Metadata-Version: 1.1
Name: pyarm
Version: 1.1.dev0
Summary: A robotic arm model and simulator.
Home-page: http://www.jdhp.org/
Author: Jeremie DECOCK
Author-email: jd.jdhp@gmail.com
License: UNKNOWN
Download-URL: http://www.jdhp.org/
Description: ======
        PyArm_
        ======
        
        Copyright (c) 2010,2015 Jeremie DECOCK (http://www.jdhp.org)
        
        
        * Web site: http://www.jdhp.org/projects_en.html#pyarm
        * Online documentation: http://pyarm.readthedocs.org
        * Source code: https://github.com/jeremiedecock/pyarm
        * Issue tracker: https://github.com/jeremiedecock/pyarm/issues
        * PyArm on PyPI: https://pypi.python.org/pypi/pyarm
        
        
        Description
        ===========
        
        Pyarm_ is a physics simulator which provides an anthropomorphic arm model
        for experiments on human like motor control.
        
        The arm model is described in the following technical report (written in
        French): http://download.tuxfamily.org/jdhp/pdf/pyarm.pdf .
        
        Pyarm has been used at the `Institute for Intelligent Systems and Robotics`_
        for experiments on adaptive systems. These experiments are described in the
        following academic paper *Learning cost-efficient control policies with XCSF:
        generalization capabilities and further improvement* by Didier Marin, Jérémie
        Decock, Lionel Rigoux and Olivier Sigaud. This scientific contribution has been
        published in the *Proceedings of the 13th annual conference on Genetic and
        evolutionary computation (GECCO'11)*, the main international conference on
        genetic and evolutionary computation.
        
        .. The following section briefly describe these experiments.
        .. 
        .. The full description of these expriments can be downloaded ...
        This paper can be downloaded on
        `www.jdhp.org <http://www.jdhp.org/articles_en.html#XCSF>`__.
        
        .. ...
        .. ---
        .. 
        .. Mettre ici une partie des slides... The goal ... (schema du bras +
        .. schéma avec légende du bras dans pyarm) - forearm - shoulder - elbow -
        .. end point effector - target - mussles - ...
        .. 
        .. First step: the learning phase. Optimal trajectories for several random
        .. targets are computed by our solver (QOPS). These trajectories are slow
        .. to compute (several minutes per trajectory). Thus this solver cannot be
        .. used for real time control of robots... Therefore we will try to use
        .. machine learning technics to create a real time controller learned from
        .. QOPS solver.
        .. 
        .. A set of optimal trajectories for several random targets are computed by
        .. our solver (QOPS). These trajectories are played and learned by our
        .. adaptive controler/system/machine learning system (XCSF)
        .. 
        .. image des trajectoires apprises
        .. 
        .. Second step: the generalisation test adaptive system learned several ...
        .. we check whether it's capable to generalize what it learned to other
        .. targets
        .. 
        .. image des trajectoires jouées
        .. 
        .. graph des résultats
        .. 
        .. conclusion: ok
        
        
        Dependencies
        ============
        
        -  Python >= 2.5
        -  Numpy_
        -  Matplotlib_ >= 0.98.1
        
        .. -  ffmpeg2theora (screencast) [optional]
        .. -  PIL (screencast) [optional]
        
        Note:
        
            If you use ``pip`` to install PyArm, Numpy and Matplotlib will be
            automatically downloaded and installed (see the following install_
            section).
        
        
        .. _install:
        
        Installation
        ============
        
        Gnu/Linux
        ---------
        
        You can install, upgrade, uninstall PyArm with these commands (in a
        terminal)::
        
            pip install --pre pyarm12
            pip install --upgrade pyarm12
            pip uninstall pyarm
        
        Or, if you have downloaded the PyArm source code::
        
            python3 setup.py install
        
        .. There's also a package for Debian/Ubuntu::
        .. 
        ..     sudo apt-get install pyarm
        
        Windows
        -------
        
        Note:
        
            The following installation procedure has been tested to work with Python
            3.4 under Windows 7.
            It should also work with recent Windows systems.
        
        You can install, upgrade, uninstall PyArm with these commands (in a
        `command prompt`_)::
        
            py -m pip install --pre pyarm
            py -m pip install --upgrade pyarm
            py -m pip uninstall pyarm
        
        Or, if you have downloaded the PyArm source code::
        
            py setup.py install
        
        MacOSX
        -------
        
        Note:
        
            The following installation procedure has been tested to work with Python
            3.4 under MacOSX 10.6 (*Snow Leopard*).
            It should also work with recent MacOSX systems.
        
        You can install, upgrade, uninstall PyArm with these commands (in a
        terminal)::
        
            pip install --pre pyarm
            pip install --upgrade pyarm
            pip uninstall pyarm
        
        Or, if you have downloaded the PyArm source code::
        
            python3 setup.py install
        
        
        Documentation
        =============
        
        .. PyArm documentation is available on the following page:
        .. 
        ..     http://pyarm.rtfd.org/
        
        - Online Documentation: http://pyarm.readthedocs.org
        - API Documentation: http://pyarm.readthedocs.org/en/latest/api.html
        
        
        Run pyarm
        =========
        
        To run Pyarm, simply type in a terminal::
        
            pyarm
        
        
        Usage example
        =============
        
        Use the following command to run simulations with graphs and logs using
        the *Mitrovic* muscle model described in the `technical report`_ and a
        *sigmoid* controler::
        
            pyarm -f -l -m mitrovic -d 0.005 -A sigmoid
        
        The following command run a simulation with the *sagittal* arm model and
        the *kambara* muscle model using a *sigmoid* controller::
        
            pyarm -a sagittal -m kambara -d 0.005 -A sigmoid
        
        
        Help
        ====
        
        A comprehensive list of available options is printed with the following
        command::
        
            pyarm -h
        
        
        Bug reports
        ===========
        
        To search for bugs or report them, please use the PyArm Bug Tracker at:
        
            https://github.com/jeremiedecock/pyarm/issues
        
        
        License
        =======
        
        The ``PyArm`` library is provided under the terms and conditions of the
        `MIT License`_.
        
        
        .. _Pyarm: http://www.jdhp.org/projects_en.html#pyarm
        .. _MIT License: http://opensource.org/licenses/MIT
        .. _technical report: http://download.tuxfamily.org/jdhp/pdf/pyarm.pdf
        .. _Institute for Intelligent Systems and Robotics: http://www.isir.upmc.fr/
        .. _Numpy: http://www.numpy.org/
        .. _Matplotlib: http://matplotlib.org/
        
        
Keywords: robotics simultion library
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.0
Classifier: Programming Language :: Python :: 3.1
Classifier: Programming Language :: Python :: 3.2
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering :: Physics
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
