Guanhua Xu
Papers
2
Total Citations
3
H-Index
1
About
Guanhua Xu is a researcher specializing in robotics, optimization algorithms, and 3D point cloud processing. His work focuses on enhancing autonomous navigation and environmental perception for mobile robots. In his most-cited paper, "An Improved Crested Porcupine Optimizer for Path Planning of Mobile Robot" (2025, 2 citations), Xu introduces a novel metaheuristic algorithm that leverages chaotic mapping to overcome local optimization traps and improve convergence accuracy in path planning tasks. This three-step optimization process demonstrates significant potential for real-world robotic applications. Additionally, his research on "Surface segmentation and weld extraction on noisy point clouds consisting of multiple quadrics" (2025, 1 citation) addresses critical challenges in industrial automation, enabling precise feature extraction from complex, noisy 3D data. Xu’s contributions are particularly notable for bridging the gap between theoretical optimization methods and practical robotic systems, offering efficient solutions for dynamic environments. With a focus on algorithmic innovation and real-world deployment, his work continues to influence the fields of autonomous navigation and computational geometry, making him a promising voice in modern robotics research.
Research Focus
Key Achievements
Top Papers
- 1
- 2