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Reinforcement Learning for Control of 2DoF Inverted Pendulum

Not that this project is not maintained, but should still be functional

This is a reinforcement Learning based control solution for the Quanser 2DoF Inverted Pendulum.

The implementation mainly focus on Stable Baselines implementation of Proximal Policy Optimization (PPO) and Keras-RL implementation of Double Deep Q Network. It also includes a generic wrapper for OpenAi GYM, Stable Baselines and Keras-RL.

About

This project was part of the course Design project in Systems, Control and Mechatronics at Chalmers University of Technology, Sweden, during autumn of 2018. An article about the findings from the project is avaliable in the repository: 2Dof_Inverted_Pendulum_RL.pdf

Group Members

Jonathan Jansson
Bernardo T. Barata
Christian Garcia
Fredrik J. Tornéus

Dependencies

(Apart from OpenAi GYM + stable-baselines/keras-rl and respective dependencies)

  • openai
  • gym
  • stable-baselines
  • numpy
  • PyQt5
  • pyqtgraph

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Reinforcement Learning for Control of 2DoF Inverted Pendulum

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