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Main Authors:	Paz, Alvaro, Mustalahti, Pauli, Dastranj, Mohammad, Mattila, Jouni
Format:	Preprint
Published:	2025
Subjects:	Robotics
Online Access:	https://arxiv.org/abs/2510.02976
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author	Paz, Alvaro Mustalahti, Pauli Dastranj, Mohammad Mattila, Jouni
author_facet	Paz, Alvaro Mustalahti, Pauli Dastranj, Mohammad Mattila, Jouni
contents	This paper presents a framework for real-time optimal controlling of a heavy-duty skid-steered mobile platform for trajectory tracking. The importance of accurate real-time performance of the controller lies in safety considerations of situations where the dynamic system under control is affected by uncertainties and disturbances, and the controller should compensate for such phenomena in order to provide stable performance. A multiple-shooting nonlinear model-predictive control framework is proposed in this paper. This framework benefits from suitable algorithm along with readings from various sensors for genuine real-time performance with extremely high accuracy. The controller is then tested for tracking different trajectories where it demonstrates highly desirable performance in terms of both speed and accuracy. This controller shows remarkable improvement when compared to existing nonlinear model-predictive controllers in the literature that were implemented on skid-steered mobile platforms.
format	Preprint
id	arxiv_https___arxiv_org_abs_2510_02976
institution	arXiv
publishDate	2025
record_format	arxiv
spellingShingle	Real-Time Nonlinear Model Predictive Control of Heavy-Duty Skid-Steered Mobile Platform for Trajectory Tracking Tasks Paz, Alvaro Mustalahti, Pauli Dastranj, Mohammad Mattila, Jouni Robotics This paper presents a framework for real-time optimal controlling of a heavy-duty skid-steered mobile platform for trajectory tracking. The importance of accurate real-time performance of the controller lies in safety considerations of situations where the dynamic system under control is affected by uncertainties and disturbances, and the controller should compensate for such phenomena in order to provide stable performance. A multiple-shooting nonlinear model-predictive control framework is proposed in this paper. This framework benefits from suitable algorithm along with readings from various sensors for genuine real-time performance with extremely high accuracy. The controller is then tested for tracking different trajectories where it demonstrates highly desirable performance in terms of both speed and accuracy. This controller shows remarkable improvement when compared to existing nonlinear model-predictive controllers in the literature that were implemented on skid-steered mobile platforms.
title	Real-Time Nonlinear Model Predictive Control of Heavy-Duty Skid-Steered Mobile Platform for Trajectory Tracking Tasks
topic	Robotics
url	https://arxiv.org/abs/2510.02976

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