WO2017099568A1 - Method for planning overflight of irregular polygons using two or more unmanned aerial vehicles for precision agriculture using multispectral and hyperspectral aerial image analysis - Google Patents

Method for planning overflight of irregular polygons using two or more unmanned aerial vehicles for precision agriculture using multispectral and hyperspectral aerial image analysis Download PDF

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Publication number
WO2017099568A1
WO2017099568A1 PCT/MX2015/000165 MX2015000165W WO2017099568A1 WO 2017099568 A1 WO2017099568 A1 WO 2017099568A1 MX 2015000165 W MX2015000165 W MX 2015000165W WO 2017099568 A1 WO2017099568 A1 WO 2017099568A1
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polygon
multispectral
unmanned aerial
aerial vehicles
planning
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PCT/MX2015/000165
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Spanish (es)
French (fr)
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Jose Antonio Pacheco Sanchez
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Jose Antonio Pacheco Sanchez
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Priority to PCT/MX2015/000165 priority Critical patent/WO2017099568A1/en
Publication of WO2017099568A1 publication Critical patent/WO2017099568A1/en

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    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01B—SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL
    • A01B79/00—Methods for working soil
    • G—PHYSICS
    • G03—PHOTOGRAPHY; CINEMATOGRAPHY; ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ELECTROGRAPHY; HOLOGRAPHY
    • G03B—APPARATUS OR ARRANGEMENTS FOR TAKING PHOTOGRAPHS OR FOR PROJECTING OR VIEWING THEM; APPARATUS OR ARRANGEMENTS EMPLOYING ANALOGOUS TECHNIQUES USING WAVES OTHER THAN OPTICAL WAVES; ACCESSORIES THEREFOR
    • G03B37/00—Panoramic or wide-screen photography; Photographing extended surfaces, e.g. for surveying; Photographing internal surfaces, e.g. of pipe
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
    • Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture

Definitions

  • the present invention relates to a method of flying over predefined crop fields using two or more computer-controlled drones and scanning to achieve photographic photography.
  • UAVs unmanned aerial vehicles
  • helicopters helicopters and multicopters
  • a permanent challenge is how to better control UAVs for each of these particular uses or in the performance of different tasks.
  • a UAV that is receiving more and more attention is the multirotor or multicopter.
  • This UAV is a helicopter with more than two rotors and multicopters often use fixed pitch motors, so that the movement control of the vehicle is achieved by varying the relative speed of each rotor to change the thrust and torque produced by each rotor.
  • multirotor aircraft Due to its ease of construction and control, multirotor aircraft are frequently used in aircraft model and radio control projects such that it provides a low-budget option for the creation of aerial photography and videos.
  • UAVs can carry as one payload one or more cameras and be remotely controlled to move over a specific geographic object or area.
  • unmanned aerial vehicles that need to be controlled in a centralized or organized way to perform the task.
  • numerous drones or unmanned aerial vehicles such as multicopters or flying robots can be used to provide surveillance of a geographical area.
  • the Swarm control can be used to control unmanned aerial vehicles while flying over the specific geographical area.
  • a swarm can be thought of as a system of self-organizing particles with numerous autonomous, reflective agents (for example, unmanned aerial vehicles are the particles in this case) whose collective movements are determined by local influences, such as wind and obstacles Like another UAV nearby.
  • Unmanned aerial vehicles are independent and are often controlled at the local level, which may include communication with a nearby UAV to determine which of them moves or if both should move to avoid an impending collision. Collisions are a problem since unmanned aerial vehicles move independently and randomly and will often have cross roads in the shared airspace. The swarm allows unmanned aerial vehicles to fly over a large area, which is useful in monitoring applications.
  • the design of dildos for use in unmanned aerial vehicles for swarms of objects or flying unmanned aerial vehicles remains a challenge for manufacturers of unmanned aerial vehicles and in some cases, collisions have proved very difficult to remove completely.
  • each UAV is controlled from a central controller that is normally placed on the ground.
