Relevant bibliographies by topics / Robotics and neuroscience

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Robotics and neuroscience'

Author: Grafiati
Published: 22 February 2025

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Journal articles on the topic "Robotics and neuroscience"

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Laxane, Rahul. "Neuro-Robotics: Bridging Neuroscience and Robotics." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (April 5, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem30166.

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The field of neurorobotics represents the combination of neuroscience and robotics, aiming to elucidate neural functional principles and use them to create intelligent robots. This article considers the symbiotic relationship between the two fields and explores how insights from neuroscience can inform the design and control of robots; Robotic platforms offer a unique opportunity to learn and validate insights from neuroscience. For example, this article focuses on the core concepts of neuroscience and robotics and highlights key advances that support the integration of these fields, including brain-computer interfaces, neurorobotic simulations, and bionic design. It examines how discoveries in neuroscience, such as the understanding of sensorimotor control, learning processes, and cognitive processes, are supporting the creation of biomimetic robots that can address behavioural challenges and interact with their environments.
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Floreano, Dario, Auke Jan Ijspeert, and Stefan Schaal. "Robotics and Neuroscience." Current Biology 24, no. 18 (September 2014): R910—R920. http://dx.doi.org/10.1016/j.cub.2014.07.058.

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Ferrández, J. M., F. de la Paz, and J. de Lope. "Intelligent robotics and neuroscience." Robotics and Autonomous Systems 58, no. 12 (December 2010): 1221–22. http://dx.doi.org/10.1016/j.robot.2010.09.001.

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Pham, Martin Do, Amedeo D’Angiulli, Maryam Mehri Dehnavi, and Robin Chhabra. "From Brain Models to Robotic Embodied Cognition: How Does Biological Plausibility Inform Neuromorphic Systems?" Brain Sciences 13, no. 9 (September 13, 2023): 1316. http://dx.doi.org/10.3390/brainsci13091316.

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We examine the challenging “marriage” between computational efficiency and biological plausibility—A crucial node in the domain of spiking neural networks at the intersection of neuroscience, artificial intelligence, and robotics. Through a transdisciplinary review, we retrace the historical and most recent constraining influences that these parallel fields have exerted on descriptive analysis of the brain, construction of predictive brain models, and ultimately, the embodiment of neural networks in an enacted robotic agent. We study models of Spiking Neural Networks (SNN) as the central means enabling autonomous and intelligent behaviors in biological systems. We then provide a critical comparison of the available hardware and software to emulate SNNs for investigating biological entities and their application on artificial systems. Neuromorphics is identified as a promising tool to embody SNNs in real physical systems and different neuromorphic chips are compared. The concepts required for describing SNNs are dissected and contextualized in the new no man’s land between cognitive neuroscience and artificial intelligence. Although there are recent reviews on the application of neuromorphic computing in various modules of the guidance, navigation, and control of robotic systems, the focus of this paper is more on closing the cognition loop in SNN-embodied robotics. We argue that biologically viable spiking neuronal models used for electroencephalogram signals are excellent candidates for furthering our knowledge of the explainability of SNNs. We complete our survey by reviewing different robotic modules that can benefit from neuromorphic hardware, e.g., perception (with a focus on vision), localization, and cognition. We conclude that the tradeoff between symbolic computational power and biological plausibility of hardware can be best addressed by neuromorphics, whose presence in neurorobotics provides an accountable empirical testbench for investigating synthetic and natural embodied cognition. We argue this is where both theoretical and empirical future work should converge in multidisciplinary efforts involving neuroscience, artificial intelligence, and robotics.
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Chawla, Suhani. "ADVANCEMENT OF ROBOTICS IN HEALTHCARE." International Journal of Social Science and Economic Research 07, no. 12 (2022): 3936–52. http://dx.doi.org/10.46609/ijsser.2022.v07i12.006.

