Sensor fault detection and identification in dead-reckoning system of mobile robot: interacting multiple model approach

Abstract

An interacting multiple-model (IMM) approach to sensor fault detection and identification (FDI) in the dead reckoning of mobile robots is proposed Changes of sensor normal/failure modes are explicitly modeled as switching from one mode to another in a probabilistic manner; mode probabilities and robot states are estimated via a bank of Kalman filters with mutual interaction. To provide better fault decision, mode probability averaging and heuristic decision-making rule are incorporated into the IMM based algorithm. The proposed FDI algorithm is implemented on our mobile robot. 16 system modes (one normal mode and 15 'hard' sensor-failure modes) of four internal sensors (two wheel-encoders, one steering potentiometer and one yaw-rate gyro) are handled. Experimental results validate that the proposed FDI algorithm allows robust navigation of the robot subject to sensor failures.