本文为美国北德克萨斯大学（作者：VENKATESH SRINIVASAN K）的硕士论文，共91页。

随着科学技术的不断进步，运输业的创新发展可以提高产品的安全性和保障性，从而造福社会。联邦政府要求每辆商用卡车在每次出行前都要接受检查。这种行车前检查确保了每辆车在使用前的安全机械状况。

无人机（UAV）可用于提供自动化检查，从而减少驾驶员工作量、检查成本和时间，同时提高检查精度。本文开发了一个基于Android应用程序的商用卡车无人机预裂检测算法的主要组件。具体来说，本论文提供了在户外环境下使用激光传感器和Android飞行控制应用程序（包括起飞、着陆、油门控制和实时视频传输）提供稳定高度控制的基础工作。高度算法是本论文研究的核心。Phantom 2 Vision+使用压力传感器计算无人机的高度，以稳定飞行高度。但是，这些高度读数不能提供本项目所需的精度。相反，在高度控制算法的开发过程中，需要使用激光测距传感器来实现高度的高精度自动控制。本论文研究的另一个主要贡献是扩展DJI软件开发包的有限功能，以便在不修改无人机动力学的情况下提供更复杂的控制目标。该项目的结果也直接适用于运输业中无人机的一些其它用途。

As science and technology continue to advance, innovative developments in transportation can enhance product safety and security for the benefit and welfare of society. The federal government requires every commercial truck to be inspected before each trip. This pretrip inspection ensures the safe mechanical condition of each vehicle before it is used. An Unmanned Aerial Vehicle (UAV) could be used to provide an automated inspection, thus reducing driver workload, inspection costs and time while increasing inspection accuracy. This thesis develops a primary component of the algorithm that is required to implement UAV pretrip inspections for commercial trucks using an android-based application. Specifically, this thesis provides foundational work of providing stable height control in an outdoor environment using a laser sensor and an android flight control application that includes take-off, landing, throttle control, and real-time video transmission. The height algorithm developed is the core of this thesis project. Phantom 2 Vision+ uses a pressure sensor to calculate the altitude of the drone for height stabilization. However, these altitude readings do not provide the precision required for this project. Rather, the goal of autonomously controlling height with great precision necessitated the use of a laser rangefinder sensor in the development of the height control algorithm. Another major contribution from this thesis research is to extend the limited capabilities of the DJI software development kit in order to provide more sophisticated control goals without modifying the drone dynamics. The results of this project are also directly applicable to a number of additional uses of drones in the transportation industry.

1.       引言

2. 自动化行车前检查与论文研究综述

3. 硬件设计需求

4. 软件设计需求

5. 项目的具体执行

6. 系统现场部署与仿真结果

7. 结论与未来展望

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