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If robots are not common everyday objects, it is maybe because we have looked robotic applications without considering sufficient attention what could be the experience of interacting with a robot. This article introduces the idea of a value profile, a notion intended to capture the general evolution of our experience with different kinds of objects. In the past two decades, robotics has evolved immensely with increased prospects in biological, healthcare, medicine and surgery industry. Robots are being used in almost everything and almost everywhere. However, they are not to replace qualified human workforce, instead, assist them in routine work and precision tasks to achieve high throughput. Advancements in micro- and nano-robotic devices is very much dependent on innovations in micro-electro-mechanical systems (MEMS) and nanoelectromechanical systems (NEMS) with collaborations among diverse domains of research viz., life science, medicine/surgery and engineering. This paper highlights the advancement of Robotics in Neuroscience, Medical Science and IOT in the context of Robotics
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Brock, Oliver, and Francisco Valero-Cuevas. "Transferring synergies from neuroscience to robotics." Physics of Life Reviews 17 (July 2016): 27–32. http://dx.doi.org/10.1016/j.plrev.2016.05.011.

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Chaminade, Thierry, and Gordon Cheng. "Social cognitive neuroscience and humanoid robotics." Journal of Physiology-Paris 103, no. 3-5 (May 2009): 286–95. http://dx.doi.org/10.1016/j.jphysparis.2009.08.011.

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Ronsse, Renaud, Philippe Lefèvre, and Rodolphe Sepulchre. "Robotics and neuroscience: A rhythmic interaction." Neural Networks 21, no. 4 (May 2008): 577–83. http://dx.doi.org/10.1016/j.neunet.2008.03.005.

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Schaal, Stefan, Yoshihiko Nakamura, and Paolo Dario. "Special issue on robotics and neuroscience." Neural Networks 21, no. 4 (May 2008): 551–52. http://dx.doi.org/10.1016/j.neunet.2008.04.002.

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Da Costa, Lancelot, Pablo Lanillos, Noor Sajid, Karl Friston, and Shujhat Khan. "How Active Inference Could Help Revolutionise Robotics." Entropy 24, no. 3 (March 2, 2022): 361. http://dx.doi.org/10.3390/e24030361.

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Recent advances in neuroscience have characterised brain function using mathematical formalisms and first principles that may be usefully applied elsewhere. In this paper, we explain how active inference—a well-known description of sentient behaviour from neuroscience—can be exploited in robotics. In short, active inference leverages the processes thought to underwrite human behaviour to build effective autonomous systems. These systems show state-of-the-art performance in several robotics settings; we highlight these and explain how this framework may be used to advance robotics.
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Dissertations / Theses on the topic "Robotics and neuroscience"

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Kazer, J. F. "The hippocampus in memory and anxiety : an exploration within computational neuroscience and robotics." Thesis, University of Sheffield, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.339963.

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Hunt, Alexander Jacob. "Neurologically Based Control for Quadruped Walking." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1445947104.

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Szczecinski, Nicholas S. "MASSIVELY DISTRIBUTED NEUROMORPHIC CONTROL FOR LEGGED ROBOTS MODELED AFTER INSECT STEPPING." Case Western Reserve University School of Graduate Studies / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=case1354648661.

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Kodandaramaiah, Suhasa Bangalore. "Robotics for in vivo whole cell patch clamping." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/51932.

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Whole-cell patch clamp electrophysiology of neurons in vivo enables the recording of electrical events in cells with great precision, and supports a wide diversity of morphological and molecular analysis experiments important for the understanding of single-cell and network functions in the intact brain. However, high levels of skill are required in order to perform in vivo patching, and the process is time-consuming and painstaking. Robotic systems for in vivo patching would not only empower a great number of neuroscientists to perform such experiments, but would also open up fundamentally new kinds of experiment enabled by the resultant high throughput and scalability. We discovered that in vivo blind whole cell patch clamp electrophysiology could be implemented as a straightforward algorithm and developed an automated robotic system that was capable of performing this algorithm. We validated the performance of the robot in both the cortex and hippocampus of anesthetized mice. The robot achieves yields, cell recording qualities, and operational speeds that are comparable to, or exceed, those of experienced human investigators. Building upon this framework, we developed a multichannel version of “autopatcher” robot capable establishing whole cell patch clamp recordings from pairs and triplets of neurons in the cortex simultaneously. These algorithms can be generalized to control arbitrarily large number of electrodes and the high yield, throughput and automation of complex set of tasks results in a practical solution for conducting patch clamp recordings in potentially dozens of interconnected neurons in vivo.
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Blitch, John G. "Engagement and not workload is implicated in automation-induced learning deficiencies for unmanned aerial system trainees." Thesis, Colorado State University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=3624259.

