AINS：基于单目相机的颜色识别实现自动驾驶车辆的经济型室内导航解决方案
AINS: Affordable Indoor Navigation Solution via Line Color Identification Using Mono-Camera for Autonomous Vehicles
AI总结：
针对室内GPS精度低且现有方案部署成本高的问题，提出基于单目相机的低成本室内导航方法AINS，通过颜色识别路径，实验证明其误差更小、耗时更短。
摘要：
近年来，研究人员一直在探索各种方法，通过研究新方法（尤其是针对室内场景）来提高自动驾驶车辆的有效性和效率。室内导航系统中的自动驾驶车辆面临许多挑战，尤其是GPS在室内场景中精度有限的问题。已经探索了几种稳健的方法来解决自动驾驶车辆在室内场景中的这一问题，但所提方法的低效之处在于部署成本高。为解决上述问题，我们提出了一种低成本的自动驾驶车辆室内导航方法，称为经济型室内导航解决方案（AINS），该方法基于单目相机。我们的解决方案主要基于单目相机，不依赖各种庞大或低功耗的传感器（如测距仪和其他导航传感器）来寻找路径。我们提出的方法表明，在考虑成本的同时，我们可以部署自动驾驶车辆室内导航系统。我们可以观察到，我们的解决方案所展示的结果优于现有解决方案，并且我们能够减少估计误差和时间消耗。
英文摘要：
Recently, researchers have been exploring various ways to improve the effectiveness and efficiency of autonomous vehicles by researching new methods, especially for indoor scenarios. Autonomous Vehicles in indoor navigation systems possess many challenges especially the limited accuracy of GPS in indoor scenarios. Several, robust methods have been explored for autonomous vehicles in indoor scenarios to solve this problem, but the ineffectiveness of the proposed methods is the high deployment cost. To address the above-mentioned problems we have presented A low-cost indoor navigation method for autonomous vehicles called Affordable Indoor Navigation Solution (AINS) which is based on based on Monocular Camera. Our proposed solution is mainly based on a mono camera without relying on various huge or power-inefficient sensors to find the path, such as range finders and other navigation sensors. Our proposed method shows that we can deploy autonomous vehicles indoor navigation systems while taking into consideration the cost. We can observe that the results shown by our solution are better than existing solutions and we can reduce the estimated error and time consumption.
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。
