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About

Jianglong Yu is a leading researcher in cooperative guidance, multi-agent systems, and formation control, with a focus on enhancing the security and robustness of autonomous vehicle networks. His major contributions include pioneering the concept of task-coupling layered cooperative guidance, which integrates mission objectives with real-time trajectory planning for missile systems, and developing practical time-varying formation tracking for non-holonomic mobile robots using distributed extended state observers. Yu’s work on secure cooperative guidance strategies introduces collision-avoidance mechanisms and leader-follower architectures with desired attack-angle interception, addressing critical vulnerabilities in multi-missile systems. His most cited paper (2022, 27 citations) lays the theoretical foundation for layered guidance, while his 2018 study on formation tracking (24 citations) demonstrates real-world applicability for robot swarms. More recently, his 2024 game-based approach to robust formation tracking with a nonautonomous leader (5 citations) advances decentralized decision-making under uncertainty. Yu’s research bridges theory and practice, offering scalable solutions for defense, robotics, and autonomous systems, and his work is widely recognized for its impact on secure, cooperative multi-agent coordination.