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Automation has been known to provide both costs and benefits to experienced humans engaged in a wide variety of operational endeavors. Its influence on skill acquisition for novice trainees, however, is poorly understood. Some previous research has identified impoverished learning as a potential cost of employing automation in training. One prospective mechanism for any such deficits can be identified from related literature that highlights automation's role in reducing cognitive workload in the form of perceived task difficulty and mental effort. However three experiments using a combination of subjective self-report and EEG based neurophysiological instruments to measure mental workload failed to find any evidence that link the presence of automation to workload or to performance deficits resulting from its previous use. Rather the results in this study implicate engagement as an underlying basis for the inadequate mental models associated with automation-induced training deficits. The conclusion from examining these various states of cognition is that automation-induced training deficits observed in novice unmanned systems operators are primarily associated with distraction and disengagement effects, not an undesirable reduction in difficulty as previous research might suggest. These findings are consistent with automation's potential to push humans too far "out of the loop" in training. The implications of these findings are discussed.

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Pike, Frankie. "Low Cost NueroChairs." DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/887.

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Electroencephalography (EEG) was formerly confined to clinical and research settings with the necessary hardware costing thousands of dollars. In the last five years a number of companies have produced simple electroencephalograms, priced below $300 and available direct to consumers. These have stirred the imaginations of enthusiasts and brought the prospects of "thought-controlled" devices ever closer to reality. While these new devices were largely targeted at video games and toys, active research on enabling people suffering from debilitating diseases to control wheelchairs was being pursued. A number of neurochairs have come to fruition offering a truly hands-free mobility solution, but whether these results could be replicated with emerging low cost products, and thus become a viable option for more people is an open question. This thesis examines existing research in the field of EEG-based assistive technologies, puts current consumer-grade hardware to the test, and explores the possibility of a system designed from the ground up to be only a fraction of the cost of currently completed research prototypes.
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Horchler, Andrew de Salle. "Design of Stochastic Neural-inspired Dynamical Architectures: Coordination and Control of Hyper-redundant Robots." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1459442036.

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Moualla, Aliaa. "Un robot au Musée : Apprentissage cognitif et conduite esthétique." Thesis, CY Cergy Paris Université, 2020. http://www.theses.fr/2020CYUN1002.

