Jinjie Li
Papers
1
Total Citations
1
H-Index
1
About
Jinjie Li is a rising researcher in robotics and intelligent optimization, whose work focuses on solving complex inverse kinematics problems for redundant manipulators. Their most notable contribution is the development of an improved Dung Beetle Optimization (I-DBO) algorithm, which addresses the challenging inverse kinematics of 7-degree-of-freedom redundant manipulators. By establishing a scene fitness function and incorporating Tent chaotic mapping, Li's algorithm enhances the manipulator's ability to move freely and adapt to dynamic environments—a critical advancement for flexible automation. Although their 2024 paper has garnered 1 citation, the work represents a novel intersection of bio-inspired computation and robotics, demonstrating potential for real-world applications in manufacturing and service robotics. Li's research is particularly valuable for students and engineers exploring how metaheuristic algorithms can overcome the computational complexity of redundant systems. As optimization techniques continue to evolve, Li's contributions offer a promising pathway toward more adaptive and efficient robotic control.
Research Focus
Key Achievements
Top Papers
- 1