Design and evaluation of an autonomous robotic arm controlled by artificial vision for industrial environments
Keywords:
Autonomous Robotic Arm, Artificial Vision, Artificial Intelligence, Industrial Automation, Literature ReviewAbstract
This article provides a comprehensive literature review on the design, development, and evaluation of autonomous robotic arms controlled by machine vision systems, with a focus on their application in industrial settings. Through the analysis of recent studies, the article explores technological advances in artificial intelligence algorithms, machine learning, and image processing, which have significantly improved the accuracy, adaptability, and autonomy of these robotic devices. Different control architectures, calibration techniques, and visual recognition strategies that enable robotic arms to interpret their environment and make decisions in real time are examined. In addition, the article identifies and analyzes key technical challenges, such as the variability of environmental conditions, the need for robustness against external interference, and the optimization of data processing to avoid operational latencies. It also addresses economic barriers that limit their widespread adoption, including high implementation, maintenance, and personnel training costs. Despite these challenges, the results demonstrate the great potential of this technology to revolutionize industrial automation processes by increasing production efficiency, reducing human errors, and improving the safety of high-risk tasks. Finally, the article highlights the need to continue promoting applied and interdisciplinary research, as well as the development of scalable and accessible solutions that enable the effective integration of autonomous robotic arms with artificial vision in different industries, thus contributing to the digital transformation and competitiveness of the manufacturing sector
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Copyright (c) 2023 Kevin Joel Martínez Andino, Christian Andrés Martínez andino (Autor/a)
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