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Un robot au Musée: Apprentissage cognitif et conduite esthétique.Dans ma thèse je traite le sujet d'un apprentissage autonome basé sur la référenciation sociale dans un environnement réel, "le musée". Je m'intéresse à l’ajout et l'analyse de mécanismes nécessaires pour qu'un robot puisse poursuivre un tel type d'apprentissage. Je m'intéresse également à l'impact d'un apprentissage spécifique et individuel à chaque robot sur l'ensemble d'un groupe de robots confronté à une situation connue ou au contraire nouvelle, plus précisément :Dans le premier chapitre, nous aborderons de manière didactique les outils nécessaires à la compréhension des modèles et des méthodes que nous utiliserons tout au long de nos travaux. Nous aborderons les bases du formalisme neuronal, de l’apprentissage par conditionnement, de la catégorisation, et des champs de neurones dynamiques.Dans le deuxième chapitre, nous présenterons brièvement le système visuel biologique puis nous passerons en revue un état de l’art des différents modèles traitant la perception visuelle et la reconnaissance d'objet. Dans le cadre d’une approche bio-inspirée, nous présenterons ensuite le modèle du système visuel du robot "Berenson", l’architecture sensori-motrice permettant d’associer une valeur émotionnelle à un objet observé. Puis nous étudions les performances du système visuel avec et sans mécanisme de compétition spatiale.Dans le troisième chapitre nous passerons au niveau des interactions Homme-Machine, nous montrerons que l’intérêt des visiteurs porté au robot ne dépend pas que de sa forme, mais de son comportement et plus précisément de sa capacité à interagir aussi sur un registre émotionnel (ici des expressions faciales). Nous analysons tout d'abord l'impact du système visuel sur le contrôle bas niveau des actions du robot. Nous montrons que le bas niveau de la compétition spatiale entre les valeurs associées aux zones d’intérêt de l’image est important pour la reconnaissance d'objets et affecte donc la cohérence du comportement du robot et donc par la suite la lisibilité de ce comportement. Nous introduisons ensuite des modifications sur le contrôle des mouvements des yeux, de la tête et du corps en s'inspirant de processus biologiques (changement du cadre de référence). À la fin, nous analysons les tests effectués dans le musée afin d’évaluer la lisibilité du comportement du robot (ses mouvements et ses expressions faciales).Dans le quatrième chapitre nos travaux se poursuivent par l’ajout de mécanismes neuronaux élémentaires bio inspirés permettant l’émergence de capacité d’attention conjointe importante pour obtenir des interactions plus " naturelles " avec les visiteurs du musée mais aussi pour discuter d’un point de vue théorique l’émergence de la notion d’agentivité. Berenson représente donc aujourd’hui une forme d’expérimentation unique dans les sciences sociales comme en robotique du développement.Dans le cinquième chapitre, nous intéresserons à l’évaluation de l’effet de l’émergence de préférences esthétiques sur toute une population de robots (en simulation). Nous soutenons que la variabilité de l'apprentissage offerte par des environnements spéciaux tels qu'un musée conduit à l'individuation des robots. Nous nous interrogeons également sur l’intérêt d’enseigner des systèmes artificiels utilisant une seule grande base de données dans le but d’améliorer leurs performances. Éviter une réponse uniforme à une situation inconnue dans une population d'individus augmente ses chances de réussite
In my thesis I treat the subject of autonomous learning based on social referencing in a real environment, "the museum". I am interested in adding and analyzing the mechanisms necessary for a robot to pursue such a type of learning. I am also interested in the impact of a specific and individual learning to each robot on the whole of a group of robots confronted with a known situation or on the contrary new, more precisely:In the first chapter, we will discuss in a didactic way the tools needed to understand the models and methods that we will use throughout our work. We will discuss the basics of neural formalism, conditioning learning, categorization, and dynamic neural fields.In the second chapter, we will briefly present the biological visual system then we will review a state of the art of different models dealing with visual perception and object recognition. As part of a bio-inspired approach, we will then present the model of the visual system of the "Berenson" robot, the sensorimotor architecture allowing to associate an emotional value with an observed object. Then we study the performances of the visual system with and without space competition mechanism.In the third chapter we will move to the level of human-machine interactions, we will show that the interest of visitors to the robot does not only depend on its shape, but on its behavior and more specifically its ability to interact on an emotional level. (here facial expressions). We first analyze the impact of the visual system on the low level control of robot actions. We show that the low level of the spatial competition between the values ​​associated with the zones of interest of the image is important for the recognition of objects and thus affects the coherence of the behavior of the robot and therefore the legibility of this behavior. . We then introduce modifications on the control of eye, head and body movements inspired by biological processes (change of the frame of reference). In the end, we analyze the tests performed in the museum to assess the readability of the behavior of the robot (its movements and facial expressions).In the fourth chapter, our work continues with the addition of inspired bio-based neural mechanisms that allow the emergence of important joint attention capacity to achieve more "natural" interactions with visitors to the museum but also to discuss a point from a theoretical point of view the emergence of the notion of agency. Berenson represents today a form of experimentation unique in the social sciences as in development robotics.In the fifth chapter, we will focus on evaluating the effect of the emergence of aesthetic preferences on a whole population of robots (in simulation). We argue that the variability of learning offered by special environments such as a museum leads to the individuation of robots. We also question the interest of teaching artificial systems using a single large database in order to improve their performance. Avoiding a uniform response to an unknown situation in a population of individuals increases its chances of success
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Chinellato, Eris. "Visual neuroscience of robotic grasping." Doctoral thesis, Universitat Jaume I, 2008. http://hdl.handle.net/10803/669156.

