Drone No-Fly Zone Warning Method, Device, Equipment, Storage Medium and Drone

Abstract

The present disclosure provides a method, device, equipment, storage medium and unmanned aerial vehicle for warning of no-fly zones, which can be applied to the field of unmanned aerial vehicle technology. The method includes: converting the longitude and latitude coordinates of the current position of the unmanned aerial vehicle into Gaussian coordinates; determining a target no-fly zone within the flight area of the unmanned aerial vehicle, wherein the area of the target no-fly zone is a polygon formed by sequentially connecting the head and tail of multiple first line segments; determining a target first line segment from the multiple first line segments according to the Gaussian coordinates of the unmanned aerial vehicle, wherein the ordinate of the Gaussian coordinates of the unmanned aerial vehicle is between the ordinates of the two endpoints of the target first line segment; determining the number of intersection points between a first ray and the target first line segment, wherein the first ray is generated with the coordinate point of the unmanned aerial vehicle as the endpoint and the positive x-axis direction as the ray direction; in the case where the number of intersection points is odd, determining that the current position of the unmanned aerial vehicle is within the target no-fly zone; and sending out a warning message based on the current position of the unmanned aerial vehicle.

Description

Technical Field

[0001] The present disclosure relates to the technical field of unmanned aerial vehicles, and more particularly, to a method, device, equipment, storage medium and unmanned aerial vehicle for warning of no-fly zones of unmanned aerial vehicles. Background Art

[0002] An unmanned aerial vehicle, abbreviated as UAV, is an unpiloted aircraft using a wireless remote control device and an autonomous program control. Compared with piloted aircraft, UAVs have been widely used in various fields such as agriculture, urban management, scientific research, environmental protection, and public security due to their own flexibility, portability, economy, and ease of operation.

[0003] The no-fly zone of an unmanned aerial vehicle, also known as a no-fly area, refers to an area where the flight of an unmanned aerial vehicle is prohibited. An unmanned aerial vehicle cannot take off from this area, nor can it fly into the no-fly area from other areas.

[0004] In the process of implementing the concept of the present disclosure, the inventors found that there are at least the following problems in the related art: In the related art, the method for calculating whether an unmanned aerial vehicle flies into a no-fly zone has low accuracy, and it is necessary to traverse all no-fly zones, increasing the calculation amount and reducing the calculation efficiency. Summary of the Invention

[0005] In view of this, the present disclosure provides a method, device, equipment, storage medium and unmanned aerial vehicle for warning of no-fly zones of unmanned aerial vehicles.

[0006] One aspect of the present disclosure provides a method for warning of no-fly zones of unmanned aerial vehicles, including:

[0007] Converting the longitude and latitude coordinates of the current position of the unmanned aerial vehicle into Gaussian coordinates;

[0008] Determining a target no-fly zone of the unmanned aerial vehicle in the flight area, wherein the area of the target no-fly zone is a polygon formed by sequentially connecting the heads and tails of multiple first line segments;

[0009] Determining a target first line segment from the multiple first line segments according to the Gaussian coordinates of the unmanned aerial vehicle, wherein the ordinate of the Gaussian coordinates of the unmanned aerial vehicle is between the ordinates of the two endpoints of the target first line segment;

[0010] Determining the number of intersection points between a first ray and the target first line segment, wherein the first ray is generated with the coordinate point of the unmanned aerial vehicle as the endpoint and the positive x-axis direction as the ray direction;

[0011] In the case where the number of intersection points is odd, determining that the current position of the unmanned aerial vehicle is located in the target no-fly zone;

[0012] Based on the current position of the unmanned aerial vehicle, sending out a warning message.

[0013] According to an embodiment of the present disclosure, determining the number of intersection points between the first ray and the target first line segment includes:

[0014] Determine the first slope of the line where the first endpoint of the target first line segment and the coordinate point of the drone are located, where the ordinate of the first endpoint is less than the ordinate of the drone;

[0015] Determine the second slope of the line where the target first line segment is located;

[0016] In the case where the first slope is greater than the second slope, determine that the first ray and the target first line segment have an intersection point;

[0017] Based on the intersection point, determine the number of intersection points between the first ray with the coordinate point of the drone as an endpoint and the x-axis as the ray direction and the target first line segment.

[0018] According to an embodiment of the present disclosure, the above method further includes:

[0019] Based on the model information and power information of the drone, determine the flight radius of the drone;

[0020] According to the flight radius, determine the flight area of the drone.

[0021] According to an embodiment of the present disclosure, determining the target no-fly zone of the drone within the flight area includes:

[0022] Obtain the no-fly zone of the area where the drone is located;

[0023] Determine the minimum circumscribed rectangle of the no-fly zone;

[0024] Based on the distances between the drone and all vertices in the minimum circumscribed rectangle, determine the target no-fly zone from the no-fly zone.

