COSCUP 2016 - ROS + Gazebo機器人模擬器工作坊
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COSCUP 2016 - ROS + Gazebo機器人模擬器工作坊
- 1. ROS + Gazebo 機器人模擬器 工作坊 Presenter: 賴柏任 https://www.facebook.com/PoJenLai 08.20.2016 Brought to you by COSCUP 2016
- 2. Who am I • 大學時有幸透過專題接觸 ROS，並陸續發表一 些 ROS 的介紹文章 https://pojenlai.wordpress.com/ • 研究所的論文內容也是用 ROS 來開發 https://github.com/Po- Jen/transparent_objects/tree/addedfeature • 工作閒暇之餘希望可以持續學習、也提供更多 資源給大家 http://blog.techbridge.cc/ http://weekly.techbridge.cc/ 2
- 3. Who am I • 順便推薦一下 ROS.Taipei 社群 https://www.facebook.com/groups/122728288090359/ 3
- 4. Outline • ROS Introduction • ROS Basic Mechanism • ROS Tool Overview • Gazebo Introduction • Gazebo Usage • Navigation & SLAM 4
- 6. What is ROS ? 6 http://answers.ros.org/question/12230/what-is-ros-exactly-middleware-framework-operating-system/#18055 • ROS is acronym for Robot OS, but it is not a traditional OS like Windows, Ubuntu or Mac OS
- 7. What is ROS ? 7 • Before we move on, we should clarify something • Robot software = Distributed computing system Decision Maker Object Recognition Object GraspingNavigation
- 8. What is ROS ? 8 • ROS is a set of tools which enables – Easy construction of distributed computing systems (Programs can be individually designed and easily connected at runtime) – Code reuse – Configuring, starting, introspecting, debugging, visualizing, logging, testing, and stopping distributed computing systems
- 9. Why is ROS preferred ? 9 • It encourages users not to reinvent the wheel
- 10. Why is ROS preferred ? 10 • Many open-sourced libraries – SLAM (OpenSLAM) – Real-time control(OROCOS) – Path Planning (Openrave) – Vision (OpenCV, PCL) – 3D Simulator (Gazebo) – 3D Visualizer (Rviz)
- 11. Why is ROS preferred ? 11 • Package can be written in multiple programming languages – C++ – Python – Lisp • And many more experimental support – C#, Go, Haskell, Java, Node.js, Lua, R, Ruby – http://wiki.ros.org/Client%20Libraries
- 12. Can ROS be used on different robot? 12 • Of course! • Check all robots using ROS - http://wiki.ros.org/Robots https://vimeo.com/146183080
- 13. ROS Basic Mechanism & Tool 13
- 14. 建立ROS workspace • 建立一個空的環境並編譯 – $ mkdir -p ~/catkin_ws/src – $ cd ~/catkin_ws/src – $ catkin_init_workspace – $ cd ~/catkin_ws – $ catkin_make 14
- 15. File System • Basic unit - package – CMakeLists.txt – package.xml • ROS package 使用catkin 這工具來進行編譯 – 按照 ROS 規定的格式寫code，就可以用catkin編譯 15
- 16. rosbuild v.s. catkin • rosbuild – ROS Groovy之前的編譯系統 – 有部分package仍未porting到catkin上，故仍需略懂 – 所有原始碼和編譯後的檔案都在同一資料夾下 • Catkin – ROS Groovy之後的編譯系統 – 原始碼和編譯後的檔案分離 • 接著直接來寫個node看看怎麼編譯 16
- 17. ROS Node • Basic unit of program 17 Decision Maker Object Recognition Object GraspingNavigation Node 1 Node 2 Node 3 Node 4
- 19. Create our first package & write a node • 步驟先全部列在這，接著讓我們一步步來做 – cd ~/catkin_ws/src catkin_create_pkg coscup_1_node rospy cd coscup_1_node vim src/node.py chmod +x src/node.py cd ../.. catkin_make source devel/setup.bash roscore rosrun coscup_1_node node.py rqt_graph 19
- 20. ROS Master • How do node knows each other? => ROS Master • Control the graph of nodes 20
- 21. rqt_graph • Visualization of nodes and topics • Part of rqt (integrates lots of debugging tools) 21
- 22. How do ROS node communicate? • ROS master as a message hub? – What if there are many nodes? 22
- 23. How do ROS node communicate? • Let nodes communicates with each other directly – Topic, Service, ActionLib • If ROS does not exists – Socket – Shared memory – We have to take care of these tedious work. 23
- 24. ROS Topic • Publisher/Subscriber mechanism (topic == bucket) 24 Perception Object Recognition Semantic Map Camera data Recognition result
- 25. rostopic • 寫一個publisher (一直丟字串到topic_name這個topic) – catkin_create_pkg coscup_2_topic rospy std_msgs cd coscup_2_topic vim src/publisher.py chmod +x src/publisher.py cd ../.. catkin_make source devel/setup.bash roscore rosrun coscup_2_topic publisher.py rqt_graph rostopic echo topic_name rostopic list rostopic list | grep topic 25
- 26. rqt_graph • Now, it should looks like 26
- 27. rostopic • 寫一個subscriber (從topic_name這個topic取出data) – cd ~/catkin_ws/src cd coscup_2_topic vim src/subscriber.py chmod +x src/subscriber.py rosrun coscup_2_node subscriber.py rqt 27
