Lishu Qin

Papers

Total Citations

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About

Lishu Qin is a researcher advancing the field of mobile robotics, with a focused expertise in path planning and optimization algorithms. Her work addresses a central challenge in robotics: enabling autonomous systems to navigate complex environments with greater efficiency and safety. Qin’s major contributions lie in developing hybrid algorithmic frameworks that overcome the limitations of traditional methods. Her 2025 paper, "GO-GASA: Grid Optimization Genetic A* Algorithm for Mobile Robots Path Planning," introduces a two-stage optimization framework that enhances navigation performance, while her 2024 work, "Robot Path Planning Based on Tabu Particle Swarm Optimization Integrating Cauchy Mutation," tackles issues like slow convergence and local optima in Particle Swarm Optimization by integrating Tabu Search and Cauchy mutation. Though early in her career, with each paper garnering 2 citations, these publications represent foundational steps toward more robust and intelligent robotic navigation systems. Qin’s research is particularly relevant for students and engineers working on autonomous vehicles, warehouse robots, or any system requiring real-time, adaptive path planning. Her innovative combination of genetic algorithms, particle swarm optimization, and mutation strategies marks her as a promising voice in the ongoing quest to make robots smarter and more autonomous.