Congfei Li
Papers
3
Total Citations
15
H-Index
3
About
Congfei Li is a robotics researcher whose work centers on the modeling, estimation, and control of hydraulically actuated quadruped robots. His primary contributions lie in advancing state estimation and active compliance control for these high-power-density machines, which are critical for navigating unstructured terrain. Li’s most cited paper (2023, 9 citations) introduces a novel approach that integrates an invariant extended Kalman filter (Invariant-EKF) with neural network-based kinematics to improve state estimation accuracy in hydraulic quadrupeds. This work addresses key challenges in real-time proprioception, enabling more robust locomotion. His earlier research (2021, 3 citations) focuses on force-based active compliance control, tackling the underdeveloped area of torque control for hydraulic robots to enhance adaptability. Additionally, Li has explored push recovery strategies using model predictive control (2023, 3 citations), contributing to stability in dynamic environments. With a growing citation impact, his research is shaping the future of agile, resilient legged robots for applications in search-and-rescue and industrial inspection.
Research Focus
Key Achievements
Top Papers
- 1
- 2Force-based Active Compliance Control of Hydraulic Quadruped Robot3 citations · 2021
- 3