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En esta tesis se define e implementa un modelo funcional de las áreas del cerebro involucradas en las acciones de agarre basadas en visión que incluye todos los pasos requeridos para la ejecución de un agarre satisfactorio. El modelo es fiel a la realidad biológica, pero también apropiado para su implementación en un entorno robótico real. Por tanto, siguiendo este modelo, se ha desarrollado un sistema completo de agarre robótico capaz de estimar la forma, tamaño y posición de un objeto desconocido usando datos visuales, planificar y ejecutar una acción de agarre integrando tales datos con la información proprioceptiva del estado del brazo y de la mano. Los resultados experimentales confirman que la nueva línea de investigación propuesta por esta tesis es significativa y prometedora para el agarre robótico. Además, tanto el modelado computacional como los experimentos robóticos ayudan a validar teorías sobre los mecanismos empleados por las áreas del cerebro involucradas en las acciones de agarre. Esta tesis ofrece nuevas ideas e hipótesis de investigación relacionadas con dichos mecanismos, y ayuda a establecer un marco de trabajo común para neurocientíficos y robóticos en el estudio de los mecanismos cerebrales.
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L'haridon, Louis. "La douleur et le plaisir dans la boucle motivation-émotion-cognition : les robots en tant qu'outils et que modèles." Electronic Thesis or Diss., CY Cergy Paris Université, 2024. http://www.theses.fr/2024CYUN1342.

