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About

Yutong Yuan is a leading researcher in swarm robotics and bioinspired multi-agent systems, with a focus on developing decentralized algorithms for collective intelligence. Their work centers on three key areas: bioinspired exploration, cooperative hunting, and self-organized task allocation in constrained environments. Yuan’s major contributions include the SUNDER framework for self-organized grouping and entrapping in multitarget environments, which enables swarms to operate without GPS or global communication—a critical advancement for real-world deployment. They also pioneered the integration of Lévy flight with artificial potential fields for efficient environment exploration, and developed adaptive gene regulatory networks (GRNs) optimized by elastic deformation algorithms for multirobot hunting tasks. With over 36 citations across their most-cited papers, Yuan’s research has demonstrated significant impact in solving challenges like excessive system communication and poor collaboration in swarm systems. Their notable achievements include the LEADs behavioral decision-making system, which allows swarms to dynamically switch between tasks, and the TH-GRN model for collective tracking in confined spaces. Yuan’s work bridges theoretical bioinspiration with practical robotics, offering scalable solutions for search-and-rescue, surveillance, and environmental monitoring.