[[Tutorial using ROS for ver.3]] * Grasping with TurtleBot3 automatically [#e93a5390] This example is a simple example that automatically grasps an object. TurtleBot3 has OpenManipulator. Object recognition by darknet_ros (YOLO) and Point Cloud data are used. ~ So CUDA must be installed in the Ubuntu in order to recognize objects using YOLO. ~ Although it is possible to check this example scene using CPU without installing CUDA, the object recognition speed is very slow. The outline of the operation is as follows. + Move the TurtleBot3 to the front of the target object by keyboard operation. + Move the TurtleBot3 so that the target object comes to the center of the color image. + Select the target object by keyboard operation. When the above operation is performed, TurtleBot3 tries to grasp the object as follows: + The darknet_ros (YOLO) performs object recognition using a color image. + Estimate the 3D position of the target object using color images and Point Cloud information. + Grasp the calculated 3D position. Please refer to [[here>http://emanual.robotis.com/docs/en/platform/turtlebot3/manipulation/#manipulation]] for the specifications of Open Manipulator. ~ Please refer to [[here>http://emanual.robotis.com/docs/en/platform/turtlebot3/appendix_realsense/]] for camera specifications.~ Because it is convenient to shorten the minimum distance of the depth sensor, RealSense SR300 is used instead of RealSense R200. ** Build Ubuntu environment [#c709f1fe] In this example, darknet_ros (YOLO) needs to be installed in Ubuntu environment. ~ It is recommended to check the operation of [[normal darknet>https://github.com/pjreddie/darknet]] without using ros. ~ ''We confirmed that it works with darknet_ros version 1.1.4.'' The procedure is as follows: + Download and install CUDA from [[here>https://developer.nvidia.com/cuda-downloads]]. (As mentioned above, it is also possible to run using the CPU without installing CUDA) ~ (For details, please adjust according to your PC and NVIDIA Driver environment.) + Git clone darknet_ros. ([[Reference>https://github.com/leggedrobotics/darknet_ros]]) ~ However, please check out the specific commit and download additional data. $ cd ~/catkin_ws/src $ git clone --recursive https://github.com/leggedrobotics/darknet_ros.git $ git checkout ac666ab8e8e3dd23a8a95d891fb90874e63c8cb5 $ cd ~/catkin_ws/src/darknet_ros/darknet_ros/yolo_network_config/weights/ $ wget http://pjreddie.com/media/files/yolo.weights + Install darknet_ros. ([[Reference>https://github.com/leggedrobotics/darknet_ros]]) $ cd ~/catkin_ws $ catkin_make -DCMAKE_BUILD_TYPE=Release ** Startup Procedure [#bc27b1e9] Start the Ubuntu side and then the Windows side. *** Ubuntu side startup procedure [#l39593fd] Open a new terminal and run the following command: $ roslaunch sigverse_turtlebot3_open_manipulator grasping_auto.launch *** Windows side startup procedure [#df821e14] Start the [Assets/SIGVerse/SampleScenes/Turtlebot3/OpenManipulatorSR300(.unity)] scene with reference to [[here>Tutorial using ROS for ver.3#open_scene]]. ** Run [#sd88b953] You can control TurtleBot3 by keyboard operation on the grasping_auto terminal. ~* Check the terminal for details of the operation. If you want to finish, stop the Unity side and then the ROS side. Ubuntu side #ref(TurtleBot3GraspAutoUbuntu.png) Windows side #ref(TurtleBot3GraspAutoWindows.png) Windows side (grasped "clock") #ref(TurtleBot3GraspAutoWindowsGrasping.png)