Cheng-Kai Chan

About

Cheng-Kai Chan is a robotics and control systems researcher whose work spans autonomous navigation, dynamic modeling, and intelligent control of unconventional robotic platforms. He is perhaps best known for his highly influential 2011 paper introducing the Parallel Elite Genetic Algorithm (PEGA) for global path planning in autonomous mobile robots, which has garnered an impressive 295 citations and stands as a landmark contribution to evolutionary computation applied to robotics. A significant thread of Chan's research focuses on ball robots — spherically-driven platforms that present unique challenges in balancing, dynamic modeling, and motion control. His investigations into inverse mouse-ball drive mechanisms, sliding-mode control, and LQR-based approaches have systematically advanced the theoretical and practical foundations of Ballbot locomotion. Chan further pushed the boundaries of intelligent control by developing adaptive frameworks employing recurrent interval type-2 fuzzy neural networks, demonstrating sophisticated uncertainty handling in nonlinear robotic systems. His broader contributions also include planned navigation architectures for self-balancing two-wheeled service robots. Collectively, his body of work reflects a consistent commitment to bridging theoretical control design with real-world autonomous systems, making him a valuable reference for researchers working at the intersection of robotics, evolutionary algorithms, and advanced control theory.

Research Focus

Key Achievements

Top Papers

1. 1
   Parallel Elite Genetic Algorithm and Its Application to Global Path Planning for Autonomous Robot Navigation

   295 citations · 2011
2. 2
   Dynamic modeling and sliding-mode control of a Ball robot with inverse mouse-ball drive

   39 citations · 2008
3. 3
   Self-balancing and position control using multi-loop approach for ball robots

   22 citations · 2010
4. 4
   LQR motion control of a ball-riding robot

   17 citations · 2012
5. 5
   Intelligent backstepping sliding-mode control using recurrent interval type 2 fuzzy neural networks for a ball robot with a four-motor inverse-mouse ball drive

   10 citations · 2012
6. 6
   Intelligent backstepping sliding-mode control using recurrent interval type 2 fuzzy neural networks for a ball-riding robot

   9 citations · 2012
7. 7
   Planned navigation of a self-balancing autonomous service robot

   9 citations · 2008
8. 8
   Direct adaptive recurrent interval type 2 fuzzy neural networks control using for a ball robot with a four-motor inverse-mouse ball drive

   6 citations · 2013

Key Collaborators

Contact & Links