US 12,372,972 B2
Method for controlling a flight movement of an aerial vehicle for landing or for dropping a cargo, and aerial vehicle
Chris Hagen, Bad Lobenstein (DE); Florian Ölsner, Jena (DE); and Stefan Milz, Saalburg-Ebersdorf (DE)
Assigned to Spleenlab GmbH, (DE)
Filed by Spleenlab GmbH, Saalburg-Ebersdorf (DE)
Filed on Mar. 19, 2024, as Appl. No. 18/609,849.
Application 18/609,849 is a division of application No. 17/837,930, filed on Jun. 10, 2022.
Claims priority of application No. 10 2021 115 140.6 (DE), filed on Jun. 11, 2021.
Prior Publication US 2024/0264599 A1, Aug. 8, 2024
Int. Cl. B64U 70/00 (2023.01); B64C 39/02 (2023.01); B64D 47/08 (2006.01); B64U 101/30 (2023.01); B64U 101/60 (2023.01); G05D 1/00 (2024.01); G05D 1/617 (2024.01); G05D 1/654 (2024.01); G06T 7/70 (2017.01); G06V 10/82 (2022.01); G06V 20/17 (2022.01)
CPC G05D 1/0676 (2013.01) [B64C 39/024 (2013.01); B64D 47/08 (2013.01); G05D 1/0688 (2019.05); G05D 1/106 (2019.05); G05D 1/621 (2024.01); G05D 1/654 (2024.01); G05D 1/6546 (2024.01); G06T 7/70 (2017.01); G06V 10/82 (2022.01); G06V 20/17 (2022.01); B64U 70/00 (2023.01); B64U 2101/30 (2023.01); B64U 2101/60 (2023.01); B64U 2201/10 (2023.01); G06T 2207/10032 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30261 (2013.01)] 10 Claims
OG exemplary drawing
 
1. A method for controlling a flight movement of an aerial vehicle, for dropping a cargo by the aerial vehicle, comprising:
recording first image data using a first camera, wherein the first camera is provided on an aerial vehicle and configured to record a first area of ground, wherein the first image data is indicative of a first sequence of first camera images;
recording of second image data using a second camera, wherein the second camera is provided on the aerial vehicle and configured to record a second area of ground, wherein the second image data register a second sequence of second camera images;
processing the first and the second image data by means of an evaluation computer, comprising:
performing a first image analysis using a neural network and an artificial intelligence algorithm based on machine learning, of the first image data, wherein at least a first drop zone is thereby determined in the first area of ground, so as to drop a cargo of the aerial vehicle;
performing a second image analysis, which is conducted free of use of the artificial intelligence algorithm, of the second image data, wherein at least a second drop zone is thereby determined in the second area of ground, so as to drop a cargo of the aerial vehicle;
determining position coordinates of a clear drop zone, which is comprised by the first and the second drop zones, when a comparison reveals that the first and the second drop zones overlap, at least in the clear drop zone, wherein the overlap includes the first and the second drop zones clear of ground obstacles that could hinder the dropping of the cargo, said ground obstacles determined in at least one of the first and the second image analyses;
receiving position coordinates of a target drop site by a control processor of the aerial vehicle;
determining release characteristics, when a comparison of the position coordinates of the clear drop zone and the position coordinates of the target drop site reveals a match; and
transmitting the release characteristics, which are indicative of an availability of the target drop site for the dropping of the cargo, to the control processor of the aerial vehicle; and
controlling a flight movement of the aerial vehicle by the control processor, so as to drop the cargo on the target drop site.