ROS学习笔记七：在ROS中使用USB摄像头

下面是一些USB摄像头的驱动（大多数摄像头都支持uvc标准）：

1 使用软件库里的uvc-camera功能包

1.1 检查摄像头

lsusb

-------------------------------------

显示如下：

Bus 002 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub
Bus 001 Device 007: ID 046d:082b Logitech, Inc. Webcam C170
Bus 001 Device 006: ID 0461:4e2a Primax Electronics, Ltd
Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub

1.2 安装uvc camera功能包

sudo apt-get install ros-indigo-uvc-camera

1.3 安装image相关功能包

sudo apt-get install ros-kinetic-image-*
sudo apt-get install ros-kinetic-rqt-image-view

1.4 运行uvc_camera节点

rosrun uvc_camera uvc_camera_node

1.5 查看图像信息

（1）使用image_view节点查看图像

rosrun image_view image_view image:=/image_raw

-------------------------------------

说明：最后面的附加选项“image:=/image_raw”是把话题列表中的话题以图像形式查看的选项。

（2）用rqt_image_view节点检查

rqt_image_view image:=/image_raw

（3）使用rviz查看

rviz

增加image，然后将[Image] → [Image Topic]的值更改为“/image_raw”。

使用apt-get安装的软件包好像只有执行程序，没有launch文件和节点源文件等等，所以采用了自建uvc-camera软件包更该参数。

2 使用usb_cam软件包

2.1 安装usb_cam软件包

sudo apt-get install ros-kinetic-usb-cam

2.2 启用launch文件

roslaunch usb_cam usb_cam-test.launch

-------------------------------------

显示如下：

launch文件的目录为：/opt/ros/kinetic/share/usb_cam，可在该目录下找到luanch文件并修改参数。

3 使用opencv驱动USB摄像头

首先创建一个工作空间：

$ mkdir -p ~/ros_ws/src
$ cd ~/ros_ws/
$ catkin_make
$ source devel/setup.bash

再建立一个功能包：

$ cd ~/ros_ws/src
$ catkin_create_pkg learning_image_transport roscpp std_msgs cv_bridge image_transport sensor_msgs 

然后在功能包learning_image_transport下的src目录中建立两个cpp文件：

$ cd ~/ros_ws/src/learning_image_transport/src/
$ gedit my_publisher.cpp

然后在功能包learning_image_transport下的src目录中建立两个cpp文件：

$ cd ~/ros_ws/src/learning_image_transport/src/
$ gedit my_publisher.cpp

将下列代码复制进去：

#include <ros/ros.h>  
#include <image_transport/image_transport.h>  
#include <opencv2/highgui/highgui.hpp>  
#include <cv_bridge/cv_bridge.h>  
#include <sstream> // for converting the command line parameter to integer  

int main(int argc, char** argv)  
{  
    // Check if video source has been passed as a parameter  
    if(argv[1] == NULL)   
    {  
        ROS_INFO("argv[1]=NULL
");  
        return 1;  
    }  

    ros::init(argc, argv, "image_publisher");  
    ros::NodeHandle nh;  
    image_transport::ImageTransport it(nh);  
    image_transport::Publisher pub = it.advertise("camera/image", 1);  

    // Convert the passed as command line parameter index for the video device to an integer  
    std::istringstream video_sourceCmd(argv[1]);  
    int video_source;  
    // Check if it is indeed a number  
    if(!(video_sourceCmd >> video_source))   
    {  
        ROS_INFO("video_sourceCmd is %d
",video_source);  
        return 1;  
    }  

    cv::VideoCapture cap(video_source);  
    // Check if video device can be opened with the given index  
    if(!cap.isOpened())   
    {  
        ROS_INFO("can not opencv video device
");  
        return 1;  
    }  
    cv::Mat frame;  
    sensor_msgs::ImagePtr msg;  

    ros::Rate loop_rate(5);  
    while (nh.ok()) 
    {  
        cap >> frame;  
        // Check if grabbed frame is actually full with some content  
        if(!frame.empty()) 
        {  
            msg = cv_bridge::CvImage(std_msgs::Header(), "bgr8", frame).toImageMsg();  
            pub.publish(msg);  
            //cv::Wait(1);  
    	}  
    }
    
    ros::spinOnce();  
    loop_rate.sleep();  
}  

保存以后，继续创建my_subscriber.cpp：

$ gedit my_subscriber.cpp

复制下列代码：

#include <ros/ros.h>  
#include <image_transport/image_transport.h>  
#include <opencv2/highgui/highgui.hpp>  
#include <cv_bridge/cv_bridge.h>  

void imageCallback(const sensor_msgs::ImageConstPtr& msg)  
{  
	try  
	{  
		cv::imshow("view", cv_bridge::toCvShare(msg, "bgr8")->image); 
		// cv::waitKey(30);  
	}  
	catch (cv_bridge::Exception& e)  
	{  
		ROS_ERROR("Could not convert from '%s' to 'bgr8'.", msg->encoding.c_str());  
	}  
}  

int main(int argc, char **argv)  
{  
	ros::init(argc, argv, "image_listener");  
	ros::NodeHandle nh;  
	cv::namedWindow("view");  
	cv::startWindowThread();  
	image_transport::ImageTransport it(nh);  
	image_transport::Subscriber sub = it.subscribe("camera/image", 1,imageCallback);  
	ros::spin();  
	cv::destroyWindow("view");  
}  

接下来要把涉及到的各种包和opencv在CMakeList中声明一下，回到程序包目录下。

$ cd ~/ros_ws/src/learning_image_transport/
$ gedit CMakeLists.txt

添加以下语句：

find_package(OpenCV REQUIRED)  
# add the publisher example  
add_executable(my_publisher src/my_publisher.cpp)  

target_link_libraries(my_publisher ${catkin_LIBRARIES} ${OpenCV_LIBRARIES})  

# add the subscriber example  
add_executable(my_subscriber src/my_subscriber.cpp)  
target_link_libraries(my_subscriber ${catkin_LIBRARIES} ${OpenCV_LIBRARIES}) 

将这个包进行编译：

$ cd ~/ros_ws/
$ catkin_make  

接下来开始运行程序,首先启动ROS。

$ roscore 

运行my_publisher节点.(如果运行不起来,需要先source devel/setup.bash)。

$ rosrun learning_image_transport my_publisher 0 

这时候会看到我们的摄像头灯已经亮起来了,0代表默认摄像头,如果有多个摄像头,则第二个是1,依次类推。

接下来运行my_subscriber节点来接收图像。

$ rosrun learning_image_transport my_subscriber

这时候如果没有错误的话就会弹出图像窗口，如下所示：

参考：

ROS-USB摄像头]

ROS学习笔记（一）：在ROS中使用USB网络摄像头传输图像