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路径规划算法

于 2021-01-20 发布

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下载积分: 1 下载次数: 6

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说明：基础的路径规划算法：人工势场，构建引力场与势力场寻找最短路径(Artificial potential field)

文件列表：

机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）\A star.zip, 180804 , 2019-05-25
机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）\GA.zip, 185906 , 2019-05-25
机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）\PRM.zip, 420957 , 2019-05-25
机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）\RRT.zip, 221003 , 2019-05-25
机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）\bidirectional RRT.zip, 207864 , 2019-05-25
机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）\fuzzy.zip, 241646 , 2019-05-25
机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）\人工势场法.zip, 249596 , 2019-05-25
机器人路径规划算法合集MATLAB版（微信公众号：优化算法交流地）, 0 , 2020-02-26

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Simulated annealing (SA) is a generic probabilistic metaheuristic for the global optimization problem of applied mathematics, namely locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete (e.g., all tours that visit a given set of cities). For certain problems, simulated annealing may be more effective than exhaustive enumeration — provided that the goal is merely to find an acceptably good solution in a fixed amount of time, rather than the best possible solution.

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