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https://github.com/stack-of-tasks/pinocchio

A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
https://github.com/stack-of-tasks/pinocchio

analytical-derivatives automatic-differentiation c-plus-plus casadi code-generation conda cppad dynamics fcl kinematics motion-planning pinocchio python rigid-body-dynamics robotics ros urdf

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A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

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README

        


Pinocchio Logo


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**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, such as the Recursive Newton-Euler Algorithm or the Articulated-Body Algorithm.

**Pinocchio** was first tailored for robotics applications, but it can be used in other 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](https://github.com/conda-forge/pinocchio-feedstock#installing-pinocchio) through [Conda](https://docs.conda.io/en/latest/).

**Pinocchio** is now at the heart of various robotics software as [Crocoddyl](https://github.com/loco-3d/crocoddyl/tree/devel), an open-source and efficient Differential Dynamic Programming solver for robotics, the [Stack-of-Tasks](http://stack-of-tasks.github.io), an open-source and versatile hierarchical controller framework or the [Humanoid Path Planner](https://humanoid-path-planner.github.io/hpp-doc), open-source software for Motion and Manipulation Planning.

If you want to learn more about **Pinocchio** internal behaviors and main features, we invite you to read the related [paper](https://hal-laas.archives-ouvertes.fr/hal-01866228) and the online [documentation](https://gepettoweb.laas.fr/doc/stack-of-tasks/pinocchio/master/doxygen-html/).

If you want to dive into **Pinocchio** directly, 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

## Table of contents

- [Table of contents](#table-of-contents)
- [Introducing Pinocchio 3](#introducing-pinocchio-3)
- [Pinocchio main features](#pinocchio-main-features)
- [Documentation](#documentation)
- [Examples](#examples)
- [Tutorials](#tutorials)
- [Pinocchio continuous integrations](#pinocchio-continuous-integrations)
- [Performances](#performances)
- [Ongoing developments](#ongoing-developments)
- [Installation](#installation)
- [ROS](#ros)
- [Visualization](#visualization)
- [Citing Pinocchio](#citing-pinocchio)
- [Questions and Issues](#questions-and-issues)
- [Credits](#credits)
- [Open-source projects relying on Pinocchio](#open-source-projects-relying-on-pinocchio)
- [Acknowledgments](#acknowledgments)

## Introducing Pinocchio 3

**Pinocchio3** is the latest major release of Pinocchio. It comes with multiple new features, such as:
- [Sparse constrained dynamics](https://laas.hal.science/hal-01790971v2/file/18-rss-analytical-derivatives-carpentier.pdf) and its analytical derivatives
- Full support of closed-loop mechanisms
- [State-of-the-art frictional contact solvers](https://hal.science/hal-04588906v1/file/simplecontacts2024.pdf)
- [Low-complexity constrained articulated body algorithms]()
- Full support of [multiple-precision floating-point (MPFR)](https://www.mpfr.org/) in Python and C++
- Full [CasADi](https://web.casadi.org/) support in Python and C++
- Increased support of [CppAD](https://github.com/coin-or/CppAD) and [CppADCodeGen]()
- New SDF and MJCF parsers
- and much more.

## Pinocchio main features

**Pinocchio** is fast:

- C++ template library,
- cache friendly,
- automatic code generation support is available via [CppADCodeGen](https://github.com/joaoleal/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 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](https://github.com/coin-or/CppAD) or [CasADi](https://web.casadi.org/).

**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](http://robotpkg.openrobots.org/rbulk/robotpkg/math/pinocchio/index.html)).

## Documentation

The online **Pinocchio** documentation of the last release is available [here](https://gepettoweb.laas.fr/doc/stack-of-tasks/pinocchio/master/doxygen-html/). A cheat sheet pdf with the main functions and algorithms can be found [here](https://github.com/stack-of-tasks/pinocchio/blob/master/doc/pinocchio_cheat_sheet.pdf).

## Examples

In the [examples](https://github.com/stack-of-tasks/pinocchio/tree/master/examples) directory, we provide some basic examples of using Pinocchio in Python.
Additional examples introducing **Pinocchio** are also available in the [documentation](https://gepettoweb.laas.fr/doc/stack-of-tasks/pinocchio/master/doxygen-html/md_doc_d-practical-exercises_intro.html).

