Design of a modular robotic system that mimics small fish locomotion and body movements for ethological studies

Bonnet, Frank; Cazenille, Léo; Séguret, Axel; Gribovskiy, Alexey; Collignon, Bertrand; Halloy, José; Mondada, Francesco

doi:10.1177/1729881417706628

Cited by 23 publications

(33 citation statements)

References 27 publications

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“…This chapter is based on the publication Infiltrating the Zebrafish Swarm: Design, Implementation and Experimental Tests of a Miniature Robotic Fish Lure for Fish-Robot Interaction Studies [Bonnet et al, 2016b] and the publication Design Methods for Miniature Underwater Soft Robots [Bonnet et al, 2016a] with slight modifications to fit the present dissertation.…”

Section: Discussionmentioning

confidence: 99%

Shoaling with Fish: Using Miniature Robotic Agents to Close the Interaction Loop with Groups of Zebrafish Danio rerio

Bonnet

Mondada

2019

Springer Tracts in Advanced Robotics

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Robotic animals are nowadays developed for various types of research, such as bio-inspired robotics, biomimetics and animal behavior studies. The miniaturization of technologies and the increase in performance of embedded systems allowed engineers to develop more powerful, sophisticated and miniature devices. The case of robotic fish is a typical example of such challenging design: the fish locomotion and body movements are difficult to reproduce and the device has to move autonomously underwater. More specifically, in the case of collective animal behavior research, the robotic device has to interact with animals by generating and exploiting signals relevant for social behavior. Once perceived by the animal society as conspecific, these robots can become powerful tools to study the animal behaviors, as they can at the same time monitor the changes in behavior and influence the collective choices of the animal society. In this work, we present novel robotized tools that can integrate shoals of fish in order to study their collective behaviors. This robotic platform is composed of two subsystems: a miniature wheeled mobile robot that can achieve dynamic movements and multi-robot long-duration experiments, and a robotic fish lure that is able to beat its tail to generate fish-like body movements. The two subsystems are coupled with magnets which allows the wheeled mobile robot to steer the robotic fish lure so that it reaches very high speeds and accelerations while achieving shoaling. An experimental setup to conduct studies on mixed societies of artificial and living fish was designed to facilitate the experiments for biologists. A software framework was also implemented to control the robots in a closed-loop using data extracted from visual tracking that retrieved the position of the robots and the fish. We selected the zebrafish Danio rerio as a model to perform experiments to qualify our system. We used the current state of the art on the zebrafish social behavior to define the specifications of the robots, and we performed stimuli analysis to improve their developments. Bio-inspired controllers were designed based on data extracted from experiments with zebrafish for the robots to mimic the zebrafish locomotion underwater. Experiments involving a robot with a shoal of fish in a constrained environment showed that the locomotion of the robot was one of the main factor to affect the collective behavior of zebrafish. We also shown that the body movements and the biomimetic appearance of the lure could increase its acceptance by fish. Finally, an experiment involving a mixed society of v Abstract fish and robots qualified the robotic system to be integrated among a zebrafish shoal and to be able to influence the collective decisions of the fish. These results are very promising for the field of fish-robot interaction studies, as we showed the effect of the robots in long-duration experiments and repetitively, with the same order of response from the animals.

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Section: Discussionmentioning

confidence: 99%

Shoaling with Fish: Using Miniature Robotic Agents to Close the Interaction Loop with Groups of Zebrafish Danio rerio

Bonnet

Mondada

2019

Springer Tracts in Advanced Robotics

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“…Every 200ms, the tracked positions of the four fish are integrated into the model to compute the target position of a fifth agent. The robot is programmed to follow this target position by using the biomimetic movement patterns as in [5], [10].…”

Section: G Robot Implementation and Controlmentioning

confidence: 99%

How to Blend a Robot Within a Group of Zebrafish: Achieving Social Acceptance Through Real-Time Calibration of a Multi-level Behavioural Model

Cazenille

Chemtob

Bonnet

et al. 2018

Biomimetic and Biohybrid Systems

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We have previously shown how to socially integrate a fish robot into a group of zebrafish thanks to biomimetic behavioural models. The models have to be calibrated on experimental data to present correct behavioural features. This calibration is essential to enhance the social integration of the robot into the group. When calibrated, the behavioural model of fish behaviour is implemented to drive a robot with closed-loop control of social interactions into a group of zebrafish. This approach can be useful to form mixed-groups, and study animal individual and collective behaviour by using biomimetic autonomous robots capable of responding to the animals in long-standing experiments. Here, we show a methodology for continuous real-time calibration and refinement of multi-level behavioural model. The real-time calibration, by an evolutionary algorithm, is based on simulation of the model to correspond to the observed fish behaviour in real-time. The calibrated model is updated on the robot and tested during the experiments. This method allows to cope with changes of dynamics in fish behaviour. Moreover, each fish presents individual behavioural differences. Thus, each trial is done with naive fish groups that display behavioural variability. This real-time calibration methodology can optimise the robot behaviours during the experiments. Our implementation of this methodology runs on three different computers that perform individual tracking, data-analysis, multi-objective evolutionary algorithms, simulation of the fish robot and adaptation of the robot behavioural models, all in real-time.

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“…This motivates robot researchers to pay close attention to biological working mechanisms that can be implemented on an autonomous mobile robot, so as to improve the navigation and motion ability of robots. [1][2][3] As an important kind of behavioral strategy in human navigation, route-based navigation strategy has been used in autonomous mobile robots, that is, a process of using real-time perceived environment information and selfmotion ability to reach the destination along the preset route. [4][5][6] Route serves as the basis of route-based navigation strategy, represented as a sequence of decision points, and considered as a part of the spatial knowledge.…”

Section: Introductionmentioning

confidence: 99%

Continuous learning route map for robot navigation using a growing-on-demand self-organizing neural network

Zhong

Liu

et al. 2017

International Journal of Advanced Robotic Systems

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This article proposes an experience-based route map continuous learning method and applies it into robot planning and navigation. First of all, the framework for robot route map learning and navigation is designed, which incorporates the four cyclic processes of planning, motion, perception, and extraction, enabling robot to constantly learn the information of the road experience and to obtain and improve the route map of the environment. Besides, a growing-on-demand selforganizing neural network learning algorithm is also proposed. This algorithm is based on growing neural gas algorithm, but it does not require presetting of network scale, and under the condition of dynamically growing input data, it can regulate the increase scale of network online in a self-adaptive and self-organized manner to obtain stable learning results. Finally, with robot roaming in an environment, this algorithm is used to conduct continuous learning of dynamically increasing route information, extract the topological structure of the raw road data in feature space, and ultimately obtain the route map of the environment. Mobile robot utilizes the route map to plan a suitable route and guides robot to move to the destination along the route and complete navigation task. Through physical experiments in outdoor environment, its feasibility and validity are verified.

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Design of a modular robotic system that mimics small fish locomotion and body movements for ethological studies

Cited by 23 publications

References 27 publications

Shoaling with Fish: Using Miniature Robotic Agents to Close the Interaction Loop with Groups of Zebrafish Danio rerio

Shoaling with Fish: Using Miniature Robotic Agents to Close the Interaction Loop with Groups of Zebrafish Danio rerio

How to Blend a Robot Within a Group of Zebrafish: Achieving Social Acceptance Through Real-Time Calibration of a Multi-level Behavioural Model

Continuous learning route map for robot navigation using a growing-on-demand self-organizing neural network

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