ROS學習筆記七：在ROS中使用USB攝像頭

下面是一些USB攝像頭的驅動（大多數攝像頭都支持uvc標准）：

1 使用軟件庫里的uvc-camera功能包

1.1 檢查攝像頭

lsusb

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顯示如下：

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 安裝uvc camera功能包

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

1.3 安裝image相關功能包

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

1.4 運行uvc_camera節點

rosrun uvc_camera uvc_camera_node

1.5 查看圖像信息

（1）使用image_view節點查看圖像

rosrun image_view image_view image:=/image_raw

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說明：最后面的附加選項“image:=/image_raw”是把話題列表中的話題以圖像形式查看的選項。

（2）用rqt_image_view節點檢查

rqt_image_view image:=/image_raw

（3）使用rviz查看

rviz

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

使用apt-get安裝的軟件包好像只有執行程序，沒有launch文件和節點源文件等等，所以采用了自建uvc-camera軟件包更該參數。

2 使用usb_cam軟件包

2.1 安裝usb_cam軟件包

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

2.2 啟用launch文件

roslaunch usb_cam usb_cam-test.launch

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顯示如下：

launch文件的目錄為：/opt/ros/kinetic/share/usb_cam，可在該目錄下找到luanch文件並修改參數。

3 使用opencv驅動USB攝像頭

首先創建一個工作空間：

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

再建立一個功能包：

$ 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目錄中建立兩個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目錄中建立兩個cpp文件：

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

將下列代碼復制進去：

#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\n");  
        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\n",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\n");  
        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，繼續創建my_subscriber.cpp：

$ gedit my_subscriber.cpp

復制下列代碼：

#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");  
}  

接下來要把涉及到的各種包和opencv在CMakeList中聲明一下，回到程序包目錄下。

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

添加以下語句：

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}) 

將這個包進行編譯：

$ cd ~/ros_ws/
$ catkin_make  

接下來開始運行程序,首先啟動ROS。

$ roscore 

運行my_publisher節點.(如果運行不起來,需要先source devel/setup.bash)。

$ rosrun learning_image_transport my_publisher 0 

這時候會看到我們的攝像頭燈已經亮起來了,0代表默認攝像頭,如果有多個攝像頭,則第二個是1,依次類推。

接下來運行my_subscriber節點來接收圖像。

$ rosrun learning_image_transport my_subscriber

這時候如果沒有錯誤的話就會彈出圖像窗口，如下所示：

參考：

ROS-USB攝像頭]

ROS學習筆記（一）：在ROS中使用USB網絡攝像頭傳輸圖像