Edge-Based Fault diagnosis of Autonomous Ground Robots with Simultaneous Actuator and Sensor Faults

In this paper, an edge-based fault diagnosis scheme is developed for a nonlinear ground vehicle model with possible occurrence of simultaneous actuator faults in the form of loss of effectiveness (LOE) and sensor bias faults. Based on the vehicle and fault models under consideration, the unknown fault parameters are estimated using online adaptive estimation methods. The estimated fault parameters can be utilized to detect, isolate, and accommodate faults in robotic system components, enabling the development of self-diagnostic smart sensors and actuators. Real-time experimental results using a ground robot are shown to illustrate the effectiveness of the proposed algorithm.