Renjie Fang

Papers

Total Citations

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About

Renjie Fang is a researcher specializing in multi-robot systems and underwater autonomous vehicle (AUV) coordination, with a focus on formation control and swarm intelligence. Their major contributions lie in developing leader-follower models for underactuated underwater robots, addressing the kinematic and dynamic challenges of maintaining stable formations in complex aquatic environments. Fang’s work on vision-guided swarm robots integrates the Hungarian algorithm for optimal task assignment and consensus algorithms for efficient path planning, enabling precise and scalable formation control. With key papers published in 2019 and 2020, their research has garnered early citations—4 and 3 respectively—reflecting its foundational role in advancing underwater robotics and swarm coordination. Notably, Fang’s studies bridge theoretical control strategies with practical implementations, offering solutions for underwater search missions and multi-robot collaboration. Their achievements include designing a formation control system that minimizes overall path length and enhances robustness, making their work a valuable reference for researchers exploring autonomous systems, robotics, and distributed control. Fang’s contributions continue to influence the development of intelligent, cooperative robot teams.