ROS2机器人编程简述humble-第四章-BASIC DETECTOR .3

书中程序适用于turtlebot、husky等多种机器人，配置相似都可以用的。

支持ROS2版本foxy、humble。

基础检测效果如下：

由于缺￥，所有设备都非常老旧，都是其他实验室淘汰或者拼凑出来的设备。机器人控制笔记本是2010年版本。

但是依然可以跑ROS1、ROS2。

book_ros2/br2_tf2_detector目录：

.
├── CMakeLists.txt
├── include
│   └── br2_tf2_detector
│       ├── ObstacleDetectorImprovedNode.hpp
│       ├── ObstacleDetectorNode.hpp
│       └── ObstacleMonitorNode.hpp
├── launch
│   ├── detector_basic.launch.py
│   ├── detector_improved.launch.py
│   ├── turtlebot_detector_basic.launch.py
│   └── turtlebot_detector_improved.launch.py
├── package.xml
└── src├── br2_tf2_detector│   ├── ObstacleDetectorImprovedNode.cpp│   ├── ObstacleDetectorNode.cpp│   ├── ObstacleMonitorNode (copy).cpp│   └── ObstacleMonitorNode.cpp├── detector_improved_main.cpp└── detector_main.cpp5 directories, 15 files

里面有两个部分basic和improved。

CMakelist（lib）：

cmake_minimum_required(VERSION 3.5)
project(br2_tf2_detector)set(CMAKE_CXX_STANDARD 17)# find dependencies
find_package(ament_cmake REQUIRED)
find_package(rclcpp REQUIRED)
find_package(tf2_ros REQUIRED)
find_package(geometry_msgs REQUIRED)
find_package(sensor_msgs REQUIRED)
find_package(visualization_msgs REQUIRED)set(dependenciesrclcpptf2_rosgeometry_msgssensor_msgsvisualization_msgs
)include_directories(include)add_library(${PROJECT_NAME} SHAREDsrc/br2_tf2_detector/ObstacleDetectorNode.cppsrc/br2_tf2_detector/ObstacleMonitorNode.cppsrc/br2_tf2_detector/ObstacleDetectorImprovedNode.cpp
)
ament_target_dependencies(${PROJECT_NAME} ${dependencies})add_executable(detector src/detector_main.cpp)
ament_target_dependencies(detector ${dependencies})
target_link_libraries(detector ${PROJECT_NAME})add_executable(detector_improved src/detector_improved_main.cpp)
ament_target_dependencies(detector_improved ${dependencies})
target_link_libraries(detector_improved ${PROJECT_NAME})install(TARGETS${PROJECT_NAME}detectordetector_improvedARCHIVE DESTINATION libLIBRARY DESTINATION libRUNTIME DESTINATION lib/${PROJECT_NAME}
)install(DIRECTORY launch DESTINATION share/${PROJECT_NAME})if(BUILD_TESTING)find_package(ament_lint_auto REQUIRED)ament_lint_auto_find_test_dependencies()
endif()ament_package()

障碍物识别节点

// Copyright 2021 Intelligent Robotics Lab
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.#include <memory>#include "br2_tf2_detector/ObstacleDetectorNode.hpp"#include "sensor_msgs/msg/laser_scan.hpp"
#include "geometry_msgs/msg/transform_stamped.hpp"#include "rclcpp/rclcpp.hpp"namespace br2_tf2_detector
{using std::placeholders::_1;ObstacleDetectorNode::ObstacleDetectorNode()
: Node("obstacle_detector")
{scan_sub_ = create_subscription<sensor_msgs::msg::LaserScan>("input_scan", rclcpp::SensorDataQoS(),std::bind(&ObstacleDetectorNode::scan_callback, this, _1));tf_broadcaster_ = std::make_shared<tf2_ros::StaticTransformBroadcaster>(*this);
}void
ObstacleDetectorNode::scan_callback(sensor_msgs::msg::LaserScan::UniquePtr msg)
{double dist = msg->ranges[msg->ranges.size() / 2];if (!std::isinf(dist)) {geometry_msgs::msg::TransformStamped detection_tf;detection_tf.header = msg->header;detection_tf.child_frame_id = "detected_obstacle";detection_tf.transform.translation.x = msg->ranges[msg->ranges.size() / 2];tf_broadcaster_->sendTransform(detection_tf);}
}}  // namespace br2_tf2_detector

