Indoor positioning of wheeled devices for Ambient Assisted Living: A case study

Indoor navigation is a well-known research topic whose relevance has been steadily growing in the last years thrust by considerable commercial interests as well as by the need for supporting and guiding users in large public environments, such as stations, airports or shopping malls. People with motion or cognitive impairments could perceive large crowded environments as intimidating. In such situations, a smart wheeled walker able to estimate its own position autonomously could be used to guide users safely towards a wanted destination. Two strong requirements for this kind of applications are: low deployment costs and the capability to work in large and crowded environments. The position tracking technique presented in this paper is based on an Extended Kalman Filter (EKF) and is analyzed through simulations in view of minimizing the amount of sensors and devices in the environment. © 2014 IEEE.