@phdthesis { Barry16,
    abstract = { 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. },
    author = { Andrew J. Barry },
    month = { Feb },
    school = { Massachusetts Institute of Technology },
    title = { High-Speed Autonomous Obstacle Avoidance with Pushbroom Stereo },
    year = { 2016 },
}