pinocchio repository

Repository Summary

Checkout URI https://github.com/stack-of-tasks/pinocchio.git
VCS Type git
VCS Version devel
Last Updated 2022-09-28
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pinocchio 2.6.10

README

Pinocchio Logo

License Coverage Report Conda Downloads Conda Version PyPI version

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics software as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

or via pip (currently only available on Linux):

pip install pin

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible. Pinocchio is multi-thread friendly. Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications). Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Pinocchio continuous integrations

Pinocchio is constantly tested for several platforms and distributions, as reported below:

<!-- -->
Continuous Integration
CI on ROS ROS
CI on Linux via APT linux
CI on OSX via Conda mac
CI on Windows via Conda windows
CI on Linux via Robotpkg Pipeline Status

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here. A cheat sheet pdf with the main functions and algorithms can be found here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples directory. Additional examples introducing Pinocchio are also available in the documentation.

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robot control. Tutorial and training documents are listed here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.
  • RViz: supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@inria.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Open-source projects relying on Pinocchio

  • Crocoddyl A software to realize model predictive control for complex robotics platform.
  • TSID A software which implements an Task Space Inverse Dynamics QP.
  • HPP A SDK which implements motion planner for humanoids and other robots.
  • Jiminy A simulator based on Pinocchio.
  • ocs2 A toolbox for Optimal Control for Switched Systems (OCS2)
  • TriFingerSimulation TriFinger Robot Simulation (a Robot to perform RL on manipulation).
  • Casadi_Kin_Dyn IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to pinocchio. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check [existing open][issues], or [recently closed][closed-issues], issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

The following guidance should be up-to-date, but the documentation as found here should prove as the final say.

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. Limited scope. Your PR should do one thing or one set of things. Avoid adding “random fixes” to PRs. Put those on separate PRs.
  2. Give your PR a descriptive title. Add a short summary, if required.
  3. Make sure the pipeline is green.
  4. Don’t be afraid to request reviews from maintainers.
  5. New code = new tests. If you are adding new functionality, always make sure to add some tests exercising the code and serving as live documentation of your original intention.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass. (make test)
  4. Commit to your fork using clear commit messages.
  5. Send a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional documentation on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As this project, by default, uses the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'][help-wanted] issues is a great place to start.

Licensing

Any contribution that you make to this repository will be under the BSD Clause 2 License, as dictated by that [license]:

BSD 2-Clause License

Copyright (c) 2014-2021, CNRS 
Copyright (c) 2018-2021, INRIA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the Pinocchio project.

issues closed-issues help-wanted license


Repository Summary

Checkout URI https://github.com/stack-of-tasks/pinocchio.git
VCS Type git
VCS Version devel
Last Updated 2022-09-28
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pinocchio 2.6.10

README

Pinocchio Logo

License Coverage Report Conda Downloads Conda Version PyPI version

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics software as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

or via pip (currently only available on Linux):

pip install pin

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible. Pinocchio is multi-thread friendly. Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications). Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Pinocchio continuous integrations

Pinocchio is constantly tested for several platforms and distributions, as reported below:

<!-- -->
Continuous Integration
CI on ROS ROS
CI on Linux via APT linux
CI on OSX via Conda mac
CI on Windows via Conda windows
CI on Linux via Robotpkg Pipeline Status

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here. A cheat sheet pdf with the main functions and algorithms can be found here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples directory. Additional examples introducing Pinocchio are also available in the documentation.

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robot control. Tutorial and training documents are listed here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.
  • RViz: supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@inria.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Open-source projects relying on Pinocchio

  • Crocoddyl A software to realize model predictive control for complex robotics platform.
  • TSID A software which implements an Task Space Inverse Dynamics QP.
  • HPP A SDK which implements motion planner for humanoids and other robots.
  • Jiminy A simulator based on Pinocchio.
  • ocs2 A toolbox for Optimal Control for Switched Systems (OCS2)
  • TriFingerSimulation TriFinger Robot Simulation (a Robot to perform RL on manipulation).
  • Casadi_Kin_Dyn IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to pinocchio. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check [existing open][issues], or [recently closed][closed-issues], issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

The following guidance should be up-to-date, but the documentation as found here should prove as the final say.

