Jingjing He

Papers

Total Citations

H-Index

About

Jingjing He is a leading researcher in robotics and swarm intelligence, with a primary focus on advancing path planning algorithms for mobile robots. Her work centers on overcoming critical limitations in traditional particle swarm optimization (PSO), particularly its slow convergence, tendency to fall into local optima, and lack of smoothness in generated paths. He’s major contribution lies in developing multiple improved PSO integration schemes that enhance both the efficiency and reliability of autonomous navigation. Her 2020 paper, “An Improved Method of Particle Swarm Optimization for Path Planning of Mobile Robot,” has garnered 53 citations, underscoring its influence in the field. This work introduced a uniform distribution strategy to accelerate convergence and broaden application scenarios. Building on this, her 2021 study proposed a multi-improved PSO algorithm to address discrete optimization and path smoothness, achieving smoother, more practical routes. He’s research is pivotal for real-world robotics, where robust and efficient path planning is essential for autonomous systems. Her achievements highlight a sustained commitment to refining bio-inspired optimization for complex, real-time navigation challenges, making her a notable figure in computational intelligence and mobile robotics.