Probabilistic inference of human arm reaching target for effective human-robot collaboration

Allowing a cobot to predict what the human operator is about to do can definitely enhance the effectiveness of human-robot collaboration. This paper addresses the problem of inferring the most likely reaching target of the human hand. The method allows the robot to promptly recognise the intention of the human to reach a certain position within the scene and can be thus used by the controller of the robot to take the optimal decision on what to do. A novel method based on Bayesian statistics has been developed in this work and its applicability in a realistic context has been verified within an industrial use case, consisting of a commercial collaborative robot and a human operator performing a collaborative assembly task.