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[Other resourceGA(C+)

Description: 遗传算法的机器人路径规划的源代码。用C++来实现的-GA robot path planning source. C to achieve the
Platform: | Size: 15977 | Author: 宋磊 | Hits:

[AI-NN-PRGA(C+)

Description: 遗传算法的机器人路径规划的源代码。用C++来实现的-GA robot path planning source. C to achieve the
Platform: | Size: 475136 | Author: 宋磊 | Hits:

[AI-NN-PRGAPathfinder

Description: 使用遗传算法的走迷宫程序。适合新手学习GA使用-use of genetic algorithms Maze procedure. Suitable for novice learning to use GA
Platform: | Size: 24576 | Author: DL | Hits:

[matlabGA

Description: 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
Platform: | Size: 40960 | Author: kevin | Hits:

[BooksUsing_Genetic_Algorithms_for_Robot_Motion_Planning

Description: 实用GA算法进行,机器人运功规划,算法很经典,美国人写的-We present an ongoing research work on robot motion plan- ning using genetic algorithms. Our goal is to use this technique to build fast motion planners for robot with six or more degree of freedom. After a short review of the existing methods, we will introduce the genetic al- gorithms by showing how they can be used to solve the invers kinematic problem. In the second part of the paper, we show that the path planning problem can be expressed as an optimization problem and thus solved with a genetic algorithm. We illustrate the approach by building a path planner for a planar arm with two degree of freedom, then we demon- strate the validity of the method by planning paths for an holonomic mobile robot. Finally we describe an implementation of the selected ge- netic algorithm on a massively parallel machine and show that fast plan- ning response is made possible by using this appro
Platform: | Size: 408576 | Author: xiaofang | Hits:

[AI-NN-PRpathing-planning-GA

Description: 用遗传算法实现对机器人的路径规划,取各障碍物顶点连线的中点为路径点,相互连接各路径点,将机器人移动的起点和终点限制在各路径点上,利用最短路径算法来求网络图的最短路径,找到从起点P1到终点Pn的最短路径。-Robot path planning using genetic algorithms, taking the midpoint of each obstacle vertex path points interconnected path the robot to move the start and end restrictions on each path point, using the shortest path algorithm to seek the shortest path to the network diagram, find the shortest path from the starting point P1 to the end of Pn.
Platform: | Size: 67584 | Author: 郭美亭 | Hits:

[matlabdastebandi

Description: Design a feedforward network is u dehaze algorithms review path planning using GA and ACO... The neural network adaboost stron TS neural network m files, fast c bp neural network, written with C Bayes net and memory based learni Design a fuzzy control system to This is a book about fuzzy system Cloud adaptive genetic algorithm BP neural network and RBF neural use a three-layers BP network to Professor Lin in Taiwan support v neural network theory Practical matlab time series ar m efficient robot path planning-pub A population-based artificial imm A description of the neural netwo Clustering AHC, K-means, SOM--Design a feedforward network is u dehaze algorithms review path planning using GA and ACO... The neural network adaboost stron TS neural network m files, fast c bp neural network, written with C Bayes net and memory based learni Design a fuzzy control system to This is a book about fuzzy system Cloud adaptive genetic algorithm BP neural network and RBF neural use a three-layers BP network to Professor Lin in Taiwan support v neural network theory Practical matlab time series ar m efficient robot path planning-pub A population-based artificial imm A description of the neural netwo Clustering AHC, K-means, SOM-NN
Platform: | Size: 91136 | Author: mohsen | Hits:

[matlabestekhraj-vijegi

Description: Design a feedforward network is u dehaze algorithms review path planning using GA and ACO... The neural network adaboost stron TS neural network m files, fast c bp neural network, written with C Bayes net and memory based learni Design a fuzzy control system to This is a book about fuzzy system Cloud adaptive genetic algorithm BP neural network and RBF neural use a three-layers BP network to Professor Lin in Taiwan support v neural network theory Practical matlab time series ar m efficient robot path planning-pub A population-based artificial imm A description of the neural netwo Clustering AHC, K-means, SOM--Design a feedforward network is u dehaze algorithms review path planning using GA and ACO... The neural network adaboost stron TS neural network m files, fast c bp neural network, written with C Bayes net and memory based learni Design a fuzzy control system to This is a book about fuzzy system Cloud adaptive genetic algorithm BP neural network and RBF neural use a three-layers BP network to Professor Lin in Taiwan support v neural network theory Practical matlab time series ar m efficient robot path planning-pub A population-based artificial imm A description of the neural netwo Clustering AHC, K-means, SOM-NN
Platform: | Size: 13312 | Author: mohsen | Hits:

[matlabGA_Path_Planning

Description: 使用遗传算法(genetic algorithm)进行路径规划,得出移动机器人的最优运动路径,,欢迎大家下载,并互相交流,共同学习,共同进步-path planning based genetic algorithm(GA) can get the optimal path of mobile robot
Platform: | Size: 67584 | Author: ljw | Hits:

[assembly languagepath-planning--based-on-GA

Description: path planning of the robot based on GA,matlab
Platform: | Size: 68608 | Author: -DYlan-12306 | Hits:

[AI-NN-PRGA

Description: This code solves robot path planning using pso.
Platform: | Size: 183296 | Author: viktrose | Hits:

[matlabGAforPathPlaning

Description: 采用栅格对机器人的工作空间进行划分,再利用优化算法对机器人路径优化,是采用智能算法求最优路径的一个经典问题。目前,采用蚁群算法在栅格地图上进行路径优化取得比较好的效果,而利用遗传算法在栅格地图上进行路径优化在算法显得更加难以实现。 利用遗传算法处理栅格地图的机器人路径规划的难点主要包括:1保证路径不间断,2保证路径不穿过障碍。 用遗传算法解决优化问题时的步骤是固定的,就是种群初始化,选择,交叉,变异,适应度计算这样,那么下面我就说一下遗传算法求栅格地图中机器人路径规划在每个步骤的问题、难点以及解决办法。(It is a classical problem to divide the workspace of the robot by grids and optimize the path of the robot by using optimization algorithm. At present, the ant colony algorithm is used to optimize the path on the grid map, and the genetic algorithm is used to optimize the path on the grid map, which is more difficult to achieve. The difficulties of using genetic algorithm to deal with the path planning of robot on raster map mainly include: 1. guaranteeing that the path is uninterrupted, 2. guaranteeing that the path does not cross obstacles. The steps of genetic algorithm in solving optimization problems are fixed, that is, population initialization, selection, crossover, mutation, fitness calculation. Then I will talk about the problems, difficulties and solutions of genetic algorithm in each step of robot path planning in raster map.)
Platform: | Size: 5120 | Author: adkuhd8wy | Hits:

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