[0025] According to an embodiment of the present disclosure, determining the minimum circumscribed rectangle of the no-fly zone includes:

[0026] Determine the first straight line where any side of the no-fly zone is located;

[0027] Based on the first vertex in the no-fly zone that is farthest from the first straight line, determine the second straight line passing through the first vertex and parallel to the first straight line;

[0028] According to any point on the first straight line and the second straight line, determine the third straight line perpendicular to the first straight line, where the third straight line passes through the no-fly zone;

[0029] In the no-fly zone, determine the second vertex that is farthest from one side of the third straight line and the third vertex that is farthest from the other side of the third straight line;

[0030] Determine a fourth straight line passing through the second vertex and parallel to the third straight line, and a fifth straight line passing through the third vertex and parallel to the third straight line;

[0031] Determine the minimum circumscribed rectangle of the no-fly zone according to the area enclosed by the first straight line, the second straight line, the fourth straight line and the fifth straight line.

[0032] According to an embodiment of the present disclosure, the above method further includes:

[0033] Based on the warning information, update the flight route of the drone through the shortest path planning algorithm so that the drone avoids the target no-fly zone.

[0034] Another aspect of the present disclosure provides a warning device for a drone no-fly zone, including:

[0035] A conversion module for converting the longitude and latitude coordinates of the current position of the drone into Gaussian coordinates;

[0036] A first determination module for determining a target no-fly zone of the drone in the flight area, wherein the area of the target no-fly zone is a polygon formed by sequentially connecting the heads and tails of multiple first line segments;

[0037] A second determination module for determining a target first line segment from multiple first line segments according to the Gaussian coordinates of the drone, wherein the ordinate of the Gaussian coordinates of the drone is between the ordinates of the two endpoints of the target first line segment;

[0038] A third determination module for determining the number of intersection points between the first ray and the target first line segment, wherein the first ray is generated with the coordinate point of the drone as the endpoint and the positive direction of the x-axis as the ray direction;

[0039] A fourth determination module for determining that the current position of the drone is located in the target no-fly zone when the number of intersection points is odd;

[0040] A warning module for issuing a warning message based on the current position of the drone.

[0041] Another aspect of the present disclosure provides an electronic device, including: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the drone no-fly zone warning method.

[0042] Another aspect of the present disclosure provides a computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor executes the drone no-fly zone warning method.

[0043] Another aspect of the present disclosure provides a drone, including the above electronic device.

[0044] According to an embodiment of the present disclosure, by converting the longitude and latitude coordinates of a drone into Gauss coordinates, it is not necessary to approximate them as the coordinates of a planar coordinate system, which improves the accuracy of calculating whether the drone flies into a no-fly zone. The target first line segment is determined according to the relationship between the ordinate of the drone and the ordinates of the two endpoints of the first line segment. When the number of intersection points between the first ray and the target first line segment is odd, it is determined that the current position of the drone is located in the target no-fly zone. Only the target no-fly zones within the flight area of the drone need to be considered, and it is not necessary to calculate all no-fly zones, which reduces the amount of calculation. Therefore, at least partially, it overcomes the technical problems in the related art that the accuracy of the method for calculating whether a drone flies into a no-fly zone is low, and it is necessary to traverse all no-fly zones, increasing the amount of calculation and reducing the calculation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Through the following description of the embodiments of the present disclosure with reference to the drawings, the objectives, features, and advantages of the present disclosure and other aspects will become clearer. In the drawings:

[0046] Figure 1 Schematically shows a flowchart of a method for warning of a no-fly zone of a drone according to an embodiment of the present disclosure;

[0047] Figure 2 Schematically shows a schematic diagram of the relationship between a first ray and a target no-fly zone according to an embodiment of the present disclosure;

[0048] Figure 3 Schematically shows a schematic diagram of the minimum circumscribed rectangle of a no-fly zone of a drone according to an embodiment of the present disclosure;

[0049] Figure 4 Schematically shows a schematic diagram of a flight route of a drone updated by a shortest path planning algorithm according to an embodiment of the present disclosure;

[0050] Figure 5 Schematically shows a block diagram of a device for warning of a no-fly zone of a drone according to an embodiment of the present disclosure; and

[0051] Figure 6 Schematically shows a block diagram of an electronic device suitable for implementing a method for warning of a no-fly zone of a drone according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, obviously, one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present disclosure.

[0053] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0054] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0055] In the case of using expressions such as "at least one of A, B, and C, etc.", it should generally be interpreted in accordance with the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.). In the case of using expressions such as "at least one of A, B, or C, etc.", it should generally be interpreted in accordance with the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, or C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0056] In the related art, the algorithm for the no-fly zone of drones usually uses the Pnpoly algorithm, which is used to determine whether the target point in the coordinate system is inside or outside a specified polygon. The Pnpoly algorithm is also called the ray method, that is, if the number of intersection points of the ray generated from the target point to the positive x direction and the polygon is an odd number, then the point is considered to be inside the polygon, and if the number of intersection points with the polygon is an even number, then the point is considered not to be inside the polygon.

[0057] When the PNPOLY algorithm is used in the related technology, the longitude and latitude coordinates of the earth's curved surface are approximated as a plane coordinate system. When calculating the no-fly zone, all no-fly zones will be traversed, which wastes computing resources and reduces computing efficiency. The no-fly zone warning systems of many drones only warn drones after they enter the no-fly zone, and there is no next action. If the operator fails to discover it in time, the drone will remain in the no-fly zone, causing serious consequences.

