How mimetic should a robotic fish be to socially integrate into zebrafish groups?

Cazenille, Léo; Collignon, Bertrand; Chemtob, Yohann; Bonnet, Frank; Gribovskiy, Alexey; Mondada, Francesco; Bredèche, Nicolas; Halloy, José

doi:10.1088/1748-3190/aa8f6a

Cited by 29 publications

(79 citation statements)

References 42 publications

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“…It also confirms the hypothesis that 'bold' behaviour is sufficient to explain the variations observed in the distribution of leadership of Danio rerio. This conclusion goes further than our previous work with autonomous robots [14], [30], [15]. Indeed, the initiations of collective departures have never been explicitly simulated by a fish robot before.…”

Section: Discussionmentioning

confidence: 66%

Strategies to modulate zebrafish collective dynamics with a closed-loop biomimetic robotic system

Chemtob

Cazenille

Bonnet

et al. 2019

Preprint

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AbstractThe objective of this study is to integrate biomimetic robots into small groups of zebrafish and to modulate their collective behaviours. A possible approach is to have the robots behave like sheepdogs. In this case, the robots would behave like a different species than the fish and would present different relevant behaviours. In this study, we explore different strategies that use biomimetic zebrafish behaviours. In past work, we have shown that robots biomimicking zebrafish can be socially integrated into zebrafish groups. We have also shown that a fish-like robot can modulate the rotation choice of zebrafish groups in a circular set-up. Here, we further study the modulation capabilities of such robots in a more complex set-up. To do this, we exploit zebrafish social behaviours we identified in previous studies. We first modulate collective departure by replicating the leadership mechanisms with the robot in a set-up composed of two rooms connected by a corridor. Then, we test different behavioural strategies to drive the fish groups towards a predefined target room. To drive the biohybrid groups towards a predefined choice, they have to adopt some specific fish-like behaviours. The first strategy is based on a single robot using the initiation behaviour. In this case, the robot keeps trying to initiate a group transition towards the target room. The second strategy is based on two robots, one initiating and one staying in the target room as a social attractant. The third strategy is based on a single robot behaving like a zebrafish but staying in the target room as a social attractant. The fourth strategy uses two robots behaving like zebrafish but staying in the target room. We conclude that robots can modulate zebrafish group behaviour by adopting strategies based on existing fish behaviours. Under these conditions, robots enable the testing of hypotheses about the behaviours of fish.

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Section: Discussionmentioning

confidence: 66%

Strategies to modulate zebrafish collective dynamics with a closed-loop biomimetic robotic system

Chemtob

Cazenille

Bonnet

et al. 2019

Preprint

Self Cite

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“…It is them analysed to track the fish positions. Experiments were carried out with 10 groups of 5 adult (6-12 months old) wild-type AB zebrafish (Danio rerio) in ten 30-minutes trials as in [6], [29]. Experiments conduced in this study were performed under the authorisation of the Buffon Ethical Committee (registered to the French National Ethical Committee for Animal Experiments #40) after submission to the French state ethical board for animal experiments.…”

Section: Experimental Set-upmentioning

confidence: 99%

Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours Using a Quality Diversity Algorithm

Cazenille

Bredèche²,

Halloy

2019

Biomimetic and Biohybrid Systems

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During the last two decades, various models have been proposed for fish collective motion. These models are mainly developed to decipher the biological mechanisms of social interaction between animals. They consider very simple homogeneous unbounded environments and it is not clear that they can simulate accurately the collective trajectories. Moreover when the models are more accurate, the question of their scalability to either larger groups or more elaborate environments remains open. This study deals with learning how to simulate realistic collective motion of collective of zebrafish, using realworld tracking data. The objective is to devise an agentbased model that can be implemented on an artificial robotic fish that can blend into a collective of real fish. We present a novel approach that uses Quality Diversity algorithms, a class of algorithms that emphasise exploration over pure optimisation. In particular, we use CVT-MAP-Elites [32], a variant of the state-of-the-art MAP-Elites algorithm [25] for high dimensional search space. Results show that Quality Diversity algorithms not only outperform classic evolutionary reinforcement learning methods at the macroscopic level (i.e. group behaviour), but are also able to generate more realistic biomimetic behaviours at the microscopic level (i.e. individual behaviour).

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“…Moreover, the design of such social robots is challenging as it involves both a luring capability including appropriate robot behaviours, and the social acceptation of the robots by the animals. We have shown that the social integration of robots into groups of fish can be improved by refining the behavioural models used to build their controllers [8]. The models have also to be calibrated to replicate accurately the animal collective behaviours in complex environments [8].…”

Section: Introductionmentioning

confidence: 99%

“…Research on animal and robot interactions need also bio-mimetic formal models as behavioural controllers of the robots if the robots have to behave as congeners [3], [2]. Robots controllers have to deal with a whole range of behaviours to allow them to take into account not only the other individuals but also the environment and in particular the walls [8], [7]. However, most of biological collective behaviour models deal only with one sub-part at a time of fish behaviours in unbounded environments.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Optimisation of Neural Network Models for Fish Collective Behaviours in Mixed Groups of Robots and Zebrafish

Cazenille¹,

Bredèche²,

Halloy³

2018

Biomimetic and Biohybrid Systems

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Animal and robot social interactions are interesting both for ethological studies and robotics. On the one hand, the robots can be tools and models to analyse animal collective behaviours, on the other hand the robots and their artificial intelligence are directly confronted and compared to the natural animal collective intelligence. The first step is to design robots and their behavioural controllers that are capable of socially interact with animals. Designing such behavioural bio-mimetic controllers remains an important challenge as they have to reproduce the animal behaviours and have to be calibrated on experimental data. Most animal collective behavioural models are designed by modellers based on experimental data. This process is long and costly because it is difficult to identify the relevant behavioural features that are then used as a priori knowledge in model building. Here, we want to model the fish individual and collective behaviours in order to develop robot controllers. We explore the use of optimised black-box models based on artificial neural networks (ANN) to model fish behaviours. While the ANN may not be biomimetic but rather bio-inspired, they can be used to link perception to motor responses. These models are designed to be implementable as robot controllers to form mixed-groups of fish and robots, using few a priori knowledge of the fish behaviours. We present a methodology with multilayer perceptron or echo state networks that are optimised through evolutionary algorithms to model accurately the fish individual and collective behaviours in a bounded rectangular arena. We assess the biomimetism of the generated models and compare them to the fish experimental behaviours.

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How mimetic should a robotic fish be to socially integrate into zebrafish groups?

Cited by 29 publications

References 42 publications

Strategies to modulate zebrafish collective dynamics with a closed-loop biomimetic robotic system

Strategies to modulate zebrafish collective dynamics with a closed-loop biomimetic robotic system

Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours Using a Quality Diversity Algorithm

Evolutionary Optimisation of Neural Network Models for Fish Collective Behaviours in Mixed Groups of Robots and Zebrafish

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