Saibao Xie

Henan University of Science and Technology

Papers

Total Citations

H-Index

About

Saibao Xie is a robotics researcher whose work centers on autonomous navigation, path planning, and environment perception for mobile robots. His most significant contribution, the "PRM-D* Method for Mobile Robot Path Planning" (2023, 33 citations), addresses a critical challenge in robotics: enabling robots to navigate dynamic environments with high success rates, speed, and effective obstacle avoidance. By fusing the probabilistic roadmap method with D* lite, Xie’s approach offers a practical solution for real-time, adaptive path planning in complex scenarios. In parallel, his work on "A Hierarchical Clustering Obstacle Detection Method Applied to RGB-D Cameras" (2023, 2 citations) tackles the limitations of both deep learning and traditional vision techniques for obstacle detection. This method enhances environment perception by using hierarchical clustering to reliably identify obstacles in challenging visual conditions, a key step toward robust, low-cost autonomous systems. Xie’s research bridges theoretical planning algorithms with practical sensor-based perception, making his work highly relevant for students and engineers developing robots for logistics, service, or search-and-rescue missions.