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Forward_kinematics_solution_of_Stewart_platform
使用matlab编写并联机器人控制的源程序(The preparation of parallel robot using matlab source control)
- 2007-07-27 20:58:08下载
- 积分：1
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atlexamp
Leveraging C++ Applications Using COM An Example Using ATL COM利用COM继承的文档视图结构的应用程序的例子(Leveraging C Applications Using COM An Example Using ATL COM COM files View succession of application examples)
- 2005-02-21 17:36:46下载
- 积分：1
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G1
说明： this program for SMIB with statcom to damp power system stabil ity
- 2013-01-12 02:50:13下载
- 积分：1
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Matlab
matlab-三维曲面的自动绘制及图形构建(matlab-dimensional surface of automatic drawing and graphics, build)
- 2013-09-16 20:35:23下载
- 积分：1
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vip_OFDM
OFDM transmitter is defined for the SDR
- 2015-02-06 01:19:05下载
- 积分：1
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esprit
频率估计的ESPRIT方法,实现频率的精确估计，并可推广到空间到达角的估计(frequency estimation with ESPRIT method)
- 2010-07-10 18:56:12下载
- 积分：1
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[H2]
8toi ruui tryuo r6yo ruo ruy tyiofd rgui
- 2011-07-05 13:46:40下载
- 积分：1
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linear-neural-network
MATLAB线性神经网络应用实例，共有13个例子。(Linear neural network applications, a total of 13 examples.)
- 2014-12-12 08:27:57下载
- 积分：1
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bpsinx
采用bp神经网络对函数y=sin（x）进行训练，然后用测试集对训练的函数进行测试，也就是函数逼近sin（x)的曲线(Bp neural network using the function y = sin (x) for training, and then use the test set to test the training function, that is, function approximation sin (x) curve)
- 2014-01-15 16:44:54下载
- 积分：1
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GAforPathPlaning
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.)
- 2019-05-02 14:56:19下载
- 积分：1
