Jingchao Li
Papers
8
Total Citations
78
H-Index
6
About
Jingchao Li is a robotics researcher whose work centers on the design, control, and state estimation of bipedal and humanoid robots, with a particular emphasis on achieving dynamic stability and robust locomotion. His most impactful contribution, a 2020 paper on the structural design and kinematics simulation of the hydraulic biped robot NWPUBR-1 (23 citations), established a foundational framework for a 12-degree-of-freedom humanoid. Li has since advanced the field by integrating sophisticated control and estimation techniques. He pioneered a learning-based model predictive control scheme for biped locomotion (13 citations) and developed an invariant cubature Kalman filtering-based visual-inertial odometry for precise robot pose estimation (12 citations). His research also addresses critical challenges in real-world deployment, including nonlinear state estimation for humanoids, external force observer-aided push recovery for torque-controlled robots, and online robust gait generation inspired by human anti-disturbance strategies. By tackling the core problems of stability, perception, and disturbance rejection, Li’s work is driving the development of more resilient and capable bipedal robots, making significant strides toward their practical application in complex environments.
Research Focus
Key Achievements
Top Papers
- 1Structural Design and Kinematics Simulation of Hydraulic Biped Robot23 citations · 2020
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- 4A nonlinear state estimation framework for humanoid robots11 citations · 2022
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