Shih-Che Chen
Papers
2
Total Citations
16
H-Index
2
About
Shih-Che Chen is a pioneering researcher in advanced robotics, specializing in adaptive motion control, multi-robot systems, and terrain-adaptive locomotion. His work addresses critical challenges in autonomous navigation, particularly for mobile robots operating in complex, unstructured environments. Chen’s most influential contribution is an adaptive motion control framework for a novel self-balancing leg-wheeled mobile robot, integrating backstepping sliding-mode control, side tilting control, and impedance control to enable stable traversal over rough and uneven terrain. This work, cited 7 times, demonstrates a significant leap in robotic mobility. Additionally, his 2023 paper on adaptive reinforcement learning formation control using output recurrent fuzzy broad learning systems (ORFBLS) for omnidirectional multi-robots has garnered 9 citations, showcasing his expertise in merging machine learning with swarm robotics. Chen’s research not only advances theoretical control methodologies but also delivers practical solutions for real-world robotic applications, from disaster response to exploration. His innovative integration of adaptive algorithms and mechanical design marks him as a rising leader in intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
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