Fault diagnosis of internal and external sensors with scan matching for mobile robot

Abstract

This paper describes a method of fault diagnosis of internal and external sensors for mobile robot. As our previous works diagnosed hard and noise faults of internal sensors, in this paper, scale faults, in which sensor gains deviate from the fault-free condition, are handled for three internal sensors (two wheel-resolvers and one gyro). The sensor gains are estimated based on the robot velocity estimated with a fault-free external sensor (a forward-looking laser range sensor) via the scan matching method, and then the scale faults are diagnosed. Abrupt faults of the external sensor are handled in this paper. They are detected based on errors related to the scan matching; if the laser images in several successive scans are not matched, the external sensor is decided to be faulty. False detection of the external sensor faults in dynamical environments is improved based on the occupancy grid method. Experimental results in an indoor environment show the performance of our method.