编写一段ros中视觉SLAM的节点代码

以下是一个简单的ROS视觉SLAM节点代码的示例，使用的是ORB-SLAM2算法：

#include <iostream>
#include <string>

#include <ros/ros.h>
#include <cv_bridge/cv_bridge.h>
#include <sensor_msgs/Image.h>
#include <sensor_msgs/CameraInfo.h>
#include <geometry_msgs/PoseStamped.h>

#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/calib3d/calib3d.hpp>
#include <opencv2/core/eigen.hpp>

#include "ORB_SLAM2/System.h"

class ORBSLAMNode {
public:
    ORBSLAMNode(const std::string& config_file_path);

    void imageCallback(const sensor_msgs::ImageConstPtr& image_msg);
    void cameraInfoCallback(const sensor_msgs::CameraInfoConstPtr& camera_info_msg);

private:
    void convertROSToCV(const sensor_msgs::ImageConstPtr& image_msg, cv::Mat& image);
    void convertROSToCV(const sensor_msgs::CameraInfoConstPtr& camera_info_msg, cv::Mat& camera_matrix, cv::Mat& distortion_coefficients, cv::Size& image_size);

    ORB_SLAM2::System* slam_system_;

    cv::Mat camera_matrix_;
    cv::Mat distortion_coefficients_;
    cv::Size image_size_;

    ros::NodeHandle nh_;
    ros::Subscriber image_sub_;
    ros::Subscriber camera_info_sub_;
    ros::Publisher pose_pub_;
};

ORBSLAMNode::ORBSLAMNode(const std::string& config_file_path) {
    // Load ORB-SLAM2 configuration file
    ORB_SLAM2::System::loadParamsORB(config_file_path);

    // Create ORB-SLAM2 system object
    slam_system_ = new ORB_SLAM2::System(config_file_path);

    // Initialize ROS node
    nh_ = ros::NodeHandle("~");

    // Subscribe to image and camera info topics
    image_sub_ = nh_.subscribe("image", 1, &ORBSLAMNode::imageCallback, this);
    camera_info_sub_ = nh_.subscribe("camera_info", 1, &ORBSLAMNode::cameraInfoCallback, this);

    // Advertise pose topic
    pose_pub_ = nh_.advertise<geometry_msgs::PoseStamped>("pose", 1);
}

void ORBSLAMNode::imageCallback(const sensor_msgs::ImageConstPtr& image_msg) {
    // Convert ROS image message to OpenCV image
    cv::Mat image;
    convertROSToCV(image_msg, image);

    // Run ORB-SLAM2 on the image and obtain the camera pose
    ORB_SLAM2::cv::Mat44 pose = slam_system_->TrackMonocular(image, 0);

    // Convert the camera pose to ROS message format
    geometry_msgs::PoseStamped pose_msg;
    pose_msg.header.stamp = image_msg->header.stamp;
    pose_msg.header.frame_id = "map";
    Eigen::Matrix4d pose_eigen;
    cv::cv2eigen(pose, pose_eigen);
    Eigen::Quaterniond q(pose_eigen.block<3, 3>(0, 0));
    Eigen::Vector3d t(pose_eigen.block<3, 1>(0, 3));
    pose_msg.pose.position.x = t.x();
    pose_msg.pose.position.y = t.y();
    pose_msg.pose.position.z = t.z();
    pose_msg.pose.orientation.x = q.x();
    pose_msg.pose.orientation.y = q.y();
    pose_msg.pose.orientation.z = q.z();
    pose_msg.pose.orientation.w = q.w();

    // Publish the camera pose
    pose_pub_.publish(pose_msg);
}

void ORBSLAMNode::cameraInfoCallback(const sensor_msgs::CameraInfoConstPtr& camera_info_msg) {
    // Convert ROS camera info message to OpenCV camera matrix and distortion coefficients
    convertROSToCV(camera_info_msg, camera_matrix_, distortion_coefficients_, image_size_);
}

void ORBSLAMNode::convertROSToCV(const sensor_msgs::ImageConstPtr& image_msg, cv::Mat& image) {
    image = cv_bridge::toCvCopy(image_msg, sensor_msgs::image_encodings::BGR8)->image;
}

void ORBSLAMNode::convertROSToCV(const sensor_msgs::CameraInfoConstPtr& camera_info_msg, cv::Mat& camera_matrix, cv::Mat& distortion_coefficients, cv::Size& image_size) {
    camera_matrix = cv::Mat(3, 3, CV_64FC1, const_cast<double*>(&camera_info_msg->K[0]));
    distortion_coefficients = cv::Mat(1, 5, CV_64FC1, const_cast<double*>(&camera_info_msg->D[0]));
    image_size = cv::Size(camera_info_msg->width, camera_info_msg->height);
}

int main(int argc, char** argv) {
    ros::init(argc, argv, "orb_slam_node");

    if (argc != 2) {
        std::cerr << "Usage: " << argv[0] << " <config_file_path>" << std::endl;
        return 1;
    }

    std::string config_file_path = argv[1];

    ORBSLAMNode node(config_file_path);

    ros::spin();

    return 0;
}

这个节点会订阅一个图像消息和一个相机信息消息，然后使用ORB-SLAM2算法对图像进行处理，并将相机位姿发布到一个话题中。请注意，此示例仅适用于单目相机。如果您使用的是双目或RGB-D相机，则需要进行适当的修改。