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Applied Sciences
Volume 16
Issue 3
10.3390/app16031199
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Control of Physically Connected Off-Road Skid-Steering Robotic Vehicles Based on Numerical Simulation and Neural Network Models

by
Miša Tomić
*,
Miloš Simonović
,
Vukašin Pavlović
,
Milan Banić
and
Miloš Milošević
Faculty of Mechanical Engineering, University of Nis, 18000 Nis, Serbia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(3), 1199; https://doi.org/10.3390/app16031199
Submission received: 13 December 2025 / Revised: 12 January 2026 / Accepted: 22 January 2026 / Published: 23 January 2026
(This article belongs to the Topic Advances in Autonomous Vehicles, Automation, and Robotics)
Versions Notes

Featured Application

The presented method provides real-time steering and wheel-to-ground load estimation for physically linked skid-steering robots, enabling a dynamically reconfigurable robotic fence capable of autonomous navigation over complex outdoor terrain.

Abstract

The use of robots in various industries has increased significantly in recent years, with mobile robots playing a central role in automation. Their applications range from service robotics and automated material handling to bomb disposal and planetary exploration. A rapidly growing area of mobile robotics involves coordinated groups of autonomous robots, commonly referred to as swarms. However, only a limited number of studies have addressed systems in which ropes or wires physically connect robots. Connecting multiple autonomous robotic vehicles with a tensioned wire can form a movable fence, enabling coordinated motion as a single dynamic entity. This paper presents a real-time control approach for the off-road motion of physically connected skid-steering robotic vehicles. A numerical-simulation-driven artificial neural network is employed as a surrogate model to estimate wheel–ground load distribution online, enabling stable steering control and accurate trajectory tracking on rough terrain while accounting for wire-induced coupling effects.
Keywords: skid-steering mobile robots; physically connected robots; multibody dynamic simulation; artificial neural networks; autonomous off-road robots skid-steering mobile robots; physically connected robots; multibody dynamic simulation; artificial neural networks; autonomous off-road robots

Share and Cite

MDPI and ACS Style

Tomić, M.; Simonović, M.; Pavlović, V.; Banić, M.; Milošević, M. Control of Physically Connected Off-Road Skid-Steering Robotic Vehicles Based on Numerical Simulation and Neural Network Models. Appl. Sci. 2026, 16, 1199. https://doi.org/10.3390/app16031199

AMA Style

Tomić M, Simonović M, Pavlović V, Banić M, Milošević M. Control of Physically Connected Off-Road Skid-Steering Robotic Vehicles Based on Numerical Simulation and Neural Network Models. Applied Sciences. 2026; 16(3):1199. https://doi.org/10.3390/app16031199

Chicago/Turabian Style

Tomić, Miša, Miloš Simonović, Vukašin Pavlović, Milan Banić, and Miloš Milošević. 2026. "Control of Physically Connected Off-Road Skid-Steering Robotic Vehicles Based on Numerical Simulation and Neural Network Models" Applied Sciences 16, no. 3: 1199. https://doi.org/10.3390/app16031199

APA Style

Tomić, M., Simonović, M., Pavlović, V., Banić, M., & Milošević, M. (2026). Control of Physically Connected Off-Road Skid-Steering Robotic Vehicles Based on Numerical Simulation and Neural Network Models. Applied Sciences, 16(3), 1199. https://doi.org/10.3390/app16031199

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