gulich +6
Recent advances in reinforcement learning (RL) have enabled impressive humanoid behaviors in simulation, yet transferring these results to new robots remains challenging. In many r…
D2M: A Decentralized, Privacy-Preserving, Incentive-Compatible Data Marketplace for Collaborative Learning
Yash Srivastava, Shalin Jain, Sneha Awathare +1
The rising demand for collaborative machine learning and data analytics calls for secure and decentralized data sharing frameworks that balance privacy, trust, and incentives. Exis…
JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes
Shalin Anand Jain, Jiazhen Liu, Siva Kailas +1
Multi-agent reinforcement learning (MARL) has emerged as a promising solution for learning complex and scalable coordination behaviors in multi-robot systems. However, established…
Capability-Aware Shared Hypernetworks for Flexible Heterogeneous Multi-Robot Coordination
Kevin Fu, Shalin Anand Jain, Pierce Howell +1
Recent advances have enabled heterogeneous multi-robot teams to learn complex and effective coordination skills. However, existing neural architectures that support heterogeneous t…