CoMoDO

Control Motion Design Optimization

CoMoDO is a suite of parametrized controllers and simulators for codesign of robots.

⚠️ REPOSITORY UNDER DEVELOPMENT ⚠️
We cannot guarantee stable API

Table of contents

• ⚙️ Dependencies
• 💾 Installation
  • 🐍 Installation with conda
  • 📦 Installation with pixi
• 🚀 Usage
• :construction_worker: Maintainer

⚙️ Dependencies

This library depends on

• casadi
• numpy
• idyntree
• bipedal-locomotion-framework
• adam-robotics
• matplotlib
• urllib3
• urchin

And, optionally, on:

• mujoco and mujoco-python-viewer
• jaxsim
• drake
• hippopt

💾 Installation

🐍 Installation with conda

To install comodo in a conda environment, you can use the following commands

```bash conda create -n comododev -c conda-forge adam-robotics bipedal-locomotion-framework=0.19.0 mujoco-python-viewer matplotlib urllib3 urchin notebook jaxsim

conda activate comododev pip install --no-deps git+https://github.com/CarlottaSartore/urdf-modifiers.git@scalar_modification pip install --no-deps -e .

```

With hippopt

To work in comodo with hippopt requires to install also the following packages:

bash conda install -c conda-forge -c robotology casadi pytest liecasadi meshcat-python ffmpeg-python pip install --no-deps git+https://github.com/ami-iit/hippopt.git

With Drake

To use drake as the simulator backend requires the following additional dependencies:

bash conda install meshio tqdm pip install drake git+https://github.com/ami-iit/amo_urdf

📦 Installation with pixi

An alternative and easy way to use comodo is with pixi package manager. It automatically handles the creation and activation of virtual environments in which to use the different simulators that comodo supports.

At the moment there is an environment associated with each simulation or planning backend, namely: - mujoco: for MuJoCo simulator - jaxsim: for JaxSim simulator - drake: for Drake simulator - hippopt: for Hippopt walking planner - all for all the simulators

To activate one of these environments in a terminal run:

bash pixi shell -e <environment-name>

It is also possible to run directly a command in one of these environments using:

bash pixi run -e <environment-name> python <script-filename.py>

For example, it is possible to run the Jupyter notebooks in the examples folder by just executing:

bash pixi run -e all jupyter notebook

and then running the examples you prefer in Jupyter.

🚀 Usage

Take a look at the examples folder!

:construction_worker: Maintainer

This repository is maintained by | | | | :----------------------------------------------------------: | :--------------------------------------------------: | | | @CarlottaSartore |