全球导航卫星系统应用
激光雷达
计算机科学
计算机视觉
拖拉机
人工智能
全球定位系统
对象(语法)
帧(网络)
跟踪系统
目标检测
遥感
实时计算
地理
工程类
汽车工程
电信
分割
滤波器(信号处理)
作者
Riikka Soitinaho,Marcel Moll,Timo Oksanen
标识
DOI:10.1016/j.ifacol.2022.11.116
摘要
Environment perception is an important capability for fully autonomous operation of agricultural machinery. High-precision work requires perception systems that are able to locate objects with high and specified accuracy. In this paper, we present an object detection and tracking system in a global coordinate frame based on 2D LiDAR data and RTK-GNSS positioning. The LiDARs and the RTK-GNSS device are installed on a tractor that is moving while the data is recorded. The final mapping result is compared to an RTK-GNSS based ground truth measurement of the object positions. For a test setup with four objects on a clover field, the average object positioning accuracy of the LiDAR system was determined to be 0.135 m (CEP50) and the worst case accuracy was 0.178m (CEP50). The preliminary results from this study can be used as a basis for determining requirements for safety margins when using this system for autonomous driving.
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