Papers
14
Total Citations
201
H-Index
8
About
Keqiang Bai is a robotics researcher whose work spans intelligent control systems, medical robotics, and advanced motion planning. His research is particularly distinguished by contributions at the intersection of machine learning and robot kinematics, most notably his 2017 paper on PSO-optimized BP neural network algorithms for precise robot positioning, which has garnered 87 citations and established him as a notable voice in solving inverse kinematics challenges that elude traditional computational methods. Bai has made significant strides in medical robotics, developing binocular vision-based optical positioning systems and computer-assisted puncture robot technologies that support minimally invasive surgical interventions. His work on humanoid robot control is equally prolific, encompassing adaptive backstepping controllers, sliding mode disturbance observers, fuzzy approximation methods, and dual-arm cooperative manipulation — research that collectively addresses the complex nonlinearities inherent in human-like robotic systems. Beyond humanoid platforms, Bai has explored bio-inspired flapping-wing aerial robots and robust autonomous planning for wheeled mobile robots operating under real-world disturbances. With over 180 cumulative citations across a decade of research, his portfolio reflects a sustained commitment to bridging theoretical control design with practical robotic applications across clinical and industrial domains.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4
- 5
- 6
- 7Fuzzy backstepping control for dual-arm cooperative robot grasp11 citations · 2015
- 8
- 9Vision solution for an assisted puncture robotics system positioning8 citations · 2018
- 10