We present an approach for safe and object-independent human-to-robot
handovers using real time robotic vision and manipulation. We aim for general
applicability with a generic object detector, a fast grasp selection algorithm
and by using a single gripper-mounted RGB-D camera, hence not relying on
external sensors. The robot is controlled via visual servoing towards the
object of interest. Putting a high emphasis on safety, we use two perception
modules: human body part segmentation and hand/finger segmentation. Pixels that
are deemed to belong to the human are filtered out from candidate grasp poses,
hence ensuring that the robot safely picks the object without colliding with
the human partner. The grasp selection and perception modules run concurrently
in real-time, which allows monitoring of the progress. In experiments with 13
objects, the robot was able to successfully take the object from the human in
81.9% of the trials.Comment: IEEE Robotics and Automation Letters (RA-L). Preprint Version.
Accepted September, 2020. The code and videos can be found at
https://patrosat.github.io/h2r_handovers