MobileH2R: Learning Generalizable Human to Mobile Robot Handover Exclusively from Scalable and Diverse Synthetic Data

https://MobileH2R.github.io (a) (b) (c) (d) Figure 1. The overview of MobileH2R. We propose a framework for generalizable human-to-mobile-robot handover, including a scalable pipeline for diverse full-body human motion synthesis (a), an automatic method for producing safe, imitation-friendly demonstrations (b), an efficient 4D imitation learning approach to learn coordinated base-arm actions (c), and successful sim2real transfer (d).