Real-Time Collision Avoidance in Human-Robot Interaction Based on Kinetostatic Safety Field

This paper addresses the problem of collision avoidance in human-robot interaction. To this end, we introduce the concept of kinetostatic safety field, a novel safety assessment about the risk in the vicinity of a rigid body (including a robot link or a human body part). The safety field depends on the position and velocity of the body but it is also influenced by its real shape and size. Since all the computation can be performed in closed form, the safety field is suitable for real-time applications. Moreover, we present a safety-oriented control strategy for redundant manipulators, based on safety field and developed entirely on the kinematic level, where the kinematic redundancy is exploited for simultaneous task performance and collision avoidance, such as self-collision avoidance and human-robot coexistence. The proposed control strategy is validated through experiments performed on ABB's FRIDA dual arm robot.