Projects¶
This is a list of projects using stable-baselines. Please tell us, if you want your project to appear on this page ;)
Learning to drive in a day¶
Implementation of reinforcement learning approach to make a donkey car learn to drive. Uses DDPG on VAE features (reproducing paper from wayve.ai)
Donkey Gym¶
OpenAI gym environment for donkeycar simulator.
Self-driving FZERO Artificial Intelligence¶
Series of videos on how to make a self-driving FZERO artificial intelligence using reinforcement learning algorithms PPO2 and A2C.
S-RL Toolbox¶
S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics. Stable-Baselines was originally developped for this project.
Roboschool simulations training on Amazon SageMaker¶
“In this notebook example, we will make HalfCheetah learn to walk using the stable-baselines […]”
MarathonEnvs + OpenAi.Baselines¶
Experimental - using OpenAI baselines with MarathonEnvs (ML-Agents)
Learning to drive smoothly in minutes¶
Implementation of reinforcement learning approach to make a car learn to drive smoothly in minutes. Uses SAC on VAE features.
Making Roboy move with elegance¶
Project around Roboy, a tendon-driven robot, that enabled it to move its shoulder in simulation to reach a pre-defined point in 3D space. The agent used Proximal Policy Optimization (PPO) or Soft Actor-Critic (SAC) and was tested on the real hardware.
Train a ROS-integrated mobile robot (differential drive) to avoid dynamic objects¶
The RL-agent serves as local planner and is trained in a simulator, fusion of the Flatland Simulator and the crowd simulator Pedsim. This was tested on a real mobile robot. The Proximal Policy Optimization (PPO) algorithm is applied.