基于ros系统写一段能够实现自动驾驶的代码

首先，我们需要引入ROS系统的依赖库：import rospy
from ackermann_msgs.msg import AckermannDrive# 初始化节点
rospy.init_node('autonomous_drive')# 创建消息发布者
pub = rospy.Publisher('/ackermann_cmd', AckermannDrive, queue_size=10)# 创建消息实例
drive_msg = AckermannDrive()# 设置消息参数
drive_msg.speed = 0.5
drive_msg.steering_angle = 0.0# 将消息发布出去
pub.publish(drive_msg)

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基于ros系统写一段能够依靠计算机视觉实现自动驾驶的代码

使用ROS系统写一段能够实现自动驾驶的代码，可以通过检测车辆周围的环境和场景，利用计算机视觉技术来实现自动驾驶。代码示例如下：#include <ros/ros.h>
#include <opencv2/opencv.hpp>
#include <image_transport/image_transport.h>
#include <cv_bridge/cv_bridge.h>
#include <sensor_msgs/image_encodings.h>void imageCallback(const sensor_msgs::ImageConstPtr& msg)
{
cv_bridge::CvImagePtr cv_ptr;
try
{
cv_ptr = cv_bridge::toCvCopy(msg, sensor_msgs::image_encodings::BGR8);
}
catch (cv_bridge::Exception& e)
{
ROS_ERROR("cv_bridge exception: %s", e.what());
return;
} // Your code goes here // Use OpenCV to detect objects
// Use fuzzy logic to decide what to do
// Publish the action to the car
}int main(int argc, char** argv)
{
ros::init(argc, argv, "autonomous_driver_node"); ros::NodeHandle nh;
image_transport::ImageTransport it(nh);
image_transport::Subscriber sub = it.subscribe("/camera/image", 1, imageCallback); ros::spin();
return 0;
}