Benchmark for Robustness Tests of Control Alrogithms

Related tags

Algorithms benchmark control gym pendulum robustness mppi mbrl smppi
Overview

Benchmark for Robustness Tests of Control Alrogithms

This repository contains classical control benchmarks for evaluating robustnesses of control and reinforcement learning algorithms. It can be used as zero-shot control performence evaluations. It is built upon OpenAI Gym.

Installation

Clone repository, then 'pip install -e .' or 'pip3 install -e .' based on your environment.

Or you can manually install dependencies:

- numpy
- gym

How to Run Example

You can run our test example by:

python unstable_pendulum.py

It's a inverted pendulum in gym environment. The sample results of the four different controllers are shown below:

Sine wave side wind Random side wind

How to Use

Simply import environments from 'unstable_gym'. For examples, for inverted pendulum:

from unstable_gym.unstable_pendulum import UnstablePendulumEnv
env = UnstablePendulumEnv(wind_type="sine", max_wind=1.0)

obs = env.reset()
for step in range(500):
    action = env.action_space.sample()
    nobs, reward, done, info = env.step(action)
    env.render()

There are two options for "wind type":

  1. "sine" : sine wave side wind
  2. "random" : random side wind

You can also adjust the magnitude of the side wind (in [N]): "max_wind"

Related Works

You can test the robustness of MPPI and Smooth_MPPI

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Comments
  • Addition of CartPole Environment, and some Error Corrections

    Addition of CartPole Environment, and some Error Corrections

    Hi Taekyung Kim, the objective of this request is to add continuous cartpole environment and to apply slight modifications on your work.

    1. New Environment
    • I added continuous action cartpole environment in your work. Unlike cartpole environment of openAI gym in which action is discrete(Left or Right), in this environment, action varies continuously from -10.0 to 10.0.
    • The magnitude of wind is converted into magnitude of torque(wind_torque), and then it is applied to system dynamics in 'step' function.
    1. Error Correction
    • If the sign of wind is plus(+), wind blows from left to right. Otherwise, wind blows from right to left. So I modified 'Line 117-118' of 'unstable_pendulum.py' to fit this sign convention.
    • Deletion of some print commands in 'unstable_pendulum.py'
    • Some Typo Corrections

    Thanks for your great work, Taekyung.

    opened by hojin1117 2
Owner
Kim Taekyung
Autonomous driving, robotics researcher @ ADD; B.S. @ DGIST; 1st winner in Samsung Robot Hackathon 2018,2019.
Kim Taekyung
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