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Algorithm on Converting a 2D Scanning LiDAR to 3D for use in Autonomous Indoor Navigation

机译:将2D扫描LiDAR转换为3D以用于自主室内导航的算法

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Autonomous indoor navigation is synonymous with military centric autonomous navigation in GPS-denied environments. Unmanned aerial systems (UAS) are routinely connected to autonomous navigation. This combination of technology has many disparate uses such as in kids toys, photography, and military applications. For each of these areas a major concern is size, weight, and power (SWaP) in the product design. SWaP has a direct effect on the operations of an autonomous UAS such as on the flight time, the maneuverability, controllability, and the durability. This paper presents a basic algorithm describing one aspect of reducing SWaP on an autonomous quad-rotor UAS, by converting a 2D scanning LiDAR sensor to a 3D sensor, thus eliminating the need for additional sensors used to perform localization and mapping. Much that is described here is derived from the thesis work presented by Cooper. The majority of work was performed during a Master’s Thesis investigation by M. A. Cooper titled “Converting a 2D Scanning LiDAR to a 3D System for Use on Quad-Rotor UAVs in Autonomous Navigation.” The work presented here develops the generalized calibration procedure.
机译:自主室内导航与GPS拒绝环境中以军事为中心的自主导航同义。无人机系统(UAS)通常连接到自主导航。这种技术的结合有许多不同的用途,例如在儿童玩具,摄影和军事应用中。对于每个这些区域,产品设计中的主要问题是尺寸,重量和功率(SWaP)。 SWaP对自主UAS的运行有直接影响,例如飞行时间,可操纵性,可控制性和耐用性。本文提出了一种基本算法,描述了通过将2D扫描LiDAR传感器转换为3D传感器来减少自主四旋翼UAS上SWaP的一个方面,从而消除了用于执行定位和映射的其他传感器的需求。这里描述的很多内容都来自Cooper提出的论文工作。大部分工作是在M. A. Cooper题为“将2D扫描LiDAR转换为3D系统以用于自动导航的四旋翼无人机”的硕士学位论文调查期间完成的。这里介绍的工作发展了通用的校准程序。

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