## 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](https://gepettoweb.laas.fr/doc/stack-of-tasks/pinocchio/master/doxygen-html/index.html#OverviewConclu).
You can also consider the interactive Jupyter notebook [set of tutorials](https://github.com/ymontmarin/_tps_robotique) developed by [Nicolas Mansard](https://gepettoweb.laas.fr/index.php/Members/NicolasMansard) and [Yann de Mont-Marin](https://github.com/ymontmarin).

## Pinocchio continuous integrations

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




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** can 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](https://hal-laas.archives-ouvertes.fr/hal-01866228).
In addition, the [introspection](https://github.com/rbd-benchmarks/rbd-benchmarks) may also help you to understand and compare the performances of the modern rigid body dynamics libraries.

## Ongoing developments

If you want to follow the current developments, you can directly refer to the [devel branch](https://github.com/stack-of-tasks/pinocchio/tree/devel).
The [master branch](https://github.com/stack-of-tasks/pinocchio/tree/master/) only contains the latest release. Any new Pull Request should then be submitted on the [devel branch](https://github.com/stack-of-tasks/pinocchio/tree/devel/).

## 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](http://stack-of-tasks.github.io/pinocchio/download.html).

### Conda

You simply need this simple line:

```bash
conda install pinocchio -c conda-forge
```

### ROS

**Pinocchio** is also deployed on ROS.
You may follow its deployment status below.

If you're interested in using Pinocchio on systems and/or with packages that integrate with the ROS ecosystem, we recommend the installation of Pinocchio via the binaries distributed via the ROS PPA.
Here, you can install Pinocchio using:

```
sudo apt install ros-$ROS_DISTRO-pinocchio
```

This installs Pinocchio with HPP-FCL support and with Python bindings.
You can then use Pinocchio in your ROS packages by:

* Depending on Pinocchio in your `package.xml` config (`pinocchio`)
* Including Pinocchio via CMake (`find_package(pinocchio REQUIRED)`) and linking against Pinocchio (`target_link_libraries(my_library pinocchio::pinocchio)`)

We include support and hooks to discover the package for both ROS 1 and ROS 2.
Examples can be found at the following repositories:
* [ROS 1 example](https://github.com/wxmerkt/pinocchio_ros_example)
* [ROS 2 example](https://github.com/sea-bass/pinocchio_ros_cpp_example)

Please note that we always advise including the `pinocchio/fwd.hpp` header as the first include to avoid compilation errors from differing Boost-variant sizes.

| ROS 1 | |      | ROS 2 | |
| ----------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------ | ------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| **Melodic** | [![](https://build.ros.org/job/Mbin_uB64__pinocchio__ubuntu_bionic_amd64__binary/badge/icon)](https://build.ros.org/job/Mbin_uB64__pinocchio__ubuntu_bionic_amd64__binary) |      | **Foxy** | [![](https://build.ros2.org/job/Fbin_uF64__pinocchio__ubuntu_focal_amd64__binary/badge/icon)](https://build.ros2.org/job/Fbin_uF64__pinocchio__ubuntu_focal_amd64__binary) |
| **Noetic** | [![](https://build.ros.org/job/Nbin_uF64__pinocchio__ubuntu_focal_amd64__binary/badge/icon)](https://build.ros.org/job/Nbin_uF64__pinocchio__ubuntu_focal_amd64__binary) |      | **Galactic** | [![](https://build.ros2.org/job/Gbin_uF64__pinocchio__ubuntu_focal_amd64__binary/badge/icon)](https://build.ros2.org/job/Gbin_uF64__pinocchio__ubuntu_focal_amd64__binary) |
| | |      | **Humble** | [![](https://build.ros2.org/job/Hbin_uJ64__pinocchio__ubuntu_jammy_amd64__binary/badge/icon)](https://build.ros2.org/job/Hbin_uJ64__pinocchio__ubuntu_jammy_amd64__binary) |
| | |      | **Rolling** | [![](https://build.ros2.org/job/Rbin_uJ64__pinocchio__ubuntu_jammy_amd64__binary/badge/icon)](https://build.ros2.org/job/Rbin_uJ64__pinocchio__ubuntu_jammy_amd64__binary) |

## Visualization

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

- [Gepetto Viewer](https://github.com/Gepetto/gepetto-viewer): a C++ viewer based on [OpenSceneGraph](https://github.com/openscenegraph/OpenSceneGraph) with Python bindings and Blender export. See [here](https://github.com/stack-of-tasks/pinocchio-gepetto-viewer) for a C++ example on mixing **Pinocchio** and **Gepetto Viewer**.
- [Meshcat](https://github.com/rdeits/meshcat): supporting visualization in Python and which can be embedded inside any browser.
- [Panda3d](https://github.com/ikalevatykh/panda3d_viewer): supporting visualization in Python and which can be embedded inside any browser.
- [RViz](https://github.com/ros-visualization/rviz): supporting visualization in Python and which can interact with other ROS packages.

