OS | Kernel Version | ROS Version | Nvidia Driver Version | CUDA Version | Unity Version | Ml Agents |
---|---|---|---|---|---|---|
Ubuntu 18.04.06 LTS | 5.4.0-58-generic | ROS Melodic | 460.27.04 | 11.2 | Unity 2020.3.22f1 | Release_17 |
- com.unity.ml-agents (C#) v2.0.0
- com.unity.ml-agents.extensions (C#) v0.4.0-preview
- ml-agents (Python) v0.26.0
- ml-agents-envs (Python) v0.26.0
- gym-unity (Python) v0.26.0
- Communicator (C#/Python) v1.5.0
The pdf presentation file: ROS2Unity
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Install ROS Melodic
-
Clone this Repository and run the automatic installer
git clone https://github.com/cxdcxd/RRS.git
cd rrs_ros
./install.sh
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Download Unity 2020.3.22f1 or above
-
Open Unity Hub and go to
Projects
, clickADD
and then browse the folderrrs_unity
from the downloaded repository and launch it. Make sure theUnity Version
is set to2020.3.22f1
or above -
Open the repository in a new terminal and type
cd rrs_ros
and build the workspace:catkin_make
-
Source the workspace:
setup ~/rrs_ros/devel/setup.bash
ros launch rrs_ros rrs_main.launch
open the scenes/DemoLiquidPouring
Unity3D -> Play
ros launch mpc real_movo_sc.launch
ntp_server_host_name: test //define the ntp server hostname (current RRS is not using ntp ignored)
local_network_address: 127.0.0.1 //local ip address
consul_network_address: 127.0.0.1 //consul ip address
consul_network_mask: 255.255.255.0 //consul network mask
consul_network_port: 8500 //consul network port
<?xml version="1.0" encoding="utf-8"?>
<Config xmlns:xsd="http://www.w3.org/2001/XMLSchema" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<consul_network_address>127.0.0.1</consul_network_address>
<local_network_address>127.0.0.1</local_network_address>
<consul_network_port>8500</consul_network_port>
<consul_network_mask>255.255.255.0</consul_network_mask>
<ntp_server_host_name>test</ntp_server_host_name> //define the ntp server hostname (current RRS is not using ntp ignored)
<use_relative_origin>false</use_relative_origin>
</Config>
open the Assets\Scenes\PourNetTraining.unity
mkdir ~/python-envs
python3 -m venv ~/python-envs/sample-env
source ~/python-envs/sample-env/bin/activate
pip3 install --upgrade pip
pip3 install --upgrade setuptools
deactivate
tensorboard.exe --logdir=".\results\PourNet-LSTM" --host="0.0.0.0" --port=6006
mlagents-learn.exe .\TrainingConfig\TrainingConfig\ppo_curriculum_curiosity_lstm.yaml --env=".\ServerBuild\ServerBuild\LearnPouring" --num-envs=32 --base-port=5000 --run-id="PourNet-LSTM-Left-2"