Investigation into Camera Calibration Flight Paths for UAV-Based Corridor Surveys

Jack Henharen, P. Helmholz
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Abstract

Abstract. There is increasing adoption of cost-effective nonmetric camera-equipped unmanned aerial vehicles due to the perceived benefits of timesaving, ease of use, and the accuracy of the digital elevation models that can be produced using structure from motion software. The introduction of systematic elevation errors, doming and bowing, has been evidenced by several authors, and various methods have been identified to reduce these errors. This paper aims to analyse the impact of flight plans on these systematic errors using the especially challenging case of a corridor survey. Two sites were flown for the survey using a DJI Zenmuse. The first site, a car park, was utilised for on-the-job pre-calibration of the camera and consisted of several orbit flights and a double grip flight. Subsequently, an adjacent road (a corridor survey overall 428 m long) was also surveyed at 60 m and 80 m heights using varying flight configurations. This study confirms that pre-calibrating the camera's IOPs significantly reduces the root mean squared elevation error (from 0.268 m to 0.034 m) compared to self-calibrated IOPs using the corridor flights. The impact of flight design on elevation errors confirms a single flight path's risk and the benefits of two or more flight paths, including a point-of-interest orbit flight.
无人机走廊勘测相机校准飞行路径调查
摘要。由于具有省时、易用以及使用运动结构软件可生成数字高程模型的准确性等明显优势,越来越多的人开始采用配备非测量相机的高性价比无人飞行器。一些学者已经证实了系统性高程误差(圆拱和弓形)的引入,并确定了各种方法来减少这些误差。本文旨在利用走廊勘测这一特别具有挑战性的案例,分析飞行计划对这些系统误差的影响。使用大疆 Zenmuse 飞行器对两个地点进行了勘测。第一个地点是一个停车场,用于相机的在职预校准,包括几次轨道飞行和一次双抓地飞行。随后,还使用不同的飞行配置在 60 米和 80 米高度对邻近的一条道路(走廊勘测总长 428 米)进行了勘测。这项研究证实,与使用走廊飞行进行自我校准的 IOP 相比,预先校准相机的 IOP 可显著减少均方根高程误差(从 0.268 米减少到 0.034 米)。飞行设计对仰角误差的影响证实了单一飞行路径的风险以及两条或更多飞行路径(包括兴趣点轨道飞行)的益处。
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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