HDL_Graph_slam骨头记（3）
作者：互联网
#include <memory>
#include <iostream>
#include <ros/ros.h>
#include <ros/time.h>
#include <ros/duration.h>
#include <pcl_ros/point_cloud.h>
#include <tf_conversions/tf_eigen.h>
#include <tf/transform_broadcaster.h>
#include <std_msgs/Time.h>
#include <nav_msgs/Odometry.h>
#include <sensor_msgs/PointCloud2.h>
#include <nodelet/nodelet.h>
#include <pluginlib/class_list_macros.h>
#include <pcl/filters/voxel_grid.h>
#include <pcl/filters/passthrough.h>
#include <pcl/filters/approximate_voxel_grid.h>
#include <hdl_graph_slam/ros_utils.hpp>
#include <hdl_graph_slam/registrations.hpp>
namespace hdl_graph_slam {
class ScanMatchingOdometryNodelet : public nodelet::Nodelet {
public:
typedef pcl::PointXYZI PointT;
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
ScanMatchingOdometryNodelet() {}
virtual ~ScanMatchingOdometryNodelet() {}
virtual void onInit() {
NODELET_DEBUG("initializing scan_matching_odometry_nodelet...");
nh = getNodeHandle();
private_nh = getPrivateNodeHandle();
initialize_params();
points_sub = nh.subscribe("/filtered_points", 256, &ScanMatchingOdometryNodelet::cloud_callback, this);
read_until_pub = nh.advertise<std_msgs::Header>("/scan_matching_odometry/read_until", 32);
odom_pub = nh.advertise<nav_msgs::Odometry>("/odom", 32);
}
private:
/**
* @brief initialize parameters
*/
void initialize_params() {
auto& pnh = private_nh;
points_topic = pnh.param<std::string>("points_topic", "/velodyne_points");
odom_frame_id = pnh.param<std::string>("odom_frame_id", "odom");
// The minimum tranlational distance and rotation angle between keyframes.
// If this value is zero, frames are always compared with the previous frame
keyframe_delta_trans = pnh.param<double>("keyframe_delta_trans", 0.25);
keyframe_delta_angle = pnh.param<double>("keyframe_delta_angle", 0.15);
keyframe_delta_time = pnh.param<double>("keyframe_delta_time", 1.0);
// Registration validation by thresholding
transform_thresholding = pnh.param<bool>("transform_thresholding", false);
max_acceptable_trans = pnh.param<double>("max_acceptable_trans", 1.0);
max_acceptable_angle = pnh.param<double>("max_acceptable_angle", 1.0);
// select a downsample method (VOXELGRID, APPROX_VOXELGRID, NONE)
std::string downsample_method = pnh.param<std::string>("downsample_method", "VOXELGRID");
double downsample_resolution = pnh.param<double>("downsample_resolution", 0.1);
if(downsample_method == "VOXELGRID") {
std::cout << "downsample: VOXELGRID " << downsample_resolution << std::endl;
boost::shared_ptr<pcl::VoxelGrid<PointT>> voxelgrid(new pcl::VoxelGrid<PointT>());
voxelgrid->setLeafSize(downsample_resolution, downsample_resolution, downsample_resolution);
downsample_filter = voxelgrid;
} else if(downsample_method == "APPROX_VOXELGRID") {
std::cout << "downsample: APPROX_VOXELGRID " << downsample_resolution << std::endl;
boost::shared_ptr<pcl::ApproximateVoxelGrid<PointT>> approx_voxelgrid(new pcl::ApproximateVoxelGrid<PointT>());
approx_voxelgrid->setLeafSize(downsample_resolution, downsample_resolution, downsample_resolution);
downsample_filter = approx_voxelgrid;
} else {
if(downsample_method != "NONE") {
std::cerr << "warning: unknown downsampling type (" << downsample_method << ")" << std::endl;
std::cerr << " : use passthrough filter" <<std::endl;
}
std::cout << "downsample: NONE" << std::endl;
boost::shared_ptr<pcl::PassThrough<PointT>> passthrough(new pcl::PassThrough<PointT>());
downsample_filter = passthrough;
}
registration = select_registration_method(pnh);
}
/**
* @brief callback for point clouds
* @param cloud_msg point cloud msg
*/
void cloud_callback(const sensor_msgs::PointCloud2ConstPtr& cloud_msg) {
if(!ros::ok()) {
return;
}
pcl::PointCloud<PointT>::Ptr cloud(new pcl::PointCloud<PointT>());
pcl::fromROSMsg(*cloud_msg, *cloud);
Eigen::Matrix4f pose = matching(cloud_msg->header.stamp, cloud);
publish_odometry(cloud_msg->header.stamp, cloud_msg->header.frame_id, pose);
// In offline estimation, point clouds until the published time will be supplied
std_msgs::HeaderPtr read_until(new std_msgs::Header());
read_until->frame_id = points_topic;
read_until->stamp = cloud_msg->header.stamp + ros::Duration(1, 0);
read_until_pub.publish(read_until);
read_until->frame_id = "/filtered_points";
read_until_pub.publish(read_until);
}
/**
* @brief downsample a point cloud
* @param cloud input cloud
* @return downsampled point cloud
*/
pcl::PointCloud<PointT>::ConstPtr downsample(const pcl::PointCloud<PointT>::ConstPtr& cloud) const {
if(!downsample_filter) {
return cloud;
}
