Pybotics

The Python Toolbox for Robotics

Item	Badges
Repo
Releases
Compatibility
Workflows
Documentation
Citations
License
Social

Pybotics

Overview

Pybotics is an open-source Python toolbox for robot kinematics and calibration. It was designed to provide a simple, clear, and concise interface to quickly simulate and evaluate common robot concepts, such as kinematics, dynamics, trajectory generations, and calibration. The toolbox is specifically designed for use with the Modified Denavit–Hartenberg parameters convention.

Usage

Documentation

Please visit https://pybotics.readthedocs.io/

Installation

# python3 is mapped to pip or inside a venv
pip install pybotics

# python3-pip
pip3 install pybotics

# https://github.com/pypa/pipenv
pipenv install pybotics

# https://github.com/sdispater/poetry
poetry add pybotics

Applications & Examples

Featured In

Citing

Please cite the following articles if you use pybotics in your research:

Nadeau, (2019). Pybotics: Python Toolbox for Robotics. Journal of Open Source Software, 4(41), 1738, https://doi.org/10.21105/joss.01738

@article{nadeau2019pybotics,
  doi = {10.21105/joss.01738},
  url = {https://doi.org/10.21105/joss.01738},
  year = {2019},
  month = sep,
  publisher = {The Open Journal},
  volume = {4},
  number = {41},
  pages = {1738},
  author = {Nicholas Nadeau},
  title = {Pybotics: Python Toolbox for Robotics},
  journal = {Journal of Open Source Software}
}

Nadeau, Nicholas A., Ilian A. Bonev, and Ahmed Joubair. "Impedance Control Self-Calibration of a Collaborative Robot Using Kinematic Coupling." Robotics 8.2 (2019): 33.

@article{nadeau2019impedance,
  title={Impedance Control Self-Calibration of a Collaborative Robot Using Kinematic Coupling},
  volume={8},
  ISSN={2218-6581},
  url={http://dx.doi.org/10.3390/robotics8020033},
  DOI={10.3390/robotics8020033},
  number={2},
  journal={Robotics},
  publisher={MDPI AG},
  author={Nadeau, Nicholas A. and Bonev, Ilian A. and Joubair, Ahmed},
  year={2019},
  month={Apr},
  pages={33}
}

Development and Community Guidelines

Local Development

Use poetry to install the dev virtual environment:

poetry install

Docker Development

Docker is a great tool to test the package in an isolated environment
It is especially useful for debugging issues between python versions

# launch container attached to current directory
docker run -v $(pwd):/$(basename $(pwd)) -w /$(basename $(pwd)) -it python:3 bash

# install deps
pip install poetry
poetry install

# run tests
make test

Commits

The repo abides by SemVer, semantic-release, and Angular commit message syntax
It is highly recommended to use the commitizen CLI
See commit examples below:

Change	Commit Type
Bumped dependency version	`build`
Bumped Python requirement	`feat`

Dependency Management

# refresh lock file
poetry lock --no-update

Submit an Issue

Navigate to the repository's issue tab
Search for related existing issues
If necessary, create a new issue using the provided templates

Contributing

Please see CONTRIBUTING.md and the Code of Conduct for how to contribute to the project

Testing

Please review the Makefile for an overview of all available tests
The most important tests and make commands are highlighted below:

# auto-format code
make format

# perform all static tests
make lint

# run all python tests
make test

GitHub Actions

This repo uses semantic-releases to generate releases and release notes automatically from commits
- A PERSONAL_TOKEN Actions secret from a Personal Token with a public_repo scope is needed for CI releases

Icons made by Pixel perfect from www.flaticon.com