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Shared Admittance Control for Human-Robot Co-manipulation based on Operator Intention Estimation

Collaborative robots are increasingly employed in industrial workplaces, assisting human operators in decreasing the weight and the repetitiveness of their activities. In this paper, we assume the presence of an operator cooperating with a lightweight robotic arm, able to autonomously navigate its workspace, while the human co-worker physically interacts with it leading and influencing the execution of the shared task. In this scenario, we propose a human-robot co-manipulation method in which the autonomy of the robot is regulated according to the operator intentions. Specifically, the operator contact forces are assessed with respect to the autonomous motion of the robot inferring how the human motion commands diverges from the autonomous ones. This information is exploited by the system to adjust its role in the shared task, leading or following the operator and to proactively assist him during the co-manipulation. The proposed approach has been demonstrated in an industrial use case consisting of a human operator that interacts with a Kuka LBR iiwa arm to perform a cooperative manipulation task. The collected results demonstrate the effectiveness of the proposed approach.