Yongfeng Ju

Papers

Total Citations

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About

Yongfeng Ju’s research lies at the intersection of multi-robot coordination, intelligent motion control, and rehabilitation robotics. His work addresses critical challenges in autonomous navigation and task allocation for multi-agent systems, particularly in high-stakes environments like emergency rescue and traffic monitoring. Ju proposed a tabu search-based flocking algorithm that enables multiple mobile robots to overcome local minima and navigate unknown obstacle environments autonomously, enhancing their collective motion control. He also advanced auction-based task allocation methods for heterogeneous rescue robot teams, optimizing efficiency in time-critical scenarios. In rehabilitation engineering, Ju developed repetitive control strategies for gait rehabilitation robots, improving the precision and safety of periodic walking training for patients. Though his most cited papers each hold around 2 citations, their conceptual contributions to decentralized coordination and adaptive control are notable. Ju’s work bridges theoretical algorithms with practical robotic applications, offering foundational insights for students and researchers in multi-agent systems, swarm robotics, and medical robotics. His interdisciplinary approach continues to influence the design of intelligent, cooperative robotic systems for real-world deployment.