Shan-Ben Chan

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About

Shan-Ben Chan is a pioneering researcher in humanoid robotics, with a primary focus on dynamic locomotion and gait planning for bipedal systems. His most-cited work, "Dynamically stable gait planning for a humanoid robot to climb sloping surface" (2005, 38 citations), represents a significant contribution to the field by formulating biped gait synthesis as an optimization problem. Chan’s innovative approach integrates critical constraints—including zero-moment point (ZMP) constraints for maintaining dynamic stability, internal force constraints for smooth transitions, and geometric constraints for navigating uneven terrain—to enable humanoid robots to climb sloping surfaces with unprecedented stability. This work has been foundational for researchers developing robots capable of operating in complex, real-world environments. Chan’s research addresses one of the most challenging aspects of humanoid robotics: achieving reliable, adaptive locomotion on non-flat surfaces. His contributions have influenced subsequent studies in gait optimization, stability control, and humanoid robot design, making him a respected figure in the robotics community. Through his methodical approach to constraint-based gait planning, Chan has helped advance the practical deployment of humanoid robots in applications ranging from disaster response to assistive technologies.