Hello, members of community.
I will introduce my project using a Jetson Nano board.
I uploaded code and explanation about this in my Github.
- Link to the GitHub repository: https://github.com/kimbring2/jetbot_soccer
- Link to the Post : https://kimbring2.github.io/2019/10/26/jetbot.html
This is the project I started to test the Deep Learning method what I’m currently studying in an actual environment. The overall plan of the project is as follows.
- Make a Gazebo simulation similar to the soccer field situation by installing the goalpost, changing the floor to lawn.
- In this stadium, placing two Jetbot. One is for kicking the footboall and another is for defending it.
- Training a Attacker Jetbot and Defender Jetbot by the Deep Reinforcement Learning method in the situation of Multi-Agent such as Self-Play of AlphaGo Zero.
- When the training is completed, confirmed the performance using the actual soccer field and Jetbot equipped with the trained model of Gazebo.
No matter how well the simulation is made, there are many cases where the operation of is not good in the actual situation becasue of various physical factor. Thus, I plan to use many Deep Reinforcement Learning methods that have been studied to solve this such as https://github.com/iclavera/learning_to_adapt .
If you have any question about my project, please leave a comment.
Thank you for reading!!