[[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/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

Windows side

Windows side (grasped "clock")

''Reference Video'' ~
(Image recognition is slow because no GPU is used.)

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