Design and performance analysis of an indoor position tracking technique for smart rollators

This paper presents a position tracking technique based on multisensor data fusion for rollators helping elderly people to move safely in large indoor spaces such as public buildings, shopping malls or airports. The proposed technique has been developed within the FP7 project DALi, and relies on an extended Kalman filter processing data from dead-reckoning sensors (i.e. encoders and gyroscopes), a short-range radio frequency identification (RFID) system and a front Kinect camera. As known, position tracking based on dead-reckoning sensors only is intrinsically affected by growing uncertainty. In order to keep such uncertainty within wanted boundaries, the position values are occasionally updated using a coarse-grained grid of low-cost passive RFID tags with known coordinates in a given map-based reference frame. Unfortunately, RFID tag detection does not provide any information about the orientation of the rollator. Therefore, a front camera detecting some markers on the walls is used ...