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About

Yiming Wu is a robotics and control systems researcher whose work spans two interconnected domains: pneumatic artificial muscle (PAM)-actuated robots and underactuated wheeled systems. His most significant contributions lie in developing advanced control strategies for soft, biologically inspired robotic systems that bridge the gap between human physiology and machine interaction. Wu's most impactful research addresses the formidable control challenges inherent in PAM-actuated robots, including nonlinearities, hysteresis, and input constraints. His energy-based motion control framework (2021, 80 citations) and fuzzy-sliding mode control approach (2021, 66 citations) represent landmark contributions to making compliant, human-safe robotic systems more practically controllable, with clear applications in rehabilitation, exoskeleton, and human-robot interaction technologies. These two papers alone demonstrate his strong influence in the soft robotics control community. Complementing this work, Wu has made meaningful advances in underactuated wheeled inverted pendulum systems, tackling challenging real-world scenarios such as slope navigation and undulating terrain through differential flatness-based and trajectory planning methods. Collectively, his research portfolio reflects a consistent focus on bridging theoretical control design with experimental validation, making his work particularly valuable for engineers and researchers developing next-generation assistive and interactive robotic platforms.