Wasik, Alicja BarbaraVentura, RodrigoPereira, Jose N.Lima, Pedro U.Martinoli, Alcherio2016-01-292016-01-292016-01-29201510.1007/978-3-319-27146-0_1https://infoscience.epfl.ch/handle/20.500.14299/122822WOS:000370651600001Relative positioning systems play a vital role in current multi-robot systems. We present a self-contained detection and tracking approach, where a robot estimates a distance (range) and an angle (bearing) to another robot using measurements extracted from the raw data provided by two laser range finders. We propose a method based on the detection of circular features with least-squares fitting and filtering out outliers using a map-based selection. We improve the estimate of the relative robot position and reduce its uncertainty by feeding measurements into a Kalman filter, resulting in an accurate tracking system. We evaluate the performance of the algorithm in a realistic indoor environment to demonstrate its robustness and reliability.Laser relative positioning systemEstimationTrackingtext::conference output::conference proceedings::conference paper