Demo Abstract: Real-Time 3D Indoor Localization with Multi-Dimensional RSSI on Mobile Robot

Indoor localization technology based on the Received Signal Strength Indicator (RSSI) holds significant practical promise for mobile robots. However, accuracy is directly diminished due to the challenge of precisely establishing correlations among 3D positional data (buildings, floors, and coordinates) from RSSI, as well as RSSI fluctuations caused by numerous signal interferences. This demonstration proposes MMLoc, a 3D indoor localization system for mobile robots. To enhance positional features, MMLoc reshapes one-dimensional RSSI data into images and jointly utilizes them as inputs to a prediction model. To further optimize the model's performance, the building prediction task works as a prerequisite for floor and coordinate prediction tasks, followed by staged feature extraction and multidimensional data fusion. Experimental results on a JetBot demonstrate that MMLoc has achieved high-precision 3D indoor localization.