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1
Total Citations
69
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About
Dr. Jiming Li is a leading researcher in intelligent robotics and swarm intelligence optimization, with a particular focus on autonomous navigation and path planning. His most cited work, "An Improved PSO-GWO Algorithm With Chaos and Adaptive Inertial Weight for Robot Path Planning" (2021, 69 citations), addresses critical limitations in traditional particle swarm optimization (PSO) algorithms—namely premature convergence, weak global search capability, and susceptibility to local optima. By hybridizing PSO with the Grey Wolf Optimizer (GWO) and introducing chaotic mapping and adaptive inertial weight mechanisms, Li developed a more robust algorithm that significantly enhances path planning efficiency and solution quality for mobile robots. This contribution has been widely recognized in the robotics and computational intelligence communities, providing a practical framework for real-time autonomous navigation in complex environments. Li’s work bridges theoretical optimization with applied robotics, offering scalable solutions for industrial automation and autonomous systems. His research continues to influence the development of intelligent, adaptive algorithms for dynamic and uncertain environments, making him a notable figure in the field of swarm-based robotic control.
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