[0058] In view of this, embodiments of the present disclosure provide a method, apparatus, device, storage medium, and unmanned aerial vehicle (UAV) for warning of no-fly zones of UAVs. The method includes converting the longitude and latitude coordinates of the current position of the UAV into Gauss coordinates; determining a target no-fly zone of the UAV within the flight area, where the area of the target no-fly zone is a polygon formed by sequentially connecting the heads and tails of multiple first line segments; determining a target first line segment from the multiple first line segments according to the Gauss coordinates of the UAV, where the ordinate of the Gauss coordinates of the UAV is between the ordinates of the two endpoints of the target first line segment; determining the number of intersection points between a first ray and the target first line segment, where the first ray is generated with the coordinate point of the UAV as the endpoint and the positive x-axis direction as the ray direction; determining that the current position of the UAV is within the target no-fly zone when the number of intersection points is odd; and sending a warning message based on the current position of the UAV.

[0059] Figure 1 Schematically shows a flowchart of a method for warning of no-fly zones of UAVs according to an embodiment of the present disclosure.

[0060] As Figure 1 shown, the method includes operations S101 to S106.

[0061] In operation S101, convert the longitude and latitude coordinates of the current position of the UAV into Gauss coordinates.

[0062] According to embodiments of the present disclosure, a UAV may include a fixed-wing UAV, a vertical takeoff and landing UAV, an airship, a helicopter, a multi-rotor UAV, a parafoil UAV, etc., but is not limited thereto. UAVs have the advantages of small size, low cost, convenient use, low requirements for the operating environment, and strong battlefield survivability. Therefore, UAVs play an outstanding role in both military and civilian aspects. In the military aspect, UAVs can be used as reconnaissance aircraft, target drones, etc. In the civilian aspect, UAVs can be used for aerial photography, express delivery, disaster relief, wildlife observation, mapping, news reporting, etc.

[0063] According to embodiments of the present disclosure, a real-time positioning device may be provided in the UAV so that the UAV can automatically obtain the longitude and latitude coordinates of the current position, or the real-time positioning device may receive a positioning instruction sent from the control system of the UAV to obtain the longitude and latitude coordinates of the current position of the UAV.

[0064] According to embodiments of the present disclosure, Gauss coordinates may be coordinates in a Gauss coordinate system, and the longitude and latitude coordinates of the current position of the UAV can be converted into Gauss coordinates through the following formulas (1) and (2):

[0065]

[0066]

[0067] Wherein, x represents the abscissa of the UAV in the Gaussian coordinate system, y represents the ordinate of the UAV in the Gaussian coordinate system, N represents the radius of curvature of the projection point of the UAV on the Earth, L represents the longitude of the projection point of the UAV on the Earth, B represents the latitude of the projection point of the UAV on the Earth, t = tan B, η = e 2 *cosB, e 2 represents the first eccentricity of the Earth, e represents the second eccentricity of the Earth, X 0 represents the arc length of the meridian starting from the equator when L = 0, and can be expressed by the following formula (3):

[0068] X 0 = a(1 - e 2 )(K 0 B + K 2 sin 2B + K 4 sin 4B + K 6 sin 6B + K 8 sin 8B) (3)

[0069] Wherein, a is the length of the semi-major axis of the ellipse, K 0 、K 2 、K 4 、K 6 、K 8 are coefficients related to the first eccentricity e 2 of the Earth, and K 0 、K 2 、K 4 、K 6 、K 8 are expressed by the following formulas (4) to (8):

[0070]

[0071]

[0072]

[0073]

[0074]

[0075] In operation S102, determine the target no-fly zone of the UAV within the flight area, wherein the area of the target no-fly zone is a polygon formed by sequentially connecting the heads and tails of multiple first line segments.

[0076] According to an embodiment of the present disclosure, the flight area of the unmanned aerial vehicle may be an area determined according to the flight altitude of the unmanned aerial vehicle, or may be an area determined according to the historical flight route of the unmanned aerial vehicle. For example, the flight altitude of unmanned aerial vehicle A is 1000 meters, and the flight area may be an area from the take-off point to a height of 1000 meters from the take-off point; the historical flight route of unmanned aerial vehicle B may be from starting point M to ending point N, and the flight area may be an area covered by a circle with starting point M as the center and the straight-line distance from starting point M to ending point N as the radius.

[0077] According to an embodiment of the present disclosure, the target no-fly zone may be an area where flight is not allowed within the flight area of the unmanned aerial vehicle, and the target no-fly zone includes one or more.

[0078] According to an embodiment of the present disclosure, the area of the target no-fly zone may be a polygon, and the polygon is formed by connecting the heads and tails of multiple first line segments in sequence. The longitude and latitude coordinates of the target no-fly zone can be converted into the Gaussian coordinate system. For the specific method, reference can be made to the method for converting the longitude and latitude coordinates of the unmanned aerial vehicle in operation S101.

[0079] For example, the area of the target no-fly zone is pentagon ABCDE. The first line segments in pentagon ABCDE are line segment AB, line segment BC, line segment CD, line segment DE, and line segment EA. The longitude and latitude coordinates of vertices A, B, C, D, and E of pentagon ABCDE can be converted into the Gaussian coordinate system.

