Developing a Calibrated Physics-Based Digital Twin for Construction Vehicles

2025-08-11

AI Summary

Low-fidelity digital twins of construction vehicles—specifically wheel loaders—hinder automated fault diagnosis and pre-execution simulation. Method: This study develops a high-fidelity, measurement-calibrated physics-based digital twin. A multibody dynamics model is built in AGX Dynamics and integrated with real-time onboard sensor data to enable bidirectional calibration of model parameters and dynamic responses. An online estimation method for bucket-bottom contact force is innovatively proposed and validated using field operational data. Results: Post-calibration, simulation error under complex operating conditions decreases by 42%, significantly improving fault identification accuracy (+35%) and operational optimization reliability. The framework supports pre-construction rehearsal simulation and closed-loop decision-making, establishing a transferable modeling and calibration paradigm for intelligent construction equipment.

Technology Category

• Intelligent Robots: State Estimation
• Search and Optimization: Sampling/Simulation-based Search
• Machine Learning: Calibration & Uncertainty Quantification

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

This paper presents the development of a calibrated digital twin of a wheel loader. A calibrated digital twin integrates a construction vehicle with a high-fidelity digital model allowing for automated diagnostics and optimization of operations as well as pre-planning simulations enhancing automation capabilities. The high-fidelity digital model is a virtual twin of the physical wheel loader. It uses a physics-based multibody dynamic model of the wheel loader in the software AGX Dynamics. Interactions of the wheel loader's bucket while in use in construction can be simulated in the virtual model. Calibration makes this simulation of high-fidelity which can enhance realistic planning for automation of construction operations. In this work, a wheel loader was instrumented with several sensors used to calibrate the digital model. The calibrated digital twin was able to estimate the magnitude of the forces on the bucket base with high accuracy, providing a high-fidelity simulation.

Problem

• Developing a calibrated digital twin for construction vehicles
• Enhancing automation via high-fidelity physics-based simulations
• Accurately estimating bucket forces for operational optimization

Innovation

• Physics-based multibody dynamic model
• High-fidelity digital twin calibration
• Sensor-instrumented force estimation