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About

Hsin-Han Chiang is a robotics and control systems researcher whose work spans intelligent robotic manipulation, assistive technologies, and autonomous navigation. With a career dedicated to bridging human-machine interaction and advanced control methodologies, Chiang has made notable contributions across several interconnected domains. His most influential work explores EMG-based robotic control, earning 20 citations for pioneering a Support Vector Machine classifier framework that enables anthropomorphic robotic arm functions through electromyographic signal processing. Complementing this, his research on pneumatic-actuated parallel manipulators — including translational parallel manipulators and linear delta robots — has advanced precision trajectory tracking in flexible, cost-effective robotic systems, collectively accumulating nearly 30 citations. Chiang has also demonstrated a sustained commitment to assistive robotics for vulnerable populations, developing robotic walking-aid systems with obstacle avoidance and human gesture recognition, and more recently proposing adaptive shared control strategies for intelligent electric wheelchairs. His work on autonomous cross-floor navigation, CNN-based obstacle avoidance, and AI-driven service robots like FoodTemi reflects a forward-looking integration of deep learning and robotic operating systems into real-world applications. With over 90 cumulative citations across a decade of research, Chiang's contributions offer valuable insights for students and researchers working at the intersection of rehabilitation robotics, autonomous systems, and intelligent control engineering.