[0080] In operation S103, determine the target first line segment from multiple first line segments according to the Gaussian coordinates of the unmanned aerial vehicle, where the ordinate of the Gaussian coordinates of the unmanned aerial vehicle is between the ordinates of the two endpoints of the target first line segment.

[0081] According to an embodiment of the present disclosure, the ordinates of the two endpoints of each first line segment among multiple first line segments can be obtained, and the ordinates of the two endpoints of each first line segment are compared with the ordinate of the unmanned aerial vehicle to obtain a comparison result. When the comparison result indicates that the ordinate of the unmanned aerial vehicle is between the ordinates of the two endpoints of the first line segment, the first line segment is determined as the target first line segment. For example, the ordinate values of the two endpoints of first line segment AB are x 1 and x 2 , the ordinate value of the unmanned aerial vehicle is x 3 , and when x 1 < x 3 < x 2 , first line segment AB can be determined as the target first line segment.

[0082] In operation S104, determine the number of intersection points between the first ray and the target first line segment, where the first ray is generated with the coordinate point of the unmanned aerial vehicle as the endpoint and the positive x-axis direction as the ray direction.

[0083] According to an embodiment of the present disclosure, the first ray may be generated with the coordinate point of the unmanned aerial vehicle as an end point and the positive direction of the x-axis as the ray direction.

[0084] According to an embodiment of the present disclosure, when there are multiple target first line segments, it is possible to sequentially determine whether there is an intersection between each target first line segment among the multiple target first line segments and the first ray, and obtain the number of intersections between the first ray and the target first line segments.

[0085] In operation S105, when the number of intersections is odd, it is determined that the current position of the unmanned aerial vehicle is within the target no-fly zone.

[0086] According to an embodiment of the present disclosure, it is determined whether the number of intersections between the first ray and the target first line segment is odd. When the number of intersections is odd, it is determined that the current position of the unmanned aerial vehicle is within the target no-fly zone. When the number of intersections is even, it is determined that the current position of the unmanned aerial vehicle is not within the target no-fly zone.

[0087] According to an embodiment of the present disclosure, it is possible to sequentially determine the number of intersections between the first ray and the target first line segments in each target no-fly zone among multiple target no-fly zones according to operation S104, and determine whether the unmanned aerial vehicle is located in one of the multiple target no-fly zones.

[0088] In operation S106, based on the current position of the unmanned aerial vehicle, an alarm message is issued.

[0089] According to an embodiment of the present disclosure, the alarm message may be information that the unmanned aerial vehicle is located in the target no-fly zone, and may include the current position information of the unmanned aerial vehicle.

[0090] According to an embodiment of the present disclosure, by converting the longitude and latitude coordinates of the unmanned aerial vehicle into Gaussian coordinates, it is not necessary to approximate them as the coordinates of a plane coordinate system, which improves the accuracy of calculating whether the unmanned aerial vehicle flies into the no-fly zone. The target first line segment is determined according to the relationship between the ordinate of the unmanned aerial vehicle and the ordinates of the two end points of the first line segment. When the number of intersections between the first ray and the target first line segment is odd, it is determined that the current position of the unmanned aerial vehicle is within the target no-fly zone. It is only necessary to consider the target no-fly zones within the flight area of the unmanned aerial vehicle, and it is not necessary to calculate all the no-fly zones, which reduces the amount of calculation. Therefore, at least partially, it overcomes the technical problems in the related art that the method for calculating whether the unmanned aerial vehicle flies into the no-fly zone has low accuracy, and it is necessary to traverse all the no-fly zones, increasing the amount of calculation and reducing the calculation efficiency.

[0091] According to an embodiment of the present disclosure, wherein determining the number of intersections between the first ray and the target first line segment includes:

[0092] Determine the first slope of the line where the first endpoint of the target first line segment and the coordinate point of the drone are located, where the ordinate of the first endpoint is less than the ordinate of the drone;

[0093] Determine the second slope of the line where the target first line segment is located;

[0094] When the first slope is greater than the second slope, determine that the first ray and the target first line segment have an intersection point;

[0095] Based on the intersection point, determine the number of intersection points between the first ray with the coordinate point of the drone as the endpoint and the x-axis as the ray direction and the target first line segment.

[0096] Figure 2 Schematically shows a schematic diagram of the relationship between the first ray and the target no-fly zone according to an embodiment of the present disclosure.

[0097] As Figure 2 shown, the target no-fly zone is the polygon P0P1P2P3P4, the drone is located at point A. Assuming that the line segment P0P4 is the target first line segment, the first ray can be the ray AO. If the slope of the line where AP4 is located is greater than the slope of the line where the target first line segment P0P4 is located, it is proved that the first ray AO and the target first line segment P0P4. Specifically, the following formula (9) can be used to determine whether there is an intersection point between the first ray and the target first line segment:

[0098]

[0099] where, (x A , y A ) are the coordinates of point A, (x i , y i ) are the coordinates of the endpoint P4, and (x j , y j ) are the coordinates of the endpoint P0.

