A comparison of optimization techniques for AUV path planning in environments with ocean currents

• A QPSO algorithm is introduced for AUV path planners.
• Important optimization techniques applied to AUV path planning are compared in several test scenarios.
• Monte Carlo trials were also run to analyse the performance of these optimization techniques.
• The weaknesses and strengths of each optimization technique have been stated.

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.