A CBR System for autonomous robot navigation

Raquel Ros, Ramon López De Màntaras, Carles Sierra, Josep Lluís Arcos

Producció científica: Capítol de llibreContribució a congrés/conferènciaAvaluat per experts

15 Cites (Scopus)


In this paper we propose the use of case-based reasoning techniques to improve the navigation of an autonomous robot in unknown semistructured environments. At the moment the current goal is to identify problematic situations (such as dead ends or obstacle layouts that the robot is not able to avoid) and take the proper actions in order to avoid them. As the first steps we propose a similarity function to retrieve similar past cases. We integrate a CBR agent into an existing multiagent navigation system in order to evaluate the performance of the CBR system. The results obtained through simulation show that the new system not only prevents the robot from getting blocked in certain situations, but also improves the performance in terms of time and distance of the path taken to reach the target.

Idioma originalAnglès
Títol de la publicacióArtificial Intelligence Research and Development
EditorsBeatriz Lopez, Joaquim Melendez, Petia Radeva, Jordi Vitria
EditorIOS Press BV
Nombre de pàgines8
ISBN (imprès)1586035606, 9781586035600
Estat de la publicacióPublicada - 2005
Publicat externament
Esdeveniment8th Catalan Conference on Artificial Intelligence, CCIA 2005 - Alguer, Italy
Durada: 26 d’oct. 200528 d’oct. 2005

Sèrie de publicacions

NomFrontiers in Artificial Intelligence and Applications
ISSN (imprès)0922-6389
ISSN (electrònic)1879-8314


Conferència8th Catalan Conference on Artificial Intelligence, CCIA 2005


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