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. Limited scope. Your PR should do one thing or one set of things. Avoid adding “random fixes” to PRs. Put those on separate PRs.
  2. Give your PR a descriptive title. Add a short summary, if required.
  3. Make sure the pipeline is green.
  4. Don’t be afraid to request reviews from maintainers.
  5. New code = new tests. If you are adding new functionality, always make sure to add some tests exercising the code and serving as live documentation of your original intention.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass. (make test)
  4. Commit to your fork using clear commit messages.
  5. Send a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional documentation on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As this project, by default, uses the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'][help-wanted] issues is a great place to start.

Licensing

Any contribution that you make to this repository will be under the BSD Clause 2 License, as dictated by that [license]:

BSD 2-Clause License

Copyright (c) 2014-2021, CNRS 
Copyright (c) 2018-2021, INRIA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the Pinocchio project.

issues closed-issues help-wanted license


Repository Summary

Checkout URI https://github.com/stack-of-tasks/pinocchio.git
VCS Type git
VCS Version devel
Last Updated 2022-09-28
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pinocchio 2.6.10

README

Pinocchio Logo

License Coverage Report Conda Downloads Conda Version PyPI version

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics software as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

or via pip (currently only available on Linux):

pip install pin

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible. Pinocchio is multi-thread friendly. Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications). Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Pinocchio continuous integrations

Pinocchio is constantly tested for several platforms and distributions, as reported below:

<!-- -->
Continuous Integration
CI on ROS ROS
CI on Linux via APT linux
CI on OSX via Conda mac
CI on Windows via Conda windows
CI on Linux via Robotpkg Pipeline Status

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here. A cheat sheet pdf with the main functions and algorithms can be found here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples directory. Additional examples introducing Pinocchio are also available in the documentation.

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robot control. Tutorial and training documents are listed here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.
  • RViz: supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@inria.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Open-source projects relying on Pinocchio

  • Crocoddyl A software to realize model predictive control for complex robotics platform.
  • TSID A software which implements an Task Space Inverse Dynamics QP.
  • HPP A SDK which implements motion planner for humanoids and other robots.
  • Jiminy A simulator based on Pinocchio.
  • ocs2 A toolbox for Optimal Control for Switched Systems (OCS2)
  • TriFingerSimulation TriFinger Robot Simulation (a Robot to perform RL on manipulation).
  • Casadi_Kin_Dyn IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to pinocchio. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check [existing open][issues], or [recently closed][closed-issues], issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

The following guidance should be up-to-date, but the documentation as found here should prove as the final say.

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. Limited scope. Your PR should do one thing or one set of things. Avoid adding “random fixes” to PRs. Put those on separate PRs.
  2. Give your PR a descriptive title. Add a short summary, if required.
  3. Make sure the pipeline is green.
  4. Don’t be afraid to request reviews from maintainers.
  5. New code = new tests. If you are adding new functionality, always make sure to add some tests exercising the code and serving as live documentation of your original intention.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass. (make test)
  4. Commit to your fork using clear commit messages.
  5. Send a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional documentation on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As this project, by default, uses the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'][help-wanted] issues is a great place to start.

Licensing

Any contribution that you make to this repository will be under the BSD Clause 2 License, as dictated by that [license]:

BSD 2-Clause License

Copyright (c) 2014-2021, CNRS 
Copyright (c) 2018-2021, INRIA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the Pinocchio project.

issues closed-issues help-wanted license


Repository Summary

Checkout URI https://github.com/stack-of-tasks/pinocchio.git
VCS Type git
VCS Version devel
Last Updated 2022-09-28
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pinocchio 2.6.10

README

Pinocchio Logo

License Coverage Report Conda Downloads Conda Version PyPI version

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics software as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

or via pip (currently only available on Linux):

pip install pin

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible. Pinocchio is multi-thread friendly. Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications). Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Pinocchio continuous integrations

Pinocchio is constantly tested for several platforms and distributions, as reported below:

<!-- -->
Continuous Integration
CI on ROS ROS
CI on Linux via APT linux
CI on OSX via Conda mac
CI on Windows via Conda windows
CI on Linux via Robotpkg Pipeline Status

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here. A cheat sheet pdf with the main functions and algorithms can be found here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples directory. Additional examples introducing Pinocchio are also available in the documentation.

