ROS Hydro实战指南：自动手册V1

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《ROS by Example Hydro》是一本实用指南，专为机器人操作系统（Robot Operating System, ROS）的Hydro版本量身定制。作者R.Patrick Goebel以“动手做”的教学方式，深入浅出地介绍了ROS的核心概念和技术，旨在帮助读者从基础到高级逐步掌握ROS在机器人生产环境中的应用。该书是第一版的第1.04版，针对Hydro版本进行了更新，发布于2014年1月，确保了与最新ROS技术的同步。本书的核心知识点包括： 1. **ROS概述**：介绍ROS的基本架构、设计哲学以及其作为机器人开发平台的优势，如模块化、分布式计算和消息传递机制。 2. **ROS工作流程**：涵盖了ROS的生命周期管理、节点间通信（topics和services）、消息类型和数据包（msg和srv）的使用，以及如何创建、发布和订阅这些通信机制。 3. **ROS包管理**：讲解如何安装、构建、发布和依赖管理，以及如何利用ROS的包管理系统如`catkin`来组织代码和资源。 4. **Hydro版本特色**：针对Hydro版本的新功能和改进进行详细介绍，比如新的API、工具改进以及与其他ROS版本的兼容性。 5. **ROS与第三方库和硬件集成**：展示了如何与LEGO Mindstorms等硬件平台配合，以及与其他开源库（如OpenCV、PCL等）的整合示例。 6. **实战项目**：书中包含一系列实际操作的案例，让读者通过编写代码来实践所学知识，例如路径规划、传感器数据处理和机器视觉任务。 7. **版权和许可**：强调所有内容的版权归属，并提醒读者在复制或传播任何部分时必须获得版权所有者和出版商的书面许可。《ROS by Example Hydro》不仅适合初学者系统学习ROS，也适合有一定基础的工程师用于深入理解和实践。对于想要在机器人领域应用ROS技术的专业人士来说，这是一本不可或缺的参考书籍。

