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- W4376454037 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." @default.
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- W4376454037 date "2012-09-01" @default.
- W4376454037 modified "2023-10-17" @default.
- W4376454037 title "Application of GA, PSO, and ACO algorithms to path planning of autonomous underwater vehicles" @default.
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- W4376454037 doi "https://doi.org/10.1007/s11804-012-1146-x" @default.
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