This package provides centralized implementations of Randomized Sequential Partitions (RSP) (see references) that are suitable for numerical simulations as well as a number of other algorithms for multi-agent planning via submodular maximization such as sequential planning and auction algorithms.
Additionally, we implemented two application scenarios
- A simple coverage problem. Agent centers are distributed across the unit square. Actions are disks near the agent centers.
- A mutual information based target tracking problem. Agents plan on (short) receding horizons via Monte Carlo tree search.
In addition to a number of registered Julia packages, some scripts for plotting data from experimental trials rely on RosDataProcess which is not yet registered with the Julia ecosystem.
If you use this package in published work, pleace consider citing either of the following:
For the coverage scenario and the initial implementation of RSP:
@inproceedings{corah2018cdc,
author = {Corah, Micah and Michael, Nathan},
title={Distributed Submodular Maximization on Partition Matroids for Planning
on Large Sensor Networks},
booktitle={Proc. of the {IEEE} Conf. on Decision and Control},
year = {2018},
month = dec,
address = {Miami, FL},
}
Please cite the thesis for the target tracking scenario and everything else:
@phdthesis{corah2020phd,
author = {Corah, Micah},
title = {Sensor Planning for Large Numbers of Robots},
school = {Carnegie Mellon University},
year = {2020}
}