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About

Runtao Yang is a leading researcher in swarm robotics, with a primary focus on developing efficient exploration and task allocation strategies for multi-robot systems. His work centers on improving the fundamental algorithms that govern how groups of simple robots can collectively search and cover unknown environments. Yang’s major contributions lie in his systematic analysis and enhancement of random walk methods—the core search mechanisms for robots with limited sensing and processing power. His most cited work, “A Swarm Robotic Exploration Strategy Based on an Improved Random Walk Method” (2019, 49 citations), demonstrates how tailored search strategies can dramatically outperform generic approaches. He further advanced the field by showing how bio-inspired techniques, such as bacterial foraging optimization with improved chemotaxis, can be applied to robotic swarms. Yang also addressed the critical challenge of autonomous task allocation, proposing a response threshold sigmoid model for foraging robots. With over 135 total citations, his research provides a rigorous, quantitative foundation for designing more effective and scalable swarm robotic systems, making him a key figure in the advancement of decentralized robotic exploration.