{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T09:47:16Z","timestamp":1749116836324,"version":"3.40.5"},"reference-count":25,"publisher":"American Institute of Aeronautics and Astronautics (AIAA)","issue":"10","funder":[{"name":"Vidi NWO Domain TTW","award":["18378"],"award-info":[{"award-number":["18378"]}]}],"content-domain":{"domain":["arc.aiaa.org"],"crossmark-restriction":true},"short-container-title":["Journal of Aerospace Information Systems"],"published-print":{"date-parts":[[2023,10]]},"abstract":"<jats:p> Loss of control (LOC) is a prevalent cause of drone crashes. Onboard prevention systems should be designed requiring low computing power, for which data-driven techniques provide a promising solution. This study proposes the use of recurrent neural networks (RNNs) for LOC prediction. Four architectures were trained in order to identify which RNN configuration is most suitable and if this model can predict LOC for changing aerodynamic characteristics, wind conditions, quadcopter types, and LOC events. One-hundred and seventy-two real-world LOC events were conducted using a 53\u00a0g Tiny Whoop, a 73\u00a0g URUAV UZ85, and a 265\u00a0g GEPRC CineGO quadcopter. For these flights, LOC was initiated by demanding an excessive yaw rate (2000\u00a0deg\/s), which provokes an unrecoverable upset and subsequent crash. All RNNs were trained using only onboard sensor measurements. It was found that the commanded rotor values provided the clearest early warning signals for LOC because these values showed saturation before LOC. Moreover, all four architectures could correctly and reliably predict the impending LOC event 2\u00a0s before it actually occurred. Furthermore, to investigate generality of the methodology, the predictors were successfully applied to flight data in which the quadcopter mass, blade diameter, and blade count were varied. <\/jats:p>","DOI":"10.2514\/1.i011231","type":"journal-article","created":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T10:59:21Z","timestamp":1690973961000},"page":"648-659","update-policy":"https:\/\/doi.org\/10.2514\/aiaa_crossmarkpolicy","source":"Crossref","is-referenced-by-count":2,"title":["Loss-of-Control Prediction of a Quadcopter Using Recurrent Neural Networks"],"prefix":"10.2514","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3898-1820","authenticated-orcid":false,"given":"Anique V.N.","family":"Altena","sequence":"first","affiliation":[{"name":"Delft University of Technology, 2629 HS Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jasper J.","family":"van Beers","sequence":"additional","affiliation":[{"name":"Delft University of Technology, 2629 HS Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Coen C.","family":"de Visser","sequence":"additional","affiliation":[{"name":"Delft University of Technology, 2629 HS Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1387","reference":[{"key":"r1","doi-asserted-by":"publisher","DOI":"10.2514\/6.2017-3269"},{"key":"r3","doi-asserted-by":"publisher","DOI":"10.2514\/6.2010-8142"},{"key":"r4","doi-asserted-by":"publisher","DOI":"10.2514\/1.G000252"},{"key":"r5","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001743"},{"key":"r6","doi-asserted-by":"publisher","DOI":"10.2514\/6.2016-0094"},{"key":"r7","doi-asserted-by":"publisher","DOI":"10.1177\/0954410019825942"},{"key":"r8","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001835"},{"key":"r9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-11690-2"},{"key":"r10","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001729"},{"key":"r11","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001728"},{"key":"r12","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001747"},{"key":"r13","doi-asserted-by":"publisher","DOI":"10.2514\/1.G001731"},{"key":"r14","doi-asserted-by":"publisher","DOI":"10.2514\/1.G003834"},{"key":"r15","doi-asserted-by":"publisher","DOI":"10.1007\/s10846-021-01393-3"},{"key":"r16","doi-asserted-by":"publisher","DOI":"10.2514\/6.2021-0778"},{"key":"r18","doi-asserted-by":"publisher","DOI":"10.2514\/6.2019-0948"},{"key":"r19","doi-asserted-by":"publisher","DOI":"10.2514\/1.I010846"},{"key":"r20","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2018.05.050"},{"key":"r21","doi-asserted-by":"publisher","DOI":"10.1162\/089976600300015015"},{"key":"r23","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2020.107929"},{"key":"r24","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2950985"},{"key":"r25","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2020.103678"},{"key":"r27","doi-asserted-by":"publisher","DOI":"10.1109\/TIM.2019.2935576"},{"key":"r28","doi-asserted-by":"publisher","DOI":"10.2514\/1.G003184"},{"key":"r29","volume-title":"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems","author":"G\u00e9ron A.","year":"2019","edition":"2"}],"container-title":["Journal of Aerospace Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/arc.aiaa.org\/doi\/pdf\/10.2514\/1.I011231","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T12:42:21Z","timestamp":1695127341000},"score":1,"resource":{"primary":{"URL":"https:\/\/arc.aiaa.org\/doi\/10.2514\/1.I011231"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10]]},"references-count":25,"journal-issue":{"issue":"10","published-print":{"date-parts":[[2023,10]]}},"alternative-id":["10.2514\/1.I011231"],"URL":"https:\/\/doi.org\/10.2514\/1.i011231","relation":{},"ISSN":["1940-3151","2327-3097"],"issn-type":[{"type":"print","value":"1940-3151"},{"type":"electronic","value":"2327-3097"}],"subject":[],"published":{"date-parts":[[2023,10]]},"assertion":[{"value":"2022-12-16","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-05-15","order":1,"name":"revised","label":"Revised","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-06-08","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-08-02","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}