Backup source of (TurtleBot3)Grasp Automatically(No. 6)

[[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
 $ cd darknet_ros
 $ 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/ExampleScenes/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)

----
''Reference Video'' ~
(Image recognition is slow because no GPU is used.)
#youtube(eZgu1bO7KMM)
Backup source of (TurtleBot3)Grasp Automatically (No. 6)