Many external viewers can also be integrated. For more information, see the example [here](https://github.com/stack-of-tasks/pinocchio/blob/master/bindings/python/pinocchio/visualize/base_visualizer.py).

## Citing Pinocchio

To cite **Pinocchio** in your academic research, please consider citing the [software paper](https://laas.hal.science/hal-01866228v2/file/19-sii-pinocchio.pdf) and use the following BibTeX entry:
```bibtex
@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}
}
```
And the following one for the link to the GitHub codebase:
```bibtex
@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}
}
```

## Citing specific algorithmic contributions

**Pinocchio** goes beyond implementing the standard rigid-body dynamics algorithms and results from active research on simulation, learning and control.
**Pinocchio** provides state-of-the-art algorithms for handling constraints, differentiating forward and inverse dynamics, etc.
If you use these algorithms, please consider citing them in your research articles.

- Le Lidec, Q., Montaut, L. & Carpentier, J. (2024, July). [From Compliant to Rigid Contact Simulation: a Unified and Efficient Approach](https://hal.science/hal-04588906). In RSS 2024-Robotics: Science and Systems.
- Montaut, L., Le Lidec, Q., Petrik, V., Sivic, J., & Carpentier, J. (2024). [GJK++: Leveraging Acceleration Methods for Faster Collision Detection](https://hal.science/hal-04070039/). IEEE Transactions on Robotics.
- Sathya, A., & Carpentier, J. (2024). [Constrained Articulated Body Dynamics Algorithms](https://hal.science/hal-04443056/). Under review.
- Montaut, L., Le Lidec, Q., Bambade, A., Petrik, V., Sivic, J., & Carpentier, J. (2023, May). [Differentiable collision detection: a randomized smoothing approach](https://hal.science/hal-03780482/). In 2023 IEEE International Conference on Robotics and Automation (ICRA).
- Le Lidec, Q., Jallet, W., Montaut, L., Laptev, I., Schmid, C., & Carpentier, J. (2023). [Contact models in robotics: a comparative analysis](https://hal.science/hal-04067291/). Under review.
- Montaut, L., Le Lidec, Q., Petrik, V., Sivic, J., & Carpentier, J. (2022, June). [Collision Detection Accelerated: An Optimization Perspective](https://hal.science/hal-03662157/). In Robotics: Science and Systems (RSS 2O22).
- Carpentier, J., Budhiraja, R., & Mansard, N. (2021, July). [Proximal and sparse resolution of constrained dynamic equations](https://hal.science/hal-03271811/). In Robotics: Science and Systems (RSS 2021).
- Carpentier, J., & Mansard, N. (2018, June). [Analytical derivatives of rigid body dynamics algorithms](https://hal.science/hal-01790971/). In Robotics: Science and systems (RSS 2018).

## Questions and Issues

Do you have a question or an issue? You may either directly open a [new question](https://github.com/stack-of-tasks/pinocchio/discussions/new?category=q-a) or a [new issue](https://github.com/stack-of-tasks/pinocchio/issues) or, directly contact us via the mailing list .

