Control in a Safe Set: Addressing Safety in Human-Robot Interactions

Abstract

Human-robot interactions (HRI) happen in a wide range of situations. Safety is one of the biggest concerns in HRI. This paper proposes a safe set method for designing the robot controller and offers theoretical guarantees of safety. The interactions are modeled in a multi-agent system framework. To deal with humans in the loop, we design a parameter adaptation algorithm (PAA) to learn the closed loop behavior of humans online. Then a safe set (a subset of the state space) is constructed and the optimal control law is mapped to the set of control which can make the safe set invariant. This algorithm is applied with different safety constraints to both mobile robots and robot arms. The simulation results confirm the effectiveness of the algorithm.