Mutualisms as a framework for multi-robot collaboration

Biology has inspired robotics since its inception as an academic discipline. However, the use of ecological principles in robotics is still relatively rare and in this paper, we explore how such principles can not only be of relevance to robotics, but can reciprocally lead to new insights into ecology. In particular, we investigate how mutualisms-jointly beneficial interactions between members of different species-can inform collaborative architectures for multi-robot systems comprised of different types of robots. To better understand how mutualisms can have practical relevance in robotics, we present a case study where the landscape heterogeneity, i.e., the configuration of the landscape, is varied, and we measure the efficiency of robots functioning independently or involved in a mutualism. We show that landscape composition impacts the benefits of forming mutualisms, which, in turn, has implications for mutualism emergence and stability in ecology. Moreover, through this case study, the concept of fitness and its components can be introduced for engineered systems, leading to notions of longevity, task fecundity, and, ultimately, robot fitness.

Authors

Institutions

Publication Details

Journal
Frontiers in Robotics and AI
Published
2025-03-28
DOI
https://doi.org/10.3389/frobt.2025.1566452
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Mutualisms as a framework for multi-robot collaboration

Mauriel Rodriguez Curras, Alexander A. Nguyen, Jonathan N. Pauli, Magnus Egerstedt
Frontiers in Robotics and AI
Evolutionary Game Theory and Cooperation
article

Mutualisms as a framework for multi-robot collaboration

Mauriel Rodriguez Curras, Alexander A. Nguyen, Jonathan N. Pauli, Magnus Egerstedt
article en

Abstract

Biology has inspired robotics since its inception as an academic discipline. However, the use of ecological principles in robotics is still relatively rare and in this paper, we explore how such principles can not only be of relevance to robotics, but can reciprocally lead to new insights into ecology. In particular, we investigate how mutualisms-jointly beneficial interactions between members of different species-can inform collaborative architectures for multi-robot systems comprised of different types of robots. To better understand how mutualisms can have practical relevance in robotics, we present a case study where the landscape heterogeneity, i.e., the configuration of the landscape, is varied, and we measure the efficiency of robots functioning independently or involved in a mutualism. We show that landscape composition impacts the benefits of forming mutualisms, which, in turn, has implications for mutualism emergence and stability in ecology. Moreover, through this case study, the concept of fitness and its components can be introduced for engineered systems, leading to notions of longevity, task fecundity, and, ultimately, robot fitness.

Frontiers in Robotics and AIVol. 12
University of Wisconsin–Madison (US), University of California, Irvine (US)
Openalex Percentile: Top 92%
Evolutionary Game Theory and Cooperation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.