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robot control. Tutorial and training documents are listed here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.
  • RViz: supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@inria.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Open-source projects relying on Pinocchio

  • Crocoddyl A software to realize model predictive control for complex robotics platform.
  • TSID A software which implements an Task Space Inverse Dynamics QP.
  • HPP A SDK which implements motion planner for humanoids and other robots.
  • Jiminy A simulator based on Pinocchio.
  • ocs2 A toolbox for Optimal Control for Switched Systems (OCS2)
  • TriFingerSimulation TriFinger Robot Simulation (a Robot to perform RL on manipulation).
  • Casadi_Kin_Dyn IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to pinocchio. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check [existing open][issues], or [recently closed][closed-issues], issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

The following guidance should be up-to-date, but the documentation as found here should prove as the final say.

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. Limited scope. Your PR should do one thing or one set of things. Avoid adding “random fixes” to PRs. Put those on separate PRs.
  2. Give your PR a descriptive title. Add a short summary, if required.
  3. Make sure the pipeline is green.
  4. Don’t be afraid to request reviews from maintainers.
  5. New code = new tests. If you are adding new functionality, always make sure to add some tests exercising the code and serving as live documentation of your original intention.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass. (make test)
  4. Commit to your fork using clear commit messages.
  5. Send a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional documentation on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As this project, by default, uses the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'][help-wanted] issues is a great place to start.

Licensing

Any contribution that you make to this repository will be under the BSD Clause 2 License, as dictated by that [license]:

BSD 2-Clause License

Copyright (c) 2014-2021, CNRS 
Copyright (c) 2018-2021, INRIA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the Pinocchio project.

issues closed-issues help-wanted license


Repository Summary

Checkout URI https://github.com/stack-of-tasks/pinocchio.git
VCS Type git
VCS Version devel
Last Updated 2022-09-28
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pinocchio 2.6.10

README

Pinocchio Logo

License Coverage Report Conda Downloads Conda Version PyPI version

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics software as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

or via pip (currently only available on Linux):

pip install pin

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible. Pinocchio is multi-thread friendly. Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications). Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Pinocchio continuous integrations

Pinocchio is constantly tested for several platforms and distributions, as reported below:

<!-- -->
Continuous Integration
CI on ROS ROS
CI on Linux via APT linux
CI on OSX via Conda mac
CI on Windows via Conda windows
CI on Linux via Robotpkg Pipeline Status

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here. A cheat sheet pdf with the main functions and algorithms can be found here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples directory. Additional examples introducing Pinocchio are also available in the documentation.

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robot control. Tutorial and training documents are listed here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.
  • RViz: supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@inria.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Open-source projects relying on Pinocchio

  • Crocoddyl A software to realize model predictive control for complex robotics platform.
  • TSID A software which implements an Task Space Inverse Dynamics QP.
  • HPP A SDK which implements motion planner for humanoids and other robots.
  • Jiminy A simulator based on Pinocchio.
  • ocs2 A toolbox for Optimal Control for Switched Systems (OCS2)
  • TriFingerSimulation TriFinger Robot Simulation (a Robot to perform RL on manipulation).
  • Casadi_Kin_Dyn IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to pinocchio. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check [existing open][issues], or [recently closed][closed-issues], issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

The following guidance should be up-to-date, but the documentation as found here should prove as the final say.

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. Limited scope. Your PR should do one thing or one set of things. Avoid adding “random fixes” to PRs. Put those on separate PRs.
  2. Give your PR a descriptive title. Add a short summary, if required.
  3. Make sure the pipeline is green.
  4. Don’t be afraid to request reviews from maintainers.
  5. New code = new tests. If you are adding new functionality, always make sure to add some tests exercising the code and serving as live documentation of your original intention.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass. (make test)
  4. Commit to your fork using clear commit messages.
  5. Send a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional documentation on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As this project, by default, uses the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'][help-wanted] issues is a great place to start.

