Papers
2
Total Citations
34
H-Index
2
About
Chade Lv is a leading researcher in mobile robot navigation and multi-sensor fusion positioning, with a focus on overcoming the limitations of single-sensor systems in complex indoor environments. Their major contributions include the development of a mobile robot integrated navigation algorithm that synergizes template matching visual odometry (VO), inertial measurement units (IMU), and ultra-wideband (UWB) technology. This work addresses critical challenges in UWB-based positioning, such as non-line-of-sight errors, multipath interference, and signal attenuation, achieving robust localization where traditional methods falter. Additionally, Lv advanced monocular visual odometry by replacing the restrictive Ackerman steering model with template matching techniques, enhancing accuracy and adaptability for mobile robots. Their most-cited papers—"Mobile Robot Integrated Navigation Algorithm Based on Template Matching VO/IMU/UWB" (18 citations) and "Monocular Visual Odometry Using Template Matching and IMU" (16 citations)—demonstrate significant impact in the field, providing foundational solutions for autonomous navigation. Lv’s work is notable for its practical application in indoor robotics, offering reliable positioning systems that integrate multiple data sources to mitigate environmental uncertainties. Their research continues to influence the development of resilient, sensor-fusion-based navigation technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2Monocular Visual Odometry Using Template Matching and IMU16 citations · 2021