Fault Recovery Through Online Adaptation of Boolean Network Robots

Being able to recover from faults is a desired capability in robotics. This requires identifying ineffective behaviors and making some changes so as to display the desired one. In this work, we consider the problem of adjusting the controller of a robot so as to produce the desired behavior. Instead of considering complex and ad-hoc modifications, we leverage the automatic discovery of suitable solutions by means of online adaptation, a mechanism for the modification of the robot control strategy in runtime. Specifically, we use a performance function to identify ineffective behaviors and drive the controller design to an effective one. We also discuss the technical requirements for this procedure to succeed. The results suggest that online adaptation is suitable for the automatic recovery of functions after the occurrence of damages. Additionally, we show that adapting an existing controller to overcome a fault is faster than searching for a new controller from scratch.