应用操纵机器人控制算法的概念,在工业中执行复杂的技术操作

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摘要

这篇文章专门研究了企业中执行复杂技术操作的操纵机器人的控制算法,以优化工作流程时间。在当今的商业环境中,为了在激烈的竞争环境中最大限度地提高生产管理效率,企业需要利用机器人和人工智能不断改进工作流程自动化方法。本文作者深入探讨了操纵机器人在工业环境中执行复杂操作时所面临的现实挑战。作品讨论了控制操纵机器人的各种方法。这些方法包括自适应控制方法、程序控制方法、传感器控制方法和协作控制方法。在操纵机器人的控制中应用人工智能,可以在分析大量数据、学习经验和适应环境的基础上做出决策。
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CONCEPT OF APPLICATION OF CONTROL ALGORITHMS FOR MANIPULATION ROBOTS TO PERFORM COMPLEX TECHNOLOGICAL OPERATIONS IN INDUSTRY
The article is devoted to the study of control algorithms for manipulation robots to perform complex technological operations at enterprises in order to optimize working process time. In today’s business environment, in order to maximize efficiency of production management in highly competitive environment, enterprises need to constantly improve work process automating methods using robots and artificial intelligence. Authors of this article take an in-depth look at the real-world challenges that manipulation robots face in performing complex operations in industrial environment. The work discusses various approaches to control manipulation robots. These approaches include adaptive control method, program control method, sensor control method and collaborative control method. Application of artificial intelligence in the control of manipulation robots allows making decisions based on analyzing of large data amounts, learning from experience and adapting to the environment.
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CONCEPT OF APPLICATION OF CONTROL ALGORITHMS FOR MANIPULATION ROBOTS TO PERFORM COMPLEX TECHNOLOGICAL OPERATIONS IN INDUSTRY OPTIMIZATION OF MODE PROPAGATION FOR AN EMBEDIER OF OPTICALVORTEX BEAMS BASED ON A MICRO-RING RESONATOR RECOMMENDATIONS ON THE URBAN NETWORK FOTL STRUCTURE WITH THE LOWEST POSSIBLE LEVEL OF DISTORTION OF INFORMATION AND CONTROL ILCF-SIGNALS STRUCTURE FEATURES OF MINIMUM FREQUENCY SHIFT KEYING SIGNAL MODEMS TRAFFIC ANOMALY DETECTION IN VEHICLE BUS BY RECURRENT LSTM NEURAL NETWORK
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