Xinhao Xiang
Papers
2
Total Citations
27
H-Index
2
About
Xinhao Xiang is a leading researcher in swarm robotics and bio-inspired optimization, with a focus on developing intelligent, decentralized algorithms for multi-target collaborative searching. His work bridges the gap between computational intelligence and real-world robotic applications, particularly through the adaptation of particle swarm optimization (PSO) and brain storm optimization (BSO) for robotic swarms. His most cited paper, "Exploration Enhanced RPSO for Collaborative Multitarget Searching of Robotic Swarms" (2020, 23 citations), introduces a novel variant of PSO that enhances exploration capabilities, enabling robotic teams to efficiently locate multiple targets in unknown environments. This work is foundational for applications in search-and-rescue, environmental monitoring, and autonomous exploration. Xiang further extends this paradigm with "Robotic Brain Storm Optimization: A Multi-target Collaborative Searching Paradigm for Swarm Robotics" (2021, 4 citations), which applies human-inspired brainstorming processes to swarm coordination. By integrating exploration-exploitation balance and swarm intelligence, Xiang’s contributions offer scalable, robust solutions for complex, dynamic tasks. His research is highly relevant for students and engineers interested in autonomous systems, collective behavior, and optimization algorithms.
Research Focus
Key Achievements
Top Papers
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