new tf2_ros::MessageFilter<sensor_msgs::msg::PointCloud2>( *sub, *tf_, global_frame_, 50, rclcpp_node_, tf2::durationFromSec(transform_tolerance))); filter->registerCallback( std::bind( &ObstacleLayer::pointCloud2Callback, this, std::placeholders::_1, observation_buffers_.back()));...
self.pcd = point_cloud(self.points, 'map') # Then I publish the PointCloud2 object self.pcd_publisher.publish(self.pcd) def point_cloud(points, parent_frame): """ Creates a point cloud message. Args: points: Nx3 array of xyz positions. parent_frame: frame in which the point cloud i...
voidOctomapProject::SetMapTopicMsg(constpcl::PointCloud<pcl::PointXYZ>::Ptr cloud, nav_msgs::msg::OccupancyGrid& msg){msg.header.stamp = builtin_interfaces::msg::Time(this->now());;msg.header.frame_id ="map";msg.info.map_load_time = builtin_inte...
ObstacleLayer内可以加载多种传感器的障碍物观测数据。但是数据类型只支持PointCloud2和LaserScan。其中LaserScan类型的数据会被转换成PointCloud2类型数据。因为ObservationBuffer只存储PointCloud2类型数据。 ObstacleLayer内有下面几个层级参数需要关注一下: 代码语言:yaml 复制 declareParameter("enabled",rclcpp::ParameterValu...
std::string pcd_file = "src/octomap_server/dat/pointcloudmap_2661935000.pcd"; pcd_cloud_.reset(new pcl::PointCloud<pcl::PointXYZ>()); if(pcl::io::loadPCDFile<pcl::PointXYZ>(pcd_file,*pcd_cloud_) == -1) { PCL_ERROR ("Couldn't read file: %s \n", pcd_file.c_str()); ...
#include <sensor_msgs/PointCloud2.h> main (intargc,char**argv) { ros::init (argc, argv,"pcl_create"); ros::NodeHandle nh; ros::Publisher pcl_pub = nh.advertise<sensor_msgs::PointCloud2> ("pcl_output", 1); pcl::PointCloud<pcl::PointXYZ> cloud; ...
pointcloud: topic: /intel_realsense_r200_depth/points max_obstacle_height: 2.0 clearing: True marking: True data_type: "PointCloud2" static_layer: plugin: "nav2_costmap_2d::StaticLayer" map_subscribe_transient_local: True inflation_layer: ...
The code above does nothing but initialize ROS, create a subscriber and a publisher for PointCloud2 data. Add the source file to CMakeLists.txt Edit the CMakeLists.txt file in your newly created package and add: 代码语言:javascript 复制 add_executable(example src/example.cpp) target_link...
cloud.points[i].x = msg.detection_array[i].f_x; cloud.points[i].y = msg.detection_array[i].f_y; cloud.points[i].z = msg.detection_array[i].f_z; } } // 转换为 PointCloud2 消息 sensor_msgs::msg::PointCloud2 msg2;
ROS几乎完全是从头开始构建的,自2007年以来一直由Willow Garage [7]和开源机器人基金会(OSRF)[2]维护.ROS提高了生产力[12],提供发布/订阅传输,多个库(例如 ,OpenCV和Point Cloud Library(PCL)[3]),以及帮助软件开发人员创建机器人应用程序的工具。