3 papers
cs.RO2026
H2RBench: A Real-to-Sim Benchmark for Evaluating Human-to-Robot Transfer
Chuyang Xiao, Haotian Zhan, Sriram Krishna +4
Learning robot manipulation policies from human video demonstrations constitutes a promising avenue for scalable robot learning. However, comparing different human-to-robot (H2R) t…
cs.RO2026
GHOST: Hierarchical Sub-Goal Policies for Generalizing Robot Manipulation
Sriram Krishna, Ben Eisner, Haotian Zhan +5
We present GHOST, a framework for learning visuomotor manipulation policies that generalize beyond the training distribution. GHOST factorizes control into (i) a high-level policy…
cs.RO2025
EgoZero: Robot Learning from Smart Glasses
Vincent Liu, Ademi Adeniji, Haotian Zhan +4
Despite recent progress in general purpose robotics, robot policies still lag far behind basic human capabilities in the real world. Humans interact constantly with the physical wo…