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Dans cette thèse, j'explore l'intégration de la douleur, sa perception, ses caractéristiques et son processus sensoriel dans des modèles robotiques, particulièrement dans des architectures motivationelles de sélection de l'action. En m'inspirant de la psychologie clinique, de la neurobiologie et des neurosciences computationelles, je souhaite fournir un cadre avec différentes perspectives pour étudier comment des mécanismes bio-inspirés de douleur peuvent affecter la sélection de l'action.La douleur joue un rôle crucial dans les systèmes biologiques, influençant les comportements essentiels à la survie et au maintien de l'homéostasie, mais elle est souvent négligée dans les modèles émotionnels. Chez l'Homme et les autres animaux, la douleur sert de réponse adaptative aux stimuli nocifs, déclenchant des actions qui protègent contre les dommages et favorisent la guérison. L'objectif de cette thèse est d'améliorer la sélection de l'action en incorporant la douleur et ses caractéristiques associées dans des robots, en élargissant la compréhension actuelle des agents artificiels et en explorant comment les robots peuvent utiliser la douleur pour moduler le comportement, s'adapter aux menaces et optimiser la survie.En adoptant le paradigme de l'intelligence artificielle incarnée et en s'appuyant sur des travaux antérieurs sur des modèles de sélection de l'action basés sur la motivation, cette thèse propose d'étudier différentes perspectives autour de la douleur et de son impact sur la sélection de l'action.Dans la première partie de ce travail, je propose une architecture améliorée de sélection de l'action basée sur la motivation en introduisant un modèle incarné qui permet aux robots de percevoir et de répondre à des stimuli nocifs. En utilisant des nocicepteurs artificiels, je simule la sensation de dommage chez les agents robotiques et calcule leur état émotionnel de douleur en tant qu'hormone artificielle. Ce modèle étudie comment différents niveaux de perception de la douleur influencent les réponses comportementales, avec des résultats soulignant la valeur adaptative de la douleur dans la modulation de la sélection de l'action, en particulier dans des environnements extrêmes ou dangereux.Ensuite, je présente un mécanisme de neuromodulation hormonale artificielle, mettant en œuvre une hormone cortisol simulée qui module le processus de sélection d'action. Ce mécanisme de cortisol simulée intègre une dynamique temporelle, ce qui entraîne des processus d'accoutumance et de sensibilisation. Je démontre comment la neuromodulation hormonale peut conduire à des comportements émergents qui améliorent la réponse globale des agents robotiques à la variabilité environnementale dans des scénarios extrêmes.De plus, je propose un nouveau cadre pour la détection tactile dans les plateformes robotiques mobiles. Ce modèle calcule un processus nociceptif et méchanoceptif capable de localiser et de classer les stimuli tactiles et nocifs. En collaboration avec Raphaël Bergoin, nous envoyons ce signal sensoriel à un réseau neuronal à spikes, démontrant la ségrégation des zones corticales pour les signaux nociceptifs et méchanoceptifs et l'apprentissage de représentations sensorielles incarnées.Enfin, je présente une architecture intégrée de sélection de l'action qui combine ces nouveaux processus sensoriels mécanoceptifs et nociceptifs, les réponses comportementales, la neuromodulation hormonale et l'apprentissage de représentations incarnées. Cette architecture est examinée dans un contexte social avec différents niveaux d'interaction avec des prédateurs. Je souligne l'importance de l'interaction sociale et des expériences au début de la vie dans l'apprentissage des représentations sensorielles incarnées et je démontre comment ce modèle basé sur le cortex améliore la gestion hormonale et la sélection de l'action dans des environnements dynamiques
In this thesis, I explore the integration of pain, its perception, its features, and its sensory process into robotic models, focusing on its influence on motivation-based action selection architecture. Drawing inspiration from clinician psychology, neurobiology, and computation neuroscience, I aim to provide a framework with different perspectives to study how bio-inspired pain mechanisms can affect decision-making systems.Pain plays a crucial role in biological systems, influencing behaviors essential to survival and maintaining homeostasis, yet it is often neglected in emotional models. In humans and other animals, pain serves as an adaptive response to noxious stimuli, triggering protective actions that prevent harm and promote recovery. This thesis seeks to improve action selection by incorporating pain and its related features into robots, extending the current understanding of artificial agents and exploring how robots can use pain to modulate behavior, adapt to threats, and optimize survival.Embracing the embodied Artificial Intelligence paradigm and building upon prior work on motivation-based action selection models, this thesis proposes to study different perspectives on pain and its impact on action selection.First, I provide an overview of related work and the state of the art in relevant disciplines.In the initial part of this work, I propose an enhanced motivation-based action selection architecture by introducing an embodied model that enables robots to perceive and respond to noxious stimuli. Using artificial nociceptors, I simulate the sensation of damage in robotic agents and compute the emotional state of pain as an artificial hormone. This model investigates how varying levels of pain perception influence behavioral responses, with results emphasizing the adaptive value of pain modulation in action selection, particularly in extreme or hazardous environments.Next, I introduce an artificial hormonal neuromodulation mechanism featuring a simulated cortisol hormone that modulates the action selection process. This cortisol mechanism incorporates temporal dynamics, resulting in habituation and sensitization processes. I demonstrate how hormonal neuromodulation can lead to emergent behaviors that improve the overall response of robotic agents to environmental variability in extreme scenarios.Additionally, I propose a novel framework for tactile sensing in mobile robotic platforms. This framework computes a nociceptive and mechanoceptive process capable of localizing and classifying noxious and tactile stimuli. In collaboration with Raphaël Bergoin, we send this sensory signal to a spiking neural network, demonstrating the segregation of cortical areas for nociceptive and mechanoceptive signals and learning embodied sensory representations.Finally, I present an integrated action selection architecture that combines these new mechanoceptive and nociceptive sensory processes, behavioral responses, hormonal neuromodulation, and the learning of embodied representations. This architecture is examined in a social context with varying levels of interaction with predators. I highlight the importance of social interaction in learning embodied sensory representations and demonstrate how this cortex-based model improves hormonal management and action selection in dynamic environments.In conclusion, I discuss the results of this research and offer perspectives for future work
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Books on the topic "Robotics and neuroscience"

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Kasaki, Masashi, Hiroshi Ishiguro, Minoru Asada, Mariko Osaka, and Takashi Fujikado, eds. Cognitive Neuroscience Robotics A. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8.

