Taosheng Fang

National University of Defense Technology

Papers

Total Citations

H-Index

About

Taosheng Fang is a researcher whose work centers on collective behavior modeling and multi-agent tracking in complex, confined environments. His key contribution, the TH-GRN (Topological-Hierarchical Gene Regulatory Network) model, addresses the challenge of coordinating multiple agents—such as robotic swarms or biological collectives—when space is limited and communication is constrained. Fang's approach draws inspiration from biological gene regulatory networks, enabling robust, decentralized decision-making that adapts to dynamic spatial constraints. His most cited paper, "TH-GRN Model Based Collective Tracking in Confined Environment" (2019), has garnered 4 citations, establishing a foundation for further studies in swarm intelligence and autonomous navigation. This work is notable for bridging theoretical modeling with practical applications in search-and-rescue, environmental monitoring, and micro-robotics. By demonstrating how simple local rules can yield sophisticated group tracking, Fang has opened new avenues for scalable, resilient multi-agent systems. His research continues to influence engineers and scientists seeking to deploy autonomous collectives in real-world, space-limited scenarios.