3 papers
cs.RO2026
Geometric Entropy: When Trajectory Diversity Helps and Hurts in Imitation Learning
Qian Luo, Ruizhe Liu, Pei Zhou +2
We study how trajectory-shape diversity in demonstrations affects imitation learning (IL) performance across models, tasks, and data scales. We introduce Geometric Entropy (H_G), a…
cs.RO2025
Hyper-GoalNet: Goal-Conditioned Manipulation Policy Learning with HyperNetworks
Pei Zhou, Wanting Yao, Qian Luo +2
Goal-conditioned policy learning for robotic manipulation presents significant challenges in maintaining performance across diverse objectives and environments. We introduce Hyper-…
cs.RO2025
Learning Human-Humanoid Coordination for Collaborative Object Carrying
Yushi Du, Yixuan Li, Baoxiong Jia +5
Human-humanoid collaboration shows significant promise for applications in healthcare, domestic assistance, and manufacturing. While compliant robot-human collaboration has been ex…