  • a predetermined flight path is designed or selected for each UAV such that none intersects, and a tolerance or space envelope is offered to account for flight variations due to conditions such as the wind that can cause a UAV to deviate from its predefined course.
  • unmanned aerial vehicles operate independently without collisions.
  • Figure 1 shows the mission planning flowchart.
  • Figure 2 is the visualization of the delimitation of the region of interest using the google maps tool.
  • Figure 4 is the image of a field in the visual spectrum.
  • Figure 5 is the image of the same field in the red spectrum.
  • Figure 6 is the image of the same field in the NDVI spectrum.
  • the system has the ability to detect deficiencies of specific nutrients, irrigation, or presence of weeds or pests; by detecting the presence, in fas images, of the respective spectrate signatures, as well as the calculation of different indices used in Precision Agriculture. In addition to making suggestions to the user, about planning of application of agraqu ⁇ micos to correct the detected problems; making use of more information, coming from climatological analysis and predictions in the crop area (made outside the system).
  • the proposed method uses aerial photography taken on the crops to be analyzed, using one or more UAV aerial vehicles (for its acronym in English) with multispectral and hyperspectral sensors, in addition to GPS systems.
  • the first stage of the process is the planning of the mission (Fig. 1), which begins with the delimitation of the region of interest (RDl), drawing a polygon on a map on the system platform. (Fig. 2) These maps are taken from Google Maps, so they are free to use and have georeferencing; saving time and increasing the practicality of the procedure.
  • the result is a KML file with a series of geodetic coordinates that describe the polygon.
  • the next step in the mission planning procedure is the specification to the system of the necessary parameters, such as: UAV model to be used (for consideration of flight capabilities and autonomy), UAV flight speed and height, wind speed and direction, percentages of horizontal and vertical overlap of photographs.
  • UAV model to be used for consideration of flight capabilities and autonomy
  • UAV flight speed and height for consideration of flight capabilities and autonomy
  • wind speed and direction percentages of horizontal and vertical overlap of photographs.
  • the system will automatically determine the number of UAVs needed to cover the RDL completely, in the most efficient way possible. If the system considers the use of more than one UAV, the RDI will be partitioned and a part of it will be assigned to each of the UAVs involved. Otherwise, the system will assign the complete RDI to a single UAV.
  • the partitioning proposes an algorithm that receives as input a region specified as a polygon, which may be non-convex and not simple (may contain empty spaces within the polygon) and also receives the number of UAVs and their initial position on the periphery of the polygon.
  • the next step in the mission planning process is the multispectral or hyperspectral scan or aerial scan; which consists in determining the routes that the aircraft will follow, so that the RDI is photographed completely.
  • the routes determined by the system are usually zigzag.
  • Each scan line is called the flight line (Fig. 4 and 5).
  • the process used begins by converting the geodetic coordinates, which specify the polygon, to Cartesian coordinates in a local navigation reference frame (NED). This conversion is necessary to be able to use planning algorithms in Euclidean spaces. From that moment it is assumed that the surface to be explored has no curvature. This assumption is reasonable if we compare the size of the land with respect to the land area.
  • the conclusion of the mission planning process is the generation of GPX files by the system, which contain the waypoints and flight routes georeferenced for one or multiple UAVs.
  • the next stage of the process is the execution of the mission (fig. 6).
  • This stage begins with the introduction to the system of the product obtained in the planning of the mission; this being the GPX files generated.
  • This introduction is made through the software included with UAVs, or through free tools available, such as Mission Planner software.
  • the next step is to perform the aerial scan or scan, through the selected sensors and cameras. Captured images are saved in the camera memory. Which are georeferenced and ready for post processing. Completing the stage of mission execution.

Abstract

The invention relates to a method by means of which it is possible to use a plurality of unmanned aerial vehicles that are radio controlled by means of a computer, to generate a multispectral photographic map of a crop field in order to generate information that helps to improve crop yield and to determine the presence of diseases, pests and weeds.

