AirLoc: Mobile Robots Assisted Indoor Localization

People carry smartphones that have a variety of radios and sensors. Increasingly, smartphone applications use the radios and sensors to determine a user's location and to sense motion. Nevertheless, most existing smartphone applications cannot avoid accumulative errors when calculating position and movement. In this paper, we propose a novel approach, AirLoc Adopting mobile robots to assist indoor Localization of smartphones. A moving robot employs a Bluetooth adapter and a known map to assist a smartphone to reduce its localization error. When a robot is near a smartphone, the robot sends accurate location information to users' smartphones via Bluetooth. We design a path planning strategy for a robot to enhance the localization accuracies of smartphones over extended time periods. Moreover, in order to promote the single robot approach, we extend it to the multi-robot assisted indoor localization. The multirobots are organized by an unbalanced tree and serve areas by the Distance/ Density First Algorithm. Through experimentation and simulation in a multi-room building, we evaluate AirLoc and believe it is promising as a cost-efficient means to yield average positioning error below 0.9 meter and possibly lead to better localization results for some scenarios, including shopping mall and hospital.