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Research on status monitoring and positioning compensation system for digital twin of parallel robots

Yuting Zhang, Pei Gao, Zongyan Wang, Quanling He

2025Scientific Reports10 citationsDOIOpen Access PDF

Abstract

Industrial parallel robots are characterized by their stable structure and grasping pick-up speed, and they are commonly used in food packaging and parts assembly industries. However, the traditional robot teaching pendants often provide monitoring data under idealized conditions. The lack of precise monitoring, combined with sensor data, frequently results in misaligned robot positioning and a reduced operational lifespan. To enhance these robots' positioning accuracy and monitoring efficiency, this paper introduces research on status monitoring and positioning compensation system for digital twin of parallel robots. Initially, the digital twin framework is constructed. Establishing a spatial kinematics model that serves as the foundation for the twin model, the kinematics model facilitates basic synchronized interaction. Furthermore, an improved IPSO-SSA-DBP algorithm calibrates the kinematics and predicts the position error. Ultimately, a digital twin system is built to visualize the status monitoring and positioning error compensation, and the system's reliability is confirmed through experimental validation.

Topics & Concepts

Computer scienceCompensation (psychology)RobotReal-time computingArtificial intelligencePsychologyPsychoanalysisRobotic Mechanisms and DynamicsIterative Learning Control SystemsRobotics and Sensor-Based Localization
Research on status monitoring and positioning compensation system for digital twin of parallel robots | Litcius