Metadata-Version: 2.1
Name: ikpy
Version: 3.0
Summary: An inverse kinematics library aiming performance and modularity
Home-page: https://github.com/Phylliade/ikpy
Author: Pierre Manceron
License: GNU GENERAL PUBLIC LICENSE Version 3
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: sympy
Provides-Extra: plot
Requires-Dist: matplotlib ; extra == 'plot'
Requires-Dist: graphviz ; extra == 'plot'

# IKPy

![Travis-CI](https://travis-ci.org/Phylliade/ikpy.svg?branch=master)
[![PyPI](https://img.shields.io/pypi/v/ikpy.svg)](https://pypi.python.org/pypi/ikpy/)


![demo](two_arms.png)

![IKPy on the bacter robot](baxter.png)

## Demo

Live demos of what IKPy can do \(click on the image below to see the video\):


[![](http://img.youtube.com/vi/H0ysr5qSbis/0.jpg)](https://www.youtube.com/watch?v=H0ysr5qSbis)
[![](http://img.youtube.com/vi/Jq0-DkEwwj4/0.jpg)](https://www.youtube.com/watch?v=Jq0-DkEwwj4)

Also, a presentation of IKPy: [Presentation](https://github.com/Phylliade/ikpy/blob/master/tutorials/IKPy%20speech.pdf).

## Features

With IKPy, you can:

* Compute the **Inverse Kinematics** of every existing robot.
* Compute the Inverse Kinematics in **position, orientation**, or both
* Define your kinematic chain using **arbitrary representations**: DH (Denavit–Hartenberg), URDF, custom...
* Automaticly import a kinematic chain from a **URDF file**.
* Use pre-configured robots, such as **baxter** or the **poppy-torso**
* 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.
* **Plot** your kinematic chain: no need to use a real robot (or a simulator) to test your algorithms!
* Define your own Inverse Kinematics methods.

Moreover, IKPy is a **pure-Python library**: the install is a matter of seconds, and no compiling is required.

## Installation

You have three options:

1. From PyPI \(recommended\) - simply run:

   ```bash
   pip install ikpy
   ```

   If you intend to plot your robot, you can install the plotting dependencies \(mainly `matplotlib`\):

   ```bash
   pip install 'ikpy[plot]'
   ```

2. If you work with Anaconda, there's also a Conda package of IKPy:
  ```bash
  conda install -c https://conda.anaconda.org/phylliade ikpy
  ```

3. From source - first download and extract the archive, then run:

   ```bash
   pip install ./
   ```

   NB: You must have the proper rights to execute this command

## Quickstart

Follow this IPython [notebook](https://github.com/Phylliade/ikpy/blob/master/tutorials/Quickstart.ipynb).

## Guides and Tutorials

Go to the [wiki](https://github.com/Phylliade/ikpy/wiki). It should introduce you to the basic concepts of IKPy.

## API Documentation

An extensive documentation of the API can be found [here](http://ikpy.readthedocs.org).

## Dependencies and compatibility

The library can work with both versions of Python \(2.7 and 3.x\). It requires `numpy` and `scipy`.

`sympy` is highly recommended, for fast hybrid computations, that's why it is installed by default.

`matplotlib` is optional: it is used to plot your models \(in 3D\).

## Contributing

IKPy 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).

Contributions are welcome: if you have an awesome patented \(but also open-source!\) IK method, don't hesitate to propose adding it to the library!

## Links

* 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.


