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Relevant bibliographies by topics / Robotics and neuroscience

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Academic literature on the topic 'Robotics and neuroscience'

Author: Grafiati

Published: 22 February 2025

Last updated: 31 July 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 (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

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Floreano, Dario, Auke Jan Ijspeert, and Stefan Schaal. "Robotics and Neuroscience." Current Biology 24, no. 18 (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 (2010): 1221–22. http://dx.doi.org/10.1016/j.robot.2010.09.001.

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Nfukwe W, Bamuraza. "Rehabilitation Robotics: Enhancing Patient Recovery." Research Output Journal of Biological and Applied Science 5, no. 2 (2025): 16–20. https://doi.org/10.59298/rojbas/2025/521620.

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Rehabilitation robotics has emerged as a transformative field that integrates engineering, medicine, and artificial intelligence to assist individuals in recovering motor functions after injuries or neurological impairments. This paper investigates the evolution of rehabilitation robotics, key technological advancements, and its clinical applications in stroke recovery, spinal cord injury rehabilitation, and pediatric therapy. The discussion highlights challenges such as cost, accessibility, patient acceptability, and regulatory barriers that hinder widespread adoption. Future directions empha

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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

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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 (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

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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 (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 (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 (2008): 551–52. http://dx.doi.org/10.1016/j.neunet.2008.04.002.

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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 ne

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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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<p> 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 combinat

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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 pur

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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 didactiqu

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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

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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

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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. 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. 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. 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. Taylor & Francis, 2005.

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1964-, Beim Graben P., ed. Lectures in supercomputational neuroscience: Dynamics in complex brain networks. 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. 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. ill., 2001.

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Chinellato, Eris, and Angel P. del Pobil. The Visual Neuroscience of Robotic Grasping. 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. Springer, 2008.

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Richter, Lars. Robotized Transcranial Magnetic Stimulation. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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, et al. "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. 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, 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 moto

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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 th

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Reports on the topic "Robotics and neuroscience"

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Pasupuleti, Murali Krishna. Neural Computation and Learning Theory: Expressivity, Dynamics, and Biologically Inspired AI. National Education Services, 2025. https://doi.org/10.62311/nesx/rriv425.

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Abstract: Neural computation and learning theory provide the foundational principles for understanding how artificial and biological neural networks encode, process, and learn from data. This research explores expressivity, computational dynamics, and biologically inspired AI, focusing on theoretical expressivity limits, infinite-width neural networks, recurrent and spiking neural networks, attractor models, and synaptic plasticity. The study investigates mathematical models of function approximation, kernel methods, dynamical systems, and stability properties to assess the generalization capa

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