Papers
1
Total Citations
35
H-Index
1
About
Baolai Xu is a leading researcher in mobile robotics, with a primary focus on sensor fusion and autonomous navigation. His most influential work tackles the fundamental challenge of global localization—estimating a robot’s position within a known map without any prior pose information. In his highly cited 2017 paper, Xu pioneered a novel approach that integrates lidar and visual features to achieve robust localization even when only sparse lidar scans are available, a scenario that often defeats traditional methods in simple or repetitive environments. This work has garnered 35 citations, underscoring its impact on the field. By combining the strengths of two distinct sensing modalities, Xu’s research enables robots to reliably determine their location under difficult conditions, advancing the practical deployment of autonomous systems in real-world settings. His contributions are essential reading for students and researchers working on sensor-based localization, offering a clear path forward for overcoming the limitations of single-sensor approaches.
Research Focus
Key Achievements
Top Papers
- 1Global localization of a mobile robot using lidar and visual features35 citations · 2017