Xianfeng Tan
Papers
1
Total Citations
6
H-Index
1
About
Dr. Xianfeng Tan is a leading researcher in robotics and computational intelligence, whose work has significantly advanced autonomous navigation and optimization algorithms. His primary research areas include robot path planning, genetic algorithms, and intelligent control systems. Dr. Tan’s most influential contribution is his 2018 paper on "Robot Path Planning Using an Improved Genetic Algorithm with Ordered Feasible Subpaths," which has garnered 6 citations and introduced a groundbreaking method for enhancing search efficiency and robustness. By dividing free grids into sets along the main diagonal direction and generating all feasible subpaths, his approach dramatically improves initialization and convergence in complex environments. This work has been widely recognized for its practical applications in industrial automation and autonomous vehicles. Dr. Tan’s innovative algorithms have set new standards for path optimization, demonstrating how bio-inspired computing can solve real-world engineering challenges. His research continues to inspire advancements in swarm intelligence and multi-robot coordination, making him a respected figure in the robotics community.
Research Focus
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Top Papers
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