Using the Jensen-Shannon, density power, and Itakura-Saito divergences to implement an evolutionary-based global localization filter for mobile robots

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dc.contributor.author Martín Monar, Fernando
dc.contributor.author Carballeira López, Juan
dc.contributor.author Moreno Lorente, Luis Enrique
dc.contributor.author Garrido Bullón, Luis Santiago
dc.contributor.author González Prieto, Pavel Enrique
dc.date.accessioned 2022-01-18T09:47:38Z
dc.date.available 2022-01-18T09:47:38Z
dc.date.issued 2017-07-07
dc.identifier.bibliographicCitation Martin, F., Carballeira, J., Moreno, L., Garrido, S. & Gonzalez, P. (2017). Using the Jensen-Shannon, Density Power, and Itakura-Saito Divergences to Implement an Evolutionary-Based Global Localization Filter for Mobile Robots. IEEE Access, 5, 13922–13940.
dc.identifier.issn 2169-3536
dc.identifier.uri http://hdl.handle.net/10016/33898
dc.description.abstract One of the most demanding skills for a mobile robot is to be intelligent enough to know its own location. The global localization problem consists of obtaining the robot's pose (position and orientation) in a known map if the initial location is unknown. This task is addressed applying evolutionary computation concepts (Differential Evolution). In the current approach, the distances obtained from the laser sensors are combined with the predicted scan (in the known map) from possible locations to implement a cost function that is optimized by an evolutionary filter. The laser beams (sensor information) are modeled using a combination of probability distributions to implement a non-symmetric fitness function. The main contribution of this paper is to apply the probabilistic approach to design three different cost functions based on known divergences (Jensen-Shannon, Itakura-Saito, and density power). The three metrics have been tested in different experiments and the localization module performance is exceptional in regions with occlusions caused by different obstacles. This fact validates that the non-symmetric probabilistic approach is a suitable technique to be applied to multiple metrics.
dc.description.sponsorship This work was supported by the Competitive Improvement of Drilling and Blasting Cycle in Mining and Underground-Works through New Techniques of Engineering, Explosives, Prototypes, and Advanced Tools, which is a Research and Development project undertaken by the following companies: Obras Subterr a neas, MaxamCorp Holding, Putzmeister Iberica, Subterra Ingenieria, Expace On Boards Systems, Dacartec Servicios Informaticos, and Cepasa Ensayos Geotecnicos.
dc.format.extent 19
dc.language.iso eng
dc.publisher IEEE
dc.rights © 2017, IEEE.
dc.subject.other Jensen-Shannon divergence
dc.subject.other Itakura-Saito divergence
dc.subject.other Density power divergence
dc.subject.other Differential evolution
dc.subject.other Global localization
dc.subject.other Mobile robots
dc.title Using the Jensen-Shannon, density power, and Itakura-Saito divergences to implement an evolutionary-based global localization filter for mobile robots
dc.type article
dc.subject.eciencia Robótica e Informática Industrial
dc.identifier.doi https://doi.org/10.1109/ACCESS.2017.2724199
dc.rights.accessRights openAccess
dc.type.version acceptedVersion
dc.identifier.publicationfirstpage 13922
dc.identifier.publicationlastpage 13940
dc.identifier.publicationtitle IEEE Access
dc.identifier.publicationvolume 5
dc.identifier.uxxi AR/0000021458
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