Predictive Fault Tolerance for Autonomous Robot Swarms

TL;DR

This paper introduces a proactive fault tolerance method for robot swarms that detects and resolves potential faults before failures occur, enhancing long-term autonomy and safety.

Contribution

It presents a novel predictive fault tolerance approach based on preemptive maintenance, differing from reactive methods by preventing failures proactively.

Findings

Improved swarm performance with predictive fault handling

Prevents robot failures in tested scenarios

Enhances safety-critical operations

Abstract

Active fault tolerance is essential for robot swarms to retain long-term autonomy. Previous work on swarm fault tolerance focuses on reacting to electro-mechanical faults that are spontaneously injected into robot sensors and actuators. Resolving faults once they have manifested as failures is an inefficient approach, and there are some safety-critical scenarios in which any kind of robot failure is unacceptable. We propose a predictive approach to fault tolerance, based on the principle of preemptive maintenance, in which potential faults are autonomously detected and resolved before they manifest as failures. Our approach is shown to improve swarm performance and prevent robot failure in the cases tested.