In this paper, we propose a distributed multi-stage optimization method for planning complex missions for heterogeneous multi-robot teams. This class of problems involves tasks that can be executed in different ways and are associated with cross-schedule dependencies that constrain the schedules of the different robots in the system. The proposed approach involves a multi-objective heuristic search of the mission, represented as a hierarchical tree that defines the mission goal. This procedure outputs several favorable ways to fulfill the mission, which directly feed into the next stage of the method. We propose a distributed metaheuristic based on evolutionary computation to allocate tasks and generate schedules for the set of chosen decompositions. The method is evaluated in a simulation setup of an automated greenhouse use case, where we demonstrate the method's ability to adapt the planning strategy depending on the available robots and the given optimization criteria.
@article{arxiv.2109.10106,
title = {Distributed Mission Planning of Complex Tasks for Heterogeneous Multi-Robot Teams},
author = {Barbara Arbanas Ferreira and Tamara Petrović and Stjepan Bogdan},
journal= {arXiv preprint arXiv:2109.10106},
year = {2021}
}