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Instead of receiving the detailed model definition from the user, the algorithm extracts and learns the information from each object automatically. How well a model represents the template that exists in the image is measured by an energy function. Its minimum corresponds to the model that best fits with the image and it is found by a genetic algorithm that handles the model deformation. At a later stage, if there is symbolic information inside the object, it is extracted and interpreted using a neural network. The resulting perception module has been integrated successfully in a complex navigation system. Various experimental results in real environments are presented in this article, showing the effectiveness and capacity of the system.<\/jats:p>","DOI":"10.1017\/s0263574707003633","type":"journal-article","created":{"date-parts":[[2007,10,25]],"date-time":"2007-10-25T05:40:08Z","timestamp":1193290808000},"page":"99-107","source":"Crossref","is-referenced-by-count":10,"title":["Object learning and detection using evolutionary deformable models for mobile robot navigation"],"prefix":"10.1017","volume":"26","author":[{"given":"M.","family":"Mata","sequence":"first","affiliation":[]},{"given":"J. M.","family":"Armingol","sequence":"additional","affiliation":[]},{"given":"J.","family":"Fern\u00e1ndez","sequence":"additional","affiliation":[]},{"given":"A.","family":"de la Escalera","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2008,1,1]]},"reference":[{"key":"S0263574707003633_ref23","doi-asserted-by":"crossref","unstructured":"23. Valveny E. and Marti E. , \u201cApplication of Deformable Template Matching to Symbol Recognition in Handwritten Architectural Drawings,\u201d Proceedings of the Fifth International Conference on Document Analysis and Recognition (1999) pp. 483\u2013486.","DOI":"10.1109\/ICDAR.1999.791830"},{"key":"S0263574707003633_ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2005.861480"},{"key":"S0263574707003633_ref18","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008953210305"},{"key":"S0263574707003633_ref15","doi-asserted-by":"publisher","DOI":"10.1109\/70.760356"},{"key":"S0263574707003633_ref13","doi-asserted-by":"publisher","DOI":"10.1023\/A:1007432422702"},{"key":"S0263574707003633_ref11","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008821210922"},{"key":"S0263574707003633_ref10","doi-asserted-by":"publisher","DOI":"10.1109\/34.982903"},{"key":"S0263574707003633_ref20","doi-asserted-by":"publisher","DOI":"10.1177\/027836402761412467"},{"key":"S0263574707003633_ref5","unstructured":"5. 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F. , Hasboun D. , Poupon C. , Magnin I. and Frouin V. , \u201cMulti-object Deformable Templates Dedicated to the Segmentation of Brain Deep Structures,\u201d Proceedings of the Medical Image Computing and Computer Assisted Intervention, First International Conference (1998) pp. 1134\u20131143.","DOI":"10.1007\/BFb0056303"},{"key":"S0263574707003633_ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TRO.2004.839228"},{"key":"S0263574707003633_ref14","doi-asserted-by":"publisher","DOI":"10.1109\/83.753745"},{"key":"S0263574707003633_ref24","first-page":"749","article-title":"Color landmark based self-localization for indoor mobile robots","volume":"7","author":"Yoon","year":"2001","journal-title":"J. Control Autom. Syst. 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