Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior
In the study of collective animal behavior, researchers usually rely on gathering empirical data from animals in the wild. While the data gathered can be highly accurate, researchers have limited control over both the test environment and the agents under study. Further aggravating the data gatherin...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-06-01
|
Series: | Frontiers in Robotics and AI |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/frobt.2022.865414/full |
_version_ | 1818236400925933568 |
---|---|
author | Nikolaj Horsevad Hian Lee Kwa Hian Lee Kwa Roland Bouffanais |
author_facet | Nikolaj Horsevad Hian Lee Kwa Hian Lee Kwa Roland Bouffanais |
author_sort | Nikolaj Horsevad |
collection | DOAJ |
description | In the study of collective animal behavior, researchers usually rely on gathering empirical data from animals in the wild. While the data gathered can be highly accurate, researchers have limited control over both the test environment and the agents under study. Further aggravating the data gathering problem is the fact that empirical studies of animal groups typically involve a large number of conspecifics. In these groups, collective dynamics may occur over long periods of time interspersed with excessively rapid events such as collective evasive maneuvers following a predator’s attack. All these factors stress the steep challenges faced by biologists seeking to uncover the fundamental mechanisms and functions of social organization in a given taxon. Here, we argue that beyond commonly used simulations, experiments with multi-robot systems offer a powerful toolkit to deepen our understanding of various forms of swarming and other social animal organizations. Indeed, the advances in multi-robot systems and swarm robotics over the past decade pave the way for the development of a new hybrid form of scientific investigation of social organization in biology. We believe that by fostering such interdisciplinary research, a feedback loop can be created where agent behaviors designed and tested in robotico can assist in identifying hypotheses worth being validated through the observation of animal collectives in nature. In turn, these observations can be used as a novel source of inspiration for even more innovative behaviors in engineered systems, thereby perpetuating the feedback loop. |
first_indexed | 2024-12-12T12:09:16Z |
format | Article |
id | doaj.art-fa174f9aeabb443cabd8e6fe6cfc779d |
institution | Directory Open Access Journal |
issn | 2296-9144 |
language | English |
last_indexed | 2024-12-12T12:09:16Z |
publishDate | 2022-06-01 |
publisher | Frontiers Media S.A. |
record_format | Article |
series | Frontiers in Robotics and AI |
spelling | doaj.art-fa174f9aeabb443cabd8e6fe6cfc779d2022-12-22T00:24:56ZengFrontiers Media S.A.Frontiers in Robotics and AI2296-91442022-06-01910.3389/frobt.2022.865414865414Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal BehaviorNikolaj Horsevad0Hian Lee Kwa1Hian Lee Kwa2Roland Bouffanais3University of Ottawa, Ottawa, ON, CanadaSingapore University of Technology and Design, Singapore, SingaporeThales Solutions Asia, Singapore, SingaporeUniversity of Ottawa, Ottawa, ON, CanadaIn the study of collective animal behavior, researchers usually rely on gathering empirical data from animals in the wild. While the data gathered can be highly accurate, researchers have limited control over both the test environment and the agents under study. Further aggravating the data gathering problem is the fact that empirical studies of animal groups typically involve a large number of conspecifics. In these groups, collective dynamics may occur over long periods of time interspersed with excessively rapid events such as collective evasive maneuvers following a predator’s attack. All these factors stress the steep challenges faced by biologists seeking to uncover the fundamental mechanisms and functions of social organization in a given taxon. Here, we argue that beyond commonly used simulations, experiments with multi-robot systems offer a powerful toolkit to deepen our understanding of various forms of swarming and other social animal organizations. Indeed, the advances in multi-robot systems and swarm robotics over the past decade pave the way for the development of a new hybrid form of scientific investigation of social organization in biology. We believe that by fostering such interdisciplinary research, a feedback loop can be created where agent behaviors designed and tested in robotico can assist in identifying hypotheses worth being validated through the observation of animal collectives in nature. In turn, these observations can be used as a novel source of inspiration for even more innovative behaviors in engineered systems, thereby perpetuating the feedback loop.https://www.frontiersin.org/articles/10.3389/frobt.2022.865414/fullcollective animal behaviorcollective decision-makingcollective roboticsmulti-robot systemsswarm intelligenceself-organization |
spellingShingle | Nikolaj Horsevad Hian Lee Kwa Hian Lee Kwa Roland Bouffanais Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior Frontiers in Robotics and AI collective animal behavior collective decision-making collective robotics multi-robot systems swarm intelligence self-organization |
title | Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior |
title_full | Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior |
title_fullStr | Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior |
title_full_unstemmed | Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior |
title_short | Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior |
title_sort | beyond bio inspired robotics how multi robot systems can support research on collective animal behavior |
topic | collective animal behavior collective decision-making collective robotics multi-robot systems swarm intelligence self-organization |
url | https://www.frontiersin.org/articles/10.3389/frobt.2022.865414/full |
work_keys_str_mv | AT nikolajhorsevad beyondbioinspiredroboticshowmultirobotsystemscansupportresearchoncollectiveanimalbehavior AT hianleekwa beyondbioinspiredroboticshowmultirobotsystemscansupportresearchoncollectiveanimalbehavior AT hianleekwa beyondbioinspiredroboticshowmultirobotsystemscansupportresearchoncollectiveanimalbehavior AT rolandbouffanais beyondbioinspiredroboticshowmultirobotsystemscansupportresearchoncollectiveanimalbehavior |