Enforcing Constraints for Dynamic Obstacle Avoidance by Compliant Robots

Abstract

In this work a control scheme is proposed to enforce dynamic obstacle avoidance constraints to the full body of actively compliant robots. We argue that both compliance and accuracy are necessary to build safe collaborative robotic systems; obstacle avoidance is usually not enough, due to the reliance on perception systems which exhibit delays and errors. Our scheme is able to successfully avoid obstacles, while remaining compliant in the entirety of the executed task. Therefore, in case of unexpected collisions due to perception system errors, the robot remains safe for humans and its environment. Our approach is validated through experiments with simulated and real obstacles utilizing a 7-dof KUKA LBR iiwa robotic manipulator.