Chengqi Lin
Papers
5
Total Citations
19
H-Index
3
About
Chengqi Lin’s research lies at the intersection of assistive robotics, rehabilitation engineering, and intelligent control systems, with a focus on restoring mobility and independence for individuals with motor impairments. A key contribution is the development of a shared-control assistive mobile robot that integrates brain-machine interfaces with computer vision, enabling stroke patients to command movement through neural signals—a pioneering step toward intuitive human-robot collaboration. Lin has also advanced robotic rehabilitation by proposing a vision-based compensation detection method that identifies harmful compensatory movements during stroke therapy, eliminating the need for complex sensor setups. In industrial robotics, Lin’s work on deep reinforcement learning with shaped exploration spaces has improved the efficiency of contact-rich assembly tasks, while the design of a seven-degree-of-freedom semi-exoskeleton upper limb robot demonstrates expertise in both mechanical design and adaptive control. With over 19 citations across five core publications, Lin’s research is characterized by its practical, user-centered approach—bridging brain-machine interfaces, computer vision, and learning-based control to create safer, more responsive robotic systems for clinical and industrial applications.
Research Focus
Key Achievements
Top Papers
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