Anticipating Degradation: A Predictive Approach to Fault Tolerance in Robot Swarms

Abstract

An active approach to fault tolerance is essential for robot swarms to achieve long-term autonomy. Previous efforts have focused on responding to spontaneous electro-mechanical faults and failures. However, many faults occur gradually over time. Waiting until such faults have manifested as failures before addressing them is both inefficient and unsustainable in a variety of scenarios. This work argues that the principles of predictive maintenance, in which potential faults are resolved before they hinder the operation of the swarm, offer a promising means of achieving long-term fault tolerance. This is a novel approach to swarm fault tolerance, which is shown to give a comparable or improved performance when tested against a reactive approach in almost all cases tested.