Description

MÉTODO DE PLANEACION DE SOBREVUELO DE POLIGONOS IRREGULARES UTILIZANDO DOS O MAS VEHÍCULOS AÉREOS NO TRIPULADOS PARA AGRICULTURA DE PRECISIÓN POR ANÁLISIS MULTIESPECTRAL E HIPERESPECTRAL DE IMÁGENES AÉREAS.  METHOD OF PLANNING FLIGHT OF IRREGULAR POLYGONS USING TWO OR MORE AIR VEHICLES NOT TRIPULATED FOR PRECISION AGRICULTURE FOR MULTIESPECTRAL AND HYPERESPECTRAL ANALYSIS OF AIR IMAGES.
CAMPO TÉCNICO DE LA INVENCIÓN La presente invención se refiere a un método para sobrevolar campos de cultivo predefinidos utilizando dos o mas drones controlados por computadora y hacer barrido para lograr un ¡ñapeo fotográfico. TECHNICAL FIELD OF THE INVENTION The present invention relates to a method of flying over predefined crop fields using two or more computer-controlled drones and scanning to achieve photographic photography.
ANTECEDENTES BACKGROUND
En los últimos años, ha habido un creciente interés en la utilización de vehículos aéreos no tripulados (UAV) como control remoto drones / aviones, helicópteros y multicopteros para realizar una amplia variedad de tareas. Un desafío permanente, sin embargo, es cómo controlar mejor los UAVs para cada uno de estos usos particulares o en el desempeño de tareas diferentes. In recent years, there has been a growing interest in the use of unmanned aerial vehicles (UAVs) such as remote control drones / airplanes, helicopters and multicopters to perform a wide variety of tasks. A permanent challenge, however, is how to better control UAVs for each of these particular uses or in the performance of different tasks.
Un UAV que está recibiendo cada vez más atención es el multirotor o multicopter. Este UAV es un helicóptero con más de dos rotores y multicopteros a menudo utilizan motores de paso fijo con lo que el control de movimiento del vehículo se consigue variando ia velocidad relativa de cada rotor para cambiar el empuje y ei par producido por cada rotor. Debido a su facilidad de la construcción y control, aviones multirotor se utilizan con frecuencia en los proyectos de modelos de aviones y control de radío tal que proporcione una opción de bajo presupuesto para la creación de ia fotografía aérea y vídeos. En estas impiementaciones, los UAVs pueden llevar como carga útil una o más cámaras y ser controlado a distanda para moverse sobre un objeto o área geográfica específica. A UAV that is receiving more and more attention is the multirotor or multicopter. This UAV is a helicopter with more than two rotors and multicopters often use fixed pitch motors, so that the movement control of the vehicle is achieved by varying the relative speed of each rotor to change the thrust and torque produced by each rotor. Due to its ease of construction and control, multirotor aircraft are frequently used in aircraft model and radio control projects such that it provides a low-budget option for the creation of aerial photography and videos. In these impiementations, UAVs can carry as one payload one or more cameras and be remotely controlled to move over a specific geographic object or area.
En algunas aplicaciones, es deseable o útil realizar una tarea mediante el uso de dos o más vehículos aéreos no tripulados que necesitan ser controlados de una manera centralizada o organizada para realizar ia tarea. Por ejemplo, numerosos aviones no tripulados o vehículos aéreos no tripulados como multicopteros o robots que vuelan se puede utilizar para proporcionar vigilancia de una zona geográfica, En tal aplicación, el control de enjambre se puede usar para controlar los vehículos aéreos no tripulados mientras vuelan sobre la zona geográfica específica. Un enjambre puede ser pensado como un sistema de partículas de auto-organización con numerosos agentes autónomos, reflexivos (por ejemplo, vehículos aéreos no tripulados son las partículas en este caso) cuyos movimientos colectivos los determinen las influencias locales, tales como el viento y obstáculos como otro UAV cerca. In some applications, it is desirable or useful to perform a task by using two or more unmanned aerial vehicles that need to be controlled in a centralized or organized way to perform the task. For example, numerous drones or unmanned aerial vehicles such as multicopters or flying robots can be used to provide surveillance of a geographical area. In such an application, the Swarm control can be used to control unmanned aerial vehicles while flying over the specific geographical area. A swarm can be thought of as a system of self-organizing particles with numerous autonomous, reflective agents (for example, unmanned aerial vehicles are the particles in this case) whose collective movements are determined by local influences, such as wind and obstacles Like another UAV nearby.