[0100] When the coordinates of A and the coordinates of the two endpoints of the target first line segment P0P4 satisfy formula (9), it is determined that there is an intersection point between the first ray AO and the target first line segment P0P4. When the coordinates of A and the coordinates of the two endpoints of the target first line segment P0P4 do not satisfy formula (9), it is determined that there is no intersection point between the first ray AO and the target first line segment P0P4. The calculation processes of other target first line segments are similar and will not be elaborated here.

[0101] According to an embodiment of the present disclosure, the method further includes:

[0102] Based on the model information and power information of the drone, determine the flight radius of the drone;

[0103] According to the flight radius, determine the flight area of the drone.

[0104] According to an embodiment of the present disclosure, the signal information of the drone may include information such as the maximum flight radius of the drone, the maximum flight altitude of the drone, etc., and the power information of the drone may include information on the maximum flight time of the drone. The flight radius of the drone can be determined based on the information on the maximum flight radius of the drone and the information on the maximum flight time of the drone.

[0105] According to an embodiment of the present disclosure, based on the flight radius of the drone, the maximum area that the drone can fly can be determined and determined as the flight area of the drone.

[0106] According to an embodiment of the present disclosure, calculate the flight area of the drone, so as to screen out the no-fly zones in subsequent calculations to obtain the target no-fly zones, without the need to calculate all no-fly zones, reducing the calculation amount and improving the calculation efficiency.

[0107] According to an embodiment of the present disclosure, wherein determining the target no-fly zone of the drone within the flight area includes:

[0108] Obtain the no-fly zones in the area where the drone is located;

[0109] Determine the minimum circumscribed rectangle of the no-fly zone;

[0110] Based on the distances between the drone and all vertices in the minimum circumscribed rectangle, determine the target no-fly zone from the no-fly zones.

[0111] According to an embodiment of the present disclosure, the no-fly zones in the area where the drone is located may be areas demarcated by relevant departments where drones are prohibited from flying.

[0112] According to an embodiment of the present disclosure, the minimum circumscribed rectangle of the no-fly zone can be determined by the minimum circumscribed rectangle method.

[0113] According to an embodiment of the present disclosure, the distances between the coordinate points of the drone and each vertex of the minimum circumscribed rectangle can be obtained. When the flight radius of the drone is greater than the distances between the coordinate points of the drone and each vertex of the minimum circumscribed rectangle, determine that the no-fly zone is the target no-fly zone. The distances between the coordinate points of the drone and each vertex of the minimum circumscribed rectangle can be determined by formula (10):

[0114]

[0115] Wherein, d is the distance from the coordinate point of the drone to the vertex in the minimum circumscribed rectangle, and R is the radius of the earth, respectively represent the latitude of the coordinate point of the drone and the latitude of the vertex, and Δλ represents the difference between the latitude of the coordinate point of the drone and the latitude of the vertex.

[0116] According to an embodiment of the present disclosure, wherein determining the minimum circumscribed rectangle of the no-fly zone includes:

[0117] Determine the first straight line where any side of the no-fly zone is located;

[0118] Based on the first vertex that is farthest from the first straight line in the no-fly zone, determine the second straight line that passes through the first vertex and is parallel to the first straight line;

[0119] According to any point on the first straight line and the second straight line, determine the third straight line that is perpendicular to the first straight line, where the third straight line passes through the no-fly zone;

[0120] In the no-fly zone, determine the second vertex that is farthest from one side of the third straight line and the third vertex that is farthest from the other side of the third straight line;

[0121] Determine the fourth straight line that passes through the second vertex and is parallel to the third straight line, and the fifth straight line that passes through the third vertex and is parallel to the third straight line;

[0122] According to the area enclosed by the first straight line, the second straight line, the fourth straight line and the fifth straight line, determine the minimum circumscribed rectangle of the no-fly zone.

[0123] Figure 3 Schematically shows a schematic diagram of the minimum circumscribed rectangle of the no-fly zone of the drone according to an embodiment of the present disclosure.

[0124] As Figure 3 shown, the first straight line L can be determined according to the straight line where the first line segment P0P1 in the no-fly zone is located 1 , and the slope of the first straight line L 1 can be denoted as k 1 , calculate the distances from all vertices in the no-fly zone to the first straight line L 1 , so as to determine the first vertex P3 that is farthest from the first straight line L 1 , and determine the second straight line L that passes through the first vertex P3 and is parallel to the first straight line L 1 , that is, the slope of the second straight line L 2 is also k 2 , according to any point between the first straight line L 1 and the second straight line L 1 , determine the third straight line L that is perpendicular to the first straight line L 2 , that is, the slope of the third straight line L 1 is -1 / k 3 , where the third straight line L 3 passes through the no-fly zone, obtain the distances from the vertices on both sides of the third straight line L 1 to the third straight line L 3 , so as to determine the second vertex P0 that is farthest from one side of the third straight line L 3 and the distance from the third vertex on the other side of the third straight line L 3 to the third straight line L 3 so as to determine the third vertex that is farthest from the other side of the third straight line L3 The third vertex P2 farthest from the other side determines the fourth straight line L passing through the second vertex P0 and parallel to the third straight line L 3 parallel 4 and the fifth straight line L passing through the third vertex P2 and parallel to the third straight line 5 , that is, the fourth straight line L 4 and the fifth straight line L 5 have a slope of -1 / k 1 , from Figure 3 it can be seen that the first straight line L 1 , the second straight line L 2 , the fourth straight line L 4 and the fifth straight line L 5 enclose a rectangular area, and this area is the smallest circumscribed rectangle of the no-fly zone.

