Fault Diagnosis for Wheeled Mobile Robots Based on Adaptive Particle Filter

Abstract

An adaptive particle filter for fault diagnosis of dead-reckoning system was presented. It provided a general framework to integrate rule-based domain knowledge into particle filter. Domain knowledge was exploited to constrain the state space to certain subset. The state space is adjusted by setting the transition matrix. Two typical advantages of this method are: (1) particles will never be drawn from hopeless area of the state space; (2) the particle numbers is reduced. The method is testified in the problem of fault diagnosis for wheeled mobile robots