Paper
14 April 2023 L3-ULS: development and evaluation of a light-weight, low-cost, low-altitude UAV-borne LiDAR system
Jiang He, Junxiang Tan, Shaoda Li, Jianfei Liu, Ronghao Yang, Yongyong Du, Qitao Li
Author Affiliations +
Proceedings Volume 12634, International Conference on Optics and Machine Vision (ICOMV 2023); 126340A (2023) https://doi.org/10.1117/12.2678637
Event: International Conference on Optics and Machine Vision (ICOMV 2023), 2023, Changsha, China
Abstract
LiDAR systems have demonstrated effectiveness for Earth observation. However, heavy weight and high cost have greatly hindered them to be widely used in large-scale scenarios. This paper provides an ultralight and low-cost UAV LiDAR system for further flexible low-altitude observation, which weighs only about 0.98 kg and is compactly integrated with multiple low-cost sensors consisting of a panoramic laser scanner, a downward-looking camera and a consumer-grade IMU, etc. Details of the developed system, data processing process and system self-calibration are introduced. Comprehensive evaluation from four aspects including planar noise, consistency among multiple strips, absolute precision and coloring accuracy is designed and tested. Road signs and rectangular targets were used to participate in experimental evaluation, and test data were obtained at two different flight altitudes (50m and 100m). Results show that the plane fitting accuracy is 1.8cm@50m and 2.4cm@100m for single strip data, and 3.7cm@50m and 4.6cm@100m for multiple strips respectively, illustrating high performance of the scanner and whole system. Consistency between multiple strips is improved from 12.7cm to 7.3cm by strip adjustment at the height of 50m. Absolute precision of the system is about 2.8cm and 4.3 cm at both flight cases, and the coloring accuracy is about 2 cm to 4 cm. The results demonstrate great potential in terms of both hardware and overall performance. We believe that the system developed in this study will have great potential applications for many fields.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jiang He, Junxiang Tan, Shaoda Li, Jianfei Liu, Ronghao Yang, Yongyong Du, and Qitao Li "L3-ULS: development and evaluation of a light-weight, low-cost, low-altitude UAV-borne LiDAR system", Proc. SPIE 12634, International Conference on Optics and Machine Vision (ICOMV 2023), 126340A (14 April 2023); https://doi.org/10.1117/12.2678637
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KEYWORDS
Point clouds

LIDAR

Unmanned aerial vehicles

Calibration

Cameras

Error analysis

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