目录
一、Python实现(推荐方法)
1.1代码cubic_spline_path.py
1.2使用方法
二、C++实现
参考博客
想让机器人/智能车无人驾驶,要有期望路径,最简单的是一条直线,或者是一条光滑曲线。
生成路径的方法有两种:
- 手动遥控机器人运动一段路径,并保存轨迹
- 人为设定几个关键点,拟合出直线或曲线
方法1通常是根据GNSS/INS位姿数据记录轨迹,可参考ROS之rviz显示GNSS/INS运动轨迹_可见一班的博客-CSDN博客
方法2是这篇博客讨论的内容。分别使用C++和Python在ROS下实现。
一、Python实现(推荐方法)
1.1代码cubic_spline_path.py
根据指定的插值算法 alg
,创建一个插值函数 cubic_spline
。如果 alg
为 “linear”,则使用线性插值函数 interp1d
创建插值函数;如果 alg
为 “cubic”,则使用三次样条插值函数 interp1d
创建插值函数。
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import rospy
import rosparam
from nav_msgs.msg import Path
from geometry_msgs.msg import PoseStamped
import sys
import os
import yaml
import numpy as np
from scipy.interpolate import interp1d
# def interpolation(waypoint_list, alg="cubic"):
def interpolation(alg="linear"):
ix = []
iy = []
temp_x = np.array([1,5,8,10])
temp_y = np.array([1,4,9,10])
cubic_spline = None
if alg == "linear":
cubic_spline = interp1d(temp_x, temp_y)
elif alg == "cubic":
cubic_spline = interp1d(temp_x, temp_y, kind='cubic')
waypoint_x_start = temp_x[0]
waypoint_x_end = temp_x[-1]
length = int(abs(waypoint_x_end - waypoint_x_start) / 0.01)
print(length)
ix = np.linspace(waypoint_x_start, waypoint_x_end, num=length)
iy = cubic_spline(ix)
return ix, iy
if __name__ == '__main__':
rospy.init_node("cubic_spline_path")
waypoint_x, waypoint_y = interpolation()
path_pub = rospy.Publisher('/spline_path', Path, queue_size=10)
path = Path()
for index in range(len(waypoint_x)):
pose = PoseStamped()
pose.pose.position.x = waypoint_x[index]
pose.pose.position.y = waypoint_y[index]
print(pose)
path.poses.append(pose)
path.header.frame_id = "map"
path.header.stamp = rospy.Time.now()
rate = rospy.Rate(10)
while not rospy.is_shutdown():
path_pub.publish(path)
rate.sleep()
rospy.spin()
1.2使用方法
- 在ROS工作空间中新建文件夹scripts
- 新建.py文件,复制上述代码
- 更改文件权限允许作为程序执行
- 终端执行 ./cubic_spline_path.py
- 打开rviz,订阅spline_path话题显示路径
二、C++实现
直线插值比较简单,三次样条插值比较复杂。
主函数中调用这个函数即可,传入参数为A、B点x,y坐标值,返回nav_msgs::Path路径。
// 线性插值路径
nav_msgs::Path LinearInterpolation(const double &Ax, const double &Ay, const double &Bx, const double &By, const double &stepsize)
{
double x1 = Ax;
double y1 = Ay;
double z1 = 0;
double x2 = Bx;
double y2 = By;
double z2 = 0;
double step_size = stepsize;
double dist = std::sqrt(std::pow((x2 - x1), 2) + std::pow((y2 - y1), 2) + std::pow((z2 - z1), 2));
int num_steps = dist / step_size;
for (int i = 0; i < num_steps; ++i)
{
double ratio = static_cast<double>(i) / num_steps;
geometry_msgs::PoseStamped interpolated_pose;
interpolated_pose.header.frame_id = "map";
interpolated_pose.header.stamp = ros::Time::now();
interpolated_pose.pose.position.x = x1 + ratio * (x2 - x1);
interpolated_pose.pose.position.y = y1 + ratio * (y2 - y1);
interpolated_pose.pose.position.z = z1 + ratio * (z2 - z1);
interpolated_pose.pose.orientation.x = 1;
interpolated_pose.pose.orientation.y = 0;
interpolated_pose.pose.orientation.z = 0;
interpolated_pose.pose.orientation.w = 0;
scatter_path.poses.push_back(interpolated_pose);
}
return scatter_path;
}
参考博客
【运动规划算法项目实战】路径规划中常用的插值方法(附ROS C++代码)_路径插值
【运动规划算法项目实战】如何使用Pure Pursuit算法进行路径跟踪(附ROS C++代码)