八叉树bt文件转为grid文件的代码及编译流程

目的

点云文件转为八叉树文件

代码

在一个文件夹中新建两个文件，pcd2bt.cpp和CMakeLists.txt，分别写入：

grid3d_node.cpp

#include <ros/ros.h>
#include <string>
#include "grid3d.hpp"int main(int argc, char **argv)
{ros::init(argc, argv, "grid3d_generator_node");  // Particle filter instancestd::string node_name = "grid3d_generator_node";if(argc != 2){ROS_ERROR("You should give the .bt path as the first argument");exit(1);}std::string map_path = std::string(argv[1]);Grid3d pf(node_name, map_path);return 0;
}

grid3d.hpp

#ifndef __GRID3D_HPP__
#define __GRID3D_HPP__/*** @file prob_map.cpp* @brief This file includes the ROS node implementation.* @author Francisco J. Perez Grau and Fernando Caballero*/#include <sys/time.h>
#include <ros/ros.h>
#include <octomap/octomap.h>
#include <octomap/OcTree.h>
#include <nav_msgs/OccupancyGrid.h>
#include <std_msgs/Float32.h>
#include <stdio.h> // PCL
#include <pcl/point_cloud.h>
#include <pcl/kdtree/kdtree_flann.h>
#include <pcl_conversions/pcl_conversions.h>
#include <pcl/registration/icp.h>
#include <pcl/point_types.h>
#include <pcl/registration/ndt.h>
#include <pcl/filters/approximate_voxel_grid.h>struct TrilinearParams
{float a0, a1, a2, a3, a4, a5, a6, a7;TrilinearParams(void){a0 = a1 = a2 = a3 = a4 = a5 = a6 = a7 = 0.0;}double interpolate(double x, double y, double z){return a0 + a1*x + a2*y + a3*z + a4*x*y + a5*x*z + a6*y*z + a7*x*y*z;}
};class Grid3d
{
private:// Ros parametersros::NodeHandle m_nh;bool m_saveGrid, m_publishPc;std::string m_mapPath, m_nodeName;std::string m_globalFrameId;float m_sensorDev, m_gridSlice;double m_publishPointCloudRate, m_publishGridSliceRate;// Octomap parametersfloat m_maxX, m_maxY, m_maxZ;float m_resolution, m_oneDivRes;octomap::OcTree *m_octomap;// 3D probabilistic grid cellstruct gridCell{float dist;float prob;gridCell(void){dist = -1.0;prob =  0.0;}};gridCell *m_grid;int m_gridSize, m_gridSizeX, m_gridSizeY, m_gridSizeZ;int m_gridStepY, m_gridStepZ;// 3D point clound representation of the mappcl::PointCloud<pcl::PointXYZ>::Ptr m_cloud;pcl::KdTreeFLANN<pcl::PointXYZ> m_kdtree;// Visualization of the map as pointcloudsensor_msgs::PointCloud2 m_pcMsg;ros::Publisher m_pcPub;ros::Timer mapTimer;// Visualization of a grid slice as 2D grid map msgnav_msgs::OccupancyGrid m_gridSliceMsg;ros::Publisher m_gridSlicePub;ros::Timer gridTimer;// Trilinear approximation parameters (for each grid cell)TrilinearParams *m_triGrid;// ICP pcl::IterativeClosestPoint<pcl::PointXYZ, pcl::PointXYZ> m_icp;// NDT pcl::NormalDistributionsTransform<pcl::PointXYZ, pcl::PointXYZ> m_ndt;public:Grid3d(std::string &node_name) : m_cloud(new pcl::PointCloud<pcl::PointXYZ>), m_triGrid(NULL){// Load paraetersdouble value;ros::NodeHandle lnh("~");m_nodeName = node_name;if(!lnh.getParam("global_frame_id", m_globalFrameId))m_globalFrameId = "map";	if(!lnh.getParam("map_path", m_mapPath))m_mapPath = "map.ot";if(!lnh.getParam("publish_point_cloud", m_publishPc))m_publishPc = false;if(!lnh.getParam("publish_point_cloud_rate", m_publishPointCloudRate))m_publishPointCloudRate = 0.2;	if(!lnh.getParam("publish_grid_slice", value))value = -1.0;if(!lnh.getParam("publish_grid_slice_rate", m_publishGridSliceRate))m_publishGridSliceRate = 0.2;m_gridSlice = (float)value;if(!lnh.getParam("sensor_dev", value))value = 0.2;m_sensorDev = (float)value;// Load octomap m_octomap = NULL;m_grid = NULL;if(loadOctomap(m_mapPath)){// Compute the point-cloud associated to the ocotmapcomputePointCloud();// Try to load tha associated grid-map from filestd::string path;if(m_mapPath.compare(m_mapPath.length()-3, 3, ".bt") == 0)path = m_mapPath.substr(0,m_mapPath.find(".bt"))+".grid";if(m_mapPath.compare(m_mapPath.length()-3, 3, ".ot") == 0)path = m_mapPath.substr(0,m_mapPath.find(".ot"))+".grid";if(!loadGrid(path)){						// Compute the gridMap using kdtree search over the point-cloudstd::cout << "Computing 3D occupancy grid. This will take some time..." << std::endl;computeGrid();std::cout << "\tdone!" << std::endl;// Save grid on fileif(saveGrid(path))std::cout << "Grid map successfully saved on " << path << std::endl;}// Build the msg with a slice of the grid if neededif(m_gridSlice >= 0 && m_gridSlice <= m_maxZ){buildGridSliceMsg(m_gridSlice);m_gridSlicePub = m_nh.advertise<nav_msgs::OccupancyGrid>(node_name+"/grid_slice", 1, true);gridTimer = m_nh.createTimer(ros::Duration(1.0/m_publishGridSliceRate), &Grid3d::publishGridSliceTimer, this);	}// Setup point-cloud publisherif(m_publishPc){m_pcPub = m_nh.advertise<sensor_msgs::PointCloud2>(node_name+"/map_point_cloud", 1, true);mapTimer = m_nh.createTimer(ros::Duration(1.0/m_publishPointCloudRate), &Grid3d::publishMapPointCloudTimer, this);}}// Setup ICPm_icp.setMaximumIterations (50);m_icp.setMaxCorrespondenceDistance (0.1);m_icp.setRANSACOutlierRejectionThreshold (1.0);// Setup NDTm_ndt.setTransformationEpsilon (0.01);  // Setting minimum transformation difference for termination condition.m_ndt.setStepSize (0.1);   // Setting maximum step size for More-Thuente line search.m_ndt.setResolution (1.0);   //Setting Resolution of NDT grid structure (VoxelGridCovariance).m_ndt.setMaximumIterations (50);   // Setting max number of registration iterations.}Grid3d(std::string &node_name, std::string &map_path) : m_cloud(new pcl::PointCloud<pcl::PointXYZ>), m_triGrid(NULL){// Load paraetersdouble value;ros::NodeHandle lnh("~");m_nodeName = node_name;if(!lnh.getParam("sensor_dev", value))value = 0.2;m_sensorDev = (float)value;m_mapPath = map_path;// Load octomap m_octomap = NULL;m_grid = NULL;if(loadOctomap(m_mapPath)){// Compute the point-cloud associated to the ocotmapcomputePointCloud();// Try to load tha associated grid-map from filestd::string path;if(m_mapPath.compare(m_mapPath.length()-3, 3, ".bt") == 0)path = m_mapPath.substr(0,m_mapPath.find(".bt"))+".grid";if(m_mapPath.compare(m_mapPath.length()-3, 3, ".ot") == 0)path = m_mapPath.substr(0,m_mapPath.find(".ot"))+".grid";if(!loadGrid(path)){						// Compute the gridMap using kdtree search over the point-cloudstd::cout << "Computing 3D occupancy grid. This will take some time..." << std::endl;computeGrid();std::cout << "\tdone!" << std::endl;// Save grid on fileif(saveGrid(path))std::cout << "Grid map successfully saved on " << path << std::endl;}			}// Setup ICPm_icp.setMaximumIterations (50);m_icp.setMaxCorrespondenceDistance (0.1);m_icp.setRANSACOutlierRejectionThreshold (1.0);// Setup NDTm_ndt.setTransformationEpsilon (0.01);  // Setting minimum transformation difference for termination condition.m_ndt.setStepSize (0.1);   // Setting maximum step size for More-Thuente line search.m_ndt.setResolution (1.0);   //Setting Resolution of NDT grid structure (VoxelGridCovariance).m_ndt.setMaximumIterations (50);   // Setting max number of registration iterations.