Prompt Human to Robot Handovers by Estimation of Object Transfer Point based on Human Partner ’ s Motion

Handing over objects is the foundation of many human-robot interaction and collaboration tasks. In the scenario of human handing over an object to the robot, the human chooses where the object needs to be transferred. The robot needs to accurately predict this point of transfer to reach out proactively, instead of waiting for the final position to be presented. This work investigates an efficient method for predicting the Object Transfer Point (OTP), which synthesizes (1) an offline OTP calculated based on the safety, comfort and reachability of the human partner with (2) a dynamic OTP prediction based on the observed human motion. Our proposed OTP predictor is implemented on a humanoid nursing robot and experimentally validated in human-robot handover tasks.