EVALUATION OF CONSUMER-GRADE AND SURVEY-GRADE UAV-LIDAR

Q2 Social Sciences
G. Mandlburger, M. Kölle, F. Pöppl, M. Cramer
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引用次数: 1

Abstract

Abstract. Driven by developments in the automotive industry, the availability of compact consumer-grade LiDAR (Light Detection and Ranging) sensors has increased significantly in recent years. Some of these sensors are also suitable for UAV-based surveying tasks. This paper first discusses the differences between consumer-grade and survey-grade LiDAR systems. Special attention will be paid to the scanning mechanisms used on the one hand and to different solutions for the transceiver units on the other hand. Based on the technical data of two concrete systems, the consumer-grade DJI Zenmuse L1 sensor and the survey-grade scanner RIEGL VUX-1UAV, the expected effects of the sensor parameters on the 3D point cloud are first discussed theoretically and then verified using an exemplary data set in Hessigheim (Baden-Württemberg, Germany). The analysis shows the possibilities and limitations of consumer-grade LiDAR. Compared to the low-cost sensor, the high-end scanner exhibits lower range measurement noise (5–10 mm) and better 3D point location accuracy. Furthermore, the higher laser beam quality of high-end devices (beam divergence, beam shape) enables more detailed object detection at the same point density. With moderate accuracy requirements of 5–10 cm, however, applications in the geodetic-cartographic context also arise for the considerably less expensive consumer-grade LiDAR systems.
消费级和测量级紫外激光雷达的评估
摘要在汽车行业发展的推动下,紧凑型消费级激光雷达(光探测和测距)传感器的可用性近年来显着增加。其中一些传感器也适用于基于无人机的测量任务。本文首先讨论了消费级和测量级激光雷达系统的区别。一方面将特别注意所使用的扫描机制,另一方面将注意收发器单元的不同解决方案。基于两个具体系统的技术数据,即消费级大疆Zenmuse L1传感器和测量级扫描仪RIEGL vx - 1uav,首先从理论上讨论了传感器参数对三维点云的预期影响,然后使用德国黑森海姆(baden - w - rttemberg)的示例数据集进行了验证。分析显示了消费级激光雷达的可能性和局限性。与低成本传感器相比,高端扫描仪具有更低的测量噪声(5-10 mm)和更好的3D点定位精度。此外,高端设备更高的激光束质量(光束发散,光束形状)使得在相同点密度下可以更详细地检测目标。然而,在5-10厘米的中等精度要求下,在测绘环境中的应用也出现了相当便宜的消费级LiDAR系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.70
自引率
0.00%
发文量
949
审稿时长
16 weeks
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