Using evolutionary algorithms to plan automatic minehunting operations

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2014

Autores

Abreu, N (Autor) Outra; Aníbal Castilho Coimbra de Matos (Autor) FEUP

Ata de Conferência Internacional

Título: ICINCO 2014 - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics

Páginas: 228-235

11th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2014

1 September 2014 through 3 September 2014

Indexação

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-009-Y71

DOI: 10.5220/0005043102280235

Abstract (EN): While autonomous underwater vehicles (AUVs) are increasingly being used to perform mine countermeasures (MCM) operations, the capability of these systems is limited by the efficiency of the planning process. In this paper we study the problem of multiobjective MCM mission planning with an AUV. In order to overcome the inherent complexity of the problem, a multi-stage algorithm is proposed and evaluated. Our algorithm combines an evolutionary algorithm (EA) with a local search procedure based on simulated annealing (SA), aiming at a more flexible and effective exploration and exploitation of the search space. An artificial neural network (ANN) model was also integrated in the evolutionary procedure to guide the search. The results show that the proposed strategy can efficiently identify a higher quality solution set and solve the mission planning problem.

Idioma: Inglês

Tipo (Avaliação Docente): Científica