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Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform

Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to...

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Autores principales: Falotico, Egidio, Vannucci, Lorenzo, Ambrosano, Alessandro, Albanese, Ugo, Ulbrich, Stefan, Vasquez Tieck, Juan Camilo, Hinkel, Georg, Kaiser, Jacques, Peric, Igor, Denninger, Oliver, Cauli, Nino, Kirtay, Murat, Roennau, Arne, Klinker, Gudrun, Von Arnim, Axel, Guyot, Luc, Peppicelli, Daniel, Martínez-Cañada, Pablo, Ros, Eduardo, Maier, Patrick, Weber, Sandro, Huber, Manuel, Plecher, David, Röhrbein, Florian, Deser, Stefan, Roitberg, Alina, van der Smagt, Patrick, Dillman, Rüdiger, Levi, Paul, Laschi, Cecilia, Knoll, Alois C., Gewaltig, Marc-Oliver
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5263131/
https://www.ncbi.nlm.nih.gov/pubmed/28179882
http://dx.doi.org/10.3389/fnbot.2017.00002
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author Falotico, Egidio
Vannucci, Lorenzo
Ambrosano, Alessandro
Albanese, Ugo
Ulbrich, Stefan
Vasquez Tieck, Juan Camilo
Hinkel, Georg
Kaiser, Jacques
Peric, Igor
Denninger, Oliver
Cauli, Nino
Kirtay, Murat
Roennau, Arne
Klinker, Gudrun
Von Arnim, Axel
Guyot, Luc
Peppicelli, Daniel
Martínez-Cañada, Pablo
Ros, Eduardo
Maier, Patrick
Weber, Sandro
Huber, Manuel
Plecher, David
Röhrbein, Florian
Deser, Stefan
Roitberg, Alina
van der Smagt, Patrick
Dillman, Rüdiger
Levi, Paul
Laschi, Cecilia
Knoll, Alois C.
Gewaltig, Marc-Oliver
author_facet Falotico, Egidio
Vannucci, Lorenzo
Ambrosano, Alessandro
Albanese, Ugo
Ulbrich, Stefan
Vasquez Tieck, Juan Camilo
Hinkel, Georg
Kaiser, Jacques
Peric, Igor
Denninger, Oliver
Cauli, Nino
Kirtay, Murat
Roennau, Arne
Klinker, Gudrun
Von Arnim, Axel
Guyot, Luc
Peppicelli, Daniel
Martínez-Cañada, Pablo
Ros, Eduardo
Maier, Patrick
Weber, Sandro
Huber, Manuel
Plecher, David
Röhrbein, Florian
Deser, Stefan
Roitberg, Alina
van der Smagt, Patrick
Dillman, Rüdiger
Levi, Paul
Laschi, Cecilia
Knoll, Alois C.
Gewaltig, Marc-Oliver
author_sort Falotico, Egidio
collection PubMed
description Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP). At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments.
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spelling pubmed-52631312017-02-08 Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform Falotico, Egidio Vannucci, Lorenzo Ambrosano, Alessandro Albanese, Ugo Ulbrich, Stefan Vasquez Tieck, Juan Camilo Hinkel, Georg Kaiser, Jacques Peric, Igor Denninger, Oliver Cauli, Nino Kirtay, Murat Roennau, Arne Klinker, Gudrun Von Arnim, Axel Guyot, Luc Peppicelli, Daniel Martínez-Cañada, Pablo Ros, Eduardo Maier, Patrick Weber, Sandro Huber, Manuel Plecher, David Röhrbein, Florian Deser, Stefan Roitberg, Alina van der Smagt, Patrick Dillman, Rüdiger Levi, Paul Laschi, Cecilia Knoll, Alois C. Gewaltig, Marc-Oliver Front Neurorobot Neuroscience Combined efforts in the fields of neuroscience, computer science, and biology allowed to design biologically realistic models of the brain based on spiking neural networks. For a proper validation of these models, an embodiment in a dynamic and rich sensory environment, where the model is exposed to a realistic sensory-motor task, is needed. Due to the complexity of these brain models that, at the current stage, cannot deal with real-time constraints, it is not possible to embed them into a real-world task. Rather, the embodiment has to be simulated as well. While adequate tools exist to simulate either complex neural networks or robots and their environments, there is so far no tool that allows to easily establish a communication between brain and body models. The Neurorobotics Platform is a new web-based environment that aims to fill this gap by offering scientists and technology developers a software infrastructure allowing them to connect brain models to detailed simulations of robot bodies and environments and to use the resulting neurorobotic systems for in silico experimentation. In order to simplify the workflow and reduce the level of the required programming skills, the platform provides editors for the specification of experimental sequences and conditions, environments, robots, and brain–body connectors. In addition to that, a variety of existing robots and environments are provided. This work presents the architecture of the first release of the Neurorobotics Platform developed in subproject 10 “Neurorobotics” of the Human Brain Project (HBP). At the current state, the Neurorobotics Platform allows researchers to design and run basic experiments in neurorobotics using simulated robots and simulated environments linked to simplified versions of brain models. We illustrate the capabilities of the platform with three example experiments: a Braitenberg task implemented on a mobile robot, a sensory-motor learning task based on a robotic controller, and a visual tracking embedding a retina model on the iCub humanoid robot. These use-cases allow to assess the applicability of the Neurorobotics Platform for robotic tasks as well as in neuroscientific experiments. Frontiers Media S.A. 2017-01-25 /pmc/articles/PMC5263131/ /pubmed/28179882 http://dx.doi.org/10.3389/fnbot.2017.00002 Text en Copyright © 2017 Falotico, Vannucci, Ambrosano, Albanese, Ulbrich, Vasquez Tieck, Hinkel, Kaiser, Peric, Denninger, Cauli, Kirtay, Roennau, Klinker, Von Arnim, Guyot, Peppicelli, Martínez-Cañada, Ros, Maier, Weber, Huber, Plecher, Röhrbein, Deser, Roitberg, van der Smagt, Dillman, Levi, Laschi, Knoll and Gewaltig. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Falotico, Egidio
Vannucci, Lorenzo
Ambrosano, Alessandro
Albanese, Ugo
Ulbrich, Stefan
Vasquez Tieck, Juan Camilo
Hinkel, Georg
Kaiser, Jacques
Peric, Igor
Denninger, Oliver
Cauli, Nino
Kirtay, Murat
Roennau, Arne
Klinker, Gudrun
Von Arnim, Axel
Guyot, Luc
Peppicelli, Daniel
Martínez-Cañada, Pablo
Ros, Eduardo
Maier, Patrick
Weber, Sandro
Huber, Manuel
Plecher, David
Röhrbein, Florian
Deser, Stefan
Roitberg, Alina
van der Smagt, Patrick
Dillman, Rüdiger
Levi, Paul
Laschi, Cecilia
Knoll, Alois C.
Gewaltig, Marc-Oliver
Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform
title Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform
title_full Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform
title_fullStr Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform
title_full_unstemmed Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform
title_short Connecting Artificial Brains to Robots in a Comprehensive Simulation Framework: The Neurorobotics Platform
title_sort connecting artificial brains to robots in a comprehensive simulation framework: the neurorobotics platform
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5263131/
https://www.ncbi.nlm.nih.gov/pubmed/28179882
http://dx.doi.org/10.3389/fnbot.2017.00002
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