A Fault-tolerant Architecture for Mobile Robot Localization

To improve the reliability of perception, autonomous mobile robots often obtain environmental information from multiple sensors. However, the redundancy of sensors and extra fusion process increase the risks of system failure. In this paper, a fault-tolerance architecture is proposed for mobile robot localization and a differential drive mobile robot is investigated. In the architecture, the relative/absolute localization methods are fused by Extended Kalman Filters (EKFs). Furthermore, fault detection and fault identification are accomplished by comparing the outputs of redundancy of fusing processes. Finally, the effectiveness of the fault-tolerance architecture is verified in several experiments conducted in the robot prototype.