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About

Cai He-gao is a robotics researcher whose work spans parallel robot kinematics, autonomous mobile systems, bioinspired robotics, and multi-robot coordination. His most influential contribution lies in the domain of parallel robot kinematics, where his 2003 paper on a geometric solution for the direct kinematics of the Delta parallel robot addressed longstanding limitations of algebra-based methods, offering a cleaner, more computationally tractable approach that has garnered 11 citations. Building on this foundation, his 2007 work introduced novel pose measurement and calibration methods for parallel robots, recognizing their advantages in stiffness and error non-accumulation for micro-electromechanical applications. Cai's research interests extend meaningfully into bioinspired robotics, including frog-inspired swimming trajectory planning, and advanced control systems, such as online neural network controllers for pneumatic robots that outperform traditional PID approaches. His investigations into multi-robot teleoperation using Petri Net-based task planners addressed critical safety and efficiency challenges posed by internet latency. More recently, his work on wheel-legged self-balancing robots and nonlinear spring jumping algorithms reflects his continued engagement with cutting-edge locomotion challenges. Across two decades of research, Cai has consistently bridged theoretical kinematics with practical robotic systems design and intelligent control.