Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin

Introduction. Control of underwater robotic complexes (URC) is complicated by factors, such as inertia, stochastic disturbances, and lack of navigation infrastructure. Existing approaches to modeling and predicting URS behavior are known for their weak or absent integration of data from real sensors...

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Main Authors: M. D. Gladyshev, A. V. Rybakov
Format: Article
Language:Russian
Published: Don State Technical University 2025-06-01
Series:Advanced Engineering Research
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Online Access:https://www.vestnik-donstu.ru/jour/article/view/2402
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author M. D. Gladyshev
A. V. Rybakov
author_facet M. D. Gladyshev
A. V. Rybakov
author_sort M. D. Gladyshev
collection DOAJ
description Introduction. Control of underwater robotic complexes (URC) is complicated by factors, such as inertia, stochastic disturbances, and lack of navigation infrastructure. Existing approaches to modeling and predicting URS behavior are known for their weak or absent integration of data from real sensors in real time. By eliminating this gap in integrated solutions, it is possible to combine physical models, digital twins, and visualization. A promising tool for overcoming the above limitations is a digital twin (DT), which provides an accurate digital representation of an object through the integration of data from physical sensors and mathematical models. The objective of the presented study is to develop a method for predicting the dynamics of the URC using a digital twin to improve the efficiency of autonomous control.Materials and Methods. The basis of the study was the development of a mathematical model of the motion of an underwater robotic complex. It included differential kinematics, modeling of environmental resistance, and rotation dynamics. The following sensors were used to collect and process data: incremental encoders, a three-axis accelerometer, and a gyroscope. A proportional-integral differentiating (PID) controller was applied to control the motion along each axis. The Unity Game Environment was used to visualize and test the model. It created a digital twin module with the ability to display the system state in real time. The Arduino IDE platform was used as software for low-level programming, as well as MATLAB and Python for data analysis and graphing.Results. To verify the model, experiments were conducted on a physical model. They were compared to the simulation of the object's behavior in a virtual environment. Graphs of discrepancies between physical and simulated trajectories were presented. Statistical metrics characterizing the accuracy of the digital twin were calculated. The maximum deviation in coordinates did not exceed 5.3 mm, the average angular deviation was 3.5°. This confirmed the reliability and practical applicability of the proposed model in autonomous control of a robotic complex. It was also found that the average error along X — 3.11 mm, along Y — 2.92 mm. The average error in angle Z — 1.8°. The response time was less than 10 ms. The stability of the digital twin to minor fluctuations in the data was provided by smoothing the input data, the stability of the system regulator, and adaptation of the model to the calibration values at the start of each cycle.Discussion and Conclusion. Digital twins are suitable for predictive control and monitoring of an object under uncertainty. The proposed approach can be scaled for various types of robotic systems operating in aggressive and poorly predictable environments. Further research in this area may involve the introduction of adaptive and neural network control methods.
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spelling doaj-art-67549a2bface475e8827cd349347e49d2025-08-20T03:57:12ZrusDon State Technical UniversityAdvanced Engineering Research2687-16532025-06-0125214215110.23947/2687-1653-2025-25-2-142-1511676Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital TwinM. D. Gladyshev0A. V. Rybakov1Astrakhan Tatishchev State UniversityAstrakhan Tatishchev State UniversityIntroduction. Control of underwater robotic complexes (URC) is complicated by factors, such as inertia, stochastic disturbances, and lack of navigation infrastructure. Existing approaches to modeling and predicting URS behavior are known for their weak or absent integration of data from real sensors in real time. By eliminating this gap in integrated solutions, it is possible to combine physical models, digital twins, and visualization. A promising tool for overcoming the above limitations is a digital twin (DT), which provides an accurate digital representation of an object through the integration of data from physical sensors and mathematical models. The objective of the presented study is to develop a method for predicting the dynamics of the URC using a digital twin to improve the efficiency of autonomous control.Materials and Methods. The basis of the study was the development of a mathematical model of the motion of an underwater robotic complex. It included differential kinematics, modeling of environmental resistance, and rotation dynamics. The following sensors were used to collect and process data: incremental encoders, a three-axis accelerometer, and a gyroscope. A proportional-integral differentiating (PID) controller was applied to control the motion along each axis. The Unity Game Environment was used to visualize and test the model. It created a digital twin module with the ability to display the system state in real time. The Arduino IDE platform was used as software for low-level programming, as well as MATLAB and Python for data analysis and graphing.Results. To verify the model, experiments were conducted on a physical model. They were compared to the simulation of the object's behavior in a virtual environment. Graphs of discrepancies between physical and simulated trajectories were presented. Statistical metrics characterizing the accuracy of the digital twin were calculated. The maximum deviation in coordinates did not exceed 5.3 mm, the average angular deviation was 3.5°. This confirmed the reliability and practical applicability of the proposed model in autonomous control of a robotic complex. It was also found that the average error along X — 3.11 mm, along Y — 2.92 mm. The average error in angle Z — 1.8°. The response time was less than 10 ms. The stability of the digital twin to minor fluctuations in the data was provided by smoothing the input data, the stability of the system regulator, and adaptation of the model to the calibration values at the start of each cycle.Discussion and Conclusion. Digital twins are suitable for predictive control and monitoring of an object under uncertainty. The proposed approach can be scaled for various types of robotic systems operating in aggressive and poorly predictable environments. Further research in this area may involve the introduction of adaptive and neural network control methods.https://www.vestnik-donstu.ru/jour/article/view/2402digital twin of an autonomous robotic systemunderwater robotic complexpredictive controlunderwater robot
spellingShingle M. D. Gladyshev
A. V. Rybakov
Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin
Advanced Engineering Research
digital twin of an autonomous robotic system
underwater robotic complex
predictive control
underwater robot
title Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin
title_full Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin
title_fullStr Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin
title_full_unstemmed Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin
title_short Integration of Sensor Data and Mathematical Modeling of Underwater Robot Behavior Using a Digital Twin
title_sort integration of sensor data and mathematical modeling of underwater robot behavior using a digital twin
topic digital twin of an autonomous robotic system
underwater robotic complex
predictive control
underwater robot
url https://www.vestnik-donstu.ru/jour/article/view/2402
work_keys_str_mv AT mdgladyshev integrationofsensordataandmathematicalmodelingofunderwaterrobotbehaviorusingadigitaltwin
AT avrybakov integrationofsensordataandmathematicalmodelingofunderwaterrobotbehaviorusingadigitaltwin