Paper
MonoSIM: An open source SIL framework for Ackermann Vehicular Systems with Monocular Vision
Authors
Shantanu Rahman, Nayeb Hasin, Mainul Islam, Md. Zubair Alom Rony, Golam Sarowar
Abstract
This paper presents an open-source Software-in-the-Loop (SIL) simulation platform designed for autonomous Ackerman vehicle research and education. The proposed framework focuses on simplicity, while making it easy to work with small-scale experimental setups, such as the XTENTH-CAR platform. The system was designed using open source tools, creating an environment with a monocular camera vision system to capture stimuli from it with minimal computational overhead through a sliding window based lane detection method. The platform supports a flexible algorithm testing and validation environment, allowing researchers to implement and compare various control strategies within an easy-to-use virtual environment. To validate the working of the platform, Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) algorithms were implemented within the SIL framework. The results confirm that the platform provides a reliable environment for algorithm verification, making it an ideal tool for future multi-agent system research, educational purposes, and low-cost AGV development. Our code is available at https://github.com/shantanu404/monosim.git.
Metadata
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Raw Data (Debug)
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"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2603.23965v1</id>\n <title>MonoSIM: An open source SIL framework for Ackermann Vehicular Systems with Monocular Vision</title>\n <updated>2026-03-25T05:59:30Z</updated>\n <link href='https://arxiv.org/abs/2603.23965v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2603.23965v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>This paper presents an open-source Software-in-the-Loop (SIL) simulation platform designed for autonomous Ackerman vehicle research and education. The proposed framework focuses on simplicity, while making it easy to work with small-scale experimental setups, such as the XTENTH-CAR platform. The system was designed using open source tools, creating an environment with a monocular camera vision system to capture stimuli from it with minimal computational overhead through a sliding window based lane detection method. The platform supports a flexible algorithm testing and validation environment, allowing researchers to implement and compare various control strategies within an easy-to-use virtual environment. To validate the working of the platform, Model Predictive Control (MPC) and Proportional-Integral-Derivative (PID) algorithms were implemented within the SIL framework. The results confirm that the platform provides a reliable environment for algorithm verification, making it an ideal tool for future multi-agent system research, educational purposes, and low-cost AGV development. Our code is available at https://github.com/shantanu404/monosim.git.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='cs.RO'/>\n <category scheme='http://arxiv.org/schemas/atom' term='eess.IV'/>\n <published>2026-03-25T05:59:30Z</published>\n <arxiv:comment>6 pages, 16 figures, Published in \"IEEE 12th International Conference on Automation, Robotics and Application 2026\"</arxiv:comment>\n <arxiv:primary_category term='cs.RO'/>\n <author>\n <name>Shantanu Rahman</name>\n </author>\n <author>\n <name>Nayeb Hasin</name>\n </author>\n <author>\n <name>Mainul Islam</name>\n </author>\n <author>\n <name>Md. Zubair Alom Rony</name>\n </author>\n <author>\n <name>Golam Sarowar</name>\n </author>\n </entry>"
}