Licensing

Any contribution that you make to this repository will be under the BSD Clause 2 License, as dictated by that [license]:

BSD 2-Clause License

Copyright (c) 2014-2021, CNRS 
Copyright (c) 2018-2021, INRIA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the Pinocchio project.

issues closed-issues help-wanted license


Repository Summary

Checkout URI https://github.com/stack-of-tasks/pinocchio.git
VCS Type git
VCS Version devel
Last Updated 2022-09-28
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pinocchio 2.6.10

README

Pinocchio Logo

License Coverage Report Conda Downloads Conda Version PyPI version

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics software as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

or via pip (currently only available on Linux):

pip install pin

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible. Pinocchio is multi-thread friendly. Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications). Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Pinocchio continuous integrations

Pinocchio is constantly tested for several platforms and distributions, as reported below:

<!-- -->
Continuous Integration
CI on ROS ROS
CI on Linux via APT linux
CI on OSX via Conda mac
CI on Windows via Conda windows
CI on Linux via Robotpkg Pipeline Status

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here. A cheat sheet pdf with the main functions and algorithms can be found here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples directory. Additional examples introducing Pinocchio are also available in the documentation.

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robot control. Tutorial and training documents are listed here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.
  • RViz: supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@inria.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Open-source projects relying on Pinocchio

  • Crocoddyl A software to realize model predictive control for complex robotics platform.
  • TSID A software which implements an Task Space Inverse Dynamics QP.
  • HPP A SDK which implements motion planner for humanoids and other robots.
  • Jiminy A simulator based on Pinocchio.
  • ocs2 A toolbox for Optimal Control for Switched Systems (OCS2)
  • TriFingerSimulation TriFinger Robot Simulation (a Robot to perform RL on manipulation).
  • Casadi_Kin_Dyn IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to pinocchio. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check [existing open][issues], or [recently closed][closed-issues], issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

The following guidance should be up-to-date, but the documentation as found here should prove as the final say.

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. Limited scope. Your PR should do one thing or one set of things. Avoid adding “random fixes” to PRs. Put those on separate PRs.
  2. Give your PR a descriptive title. Add a short summary, if required.
  3. Make sure the pipeline is green.
  4. Don’t be afraid to request reviews from maintainers.
  5. New code = new tests. If you are adding new functionality, always make sure to add some tests exercising the code and serving as live documentation of your original intention.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass. (make test)
  4. Commit to your fork using clear commit messages.
  5. Send a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional documentation on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As this project, by default, uses the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'][help-wanted] issues is a great place to start.

Licensing

Any contribution that you make to this repository will be under the BSD Clause 2 License, as dictated by that [license]:

BSD 2-Clause License

Copyright (c) 2014-2021, CNRS 
Copyright (c) 2018-2021, INRIA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the Pinocchio project.

issues closed-issues help-wanted license


Repository Summary

Checkout URI https://github.com/stack-of-tasks/pinocchio.git
VCS Type git
VCS Version devel
Last Updated 2022-09-28
Dev Status DEVELOPED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
pinocchio 2.6.10

README

Pinocchio Logo

License Coverage Report Conda Downloads Conda Version PyPI version

Pinocchio instantiates the state-of-the-art Rigid Body Algorithms for poly-articulated systems based on revisited Roy Featherstone's algorithms. Besides, Pinocchio provides the analytical derivatives of the main Rigid-Body Algorithms like the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

Pinocchio is first tailored for robotics applications, but it can be used in extra contexts (biomechanics, computer graphics, vision, etc.). It is built upon Eigen for linear algebra and FCL for collision detection. Pinocchio comes with a Python interface for fast code prototyping, directly accessible through Conda.

Pinocchio is now at the heart of various robotics software as Crocoddyl, an open-source and efficient Differential Dynamic Programming solver for robotics, the Stack-of-Tasks, an open-source and versatile hierarchical controller framework or the Humanoid Path Planner, an open-source software for Motion and Manipulation Planning.

If you want to learn more on Pinocchio internal behaviors and main features, we invite you to read the related paper.

