std::normal_distribution是C++11提供的一个正态分布函数模板类
头文件:include<random>
可以创建一个有特定期望值和方差的正态分布;
double mu {50.0}, sigma {10.0};
std::normal_distribution<> norm {mu, sigma};
下面是优达学城粒子滤波部分的一个案例,根据GPS提供初始值,初始化符合正态分布的粒子初值;
/**
* print_samples.cpp
*
* Print out to the terminal 3 samples from a normal distribution with
* mean equal to the GPS position and IMU heading measurements and
* standard deviation of 2 m for the x and y position and 0.05 radians
* for the heading of the car.
*
* Author: Tiffany Huang
*/
#include <iostream>
#include <random> // Need this for sampling from distributions
using std::normal_distribution;
/**
* Prints samples of x, y and theta from a normal distribution
* @param gps_x GPS provided x position
* @param gps_y GPS provided y position
* @param theta GPS provided yaw
*/
void printSamples(double gps_x, double gps_y, double theta);
int main() {
// Set GPS provided state of the car.
double gps_x = 4983;
double gps_y = 5029;
double theta = 1.201;
// Sample from the GPS provided position.
printSamples(gps_x, gps_y, theta);
return 0;
}
void printSamples(double gps_x, double gps_y, double theta) {
std::default_random_engine gen;
double std_x, std_y, std_theta; // Standard deviations for x, y, and theta
// TODO: Set standard deviations for x, y, and theta
std_x = 2;
std_y = 2;
std_theta = 0.5;
// This line creates a normal (Gaussian) distribution for x
normal_distribution<double> dist_x(gps_x, std_x);
// TODO: Create normal distributions for y and theta
normal_distribution<double> dist_y(gps_y, std_y);
normal_distribution<double> dist_theta(theta, std_theta);
for (int i = 0; i < 10; ++i) {
double sample_x, sample_y, sample_theta;
// TODO: Sample from these normal distributions like this:
// sample_x = dist_x(gen);
// where "gen" is the random engine initialized earlier.
sample_x = dist_x(gen);
sample_y = dist_y(gen);
sample_theta = dist_theta(gen);
// Print your samples to the terminal.
std::cout << "Sample " << i + 1 << " " << sample_x << " " << sample_y << " "
<< sample_theta << std::endl;
}
return;
}
运行结果: