Intelligent Fault Diagnosis of Wheeled Mobile Robots

This research focuses on improving the reliability of intelligent robots through artificial intelligence–based fault diagnosis. By analysing multi-sensor data, advanced deep learning methods are developed to enable robots to automatically detect and identify faults under complex and dynamic working conditions. The research further introduces privacy-preserving collaborative learning among multiple robots and efficient AI models suitable for real-world deployment. This work contributes to safer, more reliable, and intelligent robot–human collaboration in industrial and service environments.