Abstract

While the decision-making and planning framework ROS Hybrid Behaviour Planner (RHBP) has been used in a wide variety of projects, newer features have not yet been tested in complex scenarios. One of those features allows creating multiple independent levels of decision-making by encapsulating a separate behaviour network into behaviours. Another one is an extension for implicit coordination through self-organisation. This paper discusses our system that was developed for the multi-agent contest 2018 using RHBP, while especially making use of newer features wherever possible. Our team TUBDAI achieved the shared top spot in the contest, showing that RHBP and in particular the new features can be used successfully in a complex scenario and measures up to the multi-agent frameworks, other teams have used. Especially, when a last-minute change to the contest environment required us to integrate substantial strategy changes in last-minute, it turned out that RHBP fostered adaptiveness during our development.

@InProceedings{Hrabia2020hierarchies,
author={Hrabia, Christopher-Eyk
and Ettlinger, Michael Franz
and Hessler, Axel},
title={ROS Hybrid Behaviour Planner: Behaviour Hierarchies and Self-Organisation in the Multi-Agent Programming Contest},
booktitle="The Multi-Agent Programming Contest 2018 (Lecture Notes in Computer Science)",
year={2020},
publisher={Springer International Publishing},
address="Cham",
pages="120--143",
isbn="978-3-030-37959-9"
}