Shan Liang
Papers
7
Total Citations
69
H-Index
5
About
Shan Liang is a robotics researcher whose work bridges the gap between intelligent path planning and real-world industrial inspection. His primary research areas include mobile robot navigation, multi-robot coordination, and automated defect detection. Liang made significant contributions to optimal path planning for multiple-goal visiting tasks, developing tailored genetic algorithms that generate efficient, cost-minimizing routes—work that has garnered over 34 citations. He also advanced multi-robot task allocation with a distributed computing and centralized determination method, maximizing system utility. More recently, Liang has focused on pipeline inspection robotics, designing a gas-driven endoscopic robot for visual corrosion detection and an improved YOLOv5 model for automatic defect identification, both published in 2023 with 21 combined citations. His notable achievements include pioneering optimal return-path strategies for mobile robot recharging, considering road attributes like surface roughness and grade. With over 70 total citations across his portfolio, Liang’s work directly addresses practical challenges in industrial automation, from efficient robot fleet management to critical infrastructure maintenance.
Research Focus
Key Achievements
Top Papers
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- 2Optimal Path Planning for Mobile Robot Using Tailored Genetic Algorithm14 citations · 2013
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