In this paper, we propose a multi-sensor fusion algorithm based on particle filters for mobile robot localisation in crowded environments. Our system is able to fuse the information provided by sensors placed on-board, and sensors external to the robot (off-board). We also propose a methodology for fast system deployment, map construction, and sensor calibration with a limited number of training samples. We validated our proposal experimentally with a laser range-finder, a WiFi card, a magnetic compass, and an external multi-camera network. We have carried out experiments that validate our deployment and calibration methodology. Moreover, we performed localisation experiments in controlled situations and real robot operation in social events. We obtained the best results from the fusion of all the sensors available: the precision and stability was sufficient for mobile robot localisation. No single sensor is reliable in every situation, but nevertheless our algorithm works with any subset of sensors: if a sensor is not available, the performance just degrades gracefully.
Keywords: Robot localisation, WiFi localisation, Multi-camera network, Particle filter, Sensor fusion