Jie-Xin Liu

Fed-HANet: Federated Visual Grasping Learning for Human Robot Handovers

Human-robot handover is a key capability of service robots, such as those used to perform routine logistical tasks for healthcare workers. Recent algorithms have achieved tremendous advances in object-agnostic end-to-end planar grasping with up to six degrees of freedom (DoF); however, compiling the