Yunyuan Gao

Zhejiang University, Hangzhou Dianzi University

Papers

Total Citations

H-Index

About

Yunyuan Gao is a robotics researcher specializing in multi-robot systems, artificial immune systems, and autonomous cooperation algorithms. His most influential work centers on the novel application of biological immune system principles to solve complex coordination challenges in multi-robot environments — a creative cross-disciplinary approach that bridges computational intelligence and robotics engineering. Gao's most cited contribution, "A New Multi-Robot Self-Determination Cooperation Method Based on Immune Agent Network" (2006, 12 citations), introduced a groundbreaking immune agent model in which individual robots are conceptualized as antibodies and environmental conditions as antigens, enabling sophisticated autonomous decision-making. Building on this foundation, his subsequent research developed dynamic task allocation frameworks that harness antibody-antigen interaction principles to enable robots to efficiently distribute and accomplish unknown cooperative tasks without centralized control. Across his body of work, Gao has consistently advanced the field of artificial immune network (AIN) modeling as a practical solution for real-world multi-robot coordination problems. His research has collectively garnered over 26 citations, demonstrating meaningful influence within the specialized robotics and computational intelligence communities. His work offers valuable insights for researchers exploring biologically-inspired approaches to autonomous systems and swarm robotics.