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Cognitive neuroscience and robotics: Advancements and future research directions
KTH, School of Industrial Engineering and Management (ITM), Production engineering. ABB Corporate Research, Västerås, Sweden.ORCID iD: 0000-0002-1909-0507
KTH, School of Industrial Engineering and Management (ITM), Production engineering.ORCID iD: 0000-0001-8679-8049
Department of Mechanical and Aerospace Engineering, Case Western Reserve University, Cleveland, OH, USA.
Number of Authors: 32024 (English)In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 85, article id 102610Article, review/survey (Refereed) Published
Abstract [en]

In recent years, brain-based technologies that capitalise on human abilities to facilitate human–system/robot interactions have been actively explored, especially in brain robotics. Brain–computer interfaces, as applications of this conception, have set a path to convert neural activities recorded by sensors from the human scalp via electroencephalography into valid commands for robot control and task execution. Thanks to the advancement of sensor technologies, non-invasive and invasive sensor headsets have been designed and developed to achieve stable recording of brainwave signals. However, robust and accurate extraction and interpretation of brain signals in brain robotics are critical to reliable task-oriented and opportunistic applications such as brainwave-controlled robotic interactions. In response to this need, pervasive technologies and advanced analytical approaches to translating and merging critical brain functions, behaviours, tasks, and environmental information have been a focus in brain-controlled robotic applications. These methods are composed of signal processing, feature extraction, representation of neural activities, command conversion and robot control. Artificial intelligence algorithms, especially deep learning, are used for the classification, recognition, and identification of patterns and intent underlying brainwaves as a form of electroencephalography. Within the context, this paper provides a comprehensive review of the past and the current status at the intersection of robotics, neuroscience, and artificial intelligence and highlights future research directions.

Place, publisher, year, edition, pages
Elsevier BV , 2024. Vol. 85, article id 102610
Keywords [en]
Brain robotics, Brainwave/electroencephalography, Brain–computer interface, Deep learning, Robot control, Signal processing
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:kth:diva-333952DOI: 10.1016/j.rcim.2023.102610ISI: 001049545100001Scopus ID: 2-s2.0-85165534271OAI: oai:DiVA.org:kth-333952DiVA, id: diva2:1789148
Note

QC 20230818

Available from: 2023-08-18 Created: 2023-08-18 Last updated: 2023-09-01Bibliographically approved

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Liu, SichaoWang, Lihui

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