If you want to directly dive into Pinocchio, only one single line is sufficient (assuming you have Conda):

conda install pinocchio -c conda-forge

or via pip (currently only available on Linux):

pip install pin

Pinocchio main features

Pinocchio is fast:

  • C++ template library,
  • cache friendly,
  • automatic code generation support via CppADCodeGen.

Pinocchio is versatile, implementing basic and more advanced rigid body dynamics algorithms:

  • forward kinematics and its analytical derivatives,
  • forward/inverse dynamics and their analytical derivatives,
  • centroidal dynamics and its analytical derivatives,
  • support of multiple precision arithmetic via Boost.Multiprecision or any similar framework,
  • computations of kinematic and dynamic regressors for system identification and more,
  • and much more with the support of modern and open source Automatic Differentiation frameworks like CppAD or CasADi.

Pinocchio is flexible:

  • header only,
  • C++ 98/03/11/14/17/20 compliant.

Pinocchio is extensible. Pinocchio is multi-thread friendly. Pinocchio is reliable and extensively tested (unit-tests, simulations and real world robotics applications). Pinocchio is supported and tested on Windows, Mac OS X, Unix and Linux (see build status here).

Pinocchio continuous integrations

Pinocchio is constantly tested for several platforms and distributions, as reported below:

<!-- -->
Continuous Integration
CI on ROS ROS
CI on Linux via APT linux
CI on OSX via Conda mac
CI on Windows via Conda windows
CI on Linux via Robotpkg Pipeline Status

Performances

Pinocchio exploits at best the sparsity induced by the kinematic tree of robotics systems. Thanks to modern programming language paradigms, Pinocchio is able to unroll most of the computations directly at compile time, allowing to achieve impressive performances for a large range of robots, as illustrated by the plot below, obtained on a standard laptop equipped with an Intel Core i7 CPU @ 2.4 GHz.

Pinocchio Logo

For other benchmarks, and mainly the capacity of Pinocchio to exploit at best your CPU capacities using advanced code generation techniques, we refer to the technical paper. In addition, the introspection done here may also help you to understand and compare the performances of the modern rigid body dynamics librairies.

Ongoing developments

If you want to follow the current developments, you can directly refer to the devel branch. The master branch only contains latest release. Any new Pull Request should then be submitted on the devel branch.

Installation

Pinocchio can be easily installed on various Linux (Ubuntu, Fedora, etc.) and Unix distributions (Mac OS X, BSD, etc.). Please refer to the installation procedure.

If you only need the Python bindings of Pinocchio, you may prefer to install it through Conda. Please follow the procedure described here.

Pinocchio is also deployed on ROS, you may follow its deployment status on Melodic or Kinetic.

Documentation

The online Pinocchio documentation of the last release is available here. A cheat sheet pdf with the main functions and algorithms can be found here.

Examples

We provide some basic examples on how to use Pinocchio in Python in the examples directory. Additional examples introducing Pinocchio are also available in the documentation.

Tutorials

Pinocchio comes with a large bunch of tutorials aiming at introducing the basic tools for robot control. Tutorial and training documents are listed here.

Visualization

Pinocchio provides support for many open-source and free visualizers:

  • Gepetto Viewer: a C++ viewer based on OpenSceneGraph with Python bindings and Blender export. See here for a C++ example on mixing Pinocchio and Gepetto Viewer.
  • Meshcat: supporting visualization in Python and which can be embeded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embeded inside any browser.
  • RViz: supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. See example here for more information.

Citing Pinocchio

To cite Pinocchio in your academic research, please use the following bibtex lines:

@misc{pinocchioweb,
   author = {Justin Carpentier and Florian Valenza and Nicolas Mansard and others},
   title = {Pinocchio: fast forward and inverse dynamics for poly-articulated systems},
   howpublished = {https://stack-of-tasks.github.io/pinocchio},
   year = {2015--2021}
}

and the following one for the reference to the paper introducing Pinocchio:

@inproceedings{carpentier2019pinocchio,
   title={The Pinocchio C++ library -- A fast and flexible implementation of rigid body dynamics algorithms and their analytical derivatives},
   author={Carpentier, Justin and Saurel, Guilhem and Buondonno, Gabriele and Mirabel, Joseph and Lamiraux, Florent and Stasse, Olivier and Mansard, Nicolas},
   booktitle={IEEE International Symposium on System Integrations (SII)},
   year={2019}
}

