Modeling, evaluation and metrics performance of the SyncLMKD in distributed kinematics variations

Abstract

Modeling the Digital Twin (DT) is an important resource for accurately representing the physical entity, enabling it to deliver functional services, meet application requirements, and address the disturbances between the physical and digital realms. This article introduces the Log Mean Kinematics Difference Synchronization (SyncLMKD) to measure the kinematic variations distributed among Digital Twin elements to ensure symmetric values relative to a reference. The proposed method employs abductive reasoning and draws inspiration from the Log Mean Temperature Difference (LMTD). The SyncLMKD is applied to measure kinematic variations among mobile robot entities in a DT representation, and it operates following the progression of displacement. A suitable synchronization technique was also developed for experiments based on this method. The main advantage of the SyncLMKD is its high precision in displacement measurement and predictability of distances between counterparts and the dynamic target of the Digital Twin, all while requiring low computational effort. The approach was tested with robots positioned at various locations and speeds to achieve synchronization among them. The SyncLMKD method demonstrated a precision of [Formula: see text] in measuring the distances between elements, achieving synchronized movement of the counterparts with speed adjustments facilitated by the synchronization technique, with percentages ranging from 150 to 200%.