Qingkai Li
Papers
6
Total Citations
37
H-Index
3
About
Qingkai Li is a robotics researcher whose work spans pipeline robotics, robotic manipulation, and bipedal locomotion control. His early contributions include foundational work on pipeline inspection systems, most notably his 2010 study on tri-axial differential pipeline robots, which examined the differential properties and traction forces needed to navigate elbow joints — a technically demanding challenge in industrial robotics. Li's research has since expanded into humanoid and redundant robotic systems, where he has made notable strides in biologically inspired control strategies. His 2023 paper introducing CBMC — a brain-mimetic control framework for a 7-DOF robotic arm — has already garnered 10 citations, reflecting strong community interest in model-free approaches robust to dynamic uncertainties. His work on bipedal balance and locomotion is equally impactful: his 2022 studies on one-foot balancing using three-particle model predictive control (9 citations) and squat motion using whole-body control demonstrate a rigorous approach to solving the kinematic and dynamic complexities of humanoid movement. Rounding out his portfolio are contributions to quadratic programming for multi-task redundancy resolution and trajectory tracking under dynamic environments, establishing Li as a versatile contributor to modern robot motion planning and control research.
Research Focus
Key Achievements
Top Papers
- 1
- 2CBMC: A Biomimetic Approach for Control of a 7-Degree of Freedom Robotic Arm10 citations · 2023
- 3
- 4
- 5
- 6