Jiunn-Kai Huang
Papers
11
Total Citations
377
H-Index
8
About
Jiunn-Kai Huang is a leading researcher in legged robotics, specializing in feedback control, state estimation, and reactive planning for bipedal systems. His most influential work, with over 216 citations, demonstrates feedback control of the Cassie bipedal robot for walking, standing, and even riding a Segway using virtual constraints and gait libraries. Huang has made foundational contributions to state estimation for legged robots, introducing hybrid contact preintegration within factor graphs to fuse visual, inertial, and contact sensor data—a framework that has become essential for robust locomotion. He has also advanced reactive planning on undulating terrain, developing anytime control Lyapunov function (CLF) systems that enable bipedal robots to navigate challenging, unexplored environments at high frequency (300 Hz). His work on control barrier functions (CBFs) allows real-time multi-obstacle avoidance during locomotion. Beyond locomotion, Huang has contributed to LiDAR calibration and fiducial tag detection using point clouds. With over 370 total citations across his publications, Huang’s research bridges theoretical control methods with practical, real-world deployment on physical robots, making him a key figure in the push toward agile, autonomous bipedal systems.
Research Focus
Key Achievements
Top Papers
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- 9LiDARTag: A Real-Time Fiducial Tag using Point Clouds5 citations · 2019
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