Los vehículos aéreos no tripulados son independientes y están controlados a menudo a nivel local, lo que puede incluir la comunicación con un UAV cerca para determinar cuál de ellas se mueve o si ambas debe moverse para evitar una colisión inminente. Las colisiones son un problema ya que los vehículos aéreos no tripulados se mueven de forma independiente y al azar y a menudo tendrán caminos de cruce en el espacio aéreo compartido. El enjambre permite que los vehículos aéreos no tripulados puedan volar sobre un área grande, que es útil en aplicaciones de monitoreo. Sin embargo, el diseño de consoladores para su uso en vehículos aéreos no tripulados para enjambres de objetos o vehículos aéreos no tripulados voladores sigue siendo un reto a los fabricantes de vehículos aéreos no tripulados y en algunos casos, las colisiones han demostrado ser muy difíciles de eliminar por completo.  Unmanned aerial vehicles are independent and are often controlled at the local level, which may include communication with a nearby UAV to determine which of them moves or if both should move to avoid an impending collision. Collisions are a problem since unmanned aerial vehicles move independently and randomly and will often have cross roads in the shared airspace. The swarm allows unmanned aerial vehicles to fly over a large area, which is useful in monitoring applications. However, the design of dildos for use in unmanned aerial vehicles for swarms of objects or flying unmanned aerial vehicles remains a challenge for manufacturers of unmanned aerial vehicles and in some cases, collisions have proved very difficult to remove completely.
Cuando se utilizan varios vehículos aéreos no tripulados para realizar tareas, otras técnicas de control se han utilizado para permitir su uso seguro. En algunas aplicaciones, las colisiones son un riesgo aceptado del método de control, con el área bajo ¡os robots voladores que se mantiene libre de observadores humanos. En otras aplicaciones, cada UAV se controla desde un controlador central que se coloca normalmente en el suelo. Una trayectoria de vuelo predeterminada está diseñado o seleccionado para cada UAV tal que ninguno se cruza, y una tolerancia o envolvente espacial se ofrece para dar cuenta de variaciones vuelo debido a condiciones tales, como el viento que puede causar que un UAV se desvíe de su curso predefinido. En estas aplicaciones, los vehículos aéreos no tripulados operan de forma independiente sin que ocurran colisiones. When several unmanned aerial vehicles are used to perform tasks, other control techniques have been used to allow their safe use. In some applications, collisions are an accepted risk of the control method, with the area under the flying robots that remains free of human observers. In other applications, each UAV is controlled from a central controller that is normally placed on the ground. A predetermined flight path is designed or selected for each UAV such that none intersects, and a tolerance or space envelope is offered to account for flight variations due to conditions such as the wind that can cause a UAV to deviate from its predefined course. In these applications, unmanned aerial vehicles operate independently without collisions.
BREVE DESCRIPCIÓN DE FIGURAS BRIEF DESCRIPTION OF FIGURES
La figura 1 muestra el diagrama de flujo de planeación de la misión. Figure 1 shows the mission planning flowchart.
La figura 2 Es la visuaíización de la delimitación de la región de interés haciendo uso de la herramienta de google maps. Figure 2 is the visualization of the delimitation of the region of interest using the google maps tool.
La figura 4 es la imagen de un campo en el espectro visual.  Figure 4 is the image of a field in the visual spectrum.
La figura 5 es la imagen deI mismo campo en el espectro del rojo.  Figure 5 is the image of the same field in the red spectrum.
