Journal
ROBOTICS AND AUTONOMOUS SYSTEMS
Volume 82, Issue -, Pages 61-72Publisher
ELSEVIER
DOI: 10.1016/j.robot.2016.03.011
Keywords
Autonomous underwater vehicle; Path planning; Optimization
Funding
- National Natural Science Foundation of China (NSFC) [51279107]
- Open project of State Key Laboratory of Ocean Engineering, Shanghai Jiao Tong University [GKZD010067]
- Research Fund for Science and Technology Commission of Shanghai Municipality (STCSM) [13dz1204600]
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To date, a large number of optimization algorithms have been presented for Autonomous Underwater Vehicle (AUV) path planning. However, little effort has been devoted to compare these techniques. In this paper, an quantum-behaved particle swarm optimization (QPSO) algorithm is introduced for solving the optimal path planning problem of an AUV operating in environments with ocean currents. An extensive study of the most important optimization techniques applied to optimize the trajectory for an AUV in several test scenarios is presented. Extensive Monte Carlo trials were also run to analyse the performance of these optimization techniques based on solution quality and stability. The weaknesses and strengths of each technique have been stated and the most appropriate algorithm for AUV path planning has been determined. (C) 2016 Elsevier B.V. All rights reserved.
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