4.15.2 Git 23

4.15.3 Mercurial 24

4.16 Removing Packages from your Personal catkin Directory 24

4.17 How to Find Third-Party ROS Packages 25

4.17.1 Searching the ROS Wiki 25

4.17.2 Using the roslocate Command 25

4.17.3 Browsing the ROS Software Index 27

4.17.4 Doing a Google Search 27

4.18 Getting Further Help with ROS 27

5. Installing the ros-by-example Code 29

5.1 Installing the Prerequisites 29

5.2 Cloning the Hydro ros-by-example Repository 29

5.2.1 Upgrading from Electric or Fuerte 29

5.2.2 Upgrading from Groovy 30

5.2.3 Cloning the rbx1 repository for Hydro 30

5.3 About the Code Listings in this Book 31

6. Installing the Arbotix Simulator 33

6.1 Installing the Simulator 33

6.2 Testing the Simulator 33

6.3 Running the Simulator with Your Own Robot 35

7. Controlling a Mobile Base 37

7.1 Units and Coordinate Systems 37

7.2 Levels of Motion Control 37

7.2.1 Motors, Wheels, and Encoders 38

7.2.2 Motor Controllers and Drivers 38

7.2.3 The ROS Base Controller 38

7.2.4 Frame-Base Motion using the move_base ROS Package 39

7.2.5 SLAM using the gmapping and amcl ROS Packages 39

7.2.6 Semantic Goals 40

7.2.7 Summary 40

7.3 Twisting and Turning with ROS 41

7.3.1 Example Twist Messages 41

7.3.2 Monitoring Robot Motion using RViz 42

7.4 Calibrating Your Robot's Odometry 44

7.4.1 Linear Calibration 45

7.4.2 Angular Calibration 46

7.5 Sending Twist Messages to a Real Robot 47

7.6 Publishing Twist Messages from a ROS Node 49

7.6.1 Estimating Distance and Rotation Using Time and Speed 49

7.6.2 Timed Out-and-Back in the ArbotiX Simulator 49

7.6.3 The Timed Out-and-Back Script 50

7.6.4 Timed Out and Back using a Real Robot 55

7.7 Are We There Yet? Going the Distance with Odometry 57

7.8 Out and Back Using Odometry 59

7.8.1 Odometry-Based Out and Back in the ArbotiX Simulator 59

7.8.2 Odometry-Based Out and Back Using a Real Robot 60

7.8.3 The Odometry-Based Out-and-Back Script 62

7.8.4 The /odom Topic versus the /odom Frame 67

7.9 Navigating a Square using Odometry 68

7.9.1 Navigating a Square in the ArbotiX Simulator 68

7.9.2 Navigating a Square using a Real Robot 69

7.9.3 The nav_square.py Script 71

7.9.4 The Trouble with Dead Reckoning 71

7.10 Teleoperating your Robot 71

7.10.1 Using the Keyboard 72

7.10.2 Using a Logitech Game Pad 73

7.10.3 Using the ArbotiX Controller GUI 73

7.10.4 TurtleBot Teleoperation Using Interactive Markers 74

7.10.5 Writing your Own Teleop Node 74

8. Navigation, Path Planning and SLAM 75

8.1 Path Planning and Obstacle Avoidance using move_base 75

8.1.1 Specifying Navigation Goals Using move_base 76

8.1.2 Configuration Parameters for Path Planning 77

8.1.2.1 base_local_planner_params.yaml 78

8.1.2.2 costmap_common_params.yaml 79

8.1.2.3 global_costmap_params.yaml 80

8.1.2.4 local_costmap_params.yaml 80

8.2 Testing move_base in the ArbotiX Simulator 81

8.2.1 Point and Click Navigation in RViz 86

8.2.2 Navigation Display Types for RViz 87

8.2.3 Navigating a Square using move_base 87

8.2.4 Avoiding Simulated Obstacles 94

8.2.5 Setting Manual Goals with Obstacles Present 97

8.3 Running move_base on a Real Robot 97

8.3.1 Testing move_base without Obstacles 97

8.3.2 Avoiding Obstacles using a Depth Camera as a Fake Laser 99

8.4 Map Building using the gmapping Package 101

8.4.1 Laser Scanner or Depth Camera? 102

8.4.2 Collecting and Recording Scan Data 104

8.4.3 Creating the Map 106

8.4.4 Creating a Map from Bag Data 106

8.4.5 Can I Extend or Modify an Existing Map? 108

8.5 Navigation and Localization using a Map and amcl 108

8.5.1 Testing amcl with Fake Localization 108

8.5.2 Using amcl with a Real Robot 110

8.5.3 Fully Autonomous Navigation 113

8.5.4 Running the Navigation Test in Simulation 113

8.5.5 Understanding the Navigation Test Script 115

8.5.6 Running the Navigation Test on a Real Robot 120

8.5.7 What's Next? 122

9. Speech Recognition and Synthesis 123

9.1 Installing PocketSphinx for Speech Recognition 123

9.2 Testing the PocketSphinx Recognizer 123

9.3 Creating a Vocabulary 125

9.4 A Voice-Control Navigation Script 127

9.4.1 Testing Voice-Control in the ArbotiX Simulator 132

9.4.2 Using Voice-Control with a Real Robot 133

9.5 Installing and Testing Festival Text-to-Speech 134

9.5.1 Using Text-to-Speech within a ROS Node 136

9.5.2 Testing the talkback.py script 138

10. Robot Vision 139

10.1 OpenCV, OpenNI and PCL 139

10.2 A Note about Camera Resolutions 140

10.3 Installing and Testing the ROS Camera Drivers 140

10.3.1 Installing the OpenNI Drivers 140

10.3.2 Installing Webcam Drivers 140

10.3.3 Testing your Kinect or Xtion Camera 141

10.3.4 Testing your USB Webcam 142

10.4 Installing OpenCV on Ubuntu Linux 143

10.5 ROS to OpenCV: The cv_bridge Package 144

10.6 The ros2opencv2.py Utility 149

10.7 Processing Recorded Video 151

10.8 OpenCV: The Open Source Computer Vision Library 152

10.8.1 Face Detection 152

10.8.2 Keypoint Detection using GoodFeaturesToTrack 158

10.8.3 Tracking Keypoints using Optical Flow 164

10.8.4 Building a Better Face Tracker 170

10.8.5 Dynamically Adding and Dropping Keypoints 173

10.8.6 Color Blob Tracking (CamShift) 175

10.9 OpenNI and Skeleton Tracking 181

10.9.1 Checking your OpenNI installation for Hydro 182

10.9.2 Viewing Skeletons in RViz 183

10.9.3 Accessing Skeleton Frames in your Programs 183

10.10 PCL Nodelets and 3D Point Clouds 191

10.10.1 The PassThrough Filter 191

10.10.2 Combining More than One PassThrough Filter 193

10.10.3 The VoxelGrid Filter 194

11. Combining Vision and Base Control 197

11.1 A Note about Camera Coordinate Axes 197

11.2 Object Tracker 197

11.2.1 Testing the Object Tracker with rqt_plot 197

11.2.2 Testing the Object Tracker with a Simulated Robot 198

11.2.3 Understanding the Object Tracker Code 199

11.2.4 Object Tracking on a Real Robot 205

11.3 Object Follower 206

11.3.1 Adding Depth to the Object Tracker 206

11.3.2 Testing the Object Follower with a Simulated Robot 210

11.3.3 Object Following on a Real Robot 211

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