Guolun Guan

Chongqing University of Posts and Telecommunications

Papers

Total Citations

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About

Guolun Guan is a prominent researcher in the fields of robotics and intelligent optimization algorithms, with a particular focus on enhancing autonomous navigation systems. His most notable contribution is the development of the Improved Artificial Fish Swarm Algorithm (IAFSA), a novel approach to robot path planning that addresses the critical challenge of finding collision-free, shortest paths in complex environments. This work, published in 2016 and garnering 39 citations, demonstrates his ability to refine bio-inspired computational methods for practical engineering applications. Guan's research bridges the gap between theoretical swarm intelligence and real-world robotic mobility, offering solutions that improve both the efficiency and fidelity of robot navigation. His contributions are particularly valuable for students and researchers working in autonomous systems, as they provide a robust framework for tackling path planning problems in dynamic settings. Through his innovative algorithm, Guan has established himself as a key figure in advancing robotic intelligence, making his work essential reading for those exploring the intersection of nature-inspired algorithms and mobile robotics.