Evaluating mobile robot navigation behavior in flexible assembly systems through digital twin and real-world experiments
Discover Robotics, vol. 1
Abstract
Although digital twins are increasingly used for pre-deployment testing, their reliability as predictive tools remains understudied due to the lack of established validation frameworks. This paper presents a systematic methodology for validating the predictive fidelity of physics-based digital twins in robotic navigation tasks, addressing a critical gap in sim-to-real transferability for industrial mobile manipulators. We propose a novel evaluation approach combining (1) multi-metric comparison (localization accuracy, path consistency, goal accuracy, and navigation performance) between real-world and simulated navigation experiments, and (2) an uncertainty quantification method to establish confidence intervals for digital twin predictions. Using an NVIDIA Isaac Sim model of an omnidirectional mobile manipulator and digitally reconstructed production environments, we conduct 50 real-world and 50 digital twin experiments across five industrial scenarios. The results show a mean Hausdorff distance of 0.195 m between real and simulated paths, localization RMSE differences of 0.005 m, and a path prediction accuracy of ±0.229 m (95% CI). The findings contribute to robotic navigation by addressing key challenges in using digital twins for real-world applications, reducing the sim-to-real gap, and enhancing the reliable deployment of mobile manipulators in flexible assembly systems.
Authors 9
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Affiliation as printed
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany
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Affiliation as printed
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany
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Affiliation as printed
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany
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Affiliation as printed
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany
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Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology Laboratory for Machine Tools and Production Engineering (WZL)
Fraunhofer Institute for Production Technology IPT · RWTH Aachen University
Affiliation as printed
Fraunhofer Institute for Production Technology (IPT), Steinbachstraße 17, 52074, Aachen, Germany
Laboratory for Machine Tools and Production Engineering (WZL), RWTH Aachen University, Campus-Boulevard 30, 52074, Aachen, Germany
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Hong Kong Productivity Council
Affiliation as printed
Hong Kong Industrial Artificial Intelligence and Robotics Centre Limited, 5/F, HKPC Building, 78 Tat Chee Avenue, Hong Kong, China
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Hong Kong Productivity Council
Affiliation as printed
Hong Kong Industrial Artificial Intelligence and Robotics Centre Limited, 5/F, HKPC Building, 78 Tat Chee Avenue, Hong Kong, China
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Hong Kong Productivity Council
Affiliation as printed
Hong Kong Industrial Artificial Intelligence and Robotics Centre Limited, 5/F, HKPC Building, 78 Tat Chee Avenue, Hong Kong, China
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Hong Kong Productivity Council
Affiliation as printed
Hong Kong Industrial Artificial Intelligence and Robotics Centre Limited, 5/F, HKPC Building, 78 Tat Chee Avenue, Hong Kong, China
INC Innovation Center GmbH, Frankenthaler Str. 20, Munich, 81539, Germany
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