Yuanbin Xiao
Papers
2
Total Citations
4
H-Index
2
About
Yuanbin Xiao is a leading researcher in intelligent robotics and autonomous navigation for extreme industrial environments, with a primary focus on open-pit mining applications. His work centers on advancing Simultaneous Localization and Mapping (SLAM) algorithms, particularly through the fusion of visual and inertial measurement unit (IMU) data to overcome the unique challenges posed by complex, unstructured terrains. Xiao’s major contributions include the development of a robust visual–inertial SLAM algorithm that maintains high localization accuracy despite significant pitch variations, uneven highways, and low-texture rocky surfaces—conditions that typically degrade conventional systems. He further enhanced this work by introducing an optimized dense mapping algorithm with improved point-line feature extraction, building upon the ORB-SLAM3 framework to address sparse point cloud maps and boost localization precision. His 2024 and 2025 papers, each garnering 2 citations in their early publication stage, are already recognized as foundational references for deploying mobile robots in open-pit mines. Xiao’s research bridges a critical gap between theoretical SLAM advances and real-world industrial deployment, making him a key figure in the future of autonomous mining technology.
Research Focus
Key Achievements
Top Papers
- 1
- 2