/jet-leg

This is an open-source python package that shows how to compute the Feasible Region, i.e. the extension of the well known support region to include joint-torque limits constraints. The details are explained in this preprint:

Primary LanguagePythonGNU Lesser General Public License v3.0LGPL-3.0

hyqgreen planning hyqgreen planning

Feasible Region: an Actuation-Aware Extension of the Support Region

This python library contains the code used for the motion planning formulation proposed in this preprint. In here you can also find the code used to generate the figures and plots of the manuscript.

hyqgreen planning hyqgreen planning

Jet-leg performs common operations over convex polyhedra in higher dimensions in order to assess the problem of stability and motion feasibility of legged robots.

What you can do with Jet-leg:

  • compute the Support region of legged robots as in Bretl. et al. 2008;
  • compute the Feasible region of legged robots as in Orsolino. et al. 2019;
  • compute force polytopes of legged robots;
  • test various formulations of linear, convex or nonlinear optimization problems;

Dependencies

APT dependencies:

  • CVXOPT
  • GLPK
  • Cython

ROS dependencies:

sudo apt-get  install ros-kinetic-graph-msgs

Python dependencies:

  • Numpy
  • Scipy
  • Pycddlib
  • Matplotlib
  • Pypoman for the manipulation of polyhedrical object
  • Pinocchio

The above dependencies can be installed with the following commands:

sudo apt-get install cython libglpk-dev python python-dev python-pip python-scipy
CVXOPT_BUILD_GLPK=1 pip install cvxopt --user
pip install pycddlib --user
pip install pypoman

You can remove all --user arguments to install these Python modules system-wide.

Optional dependencies:

  • Ipopt and its Python interface Pypi for the solution of large-scale nonlinear optimization problems
  • ffmpeg for the generation of Matplotlib animations
sudo apt-get install ffmpeg
  • unittest for testing of dependencies installation and for development

Testing the library

After completing the installation navigate to the examples folder:

Troubleshooting

  • if CVXOPT is not found even after trying the pip-installation, we then suggest to try install the version 1.1.4 of CVXOPT using Synaptic or to clone and install it manually after building.
  • IMPORTANTE NOTE: delete every previous installation of cvxopt that is in the system using locate cvxopt (after sudo updatedb)

See also