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Citation:
　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

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Title:
Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles
Author(s):
Mohammad Pourmahmood Aghababa;  Mohammad Hossein Amrollahi and Mehdi Borjkhani
Affilations:
Author(s):
Mohammad Pourmahmood Aghababa;  Mohammad Hossein Amrollahi and Mehdi Borjkhani
Electrical Engineering Department, Urmia University of Technology, Urmia 51766, Iran
Keywords:
path planning;  autonomous underwater vehicle;  genetic algorithm (GA);  particle swarm optimization (PSO);  ant colony optimization (ACO);  collision avoidance
分类号:
-
DOI:
10.1007/s11804-012-1146-x
Abstract:
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