ROS 2 Reinforcement Learning in Gazebo

Описание: Dive into the future of robotics! This video demonstrates how run a Reinforcement Learning (RL) loop using ROS 2 and Gazebo, showcasing the training process for a simple mobile robot - cart pole.

Reinforcement Learning is essential for creating autonomous agents that learn complex behaviors through trial and error.

This demo is the foundation for implementing advanced RL algorithms like PPO or DQN with any ROS 2 robot model.

⏱️ TIMESTAMPS:
0:00 - Github Gazebo ROS 2 & Reinforcement Learning
0:50 - Create virtual enviroment using python
1:04 - Activate virtual enviroment
1:10 - Install dependencies
2:30 - Create folder
2:38 - Run Antigravity
3:10 - Create model sdf : cart_pole.sdf
4:05 - Create program rl python : cart_pole_env.py
5:08 - Run model sdf in Gazebo
5:58 - Run program python : RL Training Loop

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Link:

https://github.com/gazebosim/gz-sim/t...

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