Simultaneous fingerprinting and mapping for multimodal image and WiFi indoor positioning
In this paper, we propose an end-to-end system which can be used to simultaneously generate (a) 3D models and associated 2D floor plans and (b) multiple sensor e.g. WiFi and imagery signature databases for the large scale indoor environments in a fast, automated, scalable way. We demonstrate ways of recovering the position of a user carrying a mobile device equipped with a camera and WiFi sensor in an indoor environment. The acquisition system consists of a man portable backpack of sensors carried by an operator inside buildings walking at normal speeds. The sensor suite consists of laser scanners, cameras and an IMU. Particle filtering algorithms are used to recover 2D and 3D path of the operator, a 3D point cloud, the 2D floor plan, and 3D models of the environment. The same walkthrough that produces 2D maps also generates multi-modal sensor databases, in our case WiFi and imagery. The resulting WiFi database is generated much more rapidly than existing systems due to continuous, rather than stop-and-go or crowd-sourced WiFi signature acquisition. We also use particle filtering algorithms in an Android application to combine inertial sensors on the mobile device, with 2D maps and WiFi and image sensor databases to localize the user. Experimental for the second floor of the electrical engineering building at UC Berkeley campus show that our system achieves an average localization error of under 2m.