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 Mohammad Pourmahmood Aghababa,Mohammad Hossein Amrollahi and Mehdi Borjkhani.Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles[J].Journal of Marine Science and Application,2012,(3):378-386.[doi:10.1007/s11804-012-1146-x]
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Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles


Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles
Mohammad Pourmahmood Aghababa Mohammad Hossein Amrollahi and Mehdi Borjkhani
Mohammad Pourmahmood Aghababa Mohammad Hossein Amrollahi and Mehdi Borjkhani
Electrical Engineering Department, Urmia University of Technology, Urmia 51766, Iran
path planning autonomous underwater vehicle genetic algorithm (GA) particle swarm optimization (PSO) ant colony optimization (ACO) collision avoidance
In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a numerical solution of a nonlinear optimal control problem (NOCP). An energy performance index as a cost function, which should be minimized, was defined. The resulting problem was a two-point boundary value problem (TPBVP). A genetic algorithm (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.


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Last Update: 2012-09-06