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

Project description

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:

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 the 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.

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 depend on Pinocchio in your package.xml config (<depend>pinocchio</depend>) and include it via CMake (find_package(pinocchio REQUIRED)) -- we include support and hooks to discover the package for both ROS1 and ROS2. An example can be found here. Please note that we advise to always include the pinocchio/fwd.hpp header as the first include to avoid compilation errors from differing Boost-variant sizes.

ROS1      ROS2
Melodic      Foxy
Noetic      Galactic
     Humble
     Rolling

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 embedded inside any browser.
  • Panda3d: supporting visualization in Python and which can be embedded 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.

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SHA256 c1f4f3eed52e6ccf72ebc10125db9a11230bbdba9a8660aedba5c81913bb4594
MD5 db8a2be30a3617b7ad3a29e26597aea7
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SHA256 8c91cf6aeb9415493a0aaf47c687bc93439f7940034b6f8e2d1cb9493335acfa
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SHA256 bfac96b83de6bc5a6a37927d40e8b67701028138bb393ff8f88ecd3fe38ac5e4
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SHA256 68067ece49596c9c1ab5939e0d6d2474f5d7dddee1e796c2ae14d4e41b03ba52
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SHA256 12d57e71a9d278e891cc9c115cf71104f56c1d6666bb235c980de2870d526225
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SHA256 1f127533605622a9d97fa5dcd1bb6f367198440789cdd966d0f00096e54e628e
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SHA256 feea84fcba1ff8ecaa9602dd341f6b43d2101478906526853cc574f9ec2a5322
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SHA256 61abb1d4833f5900863c04661713dcc1397bfd06d43d7a28f8892aa86c66f663
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SHA256 4557725e70918c135df63f8a9dc764e29ddb7c018c289f761441b770d456d16d
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SHA256 8199aac50baa64217944e8c81d23679f7f944311586ad7a141df76d32eb8b31b
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SHA256 6d6fa8ad32473f04fd60891fe394af2d187c1e0415ee0f8a8d4d408546d9084b
MD5 4f31c4eb62bdcea0dad73a41a7126446
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SHA256 8c317060f3abe10af8c378226feeb5d341ddeb1207acd06224f7e2aa505faf88
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SHA256 34b6119582d00a45158ba2d4499174d084649f9f4ade5945c1fc654e21a72329
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SHA256 68bfa660edcf20c1eb58e7ccb7a850c5c55ab3613213857b5aa84735dfb07d9c
MD5 215361eda56884066f7f4bb0c8445fed
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SHA256 3dcedd41c32a0912e85386f145e1d1eb7b1cc2cdb755613e8e3c9f39d3bf4dcd
MD5 2b8730c201119952ad39a8a7c26ceaa7
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SHA256 5fd26ce39e91b56d11f2b3fb09e4abfe03d511cdc4df7af5e7fc9288aa6e3812
MD5 1cf17a41d607214a8c1ea476ceaac452
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SHA256 b051353d97640966cb090612921d4f1589b699cd99aead99937c34eda188ced2
MD5 37b81c9d4131da0c063d559fd216ec3f
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MD5 518a038673227d7ae1f7f5d46c7bfb75
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SHA256 13b366b82260acf60c2de1a08638bcc2f4a1036fba39360d339c3bface461f9d
MD5 f7fc06a147f18178c6c5d785b8f19cc1
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SHA256 883936f7d17f46812a8f1a59355193c3f67b49a432fb8770e4db5cf94c87be2c
MD5 9899ce514b36b3134300b9717a11c50a
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SHA256 f677effd16cad143dedb223330414d726da26a8ef6cc5fb923c60d80c306adc4
MD5 b5bc45eb9737256fbbfb7534102972d9
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SHA256 727578d93b5ed8d9860076f5177772e23b0dde04a5dc4f8125c863f042881a48
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SHA256 aed7ce9c811b337020c96c1b4ac8851f846f03221894dedf38c44392a197e234
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SHA256 928b118295502e330b608b0de4a26f8dd6e1c64cf9c1ec5a19bc80a7b35bd7eb
MD5 b353e8000e8ba749933b1e178da98467
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SHA256 421106a04c2675d99d5c8f73d04d36596ed0326cc0de756c1ef49ce4620f981b
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MD5 07b223920239354a11eb410fa667df49
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SHA256 9722d96902b4bf24555b52015337662e1c543b8d6ac6bf9adbb73710cdd07b33
MD5 cf1ad0e11d11a16f8bf88aebb0c53b09
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MD5 d69c3c57f8573b4b6ed77cf1a0f5ff9a
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MD5 3427cd5378356c48309eaab262846219
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SHA256 061f81ea35f622be58ca727789e508b662b90f32caf4f66d4a7c814119067c59
MD5 122cf6563b524aa5edf03bf38ced8ae0
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SHA256 61eeecb45191bcfb2867b12958d9c9fa5004fcadfd3c2b33d25c248bf426417c
MD5 4683653ad6ea407eea0f5ef1b3e46c12
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SHA256 bd611b751e5e3270dca6d4ea64c2666cdef12da4475a7d6cdab4191a9d73608f
MD5 36f6538331af4eeed959d06c8d6a8038
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SHA256 24c9372b5ce1e5fbfec94c5934fc7e8d770fa86d0afa95b8a9912302ed133a42
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