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An improved ant colony algorithm based grid environment model for global path planning method for USV was introduced. The main idea of the improved ant colony algorithm was distributing each ant route dynamically. When the active ant was selecting the next route, this algorithm program determined the nearest direction to the end point. There were many possible route points which were distributed artificially. Thereby, the probability for each ant to choose the right direction was increased. The simulating results demonstrate that the improved ant colony algorithm in this paper is very suitable for solving the question of global path planning for USV system in the complex oceanic environment where there are a lot of obstacles. At the same time, this method costs less time, and the path is very smooth.
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Chang Hui Song (2014) studied this question.
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