Kaiqing Luo
Papers
2
Total Citations
32
H-Index
2
About
Kaiqing Luo is a robotics researcher whose work focuses on control systems, simultaneous localization and mapping (SLAM), and intelligent algorithm optimization. His most impactful contribution, the "CFHBA-PID Algorithm" (2022, 23 citations), addresses a fundamental challenge in balancing robot attitude control: the difficulty of tuning PID parameters. By integrating a Complementary Factor with the Honey Badger Algorithm, Luo developed a dual-loop PID control strategy that outperforms traditional metaheuristic approaches prone to premature convergence. This work provides a practical, adaptive solution for maintaining robot stability in dynamic environments. Additionally, Luo's "Improved ORB-SLAM2 Algorithm" (2020, 9 citations) tackles the limitations of visual SLAM systems under motion blur and low-texture conditions. By incorporating information entropy and image sharpening adjustment, his method enhances feature extraction robustness, making SLAM more reliable for real-world robotic navigation. Together, these contributions demonstrate Luo's ability to bridge theoretical algorithm design with applied robotics, offering tangible improvements in both control precision and environmental perception—key areas for advancing autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2