c++实现自动驾驶pure_pursuit算法
时间: 2023-09-28 11:07:49 浏览: 61
Pure Pursuit算法是一种用于自动驾驶的路径跟踪算法,其主要思想是在车辆前方选择一个最优的目标点,使车辆沿着路径向目标点移动,从而实现路径跟踪。
以下是C++实现自动驾驶pure_pursuit算法的基本步骤:
1. 定义车辆状态和目标点:
```c++
struct State {
double x; // 车辆x坐标
double y; // 车辆y坐标
double yaw; // 车辆航向角
double v; // 车辆速度
};
// 目标点结构体
struct TargetPoint {
double x; // 目标点x坐标
double y; // 目标点y坐标
};
```
2. 计算目标点的位置:
```c++
double Lf = k * state.v + Lfc; // 前视距离
TargetPoint target_point; // 目标点结构体
double min_dist = std::numeric_limits<double>::max(); // 初始距离设为最大值
for (int i = 0; i < path_size; ++i) {
// 计算车辆到路径上每个点的距离
double dx = path[i].x - state.x;
double dy = path[i].y - state.y;
double dist = std::sqrt(dx*dx + dy*dy);
if (dist < min_dist) {
min_dist = dist;
int ind = i + 1;
if (ind >= path_size) {
ind = path_size - 1;
}
target_point.x = path[ind].x;
target_point.y = path[ind].y;
}
}
```
3. 计算车辆应该前往的目标点的航向角:
```c++
double alpha = std::atan2(target_point.y - state.y, target_point.x - state.x) - state.yaw;
```
4. 计算车辆应该施加的方向盘转角:
```c++
double delta = std::atan2(2.0 * L * std::sin(alpha) / Lf, 1.0);
```
5. 调整方向盘转角大小:
```c++
if (delta > max_delta) {
delta = max_delta;
}
else if (delta < -max_delta) {
delta = -max_delta;
}
```
6. 最后,将计算出的方向盘转角应用于车辆控制:
```c++
double steer = delta * 180.0 / M_PI; // 转换为度数
vehicle.setSteering(steer); // 设置车辆方向盘转角
vehicle.setThrottle(1.0); // 设置车辆油门
```
完整代码如下:
```c++
#include <iostream>
#include <cmath>
#include <vector>
#include <limits>
struct State {
double x;
double y;
double yaw;
double v;
};
struct TargetPoint {
double x;
double y;
};
int main() {
double Lf = 2.5; // 前视距离
double L = 2.9; // 车辆轴距
double k = 0.1; // 前视距离系数
double Lfc = 1.0; // 车辆前方距离
double max_delta = M_PI / 6.0; // 最大转角
std::vector<TargetPoint> path = {{0.0, 0.0}, {0.0, 10.0}, {10.0, 20.0}, {20.0, 30.0}, {30.0, 30.0}};
int path_size = path.size();
State state = {0.0, 0.0, 0.0, 10.0};
double dt = 0.1;
while (true) {
double min_dist = std::numeric_limits<double>::max();
TargetPoint target_point;
for (int i = 0; i < path_size; ++i) {
double dx = path[i].x - state.x;
double dy = path[i].y - state.y;
double dist = std::sqrt(dx*dx + dy*dy);
if (dist < min_dist) {
min_dist = dist;
int ind = i + 1;
if (ind >= path_size) {
ind = path_size - 1;
}
target_point.x = path[ind].x;
target_point.y = path[ind].y;
}
}
double alpha = std::atan2(target_point.y - state.y, target_point.x - state.x) - state.yaw;
double delta = std::atan2(2.0 * L * std::sin(alpha) / Lf, 1.0);
if (delta > max_delta) {
delta = max_delta;
}
else if (delta < -max_delta) {
delta = -max_delta;
}
double steer = delta * 180.0 / M_PI;
state.yaw += state.v / L * std::tan(delta) * dt;
state.x += state.v * std::cos(state.yaw) * dt;
state.y += state.v * std::sin(state.yaw) * dt;
state.v += 1.0 * dt;
std::cout << "x: " << state.x << ", y: " << state.y << ", yaw: " << state.yaw << ", v: " << state.v << ", steer: " << steer << std::endl;
}
return 0;
}
```
以上是一个简单的Pure Pursuit算法实现,你可以将其应用到自动驾驶系统中。当然,实际应用中,还需要考虑更多的因素,比如车辆动力学、传感器误差等。