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

Area of Science:

• Robotics and Automation
• Digital Twin Technology
• Control Systems Engineering

Background:

• Digital Twins (DT) are crucial for modeling physical entities, bridging the physical and digital realms.
• Accurate representation in DTs is vital for functional services and addressing real-world disturbances.
• Existing methods may lack precision in measuring kinematic variations within complex DT systems.

Purpose of the Study:

• To introduce a novel method, Log Mean Kinematics Difference Synchronization (SyncLMKD), for measuring kinematic variations in Digital Twin elements.
• To ensure symmetric kinematic values among Digital Twin components relative to a reference point.
• To develop and validate a synchronization technique for mobile robot entities within a Digital Twin framework.

Main Methods:

• The SyncLMKD method utilizes abductive reasoning, inspired by Log Mean Temperature Difference (LMTD).
• It quantifies kinematic variations among mobile robot entities in a DT representation based on displacement.
• A complementary synchronization technique was developed and applied in experimental validation.

Main Results:

• The SyncLMKD method achieved high precision in displacement measurement, with reported accuracy of [Formula: see text].
• It demonstrated predictability in distances between counterparts and the dynamic target within the Digital Twin.
• The synchronization technique facilitated synchronized movement of robot counterparts with speed adjustments of 150-200%.

Conclusions:

• SyncLMKD offers a precise and computationally efficient approach for measuring kinematic variations in Digital Twins.
• The method enables accurate synchronization of mobile robot entities, enhancing DT performance.
• This research contributes a valuable tool for improving the fidelity and functionality of Digital Twin applications.