La figura 6 es la imagen del mismo campo en el espectro NDVI.  Figure 6 is the image of the same field in the NDVI spectrum.
DESCRIPCIÓN DETALLADA DE LA INVENCIÓN El sistema tiene la capacidad de detectar deficiencias de nutrientes específicos, de irrigación, o presencia de maleza o plagas; mediante la detección de presencia, en fas imágenes, de las respectivas firmas espectrates, así como el cálculo de diferentes índices utilizados en Agricultura de Precisión. Además de hacer sugerencias al usuario, sobre planeación de aplicación de agraquímicos para corregir los problemas detectados; haciendo usó de más información, procedente de análisis y predicciones climatológicas en la zona del cultivo (realizados fuera del sistema). DETAILED DESCRIPTION OF THE INVENTION The system has the ability to detect deficiencies of specific nutrients, irrigation, or presence of weeds or pests; by detecting the presence, in fas images, of the respective spectrate signatures, as well as the calculation of different indices used in Precision Agriculture. In addition to making suggestions to the user, about planning of application of agraquímicos to correct the detected problems; making use of more information, coming from climatological analysis and predictions in the crop area (made outside the system).
El método propuesto utiliza fotografía aérea tomadas sobre los cultivos a analizar, utilizando para ello, uno o mas vehículos aéreos no tripulados UAV (por sus siglas en ingles) con sensores multiespectrales e hiperespectrales, además de sistemas GPS. La primera etapa del proceso es la planeación de ta misión (Fig. 1), la cual, inicia con la delimitación de ia región de interés (RDl), trazando un polígono sobre un mapa en la plataforma del sistema. (Fig. 2) Estos mapas son tomados de Google Maps, por lo que son de uso libre y cuentan con georreferenciación; ahorrando tiempo y aumentando la practicidad del procedimiento. El resultado es un archivo KML con una serie de coordenadas geodésicas que describen el polígono.  The proposed method uses aerial photography taken on the crops to be analyzed, using one or more UAV aerial vehicles (for its acronym in English) with multispectral and hyperspectral sensors, in addition to GPS systems. The first stage of the process is the planning of the mission (Fig. 1), which begins with the delimitation of the region of interest (RDl), drawing a polygon on a map on the system platform. (Fig. 2) These maps are taken from Google Maps, so they are free to use and have georeferencing; saving time and increasing the practicality of the procedure. The result is a KML file with a series of geodetic coordinates that describe the polygon.
El siguiente paso del procedimiento de la planeación de la misión, es la especificación al sistema, de los parámetros necesarios, tales como: modelo de UAV a utilizar (para consideración de capacidades de vuelo y autonomía), velocidad y altura de vuelo del UAV, velocidad y dirección del viento, porcentajes de traslape horizontal y vertical de fotografías. Entre otros parámetros mencionados a continuación en la Fig. 3.  The next step in the mission planning procedure is the specification to the system of the necessary parameters, such as: UAV model to be used (for consideration of flight capabilities and autonomy), UAV flight speed and height, wind speed and direction, percentages of horizontal and vertical overlap of photographs. Among other parameters mentioned below in Fig. 3.
Una vez delimitada la RDl e introducidos tos parámetros descritos previamente; el sistema determinará, de forma automática, el número de UAVs necesarios para cubrir la RDl por completo, de la forma más eficiente posible. Si el sistema considera ta utilización de más de un UAV, se particionara la RDI y asignará una parte de ella a cada uno de tos UAVs involucrados. De lo contrario, el sistema asignará la RDI completa a un único UAV. Once the RDl is delimited and the parameters previously described have been introduced; The system will automatically determine the number of UAVs needed to cover the RDL completely, in the most efficient way possible. If the system considers the use of more than one UAV, the RDI will be partitioned and a part of it will be assigned to each of the UAVs involved. Otherwise, the system will assign the complete RDI to a single UAV.
