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This project addresses the precision challenges in robot–human handover processes, particularly in surgical environments. Two different approaches are explored: (1) learning from a few human demonstrations with hand and instrument tracking and (2) collecting data from remotely controlled robot movements using a joystick or VR system. The aim is to achieve precise, natural handovers without requiri