主要就是回调函数完成大部分功能。具体参考源代码即可。

障碍物监控节点：

// Copyright 2021 Intelligent Robotics Lab
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.#include <tf2/transform_datatypes.h>
#include <tf2/LinearMath/Quaternion.h>
#include <tf2_geometry_msgs/tf2_geometry_msgs.h>#include <memory>#include "br2_tf2_detector/ObstacleMonitorNode.hpp"#include "geometry_msgs/msg/transform_stamped.hpp"#include "rclcpp/rclcpp.hpp"namespace br2_tf2_detector
{using namespace std::chrono_literals;ObstacleMonitorNode::ObstacleMonitorNode()
: Node("obstacle_monitor"),tf_buffer_(),tf_listener_(tf_buffer_)
{marker_pub_ = create_publisher<visualization_msgs::msg::Marker>("obstacle_marker", 1);timer_ = create_wall_timer(500ms, std::bind(&ObstacleMonitorNode::control_cycle, this));
}void
ObstacleMonitorNode::control_cycle()
{geometry_msgs::msg::TransformStamped robot2obstacle;try {robot2obstacle = tf_buffer_.lookupTransform("odom", "detected_obstacle", tf2::TimePointZero);} catch (tf2::TransformException & ex) {RCLCPP_WARN(get_logger(), "Obstacle transform not found: %s", ex.what());return;}double x = robot2obstacle.transform.translation.x;double y = robot2obstacle.transform.translation.y;double z = robot2obstacle.transform.translation.z;double theta = atan2(y, x);RCLCPP_INFO(get_logger(), "Obstacle detected at (%lf m, %lf m, , %lf m) = %lf rads",x, y, z, theta);visualization_msgs::msg::Marker obstacle_arrow;obstacle_arrow.header.frame_id = "odom";obstacle_arrow.header.stamp = now();obstacle_arrow.type = visualization_msgs::msg::Marker::ARROW;obstacle_arrow.action = visualization_msgs::msg::Marker::ADD;obstacle_arrow.lifetime = rclcpp::Duration(1s);geometry_msgs::msg::Point start;start.x = 0.0;start.y = 0.0;start.z = 0.0;geometry_msgs::msg::Point end;end.x = x;end.y = y;end.z = z;obstacle_arrow.points = {start, end};obstacle_arrow.color.r = 1.0;obstacle_arrow.color.g = 0.0;obstacle_arrow.color.b = 0.0;obstacle_arrow.color.a = 1.0;obstacle_arrow.scale.x = 0.02;obstacle_arrow.scale.y = 0.1;obstacle_arrow.scale.z = 0.1;marker_pub_->publish(obstacle_arrow);
}}  // namespace br2_tf2_detector

代码和原始版本稍微有些不同。

重要部分：

  try {robot2obstacle = tf_buffer_.lookupTransform("odom", "detected_obstacle", tf2::TimePointZero);} catch (tf2::TransformException & ex) {RCLCPP_WARN(get_logger(), "Obstacle transform not found: %s", ex.what());return;}double x = robot2obstacle.transform.translation.x;double y = robot2obstacle.transform.translation.y;double z = robot2obstacle.transform.translation.z;double theta = atan2(y, x);RCLCPP_INFO(get_logger(), "Obstacle detected at (%lf m, %lf m, , %lf m) = %lf rads",x, y, z, theta);

如果tf不能正常工作，会报错Obstacle transform not found：

例如odom没有

[detector-1] [WARN] [1676266943.177279939] [obstacle_monitor]: Obstacle transform not found: "odom" passed to lookupTransform argument target_frame does not exist.

例如detected_obstacle没有

[detector-1] [WARN] [1676267019.166991316] [obstacle_monitor]: Obstacle transform not found: "detected_obstacle" passed to lookupTransform argument source_frame does not exist. 

需要思考并解决问题哦^_^

如果都ok！那么"Obstacle detected at (%lf m, %lf m, , %lf m) = %lf rads"：

机器人在运动中所以角度和距离会不断变化。

此时如果查看：

rqt

其中检测tf是由激光传感器测距给出的。

节点主题图：

这个代码主程序！

// Copyright 2021 Intelligent Robotics Lab
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.#include <memory>#include "br2_tf2_detector/ObstacleDetectorNode.hpp"
#include "br2_tf2_detector/ObstacleMonitorNode.hpp"#include "rclcpp/rclcpp.hpp"int main(int argc, char * argv[])
{rclcpp::init(argc, argv);auto obstacle_detector = std::make_shared<br2_tf2_detector::ObstacleDetectorNode>();auto obstacle_monitor = std::make_shared<br2_tf2_detector::ObstacleMonitorNode>();rclcpp::executors::SingleThreadedExecutor executor;executor.add_node(obstacle_detector->get_node_base_interface());executor.add_node(obstacle_monitor->get_node_base_interface());executor.spin();rclcpp::shutdown();return 0;
}

这里需要注意！

  rclcpp::executors::SingleThreadedExecutor executor;executor.add_node(obstacle_detector->get_node_base_interface());executor.add_node(obstacle_monitor->get_node_base_interface());

