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CC BY V4.0, Open Access
Journal article
Sim2Real Transfer of Imitation Learning of Motion Control for Car-like Mobile Robots Using Digital Twin Testbed
Robotics (Basel), Vol.14(12), 180
2025
Abstract
Reliable transfer of control policies from simulation to real-world robotic systems remains a central challenge in robotics, particularly for car-like mobile robots. Digital Twin (DT) technology provides a robust framework for high-fidelity replication of physical platforms and bi-directional synchronization between virtual and real environments. In this study, a DT-based testbed is developed to train and evaluate an imitation learning (IL) control framework in which a neural network policy learns to replicate the behavior of a hybrid Model Predictive Control (MPC)–Backstepping expert controller. The DT framework ensures consistent benchmarking between simulated and physical execution, supporting a structured and safe process for policy validation and deployment. Experimental analysis demonstrates that the learned policy effectively reproduces expert behavior, achieving bounded trajectory-tracking errors and stable performance across simulation and real-world tests. The results confirm that DT-enabled IL provides a viable pathway for Sim2Real transfer, accelerating controller development and deployment in autonomous mobile robotics.
Details
- Title
- Sim2Real Transfer of Imitation Learning of Motion Control for Car-like Mobile Robots Using Digital Twin Testbed
- Authors/Creators
- Narges Mohaghegh - Murdoch UniversityHai Wang - Murdoch University, Centre for Water, Energy and WasteAmirmehdi Yazdani - Murdoch University, School of Engineering and Energy
- Publication Details
- Robotics (Basel), Vol.14(12), 180
- Publisher
- MDPI
- Number of pages
- 18
- Identifiers
- 991005845959207891
- Copyright
- © 2025 by the authors.
- Murdoch Affiliation
- School of Engineering and Energy; Centre for Water, Energy and Waste; College of Science, Technology, Engineering and Mathematics
- Language
- English
- Resource Type
- Journal article
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