Quantitative Assessment of Robotic Swarm Coverage

Brendon G. Anderson, Eva Loeser, Marissa Gee, Fei Ren, Swagata Biswas, Olga Turanova, Matt Haberland, Andrea L. Bertozzi

2018

Abstract

This paper studies a generally applicable, sensitive, and intuitive error metric for the assessment of robotic swarm density controller performance. Inspired by vortex blob numerical methods, it overcomes the shortcomings of a common strategy based on discretization, and unifies other continuous notions of coverage. We present two benchmarks against which to compare the error metric value of a given swarm configuration: nontrivial bounds on the error metric, and the probability density function of the error metric when robot positions are sampled at random from the target swarm distribution. We give rigorous results that this probability density function of the error metric obeys a central limit theorem, allowing for more efficient numerical approximation. For both of these benchmarks, we present supporting theory, computation methodology, examples, and MATLAB implementation code.

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Paper Citation


in Harvard Style

Loeser E., Gee M., Ren F., Biswas S. and Haberland M. (2018). Quantitative Assessment of Robotic Swarm Coverage.In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-989-758-321-6, pages 91-101. DOI: 10.5220/0006844600910101


in Bibtex Style

@conference{icinco18,
author={Eva Loeser and Marissa Gee and Fei Ren and Swagata Biswas and Matt Haberland},
title={Quantitative Assessment of Robotic Swarm Coverage},
booktitle={Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2018},
pages={91-101},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006844600910101},
isbn={978-989-758-321-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - Quantitative Assessment of Robotic Swarm Coverage
SN - 978-989-758-321-6
AU - Loeser E.
AU - Gee M.
AU - Ren F.
AU - Biswas S.
AU - Haberland M.
PY - 2018
SP - 91
EP - 101
DO - 10.5220/0006844600910101