Using the Dempster-Shafer theory in Data Fusion solutions for collaborative robotic manipulators within Industry 5.0

Abstract

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.