Global path planning problem for autonomous underwater vehicle (AUV) based on large-scale chart data is investigated by using ant colony optimization (in shorts, ACO) algorithm.
在大范围海洋环境中，应用蚁群算法对自主式水下潜器(AUV)的全局路径规划问题进行了研究。
To solve the problem of path planning of LAUV (Long-distance Autonomous Underwater Vehicle), a path planning algorithm based on digital charts is presented.
为了解决远程自主水下机器人(LAUV)路径规划问题，提出一种基于数字海图的路径规划算法。
Frist, the constitution of AUV system is presented. Next, path planning method of AUV is discussed. Global and local path planner that shows the autonomous ability is especially introduced.
首先介绍了自行研制的智能水下机器人的系统组成，然后讨论了其规划方法，并着重介绍了体现水下智能机器人自主能力的全局规划器和局部规划器。
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