Yuxiao Li

University of Chinese Academy of Sciences

Papers

Total Citations

H-Index

About

Yuxiao Li’s research focuses on autonomous robot navigation and multi-sensor fusion, with a particular emphasis on environmental perception for safe, real-world mobility. Their most cited work, “A method of cliff detection in robot navigation based on multi-sensor” (2020, 2 citations), introduces a novel approach that integrates RGB-D camera data with LiDAR to detect cliff edges—a critical challenge for robots operating in unstructured or uneven terrains. By fusing visual depth information with laser range data, Li’s method enables robots to autonomously identify drop-offs and adjust their paths accordingly, enhancing both exploration capabilities and operational safety. This contribution addresses a key limitation of earlier systems that relied solely on sonar or infrared sensors, which often struggled with accuracy in complex environments. While still early in their career, Li’s work demonstrates a clear commitment to bridging sensor modalities for robust robotic perception. Their research holds promise for applications in search-and-rescue, planetary exploration, and autonomous vehicles, where reliable terrain assessment is essential. As the field moves toward more adaptive and context-aware robots, Li’s multi-sensor fusion framework offers a practical foundation for future advancements in autonomous navigation.