Cheng-Hsun Xie
Papers
1
Total Citations
4
H-Index
1
About
Cheng-Hsun Xie is a researcher whose work lies at the intersection of robotics, computer vision, and sensor fusion, with a particular focus on enabling autonomous systems to perceive and map complex environments. His most notable contribution is the development of a sensor fusion-based vSLAM (visual simultaneous localization and mapping) system that integrates stereo vision and sonar data to construct detailed 3D environment grid maps. This work, published in 2013, addresses a critical challenge in robotics: the inability of stereo cameras to handle large textureless areas, which often cause mapping failures. By fusing sonar data with visual inputs, Xie’s system achieves robust and accurate 3D reconstruction, even in visually sparse environments. Though his highly specialized work has garnered modest citation counts, it represents a foundational step in practical, low-cost robotic navigation and mapping. Xie’s contributions are particularly relevant for researchers and engineers developing autonomous mobile robots for indoor exploration, search-and-rescue operations, or industrial inspection, where reliable spatial awareness in challenging conditions is paramount.
Research Focus
Key Achievements
Top Papers
- 1