Humanoid robotics controller prototyping environment based on OpenRAVE. Includes:

• Whole-body inverse kinematics (IK) based on the weight-prioritized multi-task framework
• Contact-stability areas and volumes: multi-contact ZMP support areas, CoM acceleration cones, etc.
• Linear and Nonlinear Model Predictive Control (MPC) for locomotion
• Jacobians and Hessians for center of mass (CoM) and angular momentum
• Interfaces to polyhedral geometry and numerical optimization (LP, QP and NLP) solvers

• Walking pattern generation over uneven terrains based on capturability of the variable-height inverted pendulum model
• Nonlinear model predictive control using a direct transcription of centroidal dynamics
• Linearized model predictive control using a conservative linearization of CoM acceleration cones
• Multi-contact ZMP support areas for locomotion in multi-contact scenarios (including hand contacts)
• Humanoid stair climbing demonstrated on the HRP-4 robot

• Installation instructions
• Documentation (PDF)
• FAQ
• Examples
• Tutorial: Prototyping a walking pattern generator

The following instructions were verified on Ubuntu 14.04:

• Install OpenRAVE: here are instructions for Ubuntu 14.04 as well as for Ubuntu 16.04
• Install Python dependencies:

sudo apt-get install cython libglpk-dev python python-dev python-pip python-scipy python-simplejson

• Install the LP solver: CVXOPT_BUILD_GLPK=1 pip install cvxopt --user
• Install the QP solver: pip install quadprog --user
• For polyhedral computations (optional): pip install pycddlib --user

Finally, clone this repository and run the setup script:

git clone --recursive https://github.com/stephane-caron/pymanoid.git
cd pymanoid
python setup.py build
python setup.py install --user

For nonlinear numerical optimization, you will need to install CasADi, preferably from source with the MA27 linear solver.