Songyang Lao

National University of Defense Technology

Papers

Total Citations

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About

Songyang Lao is a leading researcher in swarm robotics and bio-inspired optimization, whose work bridges theoretical algorithms and practical multirobot coordination. His major contributions center on developing novel optimization frameworks for complex robotic tasks, most notably through his highly cited 2024 paper on an Improved Artificial Electric Field Algorithm (I-AEFA) for 3D robot path planning, which has already garnered 53 citations. This work creatively extends the AEFA’s application domain, enabling efficient navigation in challenging three-dimensional environments. Lao has also advanced multirobot hunting systems with his 2023 study on an Adaptive Cooperative Gene Regulatory Network optimized by an Elastic Deformation Algorithm, addressing critical challenges in system communication and collaboration. His research demonstrates a clear trajectory from algorithmic innovation to real-world deployment, with a focus on overcoming scalability and coordination bottlenecks in multiagent systems. Lao’s impact is evident in the growing citation of his work, which is shaping the next generation of autonomous robotic systems. His achievements mark him as a rising authority in computational intelligence and swarm engineering, offering valuable insights for students and researchers pursuing efficient, adaptive robotic solutions.