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Beyond Bio-Inspired Robotics: How Multi-Robot Systems Can Support Research on Collective Animal Behavior
Nikolaj Horsevad1, Hian Lee Kwa2,3, Roland Bouffanais1
1University of Ottawa, Ottawa, ON, Canada.
Frontiers in Robotics and AI
|July 7, 2022
Summary
Multi-robot systems offer a novel approach to studying collective animal behavior, complementing wild data. This hybrid method creates a feedback loop between robot experiments and biological observations for deeper insights into social organization.
Area of Science:
- Biology
- Robotics
- Collective Behavior
Background:
- Studying collective animal behavior often relies on field data, which presents challenges due to limited control over environments and large numbers of animals.
- Empirical studies face difficulties in capturing complex dynamics, including rapid evasive maneuvers and long-term group interactions.
Purpose of the Study:
- To propose multi-robot systems as a powerful tool for investigating animal swarming and social organization.
- To establish a hybrid research framework integrating robot experiments and biological observations.
Main Methods:
- Utilizing multi-robot systems and swarm robotics to design and test agent behaviors.
- Creating a feedback loop between robot experiments ('in robotico') and natural animal observations.
Main Results:
- Multi-robot experiments can generate hypotheses for validating in wild animal collectives.
- Observations of animal behavior can inspire novel designs for engineered systems.
Conclusions:
- A hybrid approach combining multi-robot systems and field biology offers a promising avenue for understanding social organization.
- This interdisciplinary research fosters a continuous cycle of hypothesis generation and validation, advancing both robotics and biology.
