Closed-loop interactions between a shoal of zebrafish and a group of robotic fish in a circular corridor

Frank Bonnet, Alexey Gribovskiy, Francesco Mondada
Springer Verlag, 2018
Article

Collective behavior based on self-organization has been observed in populations of animals from insects to vertebrates. These findings have motivated engineers to investigate approaches to control autonomous multi-robot systems able to reproduce collective animal behaviors, and even to collectively interact with groups of animals. In this article, we show collective decision making by a group of autonomous robots and a group of zebrafish, leading to a shared decision about swimming direction. The robots can also modulate the collective decision-making process in biased and non-biased experimental setups. These results demonstrate the possibility of creating mixed societies of vertebrates and robots in order to study or control animal behavior.

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Frank Bonnet, Alexey Gribovskiy, Francesco Mondada
Springer Verlag, 2018
Article

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https://infoscience.epfl.ch/record/233686?ln=fr

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Robots mediating interactions between animals for interspecies collective behaviors

Frank Bonnet, Robert Matthew Mills, Francesco Mondada, Martina Szopek

Self-organized collective behavior has been analyzed in diverse types of gregarious animals. Such collective intelligence emerges from the synergy between individuals, which behave at their own time and spatial scales and without global rules. Recently, robots have been developed to collaborate with animal groups in the pursuit of better understanding their decision-making processes. These biohybrid systems make cooperative relationships between artificial systems and animals possible, which can yield new capabilities in the resulting mixed group. However, robots are currently tailor-made to successfully engage with one animal species at a time. This limits the possibilities of introducing distinct species-dependent perceptual capabilities and types of behaviors in the same system. Here, we show that robots socially integrated into animal groups of honeybees and zebrafish, each one located in a different city, allowing these two species to interact. This interspecific information transfer is demonstrated by collective decisions that emerge between the two autonomous robotic systems and the two animal groups. The robots enable this biohybrid system to function at any distance and operates in water and air with multiple sensorimotor properties across species barriers and ecosystems. These results demonstrate the feasibility of generating and controlling behavioral patterns in biohybrid groups of multiple species. Such interspecies connections between diverse robotic systems and animal species may open the door for new forms of artificial collective intelligence, where the unrivaled perceptual capabilities of the animals and their brains can be used to enhance autonomous decision-making, which could find applications in selective "rewiring" of ecosystems.

2019

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Bidirectional interactions facilitate the integration of a robot into a shoal of zebrafish Danio rerio

Frank Bonnet, Bertrand Eric Collignon, Francesco Mondada, Vaios Papaspyros

Many studies on collective animal behavior seek to identify the individual rules that underlie collective patterns. However, it was not until the recent advancements of micro-electronic and embedded systems that scientists were able to create mixed groups of sensor-rich robots and animals and study collective interactions from the within a bio-hybrid group. In recent work, scientists showed that a robot-controlled lure is capable of influencing the collective decisions of zebrafish Danio rerio shoals moving in a ring and a two-room setup. Here, we study a closely related topic, that is, the collective behavior patterns that emerge when different behavioral models are reproduced through the use of a robotic lure. We design a behavioral model that alternates between obeying and disobeying the collective motion decisions in order to become socially accepted by the shoal members. Subsequently, we compare it against two extreme cases: a reactive and an imposing decision model. For this, we use spatial, directional and information theoretic metrics to measure the degree of integration of the robotic agent. We show that our model leads to similar information flow as in freely roaming shoals of zebrafish and exhibits leadership skills more often than the open-loop models. Thus, in order for the robot to achieve higher degrees of integration in the zebrafish shoal, it must, like any other shoal member, be bidirectionally involved in the decision making process. These findings provide insight on the ability to form mixed societies of animals and robots and yield promising results on the degree to which a robot can influence the collective decision making.

2019

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Social Integration of Robots into Groups of Cockroaches to Control Self-Organized Choices

Masoud Asadpour, Gilles Caprari, Nicolaus Correll, Jean-Louis Deneubourg, Alcherio Martinoli, Francesco Mondada, Roland Siegwart

Collective behavior based on self-organization has been shown in group-living animals from insects to vertebrates. These findings have stimulated engineers to investigate approaches for the coordination of autonomous multirobot systems based on self-organization. In this experimental study, we show collective decision-making by mixed groups of cockroaches and socially integrated autonomous robots, leading to shared shelter selection. Individuals, natural or artificial, are perceived as equivalent, and the collective decision emerges from nonlinear feedbacks based on local interactions. Even when in the minority, robots can modulate the collective decision-making process and produce a global pattern not observed in their absence. These results demonstrate the possibility of using intelligent autonomous devices to study and control self-organized behavioral patterns in group-living animals.

2007

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