Installation Instructions
REFINE-PLAN has been tested on Ubuntu 22.04 with Python 3.10.12.
If you use this repository, please consider citing:
@inproceedings{street2025planning,
title={Planning under Uncertainty from Behaviour Trees},
author={Street, Charlie and Grubb, Oliver and Mansouri, Masoumeh},
booktitle={Under Review},
year={2025}
}
Installing Dependencies
COVERAGE-PLAN requires the following dependencies:
Numpy (Tested with 26.4)
Sympy (Tested with 1.12)
Pyeda (Tested with 0.29.0)
PyAgrum (Tested with 1.14.1)
PyMongo (Tested with 4.8.0)
Pandas (Tested with 2.2.1)
Stormpy (Tested with 1.8.0)
MongoDB (Tested with 7.0.12) - only required for unit tests.
The first six dependencies can be installed via:
pip install -r requirements.txt
MongoDB
can be installed using the official instructions.
Installing stormpy
is more involved. Please see below.
Installing Stormpy
Stormpy requires the use of Storm. Instructions for installing stormpy alongside its dependencies can be found here.
REFINE-PLAN has been tested with the following software versions during the above installation steps:
Storm - 1.8.1. Specifically we use this commit.
Carl - 14.27 (this is the
carl-storm
version of Carl, as mentioned in the Storm installation instructions)pycarl - 2.2.0
stormpy - 1.8.0
As Storm is updated, you may want newer versions of these libraries. The current master of Stormpy and Storm should usually be compatible.
Installation for Users (Pip Install)
After installing all dependencies, run the following in the root directory of this repository:
pip install .
Installation for Developers (Update PYTHONPATH)
After installing all dependencies, run the following in the root directory of this repository:
./setup_dev.sh
Run examples
Small examples of REFINE-PLAN can be found in the bin
directory.
Run the Unit Tests
To run all unit tests, run:
cd tests
python3 -m unittest discover --pattern=*.py
Running the experiments for ‘Planning under Uncertainty from Behaviour Trees’
In case of code updates after paper submission/publication, please consider downloading the iros-2025
release of this repository.
Vacuum Cleaner Search Domain
The planning script for the vacuum cleaner search experiment is found at bin/house_planning.py
.
This script behaves similarly to bin/bookstore_planning.py
, with identical function names and behaviours.
The dataset, Bayesian networks, and refined policy are already generated and can be found in data/house/
.
To generate these yourself, run write_mongodb_to_yaml(sys.argv[1])
, learn_options()
, or run_planner()
in bin/house_planning.py
by uncommenting the corresponding line in lines 249-251.
See the book store instructions above for the expected behaviour of these functions.
To execute the initial BT or refined policy in Gazebo, please install turtlebot_house_sim and read the instructions in the README.
Build the Documentation
If you want to build the REFINE-PLAN documentation locally, do the following:
Install the required packages:
pip install -r docs/requirements.txt
Install the package to be documented:
pip install refine_plan/
Or add it to your Python path:
./setup_dev.sh
Build the documentation:
cd docs
make html
Look at the documentation:
cd docs
firefox build/html/index.html
Clean documentation build artifacts
If you want to clean the documentation, you can run:
cd docs
make clean