The algorithms for the analytical derivatives of rigid-body dynamics algorithms are detailed here:

@inproceedings{carpentier2018analytical,
  title = {Analytical Derivatives of Rigid Body Dynamics Algorithms},
  author = {Carpentier, Justin and Mansard, Nicolas},
  booktitle = {Robotics: Science and Systems},
  year = {2018}
}

Questions and Issues

You have a question or an issue? You may either directly open a new issue or use the mailing list pinocchio@inria.fr.

Credits

The following people have been involved in the development of Pinocchio and are warmly thanked for their contributions:

If you have taken part to the development of Pinocchio, feel free to add your name and contribution in this list.

Open-source projects relying on Pinocchio

  • Crocoddyl A software to realize model predictive control for complex robotics platform.
  • TSID A software which implements an Task Space Inverse Dynamics QP.
  • HPP A SDK which implements motion planner for humanoids and other robots.
  • Jiminy A simulator based on Pinocchio.
  • ocs2 A toolbox for Optimal Control for Switched Systems (OCS2)
  • TriFingerSimulation TriFinger Robot Simulation (a Robot to perform RL on manipulation).
  • Casadi_Kin_Dyn IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.

Acknowledgments

The development of Pinocchio is actively supported by the Gepetto team @LAAS-CNRS and the Willow team @INRIA.

CONTRIBUTING

Contributing Guidelines

Thank you for your interest in contributing to pinocchio. Whether it's a bug report, new feature, correction, or additional documentation, we greatly value feedback and contributions from our community.

Please read through this document before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your bug report or contribution.

Reporting Bugs/Feature Requests

We welcome you to use the GitHub issue tracker to report bugs or suggest features.

When filing an issue, please check [existing open][issues], or [recently closed][closed-issues], issues to make sure somebody else hasn't already reported the issue. Please try to include as much information as you can. Details like these are incredibly useful:

  • A reproducible test case or series of steps
  • The version of our code being used
  • Any modifications you've made relevant to the bug
  • Anything unusual about your environment or deployment

Contributing via Pull Requests

The following guidance should be up-to-date, but the documentation as found here should prove as the final say.

Contributions via pull requests are much appreciated. Before sending us a pull request, please ensure that:

  1. Limited scope. Your PR should do one thing or one set of things. Avoid adding “random fixes” to PRs. Put those on separate PRs.
  2. Give your PR a descriptive title. Add a short summary, if required.
  3. Make sure the pipeline is green.
  4. Don’t be afraid to request reviews from maintainers.
  5. New code = new tests. If you are adding new functionality, always make sure to add some tests exercising the code and serving as live documentation of your original intention.

To send us a pull request, please:

  1. Fork the repository.
  2. Modify the source; please focus on the specific change you are contributing. If you also reformat all the code, it will be hard for us to focus on your change.
  3. Ensure local tests pass. (make test)
  4. Commit to your fork using clear commit messages.
  5. Send a pull request, answering any default questions in the pull request interface.
  6. Pay attention to any automated CI failures reported in the pull request, and stay involved in the conversation.

GitHub provides additional documentation on forking a repository and creating a pull request.

Finding contributions to work on

Looking at the existing issues is a great way to find something to contribute on. As this project, by default, uses the default GitHub issue labels (enhancement/bug/duplicate/help wanted/invalid/question/wontfix), looking at any ['help wanted'][help-wanted] issues is a great place to start.

Licensing

Any contribution that you make to this repository will be under the BSD Clause 2 License, as dictated by that [license]:

BSD 2-Clause License

Copyright (c) 2014-2021, CNRS 
Copyright (c) 2018-2021, INRIA
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
   list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice,
   this list of conditions and the following disclaimer in the documentation
   and/or other materials provided with the distribution.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The views and conclusions contained in the software and documentation are those
of the authors and should not be interpreted as representing official policies,
either expressed or implied, of the Pinocchio project.

issues closed-issues help-wanted license