Please use this identifier to cite or link to this item: http://www.repositorio.ufc.br/handle/riufc/64665
Title in Portuguese: Path planning of mobile robot with growing neural gas andant colony optimization
Title: Path planning of mobile robot with growing neural gas andant colony optimization
Author: Costa, Thiago Azevedo Campos
Magalhães Filho, Claudio César Martins
Gomes, Allan Costa
Forte, Marcus Davi do Nascimento
Lima, Thiago Alves
Ferreira, Vinicius dos Reis Alves
Correia, Wilkley Bezerra
Braga, Arthur Plínio de Souza
Keywords: Self-Organizing Maps
Metaheuristics
Artificial intelligence
Path planning
Mobile robot
Issue Date: 2018
Publisher: Sociedade Brasileira de Automática – SBA - https://www.sba.org.br/
Citation: COSTA, Thiago Azevedo Campos; MAGALHAES FILHO, Claudio Cesar Martins; GOMES, Allan Costa; FORTE, Marcus Davi do Nascimento; LIMA, Thiago Alves; FERREIRA, Vinicius dos Reis Alves; CORREIA, Wilkley Bezerra; BRAGA, Arthur Plínio de Souza. Path planning of mobile robot with growing neural gas andant colony optimization.In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, XXII., 9 a 12 set., 2018, João Pessoa - PB - Brasil. Anais[…], Campinas, Galoá, v.1, n. 1 (2019): CBA2018.
Abstract: This paper presents a new path planning strategy obtained from the combination between Growing Neural Gas (GNG) and Ant Colony Optimization (ACO) algorithms. The proposed strategy was tested in a real mobile robot for two di erent scenarios and compared with the APF approach. Positive and negative points of the proposed strategy are highlighted throughout the text. As one positive point, the proposed path planning strategy presented a better end positioning of the robot in comparison with APF in the performed tests - an aspect of great interest for practical applications in industry and medical area.
URI: http://www.repositorio.ufc.br/handle/riufc/64665
metadata.dc.type: Artigo de Evento
ISSN: 2525-8311
Appears in Collections:DEEL - Trabalhos apresentados em eventos

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