Papers
2
Total Citations
11
H-Index
2
About
Yankun Li’s research focuses on trajectory optimization and motion control for high-speed robotic systems, with a particular emphasis on minimizing motion jerk to enhance precision and operational smoothness. Their major contribution lies in developing an improved Chicken Swarm Optimization (CSO) algorithm, which addresses performance limitations—such as low solution accuracy and slow convergence—in traditional metaheuristic approaches. By integrating five-order B-spline interpolation, Li’s method ensures continuous and smooth acceleration profiles, enabling more efficient and jerk-suppressed robotic positioning in high-speed tasks. This work has garnered over 11 citations across two closely related papers published in 2023, reflecting its relevance to advancing industrial robotics and automation. Li’s research is notable for bridging algorithmic innovation with practical engineering challenges, offering a computationally efficient solution for real-time trajectory planning. Their findings are particularly valuable for applications requiring rapid, precise movements, such as assembly lines and pick-and-place operations. As a researcher, Li contributes to the growing field of bio-inspired optimization in robotics, demonstrating how swarm intelligence can be tailored to meet the stringent demands of modern manufacturing.
Research Focus
Key Achievements
Top Papers
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