About

Chih-Jer Lin is a distinguished robotics and automation researcher whose career spans over two decades of contributions to robot motion planning, intelligent control systems, and human-robot interaction. His early work on redundant robot motion planning, dating to the late 1990s, laid a foundation for addressing geometric singularities and task-priority challenges in robotic manipulators, a thread he continued refining through perturbation methods in his 2003 paper, which remains his most-cited work with 33 citations. Lin's research has evolved impressively to embrace modern challenges, including pneumatic artificial muscle-actuated manipulators controlled via sliding-mode algorithms and genetic algorithm-based parameter identification, as well as deep residual neural networks applied to industrial defect detection. Particularly noteworthy is his pioneering integration of brain-computer interfaces, virtual reality, and lower-limb rehabilitation exoskeletons, reflecting a compelling commitment to assistive and medical robotics. His automatic TCP calibration and vision-servo Delta robot work further demonstrate his practical impact on intelligent manufacturing systems. With publications spanning elite journals and consistent citation growth into the 2020s, Lin's interdisciplinary contributions — bridging control theory, machine learning, and rehabilitation engineering — make him a significant figure for researchers navigating the frontiers of intelligent robotics and human-centered automation.

Research Focus

Key Achievements

9
H-Index
26
Papers
235
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Motion planning of redundant robots by perturbation method
33 citations · 2003
📈 Most Prolific Year: 2022 (4 Papers)
🤝 Key Collaborators: 36
🏛 Institutions: Dayeh University, National Taipei University of Technology, National Cheng Kung University, National Taiwan University of Science and Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago