Resilient, Provably-Correct, and High-Level Robot Behaviors

Abstract

Whether robot controllers are manually designed or synthesized from high-level task specifications, assumptions about the environment need to be made, which can involve adversarial events or cooperative robots. In either case, if these assumptions are violated at runtime, the robot will fail to fulfill its task and will likely do something unexpected. In this paper, we focus on controllers synthesized from linear temporal logic. We tackle the problem of making these controllers robust against environment assumption violations that are common in robot execution. Our solution is a three-layer system: first, we propose an offline approach that accounts for transient violations such that the robot can still complete its task after temporary anomalies; the second layer is an online approach that automatically relaxes the environment assumptions to better capture environment behaviors and that allows the robot to react accordingly; and, finally, we automatically modify the actual environment behaviors, when possible, through negotiation with one of the environment robots operating in the workspace, such that our assumptions are met by the other robot and both robots accomplish their tasks.