Yangning Wu
Papers
2
Total Citations
14
H-Index
2
About
Yangning Wu is a robotics researcher whose work focuses on multi-agent coordination and swarm intelligence, particularly in the domain of non-cooperative target herding. Their most significant contribution is a general planning framework for multiple mobile robots to compel uncooperative targets toward a destination through coordinated pursuit, encirclement, and guidance operations—a critical challenge in real-world applications like wildlife management or autonomous security. This work, published in 2023, has already garnered 9 citations, reflecting its timely relevance. Wu has also advanced optimization algorithms with a self-regulating and self-perception particle swarm optimization method incorporating mutation mechanisms (2022, 5 citations), demonstrating a dual expertise in both theoretical algorithm design and practical robotic systems. By bridging swarm intelligence and multi-robot planning, Wu’s research offers scalable solutions for complex, dynamic environments where targets actively resist control. Their work stands out for addressing the underexplored problem of herding non-cooperative agents, positioning them as an emerging voice in autonomous robotics and collective behavior.
Research Focus
Key Achievements
Top Papers
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