Digital Twin-Driven 3-D Position Information Mutuality and Positioning Error Compensation for Robotic Arm

Abstract

Robotic arms for industrial applications rely on expensive, complex solutions for high-precision positioning error compensation. Digital twins (DTs) provide virtual representations of physical assets to optimize their engineering performance, which helps address the above issues. To address this problem, this article proposes a DT-driven 3-D position information mutuality and positioning error compensation for robotic arm. A DT model is developed and a virtual sensor is modeled geometrically. Information exchange between the physical and virtual sensor enables the comparison of the actual and target arm pose. Through closed-loop alignment of the physical sensor data with the virtual output, the arm joints are dynamically adjusted to reduce positioning errors. Information mutuality significantly reduces the amount of calculation necessary to determine the robotic arm’s actual angle of motion. Experimental results from various positions have confirmed the efficacy of the method, with a remarkable 81.23% reduction in positioning error.