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Understanding the brain is perhaps one of the greatest challenges facing twenty-first century science. While a traditional computer excels in precision and unbiased logic, its abilities to interact socially lags behind those of biological neural systems. Recent technologies, such as neuromorphic engineering, cloud infrastructure, and big data analytics, have emerged that can narrow the gap between traditional robots and human intelligence. Neuromorphic robotics mimicking brain functions can contribute in developing intelligent machines capable of learning and making autonomous decisions. Cloud-based robotics take advantage of remote resources for parallel computation and sharing large amounts of information while benefiting from analysis of massive sensor data from robots. In this paper, we survey recent advances in neuromorphic computing, cloud-based robotics, and big data analytics and list the most important challenges faced by robot architects. We also propose a novel dual system architecture for robots where they have a brain centered cloud with access to big data analytics.


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Accepted manuscript of Satyanarayana, A., Kusyk, J., & Chen, Y. W. (2018, May). Design of Cloud Based Robots Using Big Data Analytics and Neuromorphic Computing. In 2018 IEEE Canadian Conference on Electrical & Computer Engineering (CCECE) (pp. 1-4). IEEE. DOI: 10.1109/CCECE.2018.8447874



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