Xingsheng Gu
Papers
25
Total Citations
733
H-Index
14
About
Dr. Xingsheng Gu is a leading authority in intelligent robotic path planning, with a primary focus on welding automation. His research centers on developing advanced optimization algorithms—including genetic algorithms, particle swarm optimization (PSO), and rapidly-exploring random trees (RRT*)—to solve complex, collision-free path planning problems for spot, arc, and gantry welding robots. Dr. Gu’s pioneering work, such as the "Double global optimum genetic algorithm–particle swarm optimization-based welding robot path planning" (141 citations), has significantly improved welding efficiency in manufacturing. He has authored numerous highly cited surveys and methodologies, including a comprehensive survey on welding robot intelligent path optimization (109 citations) and novel approaches like AEB-RRT* (51 citations) and dual-objective collision-free path optimization (34 citations). His contributions directly address the critical industry challenge of minimizing cycle time while ensuring safety and precision. With a cumulative citation count exceeding 600, Dr. Gu’s research is essential reading for engineers and researchers seeking to implement intelligent, autonomous welding systems in modern manufacturing environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2A survey of welding robot intelligent path optimization109 citations · 2020
- 3Spot welding robot path planning using intelligent algorithm68 citations · 2019
- 4
- 5AEB-RRT*: an adaptive extension bidirectional RRT* algorithm51 citations · 2022
- 6Path Planning for the Gantry Welding Robot System Based on Improved RRT*43 citations · 2023
- 7Dual-Objective Collision-Free Path Optimization of Arc Welding Robot34 citations · 2021
- 8
- 9Adaptive path planning for the gantry welding robot system30 citations · 2022
- 10Intelligent welding robot path optimization based on discrete elite PSO24 citations · 2016