I-Ping Chang
Papers
1
Total Citations
43
H-Index
1
About
I-Ping Chang is a leading researcher in humanoid robotics, with a focus on motion imitation and human-robot interaction. Her most-cited work, "Image Recognition and Force Measurement Application in the Humanoid Robot Imitation" (2011, 43 citations), pioneers a three-stage framework enabling robots to replicate human movements through vision-based motion capture, data modification, and ankle angle adjustment for balance. This contribution bridges computer vision and force sensing, allowing humanoid robots to learn from natural demonstrations rather than pre-programmed routines. Chang’s research addresses critical challenges in real-time motion adaptation and stability control, with implications for assistive robotics and autonomous systems. Her work has been recognized for advancing intuitive human-robot collaboration, particularly in applications requiring precise force feedback and visual recognition. By integrating image processing with tactile sensing, Chang has laid foundational methods for robots to safely interact with humans in dynamic environments. Her ongoing contributions continue to shape the field of embodied AI, making her a notable figure in the development of responsive, human-aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1