Statistical Correlations in Active Matter Based on Robotic Swarms

Alexey Dmitriev, Alina Rozenblit, Vadim Porvatov, Anastasia Molodtsova, Ekaterina Puhtina, Oleg Burmistrov, Dmitry Filonov, Anton Souslov, Nikita Olekhno

Research output: Chapter or section in a book/report/conference proceedingChapter in a published conference proceeding

2 Citations (SciVal)

Abstract

Robotic swarms are a promising tool for exploring the fundamental physics of active matter. In these designed systems, large assemblies of simple robots exhibit versatile dynamical behavior and a broad range of collective phenomena. However, extracting detailed statistical data for the behavior of large-scale robotic ensembles remains challenging due to the amount of measurements required and the need for computational resources for processing. In this paper, we introduce an experimental setup based on a robotic swarm complete with the necessary hardware and software platforms. Performing extensive experiments and extracting detailed kinematic information, we reveal a rich set of spatial correlations in stochastic robotic ensembles on the friction between individual robots and their packing density.

Original languageEnglish
Title of host publication2021 International Conference Engineering and Telecommunication, En and T 2021
Place of PublicationU. S. A.
PublisherIEEE
ISBN (Electronic)9781728183909
DOIs
Publication statusE-pub ahead of print - 24 Jan 2022
Event2021 International Conference Engineering and Telecommunication, En and T 2021 - Dolgoprudny, Russian Federation
Duration: 24 Nov 202125 Nov 2021

Publication series

Name2021 International Conference Engineering and Telecommunication, En and T 2021

Conference

Conference2021 International Conference Engineering and Telecommunication, En and T 2021
Country/TerritoryRussian Federation
CityDolgoprudny
Period24/11/2125/11/21

Bibliographical note

Funding Information:
We acknowledge valuable discussions with Egor Kretov, Georgy Gritsenko, and Daria Petrova. The research was sup- ported by the Russian Science Foundation (project 20-19-00491).

Funding

We acknowledge valuable discussions with Egor Kretov, Georgy Gritsenko, and Daria Petrova. The research was sup- ported by the Russian Science Foundation (project 20-19-00491).

Keywords

  • Active Matter
  • Object Tracking
  • Phase Transitions
  • Self-Organization
  • Swarm Robotics

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Signal Processing
  • Aerospace Engineering
  • Electrical and Electronic Engineering
  • Instrumentation

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