## Credits

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

- [Justin Carpentier](https://jcarpent.github.io) (Inria): main developer and manager of the project
- [Nicolas Mansard](http://projects.laas.fr/gepetto/index.php/Members/NicolasMansard) (LAAS-CNRS): initial project instructor
- [Guilhem Saurel](http://projects.laas.fr/gepetto/index.php/Members/GuilhemSaurel) (LAAS-CNRS): continuous integration and deployment
- [Joseph Mirabel](http://jmirabel.github.io/) (Eureka Robotics): Lie groups and hpp-fcl implementation
- [Antonio El Khoury](https://www.linkedin.com/in/antonioelkhoury) (Wandercraft): bug fixes
- [Gabriele Buondono](http://projects.laas.fr/gepetto/index.php/Members/GabrieleBuondonno) (LAAS-CNRS): features extension, bug fixes, and Python bindings
- [Florian Valenza](https://fr.linkedin.com/in/florian-valenza-1b274082) (Astek): core developments and hpp-fcl support
- [Wolfgang Merkt](http://www.wolfgangmerkt.com/) (University of Oxford): ROS integration and support
- [Rohan Budhiraja](https://scholar.google.com/citations?user=NW9Io9AAAAAJ) (LAAS-CNRS): features extension
- [Loïc Estève](https://github.com/lesteve) (Inria): Conda integration and support
- [Igor Kalevatykh](https://github.com/ikalevatykh) (Inria): Panda3d viewer support
- [Matthieu Vigne](https://github.com/matthieuvigne) (Wandercraft): MeshCat viewer support
- [Robin Strudel](https://www.di.ens.fr/robin.strudel/) (Inria): features extension
- [François Keith](https://scholar.google.fr/citations?user=cxSxXiQAAAAJ&hl=en) (CEA): Windows support
- [Sarah El Kazdadi](https://github.com/sarah-ek) (Inria): multi-precision arithmetic support
- [Nicolas Torres Alberto](https://scholar.google.com/citations?user=gYNLhEIAAAAJ&hl=en) (Inria): features extension
- [Etienne Arlaud](https://github.com/EtienneAr) (Inria): RViz viewer support
- [Wilson Jallet](https://github.com/ManifoldFR) (LAAS-CNRS/Inria): extension of Python bindings
- [Fabian Schramm](https://github.com/fabinsch) (Inria): core developper
- [Shubham Singh](https://github.com/shubhamsingh91) (UT Austin): second-order inverse dynamics derivatives
- [Stéphane Caron](https://scaron.info) (Inria): core developper
- [Joris Vaillant](https://github.com/jorisv) (Inria): core developer and manager of the project
- [Sebastian Castro](https://roboticseabass.com) (The AI Institute): MeshCat viewer feature extension
- [Lev Kozlov](https://github.com/lvjonok): Kinetic and potential energy regressors
- [Megane Millan](https://github.com/MegMll) (Inria): Features extension and core developer
- [Simeon Nedelchev](https://github.com/simeon-ned): Pseudo inertia and Log-Cholesky parametrization
- [Ajay Sathya](https://www.ajaysathya.com/) (Inria): core developer

If you have participated in the development of **Pinocchio**, please add your name and contribution to this list.

## Open-source projects relying on Pinocchio

- [Crocoddyl](https://github.com/loco-3d/crocoddyl): A software to realize model predictive control for complex robotics platforms.
- [TSID](https://github.com/stack-of-tasks/tsid/): A software that implements a Task Space Inverse Dynamics QP.
- [HPP](https://humanoid-path-planner.github.io/hpp-doc/): A SDK that implements motion planners for humanoids and other robots.
- [Jiminy](https://github.com/duburcqa/jiminy): A simulator based on Pinocchio.
- [ocs2](https://github.com/leggedrobotics/ocs2): A toolbox for Optimal Control for Switched Systems (OCS2)
- [TriFingerSimulation](https://github.com/open-dynamic-robot-initiative/trifinger_simulation): TriFinger Robot Simulation (a Robot to perform RL on manipulation).
- [Casadi_Kin_Dyn](https://github.com/ADVRHumanoids/casadi_kin_dyn): IIT Package for generation of symbolic (SX) expressions of robot kinematics and dynamics.
- [PyRoboPlan](https://github.com/sea-bass/pyroboplan): An educational Python library for manipulator motion planning using the Pinocchio Python bindings.
- [ProxSuite-NLP](https://github.com/Simple-Robotics/proxsuite-nlp): A primal-dual augmented Lagrangian solver for nonlinear programming on manifolds.
- [Aligator](https://github.com/Simple-Robotics/aligator): A versatile and efficient framework for constrained trajectory optimization.
- [Simple](https://github.com/Simple-Robotics/Simple): The Simple Simulator: Simulation Made Simple.
- [LoIK](https://github.com/Simple-Robotics/LoIK): Low-Complexity Inverse Kinematics.

## Acknowledgments

The development of **Pinocchio** is actively supported by the [Gepetto team](http://projects.laas.fr/gepetto/) [@LAAS-CNRS](http://www.laas.fr) and the [Willow team](https://www.di.ens.fr/willow/) [@INRIA](http://www.inria.fr).