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Onboard Stereo Vision for Drone Pursuit or Sense and Avoid

Show simple item record Cigla, Cevahir Thakker, Rohan Matthies, Larry 2020-05-04T16:51:14Z 2020-05-04T16:51:14Z 2018-06-18
dc.identifier.citation The Thirtieth IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, Utah, June 18 - 22, 2018 en_US
dc.identifier.clearanceno 18-2077
dc.description.abstract Wedescribeanew,on-board,shortrangeperceptionsystem that enables micro aerial vehicles (MAVs) to detect, track, and follow or avoid nearby drones (within 2-20 meters) in GPS-denied environments. Each vehicle is able to sense its neighborhood and adapt its motion accordingly without use of centralized reasoning or inter-vehicle communication. To enable a lightweight, low power solution, on-board stereo cameras are used for detection and tracking with depth images, while a downward-looking camera and an inertial measurement unit are used to estimate the position of the observer without use of GPS. We illustrate the robustness and accuracy of this approach through real-time, outdoor leader-follower experiments with three quadrotors. Our experiments show that state-of-art trackers are far less robust in detection against cluttered background. This demonstrates that stereo vision is a highly effective approach to perception for safe navigation of multiple MAVs in close proximity. en_US
dc.description.sponsorship NASA/JPL en_US
dc.language.iso en_US en_US
dc.publisher Pasadena, CA: Jet Propulsion Laboratory, National Aeronautics and Space Administration, 2018 en_US
dc.title Onboard Stereo Vision for Drone Pursuit or Sense and Avoid en_US
dc.type Preprint en_US

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