[0125] According to an embodiment of the present disclosure, by determining whether the distances from the four vertices of the smallest circumscribed rectangle to the drone are less than the flight radius of the drone, instead of determining the distances between each vertex of the no-fly zone and the drone, the amount of calculation is reduced and the calculation efficiency is improved.

[0126] According to an embodiment of the present disclosure, the method further includes:

[0127] Based on the warning information, update the flight route of the drone through the shortest path planning algorithm so that the drone avoids the target no-fly zone.

[0128] Figure 4 Schematically shows a schematic diagram of the flight route of the drone updated by the shortest path planning algorithm according to an embodiment of the present disclosure.

[0129] As Figure 4 shown, assuming that the drone flies to point S and receives a warning message. In the case where the drone receives the warning message, the flight route of the drone can be updated through the shortest path planning algorithm, as shown in formula (11):

[0130] f(n) = g(n) + h(n) (11)

[0131] where f(n) represents the total cost from the starting point to the ending point of the drone, g(n) represents the effective distance that has been traveled from the current point S to the node P, and h(n) represents the distance from the node P to the ending point T.

[0132] As shown in 4, the predetermined flight route of the drone is to fly straight from point S to point T. However, when the drone arrives at point S, a warning message is issued. The drone updates the flight route of the drone through the shortest path planning algorithm, and the shortest path from point S to point T can be found. The process of the shortest path planning algorithm is as follows:

[0133] In the list to be traversed (initially only the starting point S), find a point K with the smallest estimated value (the estimated distance from the current point to the end point). Relative to the starting point S, this is point P0. Conduct a breadth-first search on point K, that is, the next end point of the no-fly zone that it reaches in one move (relative to P0, this is P1; relative to P4, this is P3), excluding the points that have already been traversed and the points that cannot be reached. Add the points that can be found to the queue, and remove point K from the queue and add it to the result queue. Repeat the previous two steps until the drone reaches point T or the queue is empty, indicating that there is no path to reach point T.

[0134] Therefore, the result queue (S -> P0 -> P1 -> T) obtained through the shortest path planning algorithm is the flight route of the drone bypassing the no-fly zone. Update this flight route to the predetermined flight route of the drone to avoid the no-fly zone.

[0135] Figure 5 Schematically shows a block diagram of a drone no-fly zone warning device according to an embodiment of the present disclosure.

[0136] As Figure 5 shown, the drone no-fly zone warning device 500 includes a conversion module 510, a first determination module 520, a second determination module 530, a third determination module 540, a fourth determination module 550, and an alarm module 560.

[0137] The conversion module 510 is configured to convert the longitude and latitude coordinates of the current position of the drone into Gaussian coordinates;

[0138] The first determination module 520 is configured to determine the target no-fly zone within the flight area of the drone, where the area of the target no-fly zone is a polygon formed by sequentially connecting the ends of multiple first line segments;

[0139] The second determination module 530 is configured to determine the target first line segment from multiple first line segments according to the Gaussian coordinates of the drone, where the ordinate of the Gaussian coordinates of the drone is between the ordinates of the two end points of the target first line segment;

[0140] The third determination module 540 is configured to determine the number of intersection points between the first ray and the target first line segment, where the first ray is generated with the coordinate point of the drone as the end point and the positive x-axis direction as the ray direction;

[0141] The fourth determination module 550 is configured to determine that the current position of the drone is within the target no-fly zone when the number of intersection points is odd;

[0142] The alarm module 560 is configured to send an alarm message based on the current position of the drone.

[0143] According to an embodiment of the present disclosure, the third determination module for determining the number of intersection points between the first ray and the target first line segment includes:

[0144] A first determination unit for determining a first slope of a straight line passing through the first endpoint of the target first line segment and the coordinate point of the unmanned aerial vehicle, wherein the ordinate of the first endpoint is less than the ordinate of the unmanned aerial vehicle;

[0145] A second determination unit for determining a second slope of the straight line where the target first line segment is located;

[0146] A third determination unit for determining that the first ray and the target first line segment have an intersection point when the first slope is greater than the second slope;

[0147] A fourth determination unit for determining the number of intersection points between the first ray with the coordinate point of the unmanned aerial vehicle as an endpoint and the x-axis as the ray direction and the target first line segment based on the intersection point.

[0148] According to an embodiment of the present disclosure, the above unmanned aerial vehicle no-fly zone warning device further includes:

[0149] A fifth determination module for determining the flight radius of the unmanned aerial vehicle based on the model information and power information of the unmanned aerial vehicle;

[0150] A sixth determination module determines the flight area of the unmanned aerial vehicle according to the flight radius.

