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        "description": "# IKPy #\n\n[![Join the chat at https://gitter.im/Phylliade/ikpy](https://badges.gitter.im/Phylliade/ikpy.svg)](https://gitter.im/Phylliade/ikpy?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\n![Travis-CI](https://travis-ci.org/Phylliade/ikpy.svg?branch=master)\n[![PyPI](https://img.shields.io/pypi/v/ikpy.svg)](https://pypi.python.org/pypi/ikpy/)\n[![Documentation Status](https://readthedocs.org/projects/ikpy/badge/?version=latest)](http://ikpy.readthedocs.org/en/latest/?badge=latest)\n[![PyPI](https://img.shields.io/pypi/dm/ikpy.svg)](https://pypi.python.org/pypi/ikpy/)\n[![Binder](http://mybinder.org/badge.svg)](http://mybinder.org/repo/Phylliade/ikpy)\n\n![demo](two_arms.png)\n\n# Demo\n\nLive demos of what IKPy can do (click on the image below to see the video):\n\n[![](http://img.youtube.com/vi/H0ysr5qSbis/0.jpg)](https://www.youtube.com/watch?v=H0ysr5qSbis)\n[![](http://img.youtube.com/vi/Jq0-DkEwwj4/0.jpg)](https://www.youtube.com/watch?v=Jq0-DkEwwj4)\n\nAlso, a presentation of IKPy: [Presentation](https://github.com/Phylliade/ikpy/blob/master/tutorials/IKPy%20speech.pdf).\n\n# Features\nWith IKPy, you can:\n\n* Compute the **Inverse Kinematics** of every existing robot.\n* Define your kinematic chain using **arbitrary representations**: DH (Denavit\u2013Hartenberg), URDF standard, custom...\n* Automaticly import a kinematic chain from a **URDF file**.\n* IKPy is **precise** (up to 7 digits): the only limitation being your underlying model's precision, and **fast**: from 7 ms to 50 ms (depending on your precision) for a complete IK computation.\n* **Plot** your kinematic chain: no need to use a real robot (or a simulator) to test your algorithms!\n* Define your own Inverse Kinematics methods.\n\nMoreover, IKPy is a **pure-Python library**: the install is a matter of seconds, and no compiling is required.\n\n# Installation\nYou have three options:\n\n\n1. From PyPI (recommended) - simply run:\n\n   ```bash\n   pip install ikpy\n   ```\n  If you intend to plot your robot, you can install the plotting dependencies (mainly `matplotlib`):\n  ```bash\n  pip install 'ikpy[plot]'\n  ```\n\n2. If you work with Anaconda, there's also a Conda package of IKPy:\n  ```\n  conda install -c https://conda.anaconda.org/phylliade ikpy\n  ```\n\n3. From source - first download and extract the archive, then run:\n\n   ```bash\n   pip install ./\n   ```\n   NB: You must have the proper rights to execute this command\n\n# Quickstart\nFollow this IPython [notebook](https://github.com/Phylliade/ikpy/blob/master/tutorials/Quickstart.ipynb).\n\n# Guides and Tutorials\nGo to the [wiki](https://github.com/Phylliade/ikpy/wiki). It should introduce you to the basic concepts of IKPy.\n\n# API Documentation\nAn extensive documentation of the API can be found [here](http://ikpy.readthedocs.org).\n\n# Dependencies and compatibility\nThe library can work with both versions of Python (2.7 and 3.x).\nIt requires `numpy` and `scipy`.\n\n`sympy` is highly recommended, for fast hybrid computations, that's why it is installed by default.\n\n`matplotlib` is optional: it is used to plot your models (in 3D).\n\n\n# Contributing\nIKPy is designed to be easily customisable: you can add your own IK methods or robot representations (such as DH-Parameters) using a dedicated [developer API](https://github.com/Phylliade/ikpy/wiki/Contributing).\n\nContributions are welcome: if you have an awesome patented (but also open-source!) IK method, don't hesitate to propose adding it to the library!\n\n# Links\n* If performance is your main concern, `aversive++` has an inverse kinematics [module](https://github.com/AversivePlusPlus/ik) written in C++, which works the same way IKPy does.\n\n\n",
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