pcl::PointCloud<PointT>::Ptr filtered(new pcl::PointCloud<PointT>());
downsample_filter->setInputCloud(cloud);
downsample_filter->filter(*filtered);
return filtered;
}
/**
* @brief estimate the relative pose between an input cloud and a keyframe cloud
* @param stamp the timestamp of the input cloud
* @param cloud the input cloud
* @return the relative pose between the input cloud and the keyframe cloud
*/
Eigen::Matrix4f matching(const ros::Time& stamp, const pcl::PointCloud<PointT>::ConstPtr& cloud) {
if(!keyframe) {
prev_trans.setIdentity(); //设置恒等矩阵 （恒等矩阵的值为 1）相当于初始化
keyframe_pose.setIdentity();
keyframe_stamp = stamp;
keyframe = downsample(cloud);
registration->setInputTarget(keyframe); //ROS注册
return Eigen::Matrix4f::Identity(); //使用Identity()函数的作用：在定义变量时使用Eigen::Matrix4f x = Eigen::Matrix4f::Identity();即用单位矩阵对x变量进行了初始化。
} //四维矩阵 时间戳与点云数据组成4维矩阵 此块代码做了一个初始化
auto filtered = downsample(cloud);
registration->setInputSource(filtered);
pcl::PointCloud<PointT>::Ptr aligned(new pcl::PointCloud<PointT>());
registration->align(*aligned, prev_trans);
if(!registration->hasConverged()) {
NODELET_INFO_STREAM("scan matching has not converged!!");
NODELET_INFO_STREAM("ignore this frame(" << stamp << ")");
return keyframe_pose * prev_trans;
}
Eigen::Matrix4f trans = registration->getFinalTransformation();
Eigen::Matrix4f odom = keyframe_pose * trans;
if(transform_thresholding) {
Eigen::Matrix4f delta = prev_trans.inverse() * trans;
double dx = delta.block<3, 1>(0, 3).norm(); //3*1维的block matrix.block<p,q>(i, j) :<p, q>可理解为一个p行q列的子矩阵，该定义表示从原矩阵中第(i, j)开始，获取一个p行q列的子矩阵，返回该子矩阵组成的临时矩阵对象，原矩阵的元素不变；
double da = std::acos(Eigen::Quaternionf(delta.block<3, 3>(0, 0)).w());//
if(dx > max_acceptable_trans || da > max_acceptable_angle) {
NODELET_INFO_STREAM("too large transform!! " << dx << "[m] " << da << "[rad]");
NODELET_INFO_STREAM("ignore this frame(" << stamp << ")");
return keyframe_pose * prev_trans;
}
}
prev_trans = trans;
auto keyframe_trans = matrix2transform(stamp, keyframe_pose, odom_frame_id, "keyframe");
keyframe_broadcaster.sendTransform(keyframe_trans);
double delta_trans = trans.block<3, 1>(0, 3).norm();
double delta_angle = std::acos(Eigen::Quaternionf(trans.block<3, 3>(0, 0)).w());
double delta_time = (stamp - keyframe_stamp).toSec();
if(delta_trans > keyframe_delta_trans || delta_angle > keyframe_delta_angle || delta_time > keyframe_delta_time) {
keyframe = filtered;
registration->setInputTarget(keyframe);
keyframe_pose = odom;
keyframe_stamp = stamp;
prev_trans.setIdentity();
}
return odom;
}
/**
* @brief publish odometry
* @param stamp timestamp
* @param pose odometry pose to be published
*/
void publish_odometry(const ros::Time& stamp, const std::string& base_frame_id, const Eigen::Matrix4f& pose) {
// broadcast the transform over tf
geometry_msgs::TransformStamped odom_trans = matrix2transform(stamp, pose, odom_frame_id, base_frame_id);
odom_broadcaster.sendTransform(odom_trans);
// publish the transform
nav_msgs::Odometry odom;
odom.header.stamp = stamp;
odom.header.frame_id = odom_frame_id;
odom.pose.pose.position.x = pose(0, 3);
odom.pose.pose.position.y = pose(1, 3);
odom.pose.pose.position.z = pose(2, 3);
odom.pose.pose.orientation = odom_trans.transform.rotation;
odom.child_frame_id = base_frame_id;
odom.twist.twist.linear.x = 0.0;
odom.twist.twist.linear.y = 0.0;
odom.twist.twist.angular.z = 0.0;
odom_pub.publish(odom);
}
private:
// ROS topics
ros::NodeHandle nh;
ros::NodeHandle private_nh;
ros::Subscriber points_sub;
ros::Publisher odom_pub;
tf::TransformBroadcaster odom_broadcaster;
tf::TransformBroadcaster keyframe_broadcaster;
std::string points_topic;
std::string odom_frame_id;
ros::Publisher read_until_pub;
// keyframe parameters
double keyframe_delta_trans; // minimum distance between keyframes
double keyframe_delta_angle; //
double keyframe_delta_time; //
// registration validation by thresholding
bool transform_thresholding; //
double max_acceptable_trans; //
double max_acceptable_angle;
// odometry calculation
Eigen::Matrix4f prev_trans; // previous estimated transform from keyframe
Eigen::Matrix4f keyframe_pose; // keyframe pose
ros::Time keyframe_stamp; // keyframe time
pcl::PointCloud<PointT>::ConstPtr keyframe; // keyframe point cloud
//
pcl::Filter<PointT>::Ptr downsample_filter;
pcl::Registration<PointT, PointT>::Ptr registration;
};
}
PLUGINLIB_EXPORT_CLASS(hdl_graph_slam::ScanMatchingOdometryNodelet, nodelet::Nodelet)
标签：trans,downsample,Graph,pose,slam,keyframe,odom,HDL,cloud 来源： https://www.cnblogs.com/chenlinchong/p/11811549.html