Yehao Lu

Tongji University, Ministry of Education of the People's Republic of China

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About

Yehao Lu is a researcher at the forefront of swarm intelligence and robotics, specializing in the intersection of particle swarm optimization (PSO) and mobile robot swarms. Their work bridges a critical gap between theoretical optimization algorithms and real-world robotic applications. Lu’s most influential contribution, the "Moving-Distance-Minimized PSO for Mobile Robot Swarm" (2021), has garnered 51 citations and introduces a novel approach that treats robot swarms as physical instantiations of particle swarms, minimizing movement distance to solve spatial problems efficiently. This work is complemented by their "Hybrid Topology-Based Particle Swarm Optimizer for Multi-source Location Problem in Swarm Robots" (2022), which extends these principles to multi-source localization tasks. Lu’s key insight—that the similarity between particle swarms and robot swarms can be exploited for practical deployment—has significant implications for autonomous exploration, search-and-rescue operations, and environmental monitoring. Their research is particularly notable for its focus on energy-efficient, real-time solutions, making swarm robotics more viable for field applications. By demonstrating how PSO algorithms can be physically embodied, Lu is helping to shape the next generation of intelligent, cooperative robotic systems.