An evolutionary approach for the design of autonomous underwater vehicles

  • Authors:

  • Khairul Alam;Tapabrata Ray;Sreenatha G. Anavatti

  • Affiliations:

  • School of Engineering and Information Technology, University of New South Wales, UNSW, Canberra, ACT, Australia;School of Engineering and Information Technology, University of New South Wales, UNSW, Canberra, ACT, Australia;School of Engineering and Information Technology, University of New South Wales, UNSW, Canberra, ACT, Australia

  • Venue:
  • AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
  • Year:
  • 2012

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Abstract

Autonomous underwater vehicles (AUVs) are becoming an attractive option for increasingly complex and challenging underwater search and survey operations. To meet the emerging demands of AUV mission requirements, design and tradeoff complexities, there is an increasing interest in the use of multidisciplinary design optimization (MDO) strategies. While optimization techniques have been applied successfully to a wide range of applications spanning various fields of science and engineering, there is very limited literature on optimization of AUV designs. Presented in this paper is an evolutionary approach for the design optimization of AUVs using two stochastic, population based optimization algorithms. The proposed approach is capable of modelling and solving single and multi-objective constrained formulations of the AUV design problems based on different user and mission requirements. Two formulations of the AUV design problem are considered to identify designs with minimum drag and internal clash-free assembly. The flexibility of the proposed scheme and its ability to identify optimum preliminary designs are highlighted in this paper.