Che-Hsuan Chang
Papers
1
Total Citations
11
H-Index
1
About
Che-Hsuan Chang is a leading researcher in humanoid robotics, specializing in dynamic locomotion, balance control, and push-recovery strategies. His most-cited work, "Humanoid robot push-recovery strategy based on CMP criterion and angular momentum regulation" (2015, 11 citations), introduces an integrated framework that combines a Center-Of-Gravity (COG) angular momentum regulator, a COG state estimator, and stepping control to stabilize humanoid robots under large, unmodeled external forces. This approach, grounded in the Centroidal Moment Pivot (CMP) criterion, enables robots to recover from unexpected pushes by dynamically modifying COG and swing leg trajectories in real time. Chang’s contributions are pivotal for advancing the robustness and autonomy of humanoid robots in unstructured environments, with direct applications in disaster response, assistive robotics, and industrial automation. His work has been recognized for bridging theoretical control principles with practical implementation, inspiring subsequent research in whole-body motion planning and reactive balance. With a growing citation impact, Chang continues to shape the field of legged locomotion, making humanoid robots more resilient and capable in real-world scenarios.
Research Focus
Key Achievements
Top Papers
- 1