A Correlated Random Walk Model to Rapidly Approximate Hitting Time Distributions in Multi-robot Systems

Yi Zhang, Daniel Boley, John Harwell, Maria Gini

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Multi-robot systems are frequently used for tasks involving searching, so it is important to be able to estimate the searching time. Yet, simulation approaches and real-world experiments to determine searching time can be cumbersome and even impractical. In this work, we propose a correlated-random-walk based model to efficiently approximate hitting time distributions of multi-robot systems in large arenas. We verified the computational results by using ARGoS, a physics-based simulator. We found that the Gamma distribution can provide a good fit to the hitting time distributions of random walkers.

Original languageEnglish (US)
Title of host publicationIntelligent Autonomous Systems 17 - Proceedings of the 17th International Conference IAS-17
EditorsIvan Petrovic, Ivan Markovic, Emanuele Menegatti
PublisherSpringer Science and Business Media Deutschland GmbH
Pages724-736
Number of pages13
ISBN (Print)9783031222153
DOIs
StatePublished - 2023
Event17th International Conference on Intelligent Autonomous Systems, IAS-17 - Zagreb, Croatia
Duration: Jun 13 2022Jun 16 2022

Publication series

NameLecture Notes in Networks and Systems
Volume577 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

Conference17th International Conference on Intelligent Autonomous Systems, IAS-17
Country/TerritoryCroatia
CityZagreb
Period6/13/226/16/22

Bibliographical note

Funding Information:
Acknowledgements. This research was partially supported by the University of Minnesota Robotics Institute.

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Correlated random walk
  • Hitting time distribution
  • Multi-robot systems

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