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Update to installation procedure #58

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Update to installation procedure #58

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18ab599
Update README.md
ben-greenberg Oct 15, 2018
83a907f
Update README.md
ben-greenberg Oct 15, 2018
4781de7
Update DEMO.md
ben-greenberg Oct 15, 2018
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Merge pull request #2 from ben-greenberg/installation_changes
ben-greenberg Oct 17, 2018
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Update README.md
ben-greenberg Oct 23, 2018
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3 changes: 3 additions & 0 deletions DEMO.md
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Expand Up @@ -15,6 +15,7 @@
2. Verify robot controller
Run the robot execution node and verify that the robot arm and rail joint are moved to the home position
```
pip install kitchen
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Shouldn't this step be listed under convolutional neural network installation section?

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I believe that I only got the error about missing the kitchen package when I tried to run the test_robot_execution.py script, that's why I put the installation of it prior. I think this would probably be more appropriate in the installation section of the main README if its required to run the base application (with or without the CNN)

rosrun gilbreth_grasp_planning test_robot_execution.py
```
- If the robot failed to move then start again from step *1*.
Expand All @@ -36,6 +37,8 @@
- This step will also bring up the individual nodes for tool planning, trajectory planning,
perception and robot execution, each in its own terminal window (don't close the windows).

- Run the CNN script in a new window as follows:
THEANO_FLAGS='floatX=float32' rosrun gilbreth_perception recognition_cnn.py
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The application_run.launch file step above runs the recognition_cnn.py node so it's not necessary to run it a second time. Therefore, the right procedure should probably start with the THEANO_FLAGS environment variable declaration followed by the launch file.

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When I start up using only the application_run.launch file I get the following error: "[recognition_cnn-6] process has finished cleanly"

When I run the recognition_cnn.py node seperately it does not shut down. I'm not sure why this is but it consistently works.

### Launch node seperately (Outdated):

The script will run object_recognition, tool_planning, trajectory_planning and robot_execution nodes seperately.
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -46,7 +46,7 @@ The project is based on Ubuntu 16.04, ROS Kinect, gazebo 7.0, wstool and catkin
- Source the catkin workspace

```
cd ~/catkin_ws
cd ~/gilbreth_ws
source devel/setup.bash
```

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13 changes: 11 additions & 2 deletions gilbreth_perception/README.md
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Expand Up @@ -3,12 +3,21 @@ For using Correspondence Grouping method in object recognition:

For using convolutional neural network method in object recognition:
1. Make sure your computer has Nvidia GPU;
lspci | grep VGA

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What message should we see if there's a valid GPU?

If you have an Nvidia GPU there will be an entry like this:
02:00.0 VGA compatible controller: NVIDIA Corporation GM107GL [Quadro K620] (rev a2)

2. Install voxnet at https://github.com/dimatura/voxnet;
- Install all dependent packages
Theano http://deeplearning.net/software/theano/
Lasagne https://github.com/Lasagne/Lasagne
Theano version 0.7 http://deeplearning.net/software/theano/
pip install Theano==0.7 pygpu
Lasagne version 0.1 https://github.com/Lasagne/Lasagne
pip install Lasagne==0.1
path.py https://github.com/jaraco/path.py
pip install path.py
scikit-learn http://scikit-learn.org/stable/install.html
pip install -U scikit-learn
- Install voxnet by:
git clone https://github.com/dimatura/voxnet.git
cd voxnet
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