}~Grid3d(void){if(m_octomap != NULL)delete m_octomap;if(m_grid != NULL)delete []m_grid;if(m_triGrid != NULL)delete []m_triGrid;}float computeCloudWeight(std::vector<pcl::PointXYZ> &points){float weight = 0.;int n = 0;for(int i=0; i<points.size(); i++){const pcl::PointXYZ& p = points[i];if(p.x >= 0.0 && p.y >= 0.0 && p.z >= 0.0 && p.x < m_maxX && p.y < m_maxY && p.z < m_maxZ){int index = point2grid(p.x, p.y, p.z);weight += m_grid[index].prob;n++;}}if(n > 10)return weight/n;elsereturn 0;}void publishMapPointCloud(void){m_pcMsg.header.stamp = ros::Time::now();m_pcPub.publish(m_pcMsg);}void publishGridSlice(void){m_gridSliceMsg.header.stamp = ros::Time::now();m_gridSlicePub.publish(m_gridSliceMsg);}bool isIntoMap(double x, double y, double z){return (x >= 0.0 && y >= 0.0 && z >= 0.0 && x < m_maxX && y < m_maxY && z < m_maxZ);}double getPointDist(double x, double y, double z){return m_grid[point2grid(x, y, z)].dist;}double getPointDistProb(double x, double y, double z){return m_grid[point2grid(x, y, z)].prob;}TrilinearParams getPointDistInterpolation(double x, double y, double z){TrilinearParams r;if(x >= 0.0 && y >= 0.0 && z >= 0.0 && x < m_maxX && y < m_maxY && z < m_maxZ)r = m_triGrid[point2grid(x, y, z)];return r;}bool computeTrilinearInterpolation(void){// Delete existing parameters if the existsif(m_triGrid != NULL)delete []m_triGrid;// Reserve memory for the parametersm_triGrid = new TrilinearParams[m_gridSize];// Compute the distance to the closest point of the gridint ix, iy, iz;double count = 0.0;double size = m_gridSizeX*m_gridSizeY*m_gridSizeZ;double x0, y0, z0, x1, y1, z1;double div = -1.0/(m_resolution*m_resolution*m_resolution);for(iz=0, z0=0.0, z1=m_resolution; iz<m_gridSizeZ-1; iz++, z0+=m_resolution, z1+=m_resolution){printf("Computing trilinear interpolation map: : %3.2lf%%        \r", count/size * 100.0);for(iy=0, y0=0.0, y1=m_resolution; iy<m_gridSizeY-1; iy++, y0+=m_resolution, y1+=m_resolution){for(ix=0, x0=0.0, x1=m_resolution; ix<m_gridSizeX-1; ix++, x0+=m_resolution, x1+=m_resolution){double c000, c001, c010, c011, c100, c101, c110, c111;TrilinearParams p;count++;c000 = m_grid[(ix+0) + (iy+0)*m_gridStepY + (iz+0)*m_gridStepZ].dist;c001 = m_grid[(ix+0) + (iy+0)*m_gridStepY + (iz+1)*m_gridStepZ].dist;c010 = m_grid[(ix+0) + (iy+1)*m_gridStepY + (iz+0)*m_gridStepZ].dist;c011 = m_grid[(ix+0) + (iy+1)*m_gridStepY + (iz+1)*m_gridStepZ].dist;c100 = m_grid[(ix+1) + (iy+0)*m_gridStepY + (iz+0)*m_gridStepZ].dist;c101 = m_grid[(ix+1) + (iy+0)*m_gridStepY + (iz+1)*m_gridStepZ].dist;c110 = m_grid[(ix+1) + (iy+1)*m_gridStepY + (iz+0)*m_gridStepZ].dist;c111 = m_grid[(ix+1) + (iy+1)*m_gridStepY + (iz+1)*m_gridStepZ].dist;p.a0 = (-c000*x1*y1*z1 + c001*x1*y1*z0 + c010*x1*y0*z1 - c011*x1*y0*z0 + c100*x0*y1*z1 - c101*x0*y1*z0 - c110*x0*y0*z1 + c111*x0*y0*z0)*div;p.a1 = (c000*y1*z1 - c001*y1*z0 - c010*y0*z1 + c011*y0*z0- c100*y1*z1 + c101*y1*z0 + c110*y0*z1 - c111*y0*z0)*div;p.a2 = (c000*x1*z1 - c001*x1*z0 - c010*x1*z1 + c011*x1*z0 - c100*x0*z1 + c101*x0*z0 + c110*x0*z1 - c111*x0*z0)*div;p.a3 = (c000*x1*y1 - c001*x1*y1 - c010*x1*y0 + c011*x1*y0 - c100*x0*y1 + c101*x0*y1 + c110*x0*y0 - c111*x0*y0)*div;p.a4 = (-c000*z1 + c001*z0 + c010*z1 - c011*z0 + c100*z1 - c101*z0 - c110*z1 + c111*z0)*div;p.a5 = (-c000*y1 + c001*y1 + c010*y0 - c011*y0 + c100*y1 - c101*y1 - c110*y0 + c111*y0)*div;p.a6 = (-c000*x1 + c001*x1 + c010*x1 - c011*x1 + c100*x0 - c101*x0 - c110*x0 + c111*x0)*div;p.a7 = (c000 - c001 - c010 + c011 - c100+ c101 + c110 - c111)*div;m_triGrid[ix + iy*m_gridStepY + iz*m_gridStepZ] = p;}}}printf("Computing trilinear interpolation map: 100%%                               \n");return true;}bool alignICP(std::vector<pcl::PointXYZ> &p, double &tx, double &ty, double &tz, double &a){pcl::PointCloud<pcl::PointXYZ>::Ptr c (new pcl::PointCloud<pcl::PointXYZ>);pcl::PointCloud<pcl::PointXYZ> Final;// Copy cloud into PCL structc->width = p.size();c->height = 1;c->points.resize(c->width * c->height);for(unsigned int i=0; i<p.size(); i++){c->points[i].x = p[i].x;c->points[i].y = p[i].y;c->points[i].z = p[i].z;}// Setup initial solution (poinc-cloud is tilt compensated)Eigen::AngleAxisf initRotation (a, Eigen::Vector3f::UnitZ ());Eigen::Translation3f initTranslation (tx, ty, tz);Eigen::Matrix4f initGuess = (initTranslation * initRotation).matrix ();// Setup icp and perform alignementm_icp.setInputSource(c);m_icp.align(Final, initGuess);// Get solutionEigen::Matrix4f T = m_icp.getFinalTransformation();tx = T(0,3);ty = T(1,3);tz = T(2,3);a = atan2(T(1,0),T(0,0));return true;}bool alignNDT(std::vector<pcl::PointXYZ> &p, double &tx, double &ty, double &tz, double &a){pcl::PointCloud<pcl::PointXYZ>::Ptr c (new pcl::PointCloud<pcl::PointXYZ>);pcl::PointCloud<pcl::PointXYZ> Final;// Copy cloud into PCL structc->width = p.size();c->height = 1;c->points.resize(c->width * c->height);for(unsigned int i=0; i<p.size(); i++){c->points[i].x = p[i].x;c->points[i].y = p[i].y;c->points[i].z = p[i].z;}// Setup initial solution (poinc-cloud is tilt compensated)Eigen::AngleAxisf initRotation (a, Eigen::Vector3f::UnitZ ());Eigen::Translation3f initTranslation (tx, ty, tz);Eigen::Matrix4f initGuess = (initTranslation * initRotation).matrix ();// Downsample input cloudpcl::PointCloud<pcl::PointXYZ>::Ptr filtered_cloud (new pcl::PointCloud<pcl::PointXYZ>);pcl::ApproximateVoxelGrid<pcl::PointXYZ> approximate_voxel_filter;approximate_voxel_filter.setLeafSize (2.0, 2.0, 2.0);approximate_voxel_filter.setInputCloud (c);approximate_voxel_filter.filter (*filtered_cloud);// Setup icp and perform alignementm_ndt.setInputSource(filtered_cloud);m_ndt.align(Final, initGuess);// Get solutionEigen::Matrix4f T = m_ndt.getFinalTransformation();tx = T(0,3);ty = T(1,3);tz = T(2,3);a = atan2(T(1,0),T(0,0));return true;}protected:void publishMapPointCloudTimer(const ros::TimerEvent& event){publishMapPointCloud();}void publishGridSliceTimer(const ros::TimerEvent& event){publishGridSlice();}bool loadOctomap(std::string &path){// release previously loaded dataif(m_octomap != NULL)delete m_octomap;if(m_grid != NULL)delete []m_grid;// Load octomapoctomap::AbstractOcTree *tree;if(path.length() > 3 && (path.compare(path.length()-3, 3, ".bt") == 0)){octomap::OcTree* binaryTree = new octomap::OcTree(0.1);if (binaryTree->readBinary(path) && binaryTree->size() > 1)tree = binaryTree;else return false;} else if(path.length() > 3 && (path.compare(path.length()-3, 3, ".ot") == 0)){tree = octomap::AbstractOcTree::read(path);if(!tree)return false;}	elsereturn false;/*// Load octomapoctomap::AbstractOcTree *tree = octomap::AbstractOcTree::read(path);if(!tree)return false;*/m_octomap = dynamic_cast<octomap::OcTree*>(tree);std::cout << "Octomap loaded" << std::endl;// Check loading and alloc momery for the gridif(m_octomap == NULL){std::cout << "Error: NULL octomap!!" << std::endl;return false;}// Get map parametersdouble minX, minY, minZ, maxX, maxY, maxZ, res;m_octomap->getMetricMin(minX, minY, minZ);m_octomap->getMetricMax(maxX, maxY, maxZ);res = m_octomap->getResolution();m_maxX = (float)(maxX-minX);m_maxY = (float)(maxY-minY);m_maxZ = (float)(maxZ-minZ);m_resolution = (float)res;m_oneDivRes = 1.0/m_resolution;std::cout << "Map size:\n\tx: " << minX << " to " << maxX << std::endl;std::cout << "\ty: " << minY << " to " << maxY << std::endl;std::cout << "\tz: " << minZ << " to " << maxZ << std::endl;std::cout << "\tRes: " << m_resolution << std::endl;return true;}bool saveGrid(std::string &fileName){FILE *pf;// Open filepf = fopen(fileName.c_str(), "wb");if(pf == NULL){std::cout << "Error opening file " << fileName << " for writing" << std::endl;return false;}// Write grid general info fwrite(&m_gridSize, sizeof(int), 1, pf);fwrite(&m_gridSizeX, sizeof(int), 1, pf);fwrite(&m_gridSizeY, sizeof(int), 1, pf);fwrite(&m_gridSizeZ, sizeof(int), 1, pf);fwrite(&m_sensorDev, sizeof(float), 1, pf);// Write grid cellsfwrite(m_grid, sizeof(gridCell), m_gridSize, pf);// Close filefclose(pf);return true;}bool loadGrid(std::string &fileName){FILE *pf;// Open filepf = fopen(fileName.c_str(), "rb");if(pf == NULL){std::cout << "Error opening file " << fileName << " for reading" << std::endl;return false;}// Write grid general info fread(&m_gridSize, sizeof(int), 1, pf);fread(&m_gridSizeX, sizeof(int), 1, pf);fread(&m_gridSizeY, sizeof(int), 1, pf);fread(&m_gridSizeZ, sizeof(int), 1, pf);fread(&m_sensorDev, sizeof(float), 1, pf);m_gridStepY = m_gridSizeX;m_gridStepZ = m_gridSizeX*m_gridSizeY;// Write grid cellsif(m_grid != NULL)delete []m_grid;m_grid = new gridCell[m_gridSize];fread(m_grid, sizeof(gridCell), m_gridSize, pf);// Close filefclose(pf);return true;}void computePointCloud(void){// Get map parametersdouble minX, minY, minZ;m_octomap->getMetricMin(minX, minY, minZ);// Load the octomap in PCL for easy nearest neighborhood computation// The point-cloud is shifted to have (0,0,0) as min valuesint i = 0;m_cloud->width = m_octomap->size();m_cloud->height = 1;m_cloud->points.resize(m_cloud->width * m_cloud->height);for(octomap::OcTree::leaf_iterator it = m_octomap->begin_leafs(), end = m_octomap->end_leafs(); it != end; ++it){if(it != NULL && m_octomap->isNodeOccupied(*it)){m_cloud->points[i].x = it.getX()-minX;m_cloud->points[i].y = it.getY()-minY;m_cloud->points[i].z = it.getZ()-minZ;i++;}}m_cloud->width = i;m_cloud->points.resize(i);// Create the point cloud msg for publicationpcl::toROSMsg(*m_cloud, m_pcMsg);m_pcMsg.header.frame_id = m_globalFrameId;// Create the ICP object for future registrations aginst the mapm_icp.setInputTarget(m_cloud);}void computeGrid(void){//Publish percent variablestd_msgs::Float32 percent_msg;percent_msg.data = 0;// Alloc the 3D gridm_gridSizeX = (int)(m_maxX*m_oneDivRes);m_gridSizeY = (int)(m_maxY*m_oneDivRes); m_gridSizeZ = (int)(m_maxZ*m_oneDivRes);m_gridSize = m_gridSizeX*m_gridSizeY*m_gridSizeZ;m_gridStepY = m_gridSizeX;m_gridStepZ = m_gridSizeX*m_gridSizeY;m_grid = new gridCell[m_gridSize];// Setup kdtreem_kdtree.setInputCloud(m_cloud);// Compute the distance to the closest point of the gridint index;float dist;float gaussConst1 = 1./(m_sensorDev*sqrt(2*M_PI));float gaussConst2 = 1./(2*m_sensorDev*m_sensorDev);pcl::PointXYZ searchPoint;std::vector<int> pointIdxNKNSearch(1);std::vector<float> pointNKNSquaredDistance(1);double count=0;double percent;double size=m_gridSizeX*m_gridSizeY*m_gridSizeZ;for(int iz=0; iz<m_gridSizeZ; iz++){for(int iy=0; iy<m_gridSizeY; iy++){for(int ix=0; ix<m_gridSizeX; ix++){searchPoint.x = ix*m_resolution;searchPoint.y = iy*m_resolution;searchPoint.z = iz*m_resolution;index = ix + iy*m_gridStepY + iz*m_gridStepZ;++count;percent = count/size *100.0;ROS_INFO_THROTTLE(0.5,"Progress: %lf %%", percent);	if(m_kdtree.nearestKSearch(searchPoint, 1, pointIdxNKNSearch, pointNKNSquaredDistance) > 0){dist = pointNKNSquaredDistance[0];m_grid[index].dist = dist;m_grid[index].prob = gaussConst1*exp(-dist*dist*gaussConst2);}else{m_grid[index].dist = -1.0;m_grid[index].prob =  0.0;}}}}}void buildGridSliceMsg(float z){static int seq = 0;// Setup grid msgm_gridSliceMsg.header.frame_id = m_globalFrameId;m_gridSliceMsg.header.stamp = ros::Time::now();m_gridSliceMsg.header.seq = seq++;m_gridSliceMsg.info.map_load_time = ros::Time::now();m_gridSliceMsg.info.resolution = m_resolution;m_gridSliceMsg.info.width = m_gridSizeX;m_gridSliceMsg.info.height = m_gridSizeY;m_gridSliceMsg.info.origin.position.x = 0.0;m_gridSliceMsg.info.origin.position.y = 0.0;m_gridSliceMsg.info.origin.position.z = z;m_gridSliceMsg.info.origin.orientation.x = 0.0;m_gridSliceMsg.info.origin.orientation.y = 0.0;m_gridSliceMsg.info.origin.orientation.z = 0.0;m_gridSliceMsg.info.origin.orientation.w = 1.0;m_gridSliceMsg.data.resize(m_gridSizeX*m_gridSizeY);// Extract max probabilityint offset = (int)(z*m_oneDivRes)*m_gridSizeX*m_gridSizeY;int end = offset + m_gridSizeX*m_gridSizeY;float maxProb = -1.0;for(int i=offset; i<end; i++)if(m_grid[i].prob > maxProb)maxProb = m_grid[i].prob;// Copy data into grid msg and scale the probability to [0,100]if(maxProb < 0.000001)maxProb = 0.000001;maxProb = 100.0/maxProb;for(int i=0; i<m_gridSizeX*m_gridSizeY; i++)m_gridSliceMsg.data[i] = (int8_t)(m_grid[i+offset].prob*maxProb);}inline int point2grid(const float &x, const float &y, const float &z){return (int)(x*m_oneDivRes) + (int)(y*m_oneDivRes)*m_gridStepY + (int)(z*m_oneDivRes)*m_gridStepZ;}
};#endif

