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Publication Title | High-Speed Autonomous Obstacle Avoidance with Pushbroom Stereo

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High-Speed Autonomous Obstacle Avoidance with Pushbroom Stereo
Andrew J. Barry
Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology Cambridge, MA, USA abarry@csail.mit.edu
Peter R. Florence
Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology Cambridge, MA, USA peteflo@csail.mit.edu
Russ Tedrake
Computer Science and Artificial Intelligence Lab Massachusetts Institute of Technology Cambridge, MA, USA russt@csail.mit.edu
Abstract
We present the design and implementation of a small autonomous unmanned aerial vehicle capable of high-speed flight through complex natural environments. Using only onboard GPS-denied sensing and computation, we perform obstacle detection, planning, and feedback control in realtime. We present a novel integrated approach to perception and control using pushbroom stereo, which exploits forward motion to enable efficient obstacle detection and avoidance using lightweight processors on a UAV. Our use of model-based planning and control techniques allows us to track precise trajectories that avoid obstacles identified by the vision system. We demon- strate a complete working system detecting obstacles at 120 Hz and 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 using 3D geometric information.

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