Commit f1cdc1dc authored by Guilhem Saurel's avatar Guilhem Saurel
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gepgitlab → gitlab

parent 0d535de0
# TSID - Task Space Inverse Dynamics
[![Building Status](https://travis-ci.org/stack-of-tasks/tsid.svg?branch=master)](https://travis-ci.org/stack-of-tasks/tsid)
[![Pipeline status](https://gepgitlab.laas.fr/stack-of-tasks/tsid/badges/master/pipeline.svg)](https://gepgitlab.laas.fr/stack-of-tasks/tsid/commits/master)
[![Coverage report](https://gepgitlab.laas.fr/stack-of-tasks/tsid/badges/master/coverage.svg?job=doc-coverage)](http://projects.laas.fr/gepetto/doc/stack-of-tasks/tsid/master/coverage/)
[![Pipeline status](https://gitlab.laas.fr/stack-of-tasks/tsid/badges/master/pipeline.svg)](https://gitlab.laas.fr/stack-of-tasks/tsid/commits/master)
[![Coverage report](https://gitlab.laas.fr/stack-of-tasks/tsid/badges/master/coverage.svg?job=doc-coverage)](http://projects.laas.fr/gepetto/doc/stack-of-tasks/tsid/master/coverage/)
TSID is C++ library for optimization-based inverse-dynamics control based on the rigid multi-body dynamics library [Pinocchio](https://github.com/stack-of-tasks/pinocchio).
Take a look at the project [wiki](https://github.com/stack-of-tasks/tsid/wiki) for more details.
......@@ -33,15 +33,15 @@ To use this library in python, we offer python bindings based on Boost.Python an
To install EigenPy you can compile the source code:
git clone https://github.com/stack-of-tasks/eigenpy
or, on Ubuntu, you can use apt-get:
sudo apt-get install robotpkg-py27-eigenpy
For testing the python bindings, you can run the unit test scripts in the `script` folder, for instance:
ipython script/test_formulation.py
To run the demo using gepetto-viewer:
ipython demo/demo_romeo.py
......
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