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 |
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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 |
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Description: 基于海图数据的AUV全局路径规划方法研究.
关键字 海图 遗传算法-Chart data based on global path planning for AUV Research Keywords charts GA Platform: |
Size: 3214336 |
Author:wanghui |
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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 |
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Description: 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 Platform: |
Size: 7168 |
Author:颜妍 |
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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:
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 |
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Description: 利用GA遗传算法进行动态路径规划，完成最优轨迹的生成，适合新手入门学习。(Using GA genetic algorithm for dynamic path planning, the completion of the optimal trajectory generation, suitable for beginners to learn.) Platform: |
Size: 2048 |
Author:smile2816
|
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Description: 如何使用matlab中程序工具箱，进行对各散点的matlab图像进行最佳路径规划。(How to use matlab program toolbox to carry out the best path planning for matlab images of scattered points.) Platform: |
Size: 9758720 |
Author:吃鸡的鸭 |
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Description: 通过matlab建立环境障碍物模型，通过遗传算法规划一条无碰撞路径，完成路径规划！(The environmental obstacle model is established by matlab, and a collision-free path is planned by genetic algorithm to complete the path planning.) Platform: |
Size: 9216 |
Author:dhr236521 |
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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 |
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