Kai-Hung Chang
Carnegie Mellon University, Robotics Research (United States)
Papers
4
Total Citations
136
H-Index
4
About
Kai-Hung Chang is a leading researcher at the intersection of soft robotics, computational design, and human-robot interaction, with a particular focus on creating accessible, dexterous, and expressive robotic systems. His most impactful work bridges the gap between soft material robotics and interactive animation. Chang pioneered the concept of "animated plushies," introducing a computational design pipeline that transforms soft, tendon-driven foam structures into reenactable, character-driven motions—a contribution that has garnered 49 citations and opened new avenues in entertainment and assistive robotics. His foundational research on tendon-driven soft foam hands (over 70 combined citations) has been instrumental in democratizing soft robotics. By developing low-cost, fabrication-friendly foam hands controlled via simple regression models and CyberGlove interfaces, Chang demonstrated that complex, dexterous grasping and in-hand manipulation are achievable without expensive hardware. His 2018 work on control strategies for these hands is particularly notable for enabling robust, real-time posing and manipulation. More recently, his 2019 study tackled the persistent challenge of dexterous in-hand manipulation with soft robots, advancing the field toward safer, more versatile robotic hands. Through these contributions, Chang has established himself as a key figure in making soft robotics practical, expressive, and accessible for both researchers and non-experts.
Research Focus
Key Achievements
Top Papers
- 1Interactive design of animated plushies49 citations · 2017
- 2Control of Tendon-Driven Soft Foam Robot Hands39 citations · 2018
- 3
- 4Design and Control of Foam Hands for Dexterous Manipulation16 citations · 2019