Weiping Guo
Papers
1
Total Citations
2
H-Index
1
About
Weiping Guo is a researcher focused on advancing indoor positioning and mobile robotics, with a particular emphasis on sensor fusion and signal processing. Their most cited work, "Research on multi-sensor assisted WiFi signal fingerprint indoor location method based on extended Kalman filter" (2022), addresses critical challenges in mobile robot localization—namely, the instability of WiFi signal fingerprinting and the low accuracy of single-sensor approaches. Guo proposes a novel multi-sensor fusion method that integrates WiFi signals with additional sensor data using an extended Kalman filter, significantly enhancing positioning stability and precision. Although this key paper has garnered 2 citations to date, it represents a foundational step in improving real-world navigation for autonomous systems. Guo’s contributions lie at the intersection of indoor localization, sensor integration, and robotics, offering practical solutions for environments where GPS is unavailable. Their work is particularly relevant for researchers and students exploring robust, low-cost localization techniques, and it holds promise for applications in warehouse automation, assistive robotics, and smart environments.
Research Focus
Key Achievements
Top Papers
- 1