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Bibliographic Details
Main Authors: Amir, Michael, Bruckstein, Alfred M.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2404.19564
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author Amir, Michael
Bruckstein, Alfred M.
author_facet Amir, Michael
Bruckstein, Alfred M.
contents We investigate the algorithmic problem of uniformly dispersing a swarm of robots in an unknown, gridlike environment. In this setting, our goal is to study the relationships between performance metrics and robot capabilities. We introduce a formal model comparing dispersion algorithms based on makespan, traveled distance, energy consumption, sensing, communication, and memory. Using this framework, we classify uniform dispersion algorithms according to their capability requirements and performance. We prove that while makespan and travel can be minimized in all environments, energy cannot, if the swarm's sensing range is bounded. In contrast, we show that energy can be minimized by ``ant-like'' robots in synchronous settings and asymptotically minimized in asynchronous settings, provided the environment is topologically simply connected, by using our ``Find-Corner Depth-First Search'' (FCDFS) algorithm. Our theoretical and experimental results show that FCDFS significantly outperforms known algorithms. Our findings reveal key limitations in designing swarm robotics systems for unknown environments, emphasizing the role of topology in energy-efficient dispersion.
format Preprint
id arxiv_https___arxiv_org_abs_2404_19564
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Time, Travel, and Energy in the Uniform Dispersion Problem
Amir, Michael
Bruckstein, Alfred M.
Robotics
Discrete Mathematics
Multiagent Systems
68T40
I.2.9
We investigate the algorithmic problem of uniformly dispersing a swarm of robots in an unknown, gridlike environment. In this setting, our goal is to study the relationships between performance metrics and robot capabilities. We introduce a formal model comparing dispersion algorithms based on makespan, traveled distance, energy consumption, sensing, communication, and memory. Using this framework, we classify uniform dispersion algorithms according to their capability requirements and performance. We prove that while makespan and travel can be minimized in all environments, energy cannot, if the swarm's sensing range is bounded. In contrast, we show that energy can be minimized by ``ant-like'' robots in synchronous settings and asymptotically minimized in asynchronous settings, provided the environment is topologically simply connected, by using our ``Find-Corner Depth-First Search'' (FCDFS) algorithm. Our theoretical and experimental results show that FCDFS significantly outperforms known algorithms. Our findings reveal key limitations in designing swarm robotics systems for unknown environments, emphasizing the role of topology in energy-efficient dispersion.
title Time, Travel, and Energy in the Uniform Dispersion Problem
topic Robotics
Discrete Mathematics
Multiagent Systems
68T40
I.2.9
url https://arxiv.org/abs/2404.19564