CVPR 2023, highlight paper - Learning Human-to-Robot Handovers from Point Clouds

In this episode we discuss Learning Human-to-Robot Handovers from Point Clouds by Sammy Christen, Wei Yang, Claudia Pérez-D'Arpino, Otmar Hilliges, Dieter Fox, Yu-Wei Chao. The paper proposes the first framework to teach robots how to perform vision-based human-to-robot handovers, a crucial task for human-robot interaction. The authors leverage recent advances in realistic simulations for handovers and introduce a method trained with a two-stage teacher-student framework, motion and grasp planning, reinforcement learning, and self-supervision. They report significant performance gains over baselines, both in simulation and in real-world transfer.