Publicación:
Mobile Robot Path Planning in Complex Environments Using Ant Colony Optimization Algorithm

dc.contributor.author Uriol, R es_PE
dc.contributor.author Moran, A es_PE
dc.date.accessioned 2024-05-30T23:13:38Z
dc.date.available 2024-05-30T23:13:38Z
dc.date.issued 2017
dc.description.abstract Ant Colony Optimization (ACO) algorithm has been applied to solve the path planning problem of mobile robot in complex environments. The algorithm parameters have been analysed and tuned for different working areas with obstacles in different number, sizes and shapes. Also, the performance of ACO algorithm was tested for different resolutions of working area representations. In all cases, it was possible to find optimal or near-optimal minimum-length paths from the initial to final desired positions without collision with obstacles or wall-borders.
dc.description.sponsorship Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica - Concytec
dc.identifier.doi https://doi.org/10.1109/ICCAR.2017.7942653
dc.identifier.isi 404256400003
dc.identifier.uri https://hdl.handle.net/20.500.12390/1204
dc.language.iso eng
dc.publisher International Conference on Control, Automation and Robotics (ICCAR)
dc.rights info:eu-repo/semantics/openAccess
dc.subject path planning
dc.subject ant colony optimization es_PE
dc.subject mobile robots es_PE
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#4.03.00
dc.title Mobile Robot Path Planning in Complex Environments Using Ant Colony Optimization Algorithm
dc.type info:eu-repo/semantics/conferenceObject
dspace.entity.type Publication
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