activity
20192026
most citedOn the Utility of Koopman Operator Theory in Learning Dexterous Manipulation Skills

2 citations · 9 across the 32 of their papers we have counts for

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Showing 2025Show all

5 papers · 1 filter

cs.RO2025

Towards Automated Chicken Deboning via Learning-based Dynamically-Adaptive 6-DoF Multi-Material Cutting

Zhaodong Yang, Ai-Ping Hu, Harish Ravichandar

Automating chicken shoulder deboning requires precise 6-DoF cutting through a partially occluded, deformable, multi-material joint, since contact with the bones presents serious he…

cs.RO2025

ImMimic: Cross-Domain Imitation from Human Videos via Mapping and Interpolation

Yangcen Liu, Woo Chul Shin, Yunhai Han +3

Learning robot manipulation from abundant human videos offers a scalable alternative to costly robot-specific data collection. However, domain gaps across visual, morphological, an…

cs.RO2025

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…

cs.MA2025

Evaluating and Improving Graph-based Explanation Methods for Multi-Agent Coordination

Siva Kailas, Shalin Jain, Harish Ravichandar

Graph Neural Networks (GNNs), developed by the graph learning community, have been adopted and shown to be highly effective in multi-robot and multi-agent learning. Inspired by thi…

cs.MA2025

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…