- 28. rqt_graph • Now, it should looks like 28
- 29. rqt • We can try console 29
- 30. Define our own msg for topic • 創建一個只有一個int的msg – cd ~/catkin_ws/src cd coscup_2_topic mkdir msg vim msg/Num.msg vim package.xml vim CMakeLists.txt cd ../.. catkin_make source devel/setup.bash rosmsg show coscup_2_topic/Num 30
- 31. package.xml • Add build dependency and run dependency 31
- 32. CMakeLists.txt (1) • Add package dependency • Or you can – catkin_create_pkg coscup_2_topic rospy std_msgs message_generation 32
- 33. CMakeLists.txt (2) • Add build dependency • Add msg file • We use std_msgs/int64 in our msg file 33
- 34. Publish自己寫的msg • 步驟 – cd ~/catkin_ws/src/coscup_2_topic/ vim src/my_msg_publisher.py chmod +x src/my_msg_publisher.py rosrun coscup_2_topic my_msg_publisher.py rostopic echo my_msg_topic_name 34
- 35. One more example • geometry_msgs/Twist 35
- 36. One more example • geometry_msgs/Vector3 36
- 37. How is the abstraction implemented? 37 /cmd_vel topic Base Controller Motor Speed geometry_msgs/Twist 將速度和角速度 轉成馬達命令
- 38. ROS Service • Query/Response Style 38 Object Recognition Brain 1 query 2 response
- 39. ROS Service • 建立一個自己的srv格式 – cd ~/catkin_ws/src catkin_create_pkg coscup_3_service rospy std_msgs cd coscup_3_service mkdir srv vim srv/AddTwoInts.srv vim package.xml vim CMakeLists.txt cd ../.. catkin_make source devel/setup.bash rossrv show coscup_3_service/AddTwoInts 39
- 40. package.xml • Add build dependency and run dependency 40
- 41. CMakeLists.txt • Add service file • Add std_msgs dependency 41
- 42. ROS Service • 寫一個server – cd coscup_3_service vim src/add_two_ints_server.py cd ../.. source devel/setup.bash chmod +x src/add_two_ints_server.py rosrun coscup_3_service add_two_ints_server.py 42
- 43. ROS Service • 寫一個client，送出request給server – cd coscup_3_service vim src/add_two_ints_client.py chmod +x src/add_two_ints_client.py run coscup_3_service add_two_ints_client.py 5 6 43
- 44. Rviz • An important tool for data visualization • 先啟動你們的Rviz – $ sudo apt-get install ros-indigo-rviz-* – $ roscore – $ rviz • Will be revisited when we use Gazebo 44
- 45. Find out more on ROS Cheat Sheet • https://github.com/ros/cheatsheet 45
- 47. What is Gazebo ? • 3D物理模擬器 –機器人控制 –環境模擬 –物體物理特性模擬 • 用途廣泛 –DARPA Challenge也是用Gazebo來開發 47
- 49. Gazebo Usage 49
- 50. Started Gazebo • 先確保該安裝的東西都有被安裝 – $ sudo apt-get install ros-indigo-gazebo-* – $ sudo apt-get install ros-indigo-pr2-* • 啟動Gazebo – $ gazebo • 加入一些模型並存成world file 50
- 51. Play around with Rviz 51
- 53. 先來個 SLAM 的 DEMO • Gazebo 開啟 PR2 進行 SLAM 53
- 54. 讓我們來實際操作 • Gazebo 開啟 PR2 進行 SLAM – $ roslaunch pr2_gazebo pr2_empty_world.launch – $ 加入自己喜歡的模型 – $ roslaunch pr2_build_map.launch – $ rviz – $ roslaunch pr2_teleop teleop_keyboard.launch – $ rosrun map_server map_saver 54
- 55. SLAM 演算法簡介 • gmapping package (grid mapping) http://wiki.ros.org/gmapping • Grid map –Map is presented by 2D array –Each grid • 0: free • 1: occupied 55
- 57. Map representation • Given sensor data zt and the poses of the sensor xt, estimate the map • 推導就不細講了 – http://ais.informatik.uni- freiburg.de/teaching/ws12/mapping/pdf/slam11-gridmaps-4.pdf 57
- 58. Resources you can leverage • ROS wiki http://wiki.ros.org/ • ROS Answers http://answers.ros.org/questions/ • Gazebo Answers http://answers.gazebosim.org/questions/ • ROS Taipei 中文資源整理 https://hackpad.com/-ROS-Blog--lnDeWhHXH4T 58
- 59. ROS 2.0 • 欲改進的點 – 多機器人協作 (ROS 1.0是for PR2開發的) – 嵌入式平台開發 (不必再透過一層額外driver) – real-time系統 (能有更精準的控制能力) – 適用於產品開發 (原本偏向學術研究用) – 設計模式的建立 59
- 60. ROS 2.0 學習資源 • Official website – http://design.ros2.org/ • ROS 2.0 中文翻譯( under construction…) – http://po-jen.github.io/design/ • Tutorials from Erle-Robotics – http://erlerobotics.com/docs/Robot_Operating_System/ROS_2/T utorials/index.html 60
- 61. Thanks for joining, you guys rock! 61
- 63. Example - ros_caffe • Github page – https://github.com/tzutalin/ros_caffe • Tutorial – http://www.artificialhumancompanions.com/integrating-ros-caffe- opencv-on-the-autonomous-deep-learning-robot/ • 使用topic_tools轉換Gazebo的PR2的topic name – rosrun topic_tools relay /wide_stereo/left/image_raw /camera/rgb/image_raw 63