Robot-assisted human indoor localization using the Kinect sensor and smartphones

Human indoor localization was previously implemented using wireless sensor networks at the cost of sensing infrastructure deployment. Motivated by high density of smartphones in public spaces, we propose to use a robot-assisted localization system in which the low-cost Kinect sensor and smartphone-based acoustic relative ranging are used to localize moving human targets in indoor environments. An extended Kalman filter based localization algorithm is developed for real-time dynamic position estimation. We present both simulations and real robot-smartphone experiments demonstrating the performance with a localization accuracy of approximately 0.5m.