Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic Replica

The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over 25 years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our u...

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Published inIEEE transactions on robotics Vol. 36; no. 1; pp. 28 - 41
Main Authors De Lellis, Pietro, Cadolini, Edoardo, Croce, Arrigo, Yang, Yanpeng, Bernardo, Mario di, Porfiri, Maurizio
Format Journal Article
LanguageEnglish
Published United States IEEE 01.02.2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Actuation
Animal behavior
Animal-robot
Animals
Biological system modeling
collective behavior
ethorobotics
Feedback control
Insects
Real-time systems
Robot control
Robots
Sports
stochastic differential equations
swimming
Zebrafish
Animal-robot
swimming
stochastic differential equations
ethorobotics
collective behavior
Online AccessGet full text
ISSN1552-3098
1941-0468
DOI10.1109/TRO.2019.2943066

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Abstract The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over 25 years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. In this article, we integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired three-dimensionally printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.
AbstractList The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.
The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over twenty-five years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. We integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired 3D-printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.
The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over 25 years. From early work on insects to recent endeavors on mammals, we have witnessed fascinating applications that have pushed forward our understanding of animal behavior along new directions. Despite significant progress, most of the research has focused on open-loop control systems, in which robots execute predetermined actions, independent of the animal behavior. In this article, we integrate mathematical modeling of social behavior toward the design of realistic feedback laws for robots to interact with a live animal. In particular, we leverage recent advancements in data-driven modeling of zebrafish behavior. Ultimately, we establish a novel robotic platform that allows real-time actuation of a biologically-inspired three-dimensionally printed zebrafish replica to implement model-based control of animal behavior. We demonstrate our approach through a series of experiments, designed to elucidate the appraisal of the replica by live subjects with respect to conspecifics and to quantify the biological value of closed-loop control.
Author Cadolini, Edoardo
De Lellis, Pietro
Porfiri, Maurizio
Yang, Yanpeng
Bernardo, Mario di
Croce, Arrigo
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Keywords Animal-robot
swimming
stochastic differential equations
ethorobotics
collective behavior
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Authors contribution
M.d.B. and M.P. designed the research. E.C. and A.C. developed the robotic platform. Y.Y. conducted experiments and contributed technical improvements. P.D. and M.P. analyzed the data and wrote a first draft of the manuscript. All the authors reviewed and edited the final submission.
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Snippet The possibility of regulating the behavior of live animals using biologically-inspired robots has attracted the interest of biologists and engineers for over...
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SubjectTerms Actuation
Animal behavior
Animal-robot
Animals
Biological system modeling
collective behavior
ethorobotics
Feedback control
Insects
Real-time systems
Robot control
Robots
Sports
stochastic differential equations
swimming
Zebrafish
Title Model-Based Feedback Control of Live Zebrafish Behavior via Interaction With a Robotic Replica
URI https://ieeexplore.ieee.org/document/8880671
https://www.ncbi.nlm.nih.gov/pubmed/33746643
https://www.proquest.com/docview/2352198505
https://www.proquest.com/docview/2503669134
https://pubmed.ncbi.nlm.nih.gov/PMC7970833
Volume 36
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