Model-Based Fault Diagnosis Techniques for Mobile Robots

The work presented in this paper focuses on the comparison of well-known and new techniques for designing robust fault diagnosis schemes in the robot domain. Correctly identifying and handling faults is an inherent characteristic that all autonomous mobile agents should possess, as none of the hardware and software parts used by robots are perfect; instead, they are often error-prone and able to introduce serious problems that might endanger both robots and their environment. Based on a study of literature covering model-based fault-diagnosis algorithms, we selected four of these methods based on both linear and non-linear models. We analyzed and implemented them in a mathematical model, representing a kinematics of four-wheel-OMNI mobile robot. Numerical examples were used to test the ability of three of the described algorithms to detect and identify abnormal behavior and to optimise the model parameters for the given training data. The final goal was to point out the strengths of each algorithm and to figure out which method would best suit the demands of fault diagnosis for a particular mobile robot. (C) 2016, IFAC (International federation of Antomat Control) Hosting by Elsevier Ltd. All rights reserved.