MonoSIM: 一种面向Ackermann车辆系统的开源SIL框架
MonoSIM: An open source SIL framework for Ackermann Vehicular Systems with Monocular Vision
AI总结：
本文提出一个开源SIL仿真平台，用于自主Ackermann车辆研究与教育。该框架采用单目视觉系统，通过滑动窗口车道检测方法实现低计算开销的刺激捕捉，支持灵活的算法测试与验证环境。
摘要：
本文提出了一种开源的软件在环（SIL）仿真平台，用于自主Ackermann车辆的研究和教育。该框架专注于简洁性，使其易于与小型实验设置（如XTENTH-CAR平台）配合使用。系统采用开源工具设计，利用单目摄像头视觉系统，通过基于滑动窗口的车道检测方法以最小的计算开销捕捉刺激。该平台支持灵活的算法测试和验证环境，允许研究人员在易于使用的虚拟环境中实现和比较各种控制策略。为验证平台的性能，Model Predictive Control（MPC）和Proportional-Integral-Derivative（PID）算法被实现于SIL框架中。结果证实，该平台为算法验证提供了可靠的环境，是未来多智能体系统研究、教育目的和低成本AGV开发的理想工具。我们的代码可在https://github.com/shantanu404/monosim.git获取。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
