  Simultaneous localization and mapping (SLAM) has been richly researched in
past years particularly with regard to range-based or visual-based sensors.
Instead of deploying dedicated devices that use visual features, it is more
pragmatic to exploit the radio features to achieve this task, due to their
ubiquitous nature and the wide deployment of Wifi wireless network. In this
paper, we present a novel approach for crowd-sensing simultaneous localization
and radio fingerprint mapping (C-SLAM-RF) in large unknown indoor environments.
The proposed system makes use of the received signal strength (RSS) from
surrounding Wifi access points (AP) and the motion tracking data from a smart
phone (Tango as an example). These measurements are captured duration the
walking of multiple users in unknown environments without map information and
location of the AP. The experiments were done in a university building with
dynamic environment and the results show that the proposed system is capable of
estimating the tracks of a group of users with an accuracy of 1.74 meters when
compared to the ground truth acquired from a point cloud-based SLAM.