EI particionamiento propone un algoritmo que recibe como entrada una región especificada como polígono, que puede ser no convexo y no simple (puede contener espacios vacíos dentro deI polígono) y además recibe el número de UAVs y su posición inicial en ia periferia del polígono.  The partitioning proposes an algorithm that receives as input a region specified as a polygon, which may be non-convex and not simple (may contain empty spaces within the polygon) and also receives the number of UAVs and their initial position on the periphery of the polygon.
El siguiente paso del proceso de planeación de ía misión, es el Barrido o escaneo aéreo multiespectral o hiperespectral; el cual consiste en determinar las rutas que la{s) aeronave(s) seguirá(n), de tal forma que se capture fotográficamente por completo la RDI. Los recorridos determinados por el sistema son por lo general de forma zigzag. Cada línea del barrido se le denomina línea de vuelo (Fig. 4 y 5). El proceso utilizado comienza por convertir las coordenadas geodésicas, que especifican el polígono, a coordenadas cartesianas en un marco de referencia de navegación local (NED). Esta conversión es necesaria para poder utilizar algoritmos de planificación en espacios euclidsanos. A partir de ese momento se supone que la superficie a explorar no tiene curvatura. Esta suposición es razonable si comparamos ei tamaño del terreno con respecto de la superficie terrestre.  The next step in the mission planning process is the multispectral or hyperspectral scan or aerial scan; which consists in determining the routes that the aircraft will follow, so that the RDI is photographed completely. The routes determined by the system are usually zigzag. Each scan line is called the flight line (Fig. 4 and 5). The process used begins by converting the geodetic coordinates, which specify the polygon, to Cartesian coordinates in a local navigation reference frame (NED). This conversion is necessary to be able to use planning algorithms in Euclidean spaces. From that moment it is assumed that the surface to be explored has no curvature. This assumption is reasonable if we compare the size of the land with respect to the land area.
La conclusión del proceso de planeación de la misión, es la generación por el sistema de los archivos GPX, los cuales contienen los waypoints y rutas de vuelo georreferendadas para uno o múltiples UAVs.  The conclusion of the mission planning process is the generation of GPX files by the system, which contain the waypoints and flight routes georeferenced for one or multiple UAVs.
La siguiente etapa del proceso es la ejecución de la misión (fig. 6). The next stage of the process is the execution of the mission (fig. 6).
Esta etapa comienza con la introducción al sistema del producto obtenido en la planeación de ia misión; siendo éste los archivos GPX generados. Dicha introducción se realiza mediante el software incluido con los UAVs, o bien medíante herramientas libres disponibles, tai como el software Mission Planner. This stage begins with the introduction to the system of the product obtained in the planning of the mission; this being the GPX files generated. This introduction is made through the software included with UAVs, or through free tools available, such as Mission Planner software.
El siguiente paso es la realización del escaneo aéreo o barrido, medíante los sensores y cámaras seleccionados. Las imágenes capturadas se guardan en ia memoria de la cámara. Las cuales se encuentran georreferenciadas y listas para su pos procesamiento. Dando por terminada la etapa de ejecución de la misión.  The next step is to perform the aerial scan or scan, through the selected sensors and cameras. Captured images are saved in the camera memory. Which are georeferenced and ready for post processing. Completing the stage of mission execution.

Claims

REIVINDICACIONES
1. Un método de control para dos o mas vehículos aéreos no tripulados (ORONES) de monitorao fotográfico multiespectral e hiperespectrai para el análisis de campos de cultivo con la finalidad de identificar deficiencias que impidan el óptimo desarrollo de las plantas, asi como determinar el área geográfica específica y brindar soluciones a dichas deficiencias. 1. A control method for two or more unmanned aerial vehicles (ORONES) of multispectral and hyperspectrai photographic monitoring for the analysis of crop fields in order to identify deficiencies that impede the optimal development of plants, as well as determine the area specific geographical and provide solutions to these deficiencies.
