Adaptive Particle Filter for Fault Detection and Isolation of Mobile Robots

Particle filters have recently gained major attention as a powerful diagnostic tool. Their severe drawback is the computational burden closely related to the number of particles used. Therefore, it is often necessary to work out a compromise between computation time and the quality of results, especially in the case of systems with limited computational resources such as mobile robots. This work outlines the concept of a fault detection and isolation (FDI) system for a mobile robot which is based on a bank of adaptive particle filters and accounts for the aforementioned problems.