Tools to manipulate and use task models for human robot collaboration.

If you are using this software and or one of its components, we warmly recommend you to cite the following paper:

[Roncone2017] Roncone Alessandro, Mangin Olivier, Scassellati Brian Transparent Role Assignment and Task Allocation in Human Robot Collaboration IEEE International Conference on Robotics and Automation (ICRA 2017), Singapore. [PDF] [BIB]

This package requires a binary from Anthony Cassandra's POMDP solver. Please visit pomdp.org for any matter related to the POMDP solver. In order to be using the simplex finite grid method, a fork of the version from cmansley needs to be installed that contains a fix to the original code. You can get the fork here.

The python code is looking for the pomdp-solve executable in your $PATH. Here are some instructions on how to compile and install the solver properly (assuming that ~/src is the directory in which you usually place your code):

cd ~/src
git clone https://github.com/scazlab/pomdp-solve
cd pomdp-solve
mkdir build
cd build/
../configure --prefix=$HOME/.local
make
make install

Make sure that ~/.local/bin is in yout path and now you should have pomdp-solve installed in it, and it should be available for the python package to be used.

To generate the policy from the experiment in [Roncone2017], please use the script samples/icra_scenario2pomdp.py. The script will generate the corresponding POMDP model, solve it with Anthony Cassandra's POMDP solver, and store the corresponding policy under visualization/policy/json/icra.json. To run the full experiment on the baxter robot, please refer to github.com/ScazLab/baxter_collaboration.