Coordinated multi-arm motion planning: Reaching for moving objects in the face of uncertainty

Coordinated control strategies for multi-robot systems are necessary for tasks that cannot be executed by a single robot. This encompasses tasks where the workspace of the robot is too small or where the load is too heavy for one robot to handle. Using multiple robots makes the task feasible by extending the workspace and/or increase the payload of the overall robotic system. In this paper, we consider two instances of such tasks: a co-worker scenario in which a human hands over a large object to a robot; intercepting a large flying object. The problem is made difficult as the pick-up/intercept motions must take place while the object is in motion and because the object’s motion is not deterministic. The challenge is then to adapt the motion of the robotic arms in coordination with one another and with the object. Determining the pick-up/intercept point is done by taking into account the workspace of the multi-arm system. The point is continuously recomputed to adapt to change in the object’s trajectory. We propose a virtual object based dynamical systems (DS) control law to generate autonomous and synchronized motions for a multi-arm robot system. We show theoretically that the multi-arm + virtual object system converges asymptotically to the moving object. We validate our approach on a dual-arm robotic system and demonstrate that it can resynchronize and adapt the motion of each arm in a fraction of a second, even when the motion of the object is fast and not accurately predictable.