2. EI método de la reivindicación 1 que utiliza mapas georreferenciados tomados de google maps para delimitar el polígono a escanear desde la plataforma del sistema obteniendo coordenadas geodésicas que se convierten en cartesianas para su utilización.  2. The method of claim 1 that uses geo-referenced maps taken from google maps to delimit the polygon to be scanned from the system platform obtaining geodetic coordinates that become Cartesian for use.
3. Los vehículos aéreos no tripulados de ia reivindicación 1 que pueden ser de tipo ala defta o cuadcopteros y que portan sistemas de navegación GPS y comunicación de radio control con una base para el control de vuelo, que además portan una cámara de alta resolución multiespectral e hiperespectrai.  3. The unmanned aerial vehicles of claim 1 which can be of the defta or quadcopter type and that carry GPS navigation and radio control communication systems with a base for flight control, which also carry a multispectral high resolution camera and hyperspectrai.
4. EI método de la reivindicación 1 que además utiliza parámetros específicos tales como modelo de UAVs, velocidad y altura a la que se moverá, velocidad y dirección del viento y otros parámetros específicos del tipo de cámara que utilizara mencionados anteriormente en esta patente.  4. The method of claim 1 which also uses specific parameters such as UAV model, speed and height to which it will move, wind speed and direction and other parameters specific to the type of camera that will be used previously mentioned in this patent.
5. El método de la reivindicación 1 que para el calculo deI numero de UAVs utiliza un algoritmo que recibe como entrada una región especificada como polígono, que puede ser no convexo y no simple puede contener espacios vacíos dentro del polígono, y además recibe el número de UAVs y su posición inicial en la periferia del polígono 5. The method of claim 1 which for the calculation of the number of UAVs uses an algorithm that receives as input a region specified as a polygon, which can be non-convex and not simple can contain empty spaces within the polygon, and also receives the number of UAVs and their initial position on the periphery of the polygon
6. El método de la reivindicación 1 que en un primer paso utiliza una interfaz de usuario por medio de la cual se descarga información de google maps para delimitar el polígono que conforma el campo a analizar y obtiene información adicional de sensores de tierra como velocidad y dirección del aire, humedad, temperatura, además de información brindada por ei usuario como el tipo de cultivo y que a su vez entrega los resultados del análisis final. 6. The method of claim 1 which in a first step uses a user interface by means of which information is downloaded from google maps to delimit the polygon that makes up the field to be analyzed and obtains additional information from ground sensors such as speed and air direction, humidity, temperature, in addition to information provided by the user as the type of crop and which in turn delivers the results of the final analysis.
7. El método de la reivindicación 1 que en sus segundo paso planea y calcula la misión en base a las delimitaciones del polígono y datos de usuario como altura del sobrevuelo y velocidad de desplazamiento de la aeronave.  7. The method of claim 1, which in its second step plans and calculates the mission based on the boundaries of the polygon and user data such as the height of the flyby and the speed of travel of the aircraft.
8. Ei método de ía reivindicación 1 que en el tercer paso que después de realizar eI sobrevuelo en zigzag del campo objeto, realiza el acondicionamiento de imágenes por medio de georferenciación y ortorectificación para brindar un mapa exacto del terreno. 8. The method of claim 1 that in the third step that after performing the zigzag overflight of the object field, performs the conditioning of images by means of georeferencing and orthorectification to provide an exact map of the terrain.
9. El método de la reivindicación 1 que en un cuarto paso realiza ei análisis del mapa multiespectral e hiperespectral y que a su vez genera reportes (diagnósticos) de las áreas especificas y que entrega junto con ías imágenes georeferenciadas por medio de dicha interfaz de usuario de la reivindicación 6. 9. The method of claim 1 which in a fourth step performs the multispectral and hyperspectral map analysis and which in turn generates reports (diagnoses) of the specific areas and that delivers along with the georeferenced images through said user interface of claim 6.
PCT/MX2015/000165 2015-12-11 2015-12-11 Method for planning overflight of irregular polygons using two or more unmanned aerial vehicles for precision agriculture using multispectral and hyperspectral aerial image analysis WO2017099568A1 (en)

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