Improving Safety in Human-Robot Collaboration via Dynamic Active Constraints Enforcement

The problem of motion planning in obstacle cluttered environments is an important task in robotics. In the literature several methodologies exist to address the problem. In this work we consider using the feedback-based approach, where the solution comes from designing a controller capable of guaranteeing trajectory tracking with obstacle avoidance. Commonly, all respective studies consider simplified robot dynamics, which is usually insufficient in practical applications. In this work we focus on the collision avoidance problem with respect to a moving spherical object. We assume knowledge of a nominal controller that achieves tracking of a desired trajectory in the absence of obstacles, and we design an auxiliary control scheme to guarantee that the robot’s end-effector will always operate in a safe distance from the moving obstacle’s surface. The controller we develop does not take into account the actual robot dynamics, thus constituting a truly model-free approach. Experimental studies conducted on a KUKA LWR4+ robotic manipulator clarify and verify the proposed control scheme.