Investigating the Application of Neuromorphic Computing for Real-Time Adaptation and Learning in Advanced Robotic and Autonomous Systems

Neuromorphic computing mimics biological neural systems to enable real-time adaptation and learning in robotic and autonomous systems. This study explores the application of neuromorphic architectures in improving decision-making, energy efficiency, and responsiveness. Results demonstrate significant advancements in robotic autonomy and efficiency, showcasing the transformative potential of this technology.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-04
DOI
https://doi.org/10.5281/zenodo.14275174
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
0.00
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article

Investigating the Application of Neuromorphic Computing for Real-Time Adaptation and Learning in Advanced Robotic and Autonomous Systems

Zenodo (CERN European Organization for Nuclear Research)
Advanced Memory and Neural Computing
article

Investigating the Application of Neuromorphic Computing for Real-Time Adaptation and Learning in Advanced Robotic and Autonomous Systems

article en

Abstract

Neuromorphic computing mimics biological neural systems to enable real-time adaptation and learning in robotic and autonomous systems. This study explores the application of neuromorphic architectures in improving decision-making, energy efficiency, and responsiveness. Results demonstrate significant advancements in robotic autonomy and efficiency, showcasing the transformative potential of this technology.

Zenodo (CERN European Organization for Nuclear Research)
King Abdullah University of Science and Technology (SA)
Affordable and clean energy
Openalex Percentile: Top 65%
Advanced Memory and Neural Computing
DOIOpen Access PDFOpenAlex
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Investigating the Application of Neuromorphic Computing for Real-Time Adaptation and Learning in Advanced Robotic and Autonomous Systems · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS