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Routing and monitoring algorithms for UAVs.

机译:无人机的路由和监视算法。

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摘要

Small autonomous unmanned aerial vehicles (UAVs) are increasingly seen as ideal platforms for many civilian applications such as pipeline inspection, border surveillance, traffic monitoring, natural disaster monitoring and vineyard missions. This thesis address two problems that occurs naturally in these applications involving single or multiple UAVs, namely, (1) Multiple depot resource allocation and (2) Infrastructure monitoring.;In multiple depot resource allocation, we primarily address routing problems that are generalizations of the single Travelling Salesman Problem (TSP). In particular, the routing problems we consider have the UAVs start from distinct locations. The feature that differentiates the routing problems involving UAVs from similar problems previously studied in the literature is that there are constraints on the motion of a UAV. This thesis addresses the constraint that captures the inability of a fixed wing UAV to turn at any arbitrary yaw rate. We provide both approximation algorithms and lower bounds with constant bounding factors for three generalizations of the single TSP.;In the infrastructure monitoring application, we provide vision based control algorithms that equips a fixed wing UAV to track curved and irregular structures such as roads, canals, borders, coastlines based on visual feedback. Most of the vision based tracking work in the literature mainly deals with ground vehicles. In this thesis, we present algorithms and experimental results whereby a fixed wing UAV travelling at 20 m/sec can follow locally linear structures with 10 meters of cross track error. Also, results for a fixed wing UAV searching and mapping the coordinates of a 2 mile stretch of a river with a cross track error of around 9 meters are presented.
机译:小型无人驾驶无人机(UAV)越来越被视为许多民用应用的理想平台,例如管道检查,边界监视,交通监视,自然灾害监视和葡萄园任务。本文解决了在涉及单个或多个UAV的这些应用程序中自然发生的两个问题,即(1)多个仓库资源分配和(2)基础结构监视。;在多个仓库资源分配中,我们主要解决路由问题,这些问题是单个旅行推销员问题(TSP)。特别是,我们认为无人机存在的路由问题是从不同的位置开始的。将涉及无人机的航路问题与先前文献中研究过的类似问题区分开的特征是,无人机的运动受到限制。本文解决了捕获固定翼无人机无法以任意偏航角速度转弯的约束。我们为单个TSP的三种概括提供逼近算法和具有恒定边界因子的下限。在基础设施监视应用程序中,我们提供基于视觉的控制算法,该算法配备固定翼无人机来跟踪弯曲和不规则的结构,例如道路,运河,边界,海岸线基于视觉反馈。文献中大多数基于视觉的跟踪工作主要涉及地面车辆。在本文中,我们提出了算法和实验结果,其中以20 m / sec的速度飞行的固定翼无人机可以遵循局部线性结构,并具有10米的交叉航迹误差。此外,还给出了固定机翼无人机搜索和绘制2英里长的河流的坐标的结果,交叉航迹误差约为9米。

著录项

  • 作者

    Rathinam, Sivakumar.;

  • 作者单位

    University of California, Berkeley.;

  • 授予单位 University of California, Berkeley.;
  • 学科 Engineering Civil.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 112 p.
  • 总页数 112
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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