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Description

Tutorial to learn the insights of the automatic LQR tuning framework proposed in our paper.
Remark: This code was not used to generate the results published in the paper. Instead, it is a collection of simple examples to merely illustrate how the proposed method works. It has been created for academic purposes.

Alonso Marco, Philipp Hennig, Jeannette Bohg, Stefan Schaal, Sebastian Trimpe,
"Automatic LQR Tuning Based on Gaussian Process Global Optimization", 
International Conference on Robotics and Automation (ICRA),
2016, accepted.

The following two videos summarize the benefits of our contribution, demonstrated on two robotic platforms:

  1. Robot arm balancing an inverted pole
  2. Two-legged robot performing a squatting task

The tutorials come with visualization tools and are self explanatory. Just follow the explanations.

Requirements

Matlab 2017 or higher.

Installation

Run the following script before starting the tutorial

start_up

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Tutorial to learn the insights of the automatic LQR tuning framework proposed in our [paper](https://arxiv.org/abs/1605.01950)

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