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We present an approach for safe and object-independent human-to-robothandovers using real time robotic vision and manipulation. We aim for generalapplicability with a generic object detector, a fast grasp selection algorithmand by using a single gripper-mounted RGB-D camera, hence not relying onexternal sensors. The robot is controlled via visual servoing towards theobject of interest. Putting a high emphasis on safety, we use two perceptionmodules: human body part segmentation and hand/finger segmentation. Pixels thatare deemed to belong to the human are filtered out from candidate grasp poses,hence ensuring that the robot safely picks the object without colliding withthe human partner. The grasp selection and perception modules run concurrentlyin real-time, which allows monitoring of the progress. In experiments with 13objects, the robot was able to successfully take the object from the human in81.9% of the trials.

Object-Independent Human-to-Robot Handovers using Real Time Robotic Vision