Перегляд за автором "Yevsieiv, V."

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  • Зображення мініатюри
    Публікація
    A Model of Using Computer Vision to Monitor the Environment of a Collaborative Manipulator Robot
    (2024) Yevsieiv, V.; Demska, N.
    The paper considers a model of using computer vision to monitor the environment of a collaborative manipulator robot in the context of Industry5.0. The sequence of stages of image processing is described, including detection, tracking and classification of objects, which allows the robot to respond adaptively to changes in the environment and ensure safe interaction with a person. The model contributes to increasing the flexibility and efficiency of robotic systems in modern production processes
  • Зображення мініатюри
    Публікація
    Using the Dempster-Shafer theory in Data Fusion solutions for collaborative robotic manipulators within Industry 5.0
    (2024) Yevsieiv, V.
    The paper considers the application of the Dempster-Shafer theory for solving Data Fusion problems in collaborative manipulator robots within the framework of Industry 5.0. Approaches to the integration of data from various sensors, such as cameras, ultrasonic sensors, and strain gauges, are described to improve the accuracy of decision-making in the processes of capturing and manipulating objects. An analysis of the effectiveness of this methodology in complex production environments with heterogeneous data was carried out.
  • Зображення мініатюри
    Публікація
    Using the Triangulation Method to Measure the Distance to Objects in the Working Area of a Collaborative Manipulator Robot
    (2024) Yevsieiv, V.; Starikova, S.
    This report considers the use of the triangulation method to measure the distance to objects in the working area of a collaborative manipulator robot. The proposed approach provides high accuracy and speed of determining the positions of objects, which is critically important for safe and efficient performance of tasks. The use of triangulation allows robots to adapt their actions to changing environmental conditions, helping to increase productivity and reduce risks. The results of the study confirm the importance of the triangulation method as an important tool for the integration of robotic systems into modern production processes