Abstract

In the last years Autonomous vehicle navigation has had considerable improvements; however, this technology has not yet been able to effectively be integrated with mobile systems that work inside buildings, houses or without the influence of absolute references such as GPS. It is for this reason that this paper provides a methodological proposal that allows the integration of the use of object detection methods such as YOLO (You Only Look Once) or R-CNN (Region Convolutional Neural Networks), with laser scanning systems for the measurement of spatial coordinates and an INS system to obtain spatial positioning through relative references. This method integrates the principle of dynamic triangulation and the methodological proposal IKZ (Inertial Navigation with Kalman and Zero Update) that allow to obtain acceptable mobile autonomy times in which the sector of interest is re-scanned.

中文翻译：

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激光扫描仪系统与INS集成的智能自动目标跟踪方法

摘要

在过去的几年中，自动驾驶汽车有了很大的进步。但是，该技术尚未能够有效地与在建筑物，房屋内部工作或不受诸如GPS等绝对参考的影响的移动系统集成。出于这个原因，本文提供了一种方法学建议，允许将诸如YOLO（仅查看一次）或R-CNN（区域卷积神经网络）之类的对象检测方法与激光扫描系统集成在一起进行测量空间坐标系和INS系统以通过相对参考获得空间定位。