Fault Tolerant Control for Networked Mobile Robots

TL;DR

This paper presents a two-stage fault detection and accommodation method for networked mobile robots, enhancing system robustness against measurement biases through a fault identification filter and leader-based control, validated by simulations and experiments.

Contribution

It introduces a novel two-stage approach combining fault detection and optimal control for networked robots with relative position measurements.

Findings

Effective fault detection in networked robots demonstrated.

Successful fault accommodation improves system resilience.

Validated through simulations and real robot experiments.

Abstract

Teams of networked autonomous agents have been used in a number of applications, such as mobile sensor networks and intelligent transportation systems. However, in such systems, the effect of faults and errors in one or more of the sub-systems can easily spread throughout the network, quickly degrading the performance of the entire system. In consensus-driven dynamics, the effects of faults are particularly relevant because of the presence of unconstrained rigid modes in the transfer function of the system. Here, we propose a two-stage technique for the identification and accommodation of a biased-measurements agent, in a network of mobile robots with time invariant interaction topology. We assume these interactions to only take place in the form of relative position measurements. A fault identification filter deployed on a single observer agent is used to estimate a single fault occurring anywhere in the network. Once the fault is detected, an optimal leader-based accommodation strategy is initiated. Results are presented by means of numerical simulations and robot experiments.