Xiaotian Wang
Papers
5
Total Citations
139
H-Index
4
About
Xiaotian Wang is a leading researcher in autonomous robotics, with a primary focus on simultaneous localization and mapping (SLAM) and multi-robot path planning, particularly in challenging underwater and dynamic environments. His major contributions include developing robust visual SLAM methods, such as an improved adaptive ORB-SLAM that enhances localization accuracy in dynamic scenes by filtering moving objects, and a map-point reliability-based approach that boosts system stability. In multi-robot systems, Wang pioneered a real-time path planning method using an enhanced Dragonfly Algorithm, enabling efficient navigation for heterogeneous robot teams in unknown 3D spaces. His work extends to underwater perception, with a recent hybrid U-Net-Transformer model for image enhancement that addresses light absorption and scattering. Wang’s research has garnered over 140 citations, with his 2023 overview of underwater SLAM technologies being particularly influential, earning 61 citations. His achievements include advancing SLAM from ideal conditions to real-world, dynamic, and degraded environments, bridging critical gaps in marine robotics and archaeological applications.
Research Focus
Key Achievements
Top Papers
- 1An Overview of Key SLAM Technologies for Underwater Scenes61 citations · 2023
- 2
- 3
- 4
- 5