开源工具包AARK降低自动驾驶赛车研究门槛,助力安全系统开发。
AARK: An Open Toolkit for Autonomous Racing Research
- 提供视觉友好接口与模块化控制栈,支持赛车环境下的自主系统研究
- 可生成深度、法线与语义分割数据,用于训练感知模型
- 适合自动驾驶初学者及希望提升实验可复现性的研究人员
自动驾驶赛车需在长时间内安全控制车辆达到物理极限,为依赖车辆自主干预的先进安全系统提供重要洞察。当前该领域参与门槛高,物理平台与传感器套件成本高昂,而现有仿真器在视觉与动态保真度上不足,定制性差且使用困难。AARK 提供三个模块:ACI 实现对 Assetto Corsa 的计算机视觉友好接口,便于评估自主控制方案;ACDG 可生成深度图、法线图和语义分割数据,用于训练感知模型;ACMPC 为新手提供可扩展的全栈自主控制解决方案,支持车辆控制开发。AARK 致力于统一并普及这一关键领域研究,推动更安全、可信赖的自动驾驶系统发展。
原文摘要 · Abstract (English)
Autonomous racing demands safe control of vehicles at their physical limits for extended periods of time, providing insights into advanced vehicle safety systems which increasingly rely on intervention provided by vehicle autonomy. Participation in this field carries with it a high barrier to entry. Physical platforms and their associated sensor suites require large capital outlays before any demonstrable progress can be made. Simulators allow researches to develop soft autonomous systems without purchasing a platform. However, currently available simulators lack visual and dynamic fidelity, can still be expensive to buy, lack customisation, and are difficult to use. AARK provides three packages, ACI, ACDG, and ACMPC. These packages enable research into autonomous control systems in the demanding environment of racing to bring more people into the field and improve reproducibility: ACI provides researchers with a computer vision-friendly interface to Assetto Corsa for convenient comparison and evaluation of autonomous control solutions; ACDG enables generation of depth, normal and semantic segmentation data for training computer vision models to use in perception systems; and ACMPC gives newcomers to the field a modular full-stack autonomous control solution, capable of controlling vehicles to build from. AARK aims to unify and democratise research into a field critical to providing safer roads and trusted autonomous systems.
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