MonoSIM: An open source SIL framework for Ackermann Vehicular Systems with Monocular Vision
This provides a low-cost tool for researchers and educators working on autonomous vehicle control, but it is incremental as it builds on existing simulation and control methods.
The authors developed an open-source Software-in-the-Loop simulation platform for autonomous Ackermann vehicle research, focusing on simplicity and compatibility with small-scale setups like the XTENTH-CAR, and validated it by implementing MPC and PID control algorithms to confirm reliability for algorithm verification.
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.