YU Hui-qun

Papers

Total Citations

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About

YU Hui-qun is a researcher whose work focuses on path planning and optimization algorithms for mobile robotics, with a particular emphasis on bio-inspired computational methods. His most notable contribution is the development of the Social Group Search Algorithm (SGSA), a novel swarm intelligence approach inspired by the collective decision-making behaviors observed in social animal groups. This algorithm was applied to mobile robot path planning in his 2013 paper, which has accumulated 5 citations and laid the groundwork for further exploration into nature-inspired optimization techniques. While his citation count reflects a niche but dedicated impact, Yu’s work contributes to the broader field of autonomous navigation by addressing the challenge of efficient, collision-free route generation in dynamic environments. His research bridges theoretical algorithm design with practical robotic applications, offering insights into how social behaviors can be modeled for computational problem-solving. For students and researchers in robotics and optimization, Yu’s work serves as a stepping stone into the intersection of swarm intelligence and autonomous systems, highlighting the potential of biologically inspired algorithms to solve real-world engineering problems.