Papers
2
Total Citations
4
H-Index
2
About
Kai Ming Chang is a leading researcher in autonomous robotics and industrial automation, with a focus on intelligent navigation and control systems for dynamic environments. His work addresses critical challenges in Industry 4.0 applications, particularly the development of robust, GPS-denied navigation workflows for autonomous robots operating in factories with frequently changing layouts and human interference. Chang’s 2024 paper on autonomous robot navigation systems introduces a novel workflow that enhances flexibility and adaptability over traditional automated guided vehicles, offering a scalable solution for real-time monitoring and maintenance. In his 2023 study, he advanced control theory by designing and analyzing a super-twisting sliding mode-PID controller for two-wheeled self-balancing robots, improving stability and disturbance rejection. Though early in his career, his papers have already garnered citations, signaling growing influence. Chang’s contributions are pivotal for the next generation of flexible, autonomous industrial systems, bridging the gap between theoretical control methods and practical deployment in smart manufacturing environments.
Research Focus
Key Achievements
Top Papers
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