Luyao Yang

Suzhou University of Science and Technology

Papers

Total Citations

H-Index

About

Luyao Yang is a researcher specializing in multi-robot systems, path planning, and optimization algorithms, with a particular focus on dynamic environments and priority-based coordination. Their most notable contribution is the development of a multi-robot dynamic path planning framework that integrates simulated annealing to resolve conflicts and optimize trajectories in real-time, as demonstrated in their highly cited 2024 paper. This work addresses critical challenges in autonomous navigation, such as collision avoidance and task efficiency, offering a scalable solution for applications in warehouse logistics, search-and-rescue, and industrial automation. With 11 citations to date, Yang’s research has quickly gained recognition for its practical relevance and innovative use of metaheuristic optimization. Their approach stands out for balancing computational efficiency with robust performance in complex, unpredictable settings. By advancing priority-based coordination strategies, Yang has laid groundwork for future studies on decentralized multi-agent systems. Their work is essential reading for students and researchers exploring intelligent robotics, swarm intelligence, or real-time decision-making under constraints.