Using evolutionary algorithms to plan automatic minehunting operations

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Abreu, N (Author) Other; Aníbal Castilho Coimbra de Matos (Author) FEUP

Conference proceedings International

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

Pages: 228-235

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

1 September 2014 through 3 September 2014

Indexing

Scopus - 0 Citations

Other information

Authenticus ID: 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.

Language: English

Type (Professor's evaluation): Scientific