Papers
1
Total Citations
18
H-Index
1
About
Tao Xi is a researcher in autonomous robotics, with a primary focus on stereo vision systems for unmanned ground vehicles (UGVs). His work addresses a critical gap in obstacle detection: while positive obstacles like walls and rocks have been extensively studied, negative obstacles such as ditches, potholes, and drop-offs remain a significant challenge for safe autonomous navigation. Xi’s most cited paper, "Stereo vision based negative obstacle detection" (2017, 18 citations), introduces a novel approach to identifying these hazards using stereo camera data, enhancing the perception capabilities of UGVs in unstructured environments. This contribution is particularly valuable for applications in search and rescue, agricultural robotics, and military operations, where terrain hazards can be fatal to autonomous systems. By advancing negative obstacle detection, Xi has helped bridge a key gap in UGV safety and reliability. His work continues to influence researchers developing robust, real-world autonomous navigation systems, and his findings are cited by those working to improve perception in challenging off-road conditions.
Research Focus
Key Achievements
Top Papers
- 1Stereo vision based negative obstacle detection18 citations · 2017