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这个一个遗传算法的实例，可以解决机器人轨迹规划的问题-This example of a genetic algorithm, can solve the problem of robot path planning
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This project is about implementing a world model that allows the path planning algorithm to query if a certain point in space is free from obstacles. -Planning a path from one point of the environment to another while avoiding collisions with the env
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遗传算法路径规划仿真,运用遗传算法仿真机器人路径规划问题，属于静态规划-Genetic algorithm path planning simulation, using genetic algorithms simulation robot path planning problem, belongs to the static planning
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利用遗传算法解决机器人路径规划问题,较好的一个例程，在VC++平台下开发-Using the genetic algorithm to solve robot path planning problem, the better a routine in VC++ platform development
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A large number of real-world planning problems called combinatorial
optimization problems share the following properties: They are optimiza-
tion problems, are easy to state, and have a nite but usually very large
number of feasible solutions.
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用matlab程序编写的遗传算法路径规划程序用来实现最短路径问题。-Programming using genetic algorithm matlab path planning process used to achieve the shortest path problem.
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此段程序是一套完整的设计程序（包括拓扑图、分析表），运用遗传算法优化解决路径规划问题。-The procedures of this section is a complete set of design procedures (including topology, analysis, table), the use of genetic algorithm optimization to solve the path planning problem.
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基于势场法的机器人路径规划问题。机器人利用势力场避开障碍物到达目标点位置。-Based on the potential field method for robot path planning problem. Robot to avoid obstacles to reach the target position forces field.
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蚁群算法,路径规划问题，通过迭代寻找全局最优解-Ant colony algorithm, path planning problem, find the global optimal solution through iteration
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应用A*算法解决八自由度迷宫问题，具有地图读入写出功能，可以扩展应用到路径规划问题。-Application of A* algorithm to solve the eight DOF maze problem with map reading into the write function, can be extended to the path planning problem.
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实现简单路径规划问题，也可以说是旅行商问题，货郎担问题 -Simple path planning problem is the traveling salesman problem, traveling salesman problem
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matlab编写的用于二维的巡航路径规划问题，采用的蚁群算法-matlab prepared for the two-dimensional cruise path planning problem, the use of ant colony algorithm. .
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机器人障碍环境下路径规划问题，采用改进的回退蚁群算法，matlab版源代码，有可视化界面。-Robot obstacle environment path planning problem, using an improved back colony algorithm, matlab version of the source code, visual interface.
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经典的基于GA遗传算法的路径规划问题的实现，能动态的实现所需功能，值得学习研究-The path planning problem of GA based on genetic algorithm classic, can realize the dynamic functions are required, it is worth learning research
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(不错的一篇文章，已被EI收录)模型预测控制（model predictive control，MPC）路径规划算法适用于三维动态环境下的无人机（un-manned aerial vehicle，UAV）路径规划；动态贝叶斯网络（dynamic Bayesian network，DBN）能够有效推理战场态势，对无人机进行威胁评估。针对威胁尾随无人机时的路径规划问题，构建 DBN 威胁评估模型，将 UAV 在战场环境中的威胁态势用威胁等级概率表示，与 MPC 路径规划算法相结合，得到基于 DBN
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针对自治水下机器人(AUV)的路径规划问题进行了研究,依据模糊控制规则,提出了一种基于粒子群优化(PSO)的模糊路径规划算法.首先建立水下水平面内路径规划的模糊规则,并应用A/B模型进行静态和动态障碍物的避障.同时考虑到模糊边界的选择具有很大的随意性,所生成的路径并非最优,利用PSO算法进行模糊集合的优化,使得最终生成的路径最优.应用设计的粒子群优化模糊(PSO-fuzzy)算法针对动静态障碍物进行了避障路径规划,仿真结果验证了所设计的方法的有效性.-The study was conducte
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基于蚁群算法的机器人路径规划。使用网格离散化的方法对带有障碍物的环境建模，使用邻接矩阵存储该环境，使得问题转化为蚁群算法寻找最短路径。-Robot path planning based on ant colony algorithm. Use grid discretization methods with obstacles environment modeling, the use of adjacency matrix to store the environment, the prob
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Path Planning using A star method(Using LabVIEW to deal with the path planning problem)
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基于传统的人工势场法实现的路径规划问题，可以躲避障碍物(The path planning problem based on the traditional artificial potential field method can avoid obstacles)
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针对自治水下机器人(AUV)的路径规划问题进行了研究,依据模糊控制规则,提出了一种基于粒子群优化(PSO)的模糊路径规划算法(The path planning problem of autonomous underwater vehicle (AUV) is studied. According to the fuzzy control rules, a fuzzy path planning algorithm based on particle swarm optimization (PS
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