<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>5</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Marta Marron</style></author><author><style face="normal" font="default" size="100%">Miguel Angel Sotelo</style></author><author><style face="normal" font="default" size="100%">Garcia, Juan Carlos</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">A PROBABILISTIC MULTIMODAL ALGORITHM FOR TRACKING MULTIPLE AND DYNAMIC OBJECTS</style></title><secondary-title><style face="normal" font="default" size="100%">ROBOTICS: TRENDS, PRINCIPLES AND APPLICATIONS</style></secondary-title><tertiary-title><style face="normal" font="default" size="100%">Intelligent Automation and Soft Computing</style></tertiary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Crowded Environments</style></keyword><keyword><style  face="normal" font="default" size="100%">Multi-Object Tracking</style></keyword><keyword><style  face="normal" font="default" size="100%">Particle Filters</style></keyword><keyword><style  face="normal" font="default" size="100%">Probabilistic Algorithms</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2004</style></year><pub-dates><date><style  face="normal" font="default" size="100%">07/2004</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">https://geintra-uah.org/system/files/isora-066.pdf</style></url></related-urls></urls><publisher><style face="normal" font="default" size="100%">TSI Press</style></publisher><pub-location><style face="normal" font="default" size="100%">Alburquerque (USA)</style></pub-location><volume><style face="normal" font="default" size="100%">15</style></volume><pages><style face="normal" font="default" size="100%">511-516</style></pages><isbn><style face="normal" font="default" size="100%">1-889335-21-5</style></isbn><language><style face="normal" font="default" size="100%">English</style></language><abstract><style face="normal" font="default" size="100%">The work presented is related to the research area of autonomous navigation for mobile robots in unstructured, heavily crowded, and highly dynamic environments. One of the main tasks involved in this research topic is the obstacle tracking module that has been successfully developed with different kind of probabilistic algorithms. The reliability that these techniques have shown estimating position with noisy measurements make them the most adequate to the mentioned problem, but their high computational cost has made them only useful with few objects. In this paper a computational simple solution based on a multimodal particle filter is proposed to track multiple and dynamic obstacles in an unstructured environment and based on the noisy position measurements taken from sonar sensors.</style></abstract></record></records></xml>