Double-Layer Soft Data Fusion for Indoor Robot WiFi-Visual Localization
This paper presents a novel WiFi-Visual data fusion method for indoor robot (TIAGO++) localization. This method can use 10 WiFi samples and 4 low-resolution images ($58 \times 58$ in pixels) to localize a indoor robot with an average error distance about 1.
Evidence notes
- Experiments use TIAGo as the physical evaluation platform.
- The reported results provide an independent evaluation on TIAGo hardware.
Company context
Develops service and humanoid robots for research, industrial, and public-facing environments, with a focus on modular platforms and long-term deployment in real-world settings.