@inproceedings{91233d5ae67b44cdb09c8e5f823d74a4,
title = "Statistical Correlations in Active Matter Based on Robotic Swarms",
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. ",
keywords = "Active Matter, Object Tracking, Phase Transitions, Self-Organization, Swarm Robotics",
author = "Alexey Dmitriev and Alina Rozenblit and Vadim Porvatov and Anastasia Molodtsova and Ekaterina Puhtina and Oleg Burmistrov and Dmitry Filonov and Anton Souslov and Nikita Olekhno",
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). ; 2021 International Conference Engineering and Telecommunication, En and T 2021 ; Conference date: 24-11-2021 Through 25-11-2021",
year = "2022",
month = jan,
day = "24",
doi = "10.1109/EnT50460.2021.9681775",
language = "English",
series = "2021 International Conference Engineering and Telecommunication, En and T 2021",
publisher = "IEEE",
booktitle = "2021 International Conference Engineering and Telecommunication, En and T 2021",
address = "USA United States",
}