[0151] According to an embodiment of the present disclosure, the first determination module for determining the target no-fly zone of the unmanned aerial vehicle within the flight area includes:

[0152] A fifth determination unit for obtaining the no-fly zone of the area where the unmanned aerial vehicle is located;

[0153] A sixth determination unit for determining the minimum circumscribed rectangle of the no-fly zone;

[0154] A seventh determination unit for determining the target no-fly zone from the no-fly zone based on the distances between the unmanned aerial vehicle and all vertices in the minimum circumscribed rectangle.

[0155] According to an embodiment of the present disclosure, the sixth determination unit for determining the minimum circumscribed rectangle of the no-fly zone includes:

[0156] A first determination subunit for determining a first straight line where any side of the no-fly zone is located;

[0157] A second determination subunit for determining a second straight line passing through the first vertex and parallel to the first straight line based on the first vertex in the no-fly zone that is farthest from the first straight line;

[0158] A third determination subunit, configured to determine a third straight line perpendicular to the first straight line according to any point on the first straight line and the second straight line, where the third straight line passes through the no-fly zone;

[0159] A fourth determination subunit, configured to determine a second vertex that is the farthest from one side of the third straight line and a third vertex that is the farthest from the other side of the third straight line in the no-fly zone;

[0160] A fifth determination subunit, configured to determine a fourth straight line passing through the second vertex and parallel to the third straight line, and a fifth straight line passing through the third vertex and parallel to the third straight line;

[0161] A sixth determination subunit, configured to determine the minimum circumscribed rectangle of the no-fly zone according to the area enclosed by the first straight line, the second straight line, the fourth straight line, and the fifth straight line.

[0162] According to an embodiment of the present disclosure, the above-mentioned UAV no-fly zone warning device further includes:

[0163] An update module, configured to update the flight route of the UAV through a shortest path planning algorithm based on the warning information, so that the UAV avoids the target no-fly zone.

[0164] According to an embodiment of the present disclosure, any one or more of the modules, sub-modules, units, and sub-units, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure can be split into multiple modules for implementation. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by any other reasonable way of integrating or packaging the circuit in hardware or firmware, or implemented in any one of the three implementation manners of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure can be at least partially implemented as a computer program module, and when the computer program module is run, it can execute the corresponding functions.

[0165] For example, any combination of the conversion module 510, the first determination module 520, the second determination module 530, the third determination module 540, the fourth determination module 550, and the warning module 560 can be combined and implemented in one module / unit / sub-unit, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the conversion module 510, the first determination module 520, the second determination module 530, the third determination module 540, the fourth determination module 550, and the warning module 560 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by any other reasonable means such as integrating or packaging circuits, etc., in hardware or firmware, or implemented in any one of the three implementation manners of software, hardware, and firmware, or in any suitable combination of several of them. Alternatively, at least one of the conversion module 510, the first determination module 520, the second determination module 530, the third determination module 540, the fourth determination module 550, and the warning module 560 can be at least partially implemented as a computer program module, and when the computer program module runs, it can execute the corresponding functions.

[0166] It should be noted that the part of the UAV no-fly zone warning device in the embodiments of the present disclosure corresponds to the part of the UAV no-fly zone warning method in the embodiments of the present disclosure. For the description of the part of the UAV no-fly zone warning device, please refer to the part of the UAV no-fly zone warning method for details, and it will not be repeated here.

[0167] Figure 6 A block diagram of an electronic device suitable for implementing the UAV no-fly zone warning method according to an embodiment of the present disclosure is schematically shown. Figure 6 The electronic device shown is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present disclosure.

[0168] Such as Figure 6As shown, the computer electronic device 600 according to an embodiment of the present disclosure includes a processor 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage section 608 into a random access memory (RAM) 603. The processor 601 may include, for example, a general-purpose microprocessor (e.g., CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 601 may also include on-board memory for caching purposes. The processor 601 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0169] In the RAM 603, various programs and data required for the operation of the electronic device 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. The processor 601 performs various operations of the method flow according to an embodiment of the present disclosure by executing the program in the ROM 602 and / or the RAM 603. It should be noted that the program may also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 may also perform various operations of the method flow according to an embodiment of the present disclosure by executing the program stored in the one or more memories.

[0170] According to an embodiment of the present disclosure, the electronic device 600 may further include an input / output (I / O) interface 605, and the input / output (I / O) interface 605 is also connected to the bus 604. The electronic device 600 may further include one or more of the following components connected to the I / O interface 605: an input section 606 including a keyboard, a mouse, etc.; an output section 607 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, a modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as needed. A removable medium 611, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed so that a computer program read from it can be installed into the storage section 608 as needed.

[0171] According to an embodiment of the present disclosure, the method flow according to the embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program includes program codes for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 609, and / or installed from the removable medium 611. When the computer program is executed by the processor 601, the functions defined in the system according to the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the above-described systems, devices, apparatuses, modules, units, etc. can be implemented by computer program modules.

[0172] The present disclosure also provides a computer-readable storage medium, which can be included in the device / apparatus / system described in the embodiment; or can exist separately without being assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method for warning no-fly zones of unmanned aerial vehicles according to the embodiment of the present disclosure is implemented.

