Libin Song
Papers
2
Total Citations
71
H-Index
2
About
Dr. Libin Song is a leading researcher in robotic painting automation, with a focus on optimizing industrial manipulators for large-scale manufacturing. His work centers on two critical challenges: the precise positioning of mobile painting robots under multiple constraints, and the intelligent segmentation of complex surfaces for autonomous coating. In his highly cited 2018 paper (58 citations), Song developed a base position optimization method that enables mobile manipulators to achieve maximum reachability and dexterity while respecting kinematic and environmental constraints—a fundamental advance for painting large structures. His 2019 work (13 citations) introduced a deep learning-based automatic surface segmentation algorithm for 6-DOF robots painting large-size aircraft, creatively converting point cloud data into optimized painting blocks. This innovation directly addresses the industry’s need for efficient, adaptable automation across different aircraft models. Song’s contributions bridge robotics, computer vision, and manufacturing, providing practical solutions that reduce manual programming and improve coating quality. His research is essential reading for engineers and researchers working on industrial robot path planning, surface coverage, and the integration of AI into traditional manufacturing processes.
Research Focus
Key Achievements
Top Papers
- 1
- 2