如果C++掌握一般推荐看一看：

蓝桥ROS机器人之现代C++学习笔记7.1 并行基础

多线程是如何实现的。

整个程序要跑起来：

终端1-gazebo仿真：ros2 launch turtlebot3_gazebo empty_world.launch.py

ros2 launch turtlebot3_gazebo empty_world.launch.py 
[INFO] [launch]: All log files can be found below /home/zhangrelay/.ros/log/2023-02-13-13-43-10-244500-Aspire4741-10860
[INFO] [launch]: Default logging verbosity is set to INFO
urdf_file_name : turtlebot3_burger.urdf
[INFO] [gzserver-1]: process started with pid [10862]
[INFO] [gzclient   -2]: process started with pid [10864]
[INFO] [ros2-3]: process started with pid [10868]
[INFO] [robot_state_publisher-4]: process started with pid [10870]
[robot_state_publisher-4] [WARN] [1676266991.467830827] [robot_state_publisher]: No robot_description parameter, but command-line argument available.  Assuming argument is name of URDF file.  This backwards compatibility fallback will be removed in the future.
[robot_state_publisher-4] Parsing robot urdf xml string.
[robot_state_publisher-4] Link base_link had 5 children
[robot_state_publisher-4] Link caster_back_link had 0 children
[robot_state_publisher-4] Link imu_link had 0 children
[robot_state_publisher-4] Link base_scan had 0 children
[robot_state_publisher-4] Link wheel_left_link had 0 children
[robot_state_publisher-4] Link wheel_right_link had 0 children
[robot_state_publisher-4] [INFO] [1676266991.472337172] [robot_state_publisher]: got segment base_footprint
[robot_state_publisher-4] [INFO] [1676266991.472419811] [robot_state_publisher]: got segment base_link
[robot_state_publisher-4] [INFO] [1676266991.472444636] [robot_state_publisher]: got segment base_scan
[robot_state_publisher-4] [INFO] [1676266991.472465018] [robot_state_publisher]: got segment caster_back_link
[robot_state_publisher-4] [INFO] [1676266991.472485972] [robot_state_publisher]: got segment imu_link
[robot_state_publisher-4] [INFO] [1676266991.472505808] [robot_state_publisher]: got segment wheel_left_link
[robot_state_publisher-4] [INFO] [1676266991.472525491] [robot_state_publisher]: got segment wheel_right_link
[ros2-3] Set parameter successful
[INFO] [ros2-3]: process has finished cleanly [pid 10868]
[gzserver-1] [INFO] [1676266994.292818234] [turtlebot3_imu]: <initial_orientation_as_reference> is unset, using default value of false to comply with REP 145 (world as orientation reference)
[gzserver-1] [INFO] [1676266994.417396256] [turtlebot3_diff_drive]: Wheel pair 1 separation set to [0.160000m]
[gzserver-1] [INFO] [1676266994.417528534] [turtlebot3_diff_drive]: Wheel pair 1 diameter set to [0.066000m]
[gzserver-1] [INFO] [1676266994.420616206] [turtlebot3_diff_drive]: Subscribed to [/cmd_vel]
[gzserver-1] [INFO] [1676266994.425994254] [turtlebot3_diff_drive]: Advertise odometry on [/odom]
[gzserver-1] [INFO] [1676266994.428920116] [turtlebot3_diff_drive]: Publishing odom transforms between [odom] and [base_footprint]
[gzserver-1] [INFO] [1676266994.460852885] [turtlebot3_joint_state]: Going to publish joint [wheel_left_joint]
[gzserver-1] [INFO] [1676266994.461009035] [turtlebot3_joint_state]: Going to publish joint [wheel_right_joint]

终端2-障碍物检测：

ros2 launch br2_tf2_detector turtlebot_detector_basic.launch.py

终端3-rqt：rqt

终端4-rviz2：rviz2

windows端也可以获取信息。

补充：

四元数是方向的4元组表示，它比旋转矩阵更简洁。四元数对于分析涉及三维旋转的情况非常有效。四元数广泛应用于机器人、量子力学、计算机视觉和3D动画。

可以在维基百科上了解更多关于基础数学概念的信息。还可以观看一个可探索的视频系列，将3blue1brown制作的四元数可视化。

官方教程将指导完成调试典型tf2问题的步骤。它还将使用许多tf2调试工具，如tf2_echo、tf2_monitor和view_frames。

TF2完整教程提纲：

tf2

许多tf2教程都适用于C++和Python。这些教程经过简化，可以完成C++曲目或Python曲目。如果想同时学习C++和Python，应该学习一次C++教程和一次Python教程。

目录

工作区设置

学习tf2

调试tf2

将传感器消息与tf2一起使用

工作区设置

如果尚未创建完成教程的工作空间，请遵循本教程。

学习tf2

tf2简介。

本教程将让了解tf2可以为您做什么。它在一个多机器人的例子中展示了一些tf2的力量，该例子使用了turtlesim。这还介绍了使用tf2_echo、view_frames和rviz。

编写静态广播（Python）（C++）。

本教程教如何向tf2广播静态坐标帧。

编写广播（Python）（C++）。

本教程教如何向tf2广播机器人的状态。

编写监听器（Python）（C++）。

本教程教如何使用tf2访问帧变换。

添加框架（Python）（C++）。

本教程教如何向tf2添加额外的固定帧。

使用时间（Python）（C++）。

本教程教使用lookup_transform函数中的超时来等待tf2树上的转换可用。

时间旅行（Python）（C++）。

本教程向介绍tf2的高级时间旅行功能。

调试tf2

四元数基本原理。

本教程介绍ROS 2中四元数的基本用法。

调试tf2问题。

本教程向介绍调试tf2相关问题的系统方法。

将传感器消息与tf2一起使用

对tf2_ros：：MessageFilter使用标记数据类型。

本教程教您如何使用tf2_ros：：MessageFilter处理标记的数据类型。