Development of real-time digital twin model of autonomous field robot for prediction of vehicle stability

Abstract

This study aimed to develop a real-time digital twin model for an autonomous field robot. Autonomous control involves controlling vehicle stability parameters such as angular and translational velocities. However, stability is lost when a vehicle run over rough terrain. Therefore, it is necessary to accurately predict vehicle stability in real time using a digital twin model. In this study, we developed the digital twin model for an autonomous driving robot using real-time multibody dynamics. To verify the accuracy, we carried out real road tests on a flat road, and roads with symmetric and asymmetric bumps. We regulated the dynamic parameters such as the position of the center of gravity and coefficients of force elements in the built digital twin model and evaluated its efficiency as well. ？ ICROS 2021.