This thesis presents the design and implementation of a small autonomous unmanned aerial vehicle capable of high-speed flight through complex natural environments. Using only onboard sensing and computation, we perform obstacle detection, planning, and feedback control in realtime. We introduce a novel stereo vision algorithm, pushbroom stereo, capable of detecting obstacles at 120 frames per second without overburdening our lightweight processors. Our use of model-based planning and control techniques allows us to track precise trajectories that avoid obstacles identified by the vision system. We demonstrate a complete working system avoiding trees at up to 14 m/s (31 MPH). To the best of our knowledge this is the fastest lightweight aerial vehicle to perform collision avoidance in such a complex environment.
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机译：本文提出了一种能够在复杂的自然环境中高速飞行的小型自主无人机。仅使用板载传感和计算，我们就可以实时执行障碍物检测，计划和反馈控制。我们推出了一种新颖的立体视觉算法，即推扫式立体声，能够以每秒120帧的速度检测障碍物，而不会给我们的轻量级处理器增加负担。我们基于模型的计划和控制技术的使用使我们能够跟踪避免视觉系统识别出障碍的精确轨迹。我们展示了一个完整的工作系统，可避免树木以高达14 m / s（31 MPH）的速度行驶。据我们所知，这是在如此复杂的环境中能够避免碰撞的最快的轻型飞机。
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