Shuai Chang

National University of Singapore, Beihang University, Hefei University of Technology

Papers

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About

Shuai Chang is a robotics researcher whose work focuses on advancing automation in complex, real-world environments—from the operating room to high-voltage transmission towers. His research spans surgical robotics, redundant manipulator control, and specialized climbing robots for infrastructure maintenance. In a notable early contribution, Chang designed an active motor skill learning platform using a robot-assisted laparoscopic trainer, addressing the critical challenge of hand-eye coordination in minimally invasive surgery. This work, cited 5 times, laid groundwork for improving surgical proficiency beyond traditional training. More recently, Chang has tackled the inverse kinematics of redundant manipulators, developing an improved gradient projection method for trajectory planning in automated systems like railway water-carrying robots (2 citations). He has also pioneered a new positioning method for climbing robots on transmission towers, integrating 3D models with visual sensors to enable safe, autonomous high-altitude work (2 citations). These contributions demonstrate Chang’s commitment to pushing the boundaries of robotic autonomy in high-stakes, unstructured settings—a promising trajectory for a researcher dedicated to making robots more capable partners in human endeavors.