Successful Recovery of an Observed Meteorite Fall Using Drones and Machine Learning

Anderson, Seamus L. and Towner, Martin C. and Fairweather, John and Bland, Philip A. and Devillepoix, Hadrien A. R. and Sansom, Eleanor K. and Cupák, Martin and Shober, Patrick M. and Benedix, Gretchen K. (2022) Successful Recovery of an Observed Meteorite Fall Using Drones and Machine Learning. The Astrophysical Journal Letters, 930 (2). L25. ISSN 2041-8205

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We report the first-time recovery of a fresh meteorite fall using a drone and a machine-learning algorithm. The fireball was observed on 2021 April 1 over Western Australia by the Desert Fireball Network, for which a fall area was calculated for the predicted surviving mass. A search team arrived on-site and surveyed 5.1 km2 area over a 4 day period. A convolutional neural network, trained on previously recovered meteorites with fusion crusts, processed the images on our field computer after each flight. Meteorite candidates identified by the algorithm were sorted by team members using two user interfaces to eliminate false positives. Surviving candidates were revisited with a smaller drone, and imaged in higher resolution, before being eliminated or finally being visited in person. The 70 g meteorite was recovered within 50 m of the calculated fall line, demonstrating the effectiveness of this methodology, which will facilitate the efficient collection of many more observed meteorite falls.

Item Type: Article
Subjects: Eprints STM archive > Physics and Astronomy
Depositing User: Unnamed user with email admin@eprints.stmarchive
Date Deposited: 06 May 2023 10:17
Last Modified: 18 Sep 2023 11:48

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