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Kasaki, Masashi, Hiroshi Ishiguro, Minoru Asada, Mariko Osaka, and Takashi Fujikado, eds. Cognitive Neuroscience Robotics B. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54598-9.

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Giannopulu, Irini. Neuroscience, Robotics and Virtual Reality: Internalised vs Externalised Mind/Brain. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-95558-2.

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N, Reeke George, ed. Modeling in the neurosciences: From biological systems to neuromimetic robotics. 2nd ed. Boca Raton, Fla: Taylor & Francis, 2005.

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1964-, Beim Graben P., ed. Lectures in supercomputational neuroscience: Dynamics in complex brain networks. Berlin: Springer, 2008.

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Lee, Gary. Advances in Intelligent Systems: Selected papers from 2012 International Conference on Control Systems (ICCS 2012), March 1-2, Hong Kong. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

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1947-, Kitamura Tadashi, ed. What should be computed to understand and model brain function?: From robotics, soft computing, biology and neuroscience to cognitive philosophy. xii, 309 p: ill., 2001.

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Chinellato, Eris, and Angel P. del Pobil. The Visual Neuroscience of Robotic Grasping. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-20303-4.

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Haken, H. Brain dynamics. 2nd ed. New York: Springer, 2008.

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Richter, Lars. Robotized Transcranial Magnetic Stimulation. New York, NY: Springer New York, 2013.

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Book chapters on the topic "Robotics and neuroscience"

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Arai, Tatsuo, and Hiroko Kamide. "Robotics for Safety and Security." In Cognitive Neuroscience Robotics A, 173–92. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_8.

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Hosoda, Koh. "Compliant Body as a Source of Intelligence." In Cognitive Neuroscience Robotics A, 1–23. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_1.

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Hirai, Hiroaki, Hang Pham, Yohei Ariga, Kanna Uno, and Fumio Miyazaki. "Motor Control Based on the Muscle Synergy Hypothesis." In Cognitive Neuroscience Robotics A, 25–50. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_2.

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Nagai, Yukie. "Mechanism for Cognitive Development." In Cognitive Neuroscience Robotics A, 51–72. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_3.

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Asada, Minoru. "Mirror Neuron System and Social Cognitive Development." In Cognitive Neuroscience Robotics A, 73–93. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_4.

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Yoshikawa, Yuichiro. "Attention and Preference of Humans and Robots." In Cognitive Neuroscience Robotics A, 95–119. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_5.

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Kanda, Takayuki, and Takahiro Miyashita. "Communication for Social Robots." In Cognitive Neuroscience Robotics A, 121–51. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_6.

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Nakanishi, Hideyuki. "System Evaluation and User Interfaces." In Cognitive Neuroscience Robotics A, 153–71. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_7.

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Ishiguro, Hiroshi. "Android Science." In Cognitive Neuroscience Robotics A, 193–234. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54595-8_9.

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Shinohara, Kazumitsu. "Perceptual and Cognitive Processes in Human Behavior." In Cognitive Neuroscience Robotics B, 1–22. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-54598-9_1.

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Conference papers on the topic "Robotics and neuroscience"

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Duenas, J., D. Chapuis, C. Pfeiffer, R. Martuzzi, S. Ionta, O. Blanke, and R. Gassert. "Neuroscience robotics to investigate multisensory integration and bodily awareness." In 2011 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2011. http://dx.doi.org/10.1109/iembs.2011.6092059.