 CMakeLists.txt

cmake_minimum_required(VERSION 2.8.3)
project(bt2grid)## Find catkin macros and libraries
## if COMPONENTS list like find_package(catkin REQUIRED COMPONENTS xyz)
## is used, also find other catkin packages
set(CMAKE_CXX_STANDARD 11)
find_package(catkin REQUIRED COMPONENTSroscppstd_msgstfgeometry_msgspcl_conversions pcl_rosoctomap_rosnav_msgs
)# Ceres solver
find_package(Ceres REQUIRED)## Uncomment this if the package has a setup.py. This macro ensures
## modules and global scripts declared therein get installed
## See http://ros.org/doc/api/catkin/html/user_guide/setup_dot_py.html
# catkin_python_setup()###########
## Build ##
############# Specify additional locations of header files
## Your package locations should be listed before other locations
# include_directories(include)
include_directories(${catkin_INCLUDE_DIRS}${CERES_INCLUDE_DIRS}
)## Declare a cpp executable
add_executable(bt2grid grid3d_node.cpp)## Add cmake target dependencies of the executable/library
## as an example, message headers may need to be generated before nodes
add_dependencies(bt2grid ${catkin_EXPORTED_TARGETS})## Specify libraries to link a library or executable target against
target_link_libraries(bt2grid${catkin_LIBRARIES}
)

参考

https://github.com/robotics-upo/dll

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