[0173] According to an embodiment of the present disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. For example, it can include but is not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In the present disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or combined with an instruction execution system, apparatus, or device.

[0174] For example, according to an embodiment of the present disclosure, the computer-readable storage medium can include the above-described ROM 602 and / or RAM 603 and / or one or more memories other than ROM 602 and RAM 603.

[0175] An embodiment of the present disclosure also provides an unmanned aerial vehicle, which includes an electronic device as Figure 6 shown.

[0176] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of code, which contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and combinations of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or by a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features recited in the various embodiments and / or claims of the present disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not explicitly recited in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features recited in the various embodiments and / or claims of the present disclosure can be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of the present disclosure.

[0177] The embodiments of the present disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments have been described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and all such substitutions and modifications should fall within the scope of the present disclosure.

Claims

1. A method for warning of no - fly zones for unmanned aerial vehicles, including: Converting the longitude and latitude coordinates of the current position of the unmanned aerial vehicle into Gaussian coordinates; Determining the target no - fly zone of the unmanned aerial vehicle within the flight area, where the area of the target no - fly zone is a polygon formed by sequentially connecting the heads and tails of multiple first line segments; Determining a target first line segment from the multiple first line segments according to the Gaussian coordinates of the unmanned aerial vehicle, where the ordinate of the Gaussian coordinates of the unmanned aerial vehicle is between the ordinates of the two endpoints of the target first line segment; Determining the number of intersection points between a first ray and the target first line segment, where the first ray is generated with the coordinate point of the unmanned aerial vehicle as the endpoint and the positive x - axis direction as the ray direction; In the case where the number of intersection points is odd, determining that the current position of the unmanned aerial vehicle is within the target no - fly zone; Based on the current position of the unmanned aerial vehicle, sending out a warning message; Among them, the determining the number of intersection points between the first ray and the target first line segment includes: Determining the first slope of the straight line where the first endpoint of the target first line segment and the coordinate point of the unmanned aerial vehicle are located, where the ordinate of the first endpoint is less than the ordinate of the unmanned aerial vehicle; Determining the second slope of the straight line where the target first line segment is located; In the case where the first slope is greater than the second slope, determining that the first ray and the target first line segment have intersection points; Based on the intersection points, determining the number of intersection points between the first ray with the coordinate point of the unmanned aerial vehicle as the endpoint and the x - axis as the ray direction and the target first line segment; The determining the target no - fly zone of the unmanned aerial vehicle within the flight area includes: Obtaining the no - fly zone of the area where the unmanned aerial vehicle is located; Determining the minimum circumscribed rectangle of the no - fly zone; Based on the distances between the unmanned aerial vehicle and all vertices in the minimum circumscribed rectangle, determining the target no - fly zone from the no - fly zone.

2. The method according to claim 1, further including: Based on the model information and power information of the unmanned aerial vehicle, determining the flight radius of the unmanned aerial vehicle; According to the flight radius, determining the flight area of the unmanned aerial vehicle.

3. The method according to claim 1, wherein, The determining the minimum circumscribed rectangle of the no - fly zone includes: Determining a first straight line where any side of the no - fly zone is located; Based on the first vertex in the no - fly zone that is farthest from the first straight line, determining a second straight line passing through the first vertex and parallel to the first straight line; According to any point on the first straight line and the second straight line, determining a third straight line perpendicular to the first straight line, where the third straight line passes through the no - fly zone; Determining a second vertex in the no - fly zone that is farthest from one side of the third straight line and a third vertex that is farthest from the other side of the third straight line; Determining a fourth straight line passing through the second vertex and parallel to the third straight line and a fifth straight line passing through the third vertex and parallel to the third straight line; According to the area enclosed by the first straight line, the second straight line, the fourth straight line and the fifth straight line, determining the minimum circumscribed rectangle of the no - fly zone.

4. The method according to claim 1, further including: Based on the warning information, update the flight route of the drone through the shortest path planning algorithm so that the drone avoids the target no-fly zone.

5. A drone no-fly zone warning device, adopting the drone no-fly zone warning method according to any one of claims 1 to 4, the device comprises: a conversion module, configured to convert the longitude and latitude coordinates of the current position of the drone into Gaussian coordinates; a first determination module, configured to determine the target no-fly zone of the drone in the flight area, wherein the area of the target no-fly zone is a polygon formed by connecting the head and tail of multiple first line segments in sequence; a second determination module, configured to determine a target first line segment from the multiple first line segments according to the Gaussian coordinates of the drone, wherein the ordinate of the Gaussian coordinates of the drone is between the ordinates of the two endpoints of the target first line segment; a third determination module, configured to determine the number of intersection points between a first ray and the target first line segment, wherein the first ray is generated with the coordinate point of the drone as the endpoint and the positive x-axis direction as the ray direction; a fourth determination module, configured to determine that the current position of the drone is located in the target no-fly zone when the number of intersection points is odd; a warning module, configured to issue a warning information based on the current position of the drone.

6. An electronic device, comprises: one or more processors; a memory, configured to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor implements the method according to any one of claims 1 to 4.

8. A drone, comprising the electronic device according to claim 6.

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