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Norman-Tenazas, Raphael, Jordan Matelsky, Kapil Katyal, Erik Johnson, and William Gray-Roncal. "Worminator: A platform to enable bio-inspired (C. elegans) robotics." In 2018 Conference on Cognitive Computational Neuroscience. Brentwood, Tennessee, USA: Cognitive Computational Neuroscience, 2018. http://dx.doi.org/10.32470/ccn.2018.1149-0.

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Gordon Cheng, Sang-Ho Hyon, Ales Ude, Jun Morimoto, Joshua G. Hale, Joseph Hart, Jun Nakanishi, et al. "CB: Exploring neuroscience with a humanoid research platform." In 2008 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2008. http://dx.doi.org/10.1109/robot.2008.4543459.

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Romero, J. A., L. A. Diago, J. Shinoda, and I. Hagiwara. "Evaluation of Brain Models to Control a Robotic Origami Arm Using Holographic Neural Networks." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-48074.

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In robotics, one of the most difficult task is to perform a precisely and fast movement of a robotic arm. For paper-folding robots, it is still extremely difficult to execute the required manipulations of the paper mainly because the difficulties in modeling and control of the paper. In this paper two control models are proposed to solve this problem. One of the best approaches comes from Neuroscience, where using a human’s brain inspired control system known as Cerebellar control model (CCM), precisely and fast movements of a robotic arm can be performed. In the CCM a Feedback controller motor command is used as a target signal to train an Artificial Neural Network (NN), and use the output of the NN as a Feed-forward signal. In this paper two training methods were evaluated in order to improve the behavior in CCM: the traditional Back propagation and a Holographic method.
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Renno-Costa, Cesar, Andre L. Luvizotto, Encarni Marcos, Armin Duff, Marti Sanchez-Fibla, and Paul F. M. J. Verschure. "Integrating neuroscience-based models towards an autonomous biomimetic Synthetic Forager." In 2011 IEEE International Conference on Robotics and Biomimetics (ROBIO). IEEE, 2011. http://dx.doi.org/10.1109/robio.2011.6181287.

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Broucke, Mireille. "On the Use of Regulator Theory in Neuroscience with Implications for Robotics." In 18th International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010639100110023.

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Broucke, Mireille. "On the Use of Regulator Theory in Neuroscience with Implications for Robotics." In 18th International Conference on Informatics in Control, Automation and Robotics. SCITEPRESS - Science and Technology Publications, 2021. http://dx.doi.org/10.5220/0010639100002994.

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Tuan, Tran Minh, Philippe Soueres, Michel Taix, and Benoit Girard. "Eye-centered vs body-centered reaching control: A robotics insight into the neuroscience debate." In 2009 IEEE International Conference on Robotics and Biomimetics (ROBIO 2009). IEEE, 2009. http://dx.doi.org/10.1109/robio.2009.5420609.

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Billard, Aude. "Building adaptive connectionist-based controllers: review of experiments in human-robot interaction, collective robotics, and computational neuroscience." In Intelligent Systems and Smart Manufacturing, edited by Gerard T. McKee and Paul S. Schenker. SPIE, 2000. http://dx.doi.org/10.1117/12.403750.

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Dragusanu, Mihai, Zubair Iqbal, Domenico Prattichizzo, and Monica Malvezzi. "Design of a Modular Hand Exoskeleton for Rehabilitation and Training." In ASME 2021 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2021. http://dx.doi.org/10.1115/imece2021-70343.

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Abstract Nowadays, the rehabilitation process can significantly increase the efficacy exploiting the potentialities of robot-mediated therapies. Robot rehabilitation is an emerging and promising topic that incorporates robotics with neuroscience and rehabilitation to define new methods for supporting patients with neurological diseases. In this paper we present the design of an innovative exoskeleton for hand finger flexion/extension motion rehabilitation and training. It is designed to be modular, wearable, and easy to control and manage. It can be used by the patient in collaboration with the therapist or autonomously. The paper introduces the main steps of device design and development and presents and compare three different solutions.
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