Guan Luo

University of Electronic Science and Technology of China, China Institute of Atomic Energy

Papers

Total Citations

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About

Guan Luo is a researcher in robotics and autonomous systems, with a primary focus on path planning and optimization algorithms. Their most influential work, "Robot Path Planning Based on Improved A* Algorithm" (2015), has garnered 45 citations and addresses a critical bottleneck in mobile robotics: the computational inefficiency of traditional A* search when managing OPEN and CLOSED tables. By introducing a novel array storage method, Luo significantly reduced traversal time, enabling faster and more practical real-time navigation for robots. This contribution is foundational for applications ranging from warehouse automation to autonomous vehicles. In earlier work, Luo explored bio-inspired optimization with "Robot Global Path Planning Based on Improved Artificial Fish-Swarm Algorithm" (2013), enhancing foraging behavior models to yield more realistic and efficient search states for global path planning. While less cited, this study demonstrates Luo’s breadth in applying nature-inspired heuristics to robotics challenges. Together, Luo’s research advances the efficiency and adaptability of robot navigation, offering tangible improvements to core algorithms that underpin modern autonomous systems.