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
- Mauriel Rodriguez Curras (ORCID: https://orcid.org/0000-0003-2837-359X)
- Alexander A. Nguyen (ORCID: https://orcid.org/0000-0001-9798-033X)
- Jonathan N. Pauli (ORCID: https://orcid.org/0000-0001-5908-6628)
- Magnus Egerstedt (ORCID: https://orcid.org/0000-0003-4213-5299)
Institutions
- University of Wisconsin–Madison (US)
- University of California, Irvine (US)
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