The Importance of Big Data in the Advancement of Robotic Capabilities

Autor: Tetiana Konrad, Firas Mahmood Mustafa, Sabah M. Kallow, Noor Ali Thamer, Hanaa Hameed Merzah, Moroj Mohammed, Donya Y. Abdulhussain
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Proceedings of the XXth Conference of Open Innovations Association FRUCT, Vol 36, Iss 1, Pp 423-432 (2024)
Druh dokumentu: article
ISSN: 2305-7254
2343-0737
DOI: 10.23919/FRUCT64283.2024.10749938
Popis: Background: In recent years, Big Data has invaded many technical sectors, enabling extraordinary advances, notably in robotics. Large amounts of data from many areas may improve robotic system functionality and adaptability. Objective: This article examines Big Data's effects on robotic learning, decision-making, and adaptability to help explain how it advances robotic capabilities and provide a thorough review of integrated data-driven robotic systems. Methods: A thorough evaluation and synthesis of the literature was undertaken to examine the integration and implementation of Big Data in robotics. Case studies, and theoretical frameworks on Big Data analytics and robotics were sought from databases and academic publications. Results: Big Data analytics in robots improves learning in predictive analytics and machine learning algorithms, improving decision-making. Industrial robots and autonomous vehicles boost operational efficiency and flexibility by improving data processing, anomaly detection, and real-time decision-making. Conclusion: Technology such as Big Data and robotics makes robots more adaptive and decision-making. Integration improves robotic capabilities and allows for innovative applications across domains, supporting data-driven robotic ability and improvement decisions. The findings propose using Big Data analytics to improve robotics and study future applications, contributing to the conversation on technological convergences and societal implications.
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