A Cloud-Based Tool for Meteorite Recovery Using Drones and Machine Learning
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2026
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| author | Anderson, Seamus L. Devillepoix, Hadrien A. R. Lakerink, Lewis Tippaya, Sawitchaya Giancono, Dale P. Towner, Martin C. Clemente, Iona Cupák, Martin Rogers, Ashley F. Fairweather, John H. Walker, Mia Burgin, Daniel Frazer, Michael A. Deam, Sophie E. Pazderová, Veronika Sansom, Eleanor K. Hartig, Benjamin A. D. Branco, Hely C. Stevenson, Thomas Hatty, Isabella Zappatini, Anna Lagain, Anthony Lovelock, Tom Egal, Auriane Forman, Lucy Belton, David Windsor, Simon Saleheen, Shibli Leslie, Asher Poole, Gregory B. Langendam, Andrew Kirby, Rachel S. Tomkins, Andrew G. |
| author_facet | Anderson, Seamus L. Devillepoix, Hadrien A. R. Lakerink, Lewis Tippaya, Sawitchaya Giancono, Dale P. Towner, Martin C. Clemente, Iona Cupák, Martin Rogers, Ashley F. Fairweather, John H. Walker, Mia Burgin, Daniel Frazer, Michael A. Deam, Sophie E. Pazderová, Veronika Sansom, Eleanor K. Hartig, Benjamin A. D. Branco, Hely C. Stevenson, Thomas Hatty, Isabella Zappatini, Anna Lagain, Anthony Lovelock, Tom Egal, Auriane Forman, Lucy Belton, David Windsor, Simon Saleheen, Shibli Leslie, Asher Poole, Gregory B. Langendam, Andrew Kirby, Rachel S. Tomkins, Andrew G. |
| contents | We present a cloud-based tool that uses drones and machine learning to help recover instrumentally observed meteorite falls. We showcase a collection of improvements made upon previous iterations of our system, as well as detail the successes and limitations of this technique when applied to observed meteorite falls in South and Western Australia. This tool is available to the meteoritics research community upon request at https://find.gfo.rocks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_19179 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | A Cloud-Based Tool for Meteorite Recovery Using Drones and Machine Learning Anderson, Seamus L. Devillepoix, Hadrien A. R. Lakerink, Lewis Tippaya, Sawitchaya Giancono, Dale P. Towner, Martin C. Clemente, Iona Cupák, Martin Rogers, Ashley F. Fairweather, John H. Walker, Mia Burgin, Daniel Frazer, Michael A. Deam, Sophie E. Pazderová, Veronika Sansom, Eleanor K. Hartig, Benjamin A. D. Branco, Hely C. Stevenson, Thomas Hatty, Isabella Zappatini, Anna Lagain, Anthony Lovelock, Tom Egal, Auriane Forman, Lucy Belton, David Windsor, Simon Saleheen, Shibli Leslie, Asher Poole, Gregory B. Langendam, Andrew Kirby, Rachel S. Tomkins, Andrew G. Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics Machine Learning We present a cloud-based tool that uses drones and machine learning to help recover instrumentally observed meteorite falls. We showcase a collection of improvements made upon previous iterations of our system, as well as detail the successes and limitations of this technique when applied to observed meteorite falls in South and Western Australia. This tool is available to the meteoritics research community upon request at https://find.gfo.rocks. |
| title | A Cloud-Based Tool for Meteorite Recovery Using Drones and Machine Learning |
| topic | Earth and Planetary Astrophysics Instrumentation and Methods for Astrophysics Machine Learning |
| url | https://arxiv.org/abs/2605.19179 |