Leg detection and tracking for a mobile robot and based on a laser device, supervised learning and particle filtering Aguirre Molina, Eugenio García Silvente, Miguel Plata, Javier Leg detection and tracking Laser range finder Supervised learning Particle filter Mobile robots This work have been partially supported by Andalusian Regional Government project P09-TIC-04813 and the Spanish Government project TIN2012-38969. People detection and tracking is an essential skill to obtain social and interactive robots. Computer vision has been widely used to solve this task but images are affected by noise and illumination changes. Laser range finder is robust against illumination changes so that it can bring useful information to carry out the detection and tracking. In fact, multisensor approaches are showing the best results. In this work, we present a new method to detect and track people using a laser range finder. Patterns of leg are learnt from 2d laser data using supervised learning. Unlike others leg detection approaches, people can be still or moving at the surroundings of the robot. The method of leg detection is used as observation model in a particle filter to track the motion of a person. Experiments in a real indoor environment have been carried out to validate the proposal. 2023-12-22T08:34:04Z 2023-12-22T08:34:04Z 2014 conference output Published version: Aguirre, E., Garcia-Silvente, M., Plata, J. (2014). Leg Detection and Tracking for a Mobile Robot and Based on a Laser Device, Supervised Learning and Particle Filtering. In: Armada, M., Sanfeliu, A., Ferre, M. (eds) ROBOT2013: First Iberian Robotics Conference. Advances in Intelligent Systems and Computing, vol 252. Springer, Cham. [https://doi.org/10.1007/978-3-319-03413-3_31] https://hdl.handle.net/10481/86428 10.1007/978-3-319-03413-3_31 eng Advances in Intelligent Systems and Computing;252 http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Springer