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Design Considerations for Remote Sensing Payloads on Inexpensive Unmanned Autonomous Aerial Vehicles

机译:廉价无人机上遥感有效载荷的设计考虑

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摘要

This paper describes the latest version of the University of Florida (UF)'s unmanned autonomous vehicle (UAV), named the MAKO MAKO. The MAKO MAKO can operate in fully autonomous way-point navigation mode, including autonomous takeoff and landing, allowing for repeatable, predictable ground coverage. Other features essential for the mission profile include hand-launch ability for takeoff, as well as a waterproof fuselage for aquatic landing. Low-altitude, high-resolution imaging is facilitated by a cruise speed of 15 m/s. The sensor payload on the MAKO is a digital single lens reflex (DSLR) camera operated at the shortest exposure to minimize the effect of motion blurring. The resulting images are capable of resolving objects on the ground as small as six cm. The MAKO has been used for a number of applications, including mapping wading bird nests in the Florida Everglades and elsewhere, monitoring the efficacy of defoliant spray programs in Lake Okeechobee, identification of invasive exotic vegetation, and mapping of bison.
机译:本文介绍了佛罗里达大学(UF)无人驾驶自动驾驶汽车(UAV)的最新版本,名为MAKO MAKO。 MAKO MAKO可以在完全自主的航点导航模式下运行,包括自主起飞和着陆,从而实现可重复,可预测的地面覆盖。任务配置文件的其他重要功能包括起飞的手动发射能力以及用于水上着陆的防水机身。 15 m / s的巡航速度有助于进行低空,高分辨率成像。 MAKO上的传感器有效负载是数字单镜头反射(DSLR)相机,其操作时间最短,以最大程度地减少运动模糊的影响。生成的图像能够分辨小至6厘米的地面物体。 MAKO已用于许多应用程序,包括在佛罗里达大沼泽地和其他地方绘制涉水鸟巢,监控奥基乔比湖的脱叶喷雾程序的功效,识别外来入侵植物以及对野牛进行制图。

著录项

  • 来源
    《Surveying and land information science》 |2010年第3期|p.131-137|共7页
  • 作者单位

    School of Forest Resources and Conservation, Geomatics Program, 301 Reed Lab, P.O. Box 110565, University of Florida, Gainesville, Florida 32611-0565;

    School of Forest Resources and Conservation, Geomatics Program, 301 Reed Lab, P.O. Box 110565, University of Florida, Gainesville, Florida 32611-0565;

    School of Forest Resources and Conservation, Geomatics Program, 301 Reed Lab, P.O. Box 110565, University of Florida, Gainesville, Florida 32611-0565;

    Florida Cooperative Fish and Wildlife Research, Building 810, University of Florida, Gainesville, Florida 32611-0565;

    Department of Mechanical and Aerospace Engineering, Micro Air Vehicles Lab, 114 NEB, University of Florida, Gainesville, Florida 32611-0565;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    unmanned automous vehicle; remote sensing; digital single lens reflex;

    机译:无人驾驶自动驾驶汽车;遥感;数码单镜反光;
  • 入库时间 2022-08-18 03:40:34

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