Unmanned Aerial Vehicle Path Planning Method, Unmanned Aerial Vehicle Path Planning Device and Electronic Device

Abstract

The present disclosure provides a method for unmanned aerial vehicle path planning, an apparatus for unmanned aerial vehicle path planning, and an electronic device. The method includes determining two adjacent target path points of the unmanned aerial vehicle in a target flight area on a three-dimensional space map; determining an i-th yaw point between the target path point with a higher flight order and the boundary point of the obstacle when an obstacle is detected between two adjacent target path points; adjusting the yaw orientation of the unmanned aerial vehicle according to the i-th yaw point and a preset yaw rule; after the unmanned aerial vehicle performs path planning based on the adjusted yaw orientation, in response to an obstacle existing between the current position after path planning and the target path point with a lower flight order, continuously and iteratively adjusting the yaw orientation of the unmanned aerial vehicle according to the (i + 1)-th yaw point and the preset yaw rule; generating a target path between two adjacent target path points according to the two adjacent target path points and all the yaw points.

Description

Technical Field

[0001] The present disclosure relates to the technical field of unmanned aerial vehicles, and more particularly, to a method for path planning of an unmanned aerial vehicle, a device for path planning of an unmanned aerial vehicle, an electronic device, a computer-readable storage medium, and a computer program product. 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, or is completely or intermittently controlled by a computer. In the civilian field, compared with manned 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] During the flight of a UAV, the flight altitude of the UAV may be lower than some tall buildings in the city. If there are buildings higher than the flight altitude on the planned path, it will cause damage or even crash of the UAV.

[0004] However, during the flight of current UAVs, one control method is to rely on manual control of the UAV flight. The operator judges whether there will be a conflict with the building in the next time period through the real-time video transmitted back by the UAV, and changes the flight path or the UAV altitude by manual control to avoid the conflict. Constantly staring at the real-time video consumes a lot of manpower, and the delay of the real-time video will cause untimely operation, resulting in serious consequences. In another control method, the flight path of a computer-controlled UAV usually depends on the municipal road planning, and the UAV flies along the planned road. In this way, the execution efficiency of the UAV is relatively low. Summary of the Invention

[0005] In view of this, embodiments of the present disclosure provide a method for path planning of an unmanned aerial vehicle, a device for path planning of an unmanned aerial vehicle, an electronic device, a computer-readable storage medium, and a computer program product.

[0006] One aspect of the embodiments of the present disclosure provides a method for path planning of an unmanned aerial vehicle, including:

[0007] Determine two adjacent target path points of the unmanned aerial vehicle in a target flight area on a three-dimensional space map, wherein the three-dimensional space map is loaded with a building model;

[0008] In the case where an obstacle is detected between two adjacent target path points, determine an i-th yaw point between the target path point with a forward flight order and the boundary point of the obstacle;

[0009] Adjust the yaw orientation of the above-mentioned UAV according to the above-mentioned i-th yaw point and the preset yaw rule, where the above-mentioned preset yaw rule includes a yaw angle and a yaw distance determined based on a reference line;

[0010] After the above-mentioned UAV performs path planning based on the adjusted yaw orientation, in response to an obstacle existing between the current position after the above-mentioned path planning and the above-mentioned target path point with a later flight order, continue to iteratively adjust the yaw orientation of the above-mentioned UAV according to the (i + 1)-th yaw point and the above-mentioned preset yaw rule until there is no obstacle between the current position after the path planning based on the iteratively adjusted yaw orientation of the above-mentioned UAV and the above-mentioned target path point with a later flight order;

[0011] Generate a target path between two adjacent above-mentioned target path points according to two adjacent above-mentioned target path points and all the above-mentioned yaw points.

[0012] According to an embodiment of the present disclosure, the above-mentioned adjusting the yaw orientation of the above-mentioned UAV according to the above-mentioned i-th yaw point and the preset yaw rule includes:

[0013] Determine the yaw direction of the i-th yaw point according to the above-mentioned i-th yaw point, the above-mentioned reference line, and the preset above-mentioned yaw angle;

[0014] Determine the above-mentioned adjusted yaw orientation according to the above-mentioned i-th yaw point, the above-mentioned yaw direction, and the preset above-mentioned yaw distance.

[0015] According to an embodiment of the present disclosure, the above-mentioned continuing to iteratively adjust the yaw orientation of the above-mentioned UAV according to the (i + 1)-th yaw point and the above-mentioned preset yaw rule includes:

[0016] Correct the above-mentioned yaw angle using an iterative variation amount to obtain a new yaw angle;

[0017] Iteratively determine the iteratively adjusted yaw orientation according to the above-mentioned (i + 1)-th yaw point, the above-mentioned reference line, the above-mentioned new yaw angle, and the above-mentioned yaw distance, where, during the iteration process, the difference between two above-mentioned new yaw angles corresponding to two adjacent above-mentioned yaw points is the above-mentioned iterative variation amount.

[0018] According to an embodiment of the present disclosure, the above-mentioned determining the yaw direction of the i-th yaw point according to the above-mentioned i-th yaw point, the above-mentioned reference line, and the preset above-mentioned yaw angle includes:

[0019] Determine an acute angle region between a target connection line between the above-mentioned i-th yaw point and the above-mentioned target path point with a later flight order and the above-mentioned reference line;

[0020] Process the above target connection line using the above yaw angle to obtain the above yaw direction, where the yaw direction of the above $i$-th yaw point is located in the above acute angle region.

[0021] According to an embodiment of the present disclosure, before performing the above path planning, it further includes:

[0022] When it is detected that there is no obstacle between the above adjusted $(i + 1)$-th yaw point and the above $i$-th yaw point, perform the above path planning.

[0023] According to an embodiment of the present disclosure, before performing the above path planning, it further includes:

[0024] When it is detected that there is an obstacle between the above adjusted $(i + 1)$-th yaw point and the above $i$-th yaw point, adjust the above yaw angle to obtain a first transition yaw angle;

[0025] Determine a new $(i + 1)$-th yaw point according to the above first transition yaw angle and the above $i$-th yaw point, so that the above unmanned aerial vehicle performs path planning based on the above new $(i + 1)$-th yaw point.

[0026] According to an embodiment of the present disclosure, the method for constructing the above three-dimensional space map includes:

[0027] Load the image data of the above target flight area in the initial coordinate system to generate a transition space map;

[0028] Load the above building model of the above target flight area on the above transition space map to generate the above three-dimensional space map, where the above building model includes the three-dimensional layout structure and geographical location of the building.

[0029] According to an embodiment of the present disclosure, the unmanned aerial vehicle path planning method further includes:

[0030] Generate a total path according to multiple above target paths, where different above target paths correspond to different adjacent two above target path points;

[0031] Transmit the above total path to the above unmanned aerial vehicle so that the unmanned aerial vehicle executes a flight mission according to the above total path.

[0032] Another aspect of the embodiments of the present disclosure provides an unmanned aerial vehicle path planning device, including:

[0033] A first determination module, configured to determine two adjacent target path points of the above unmanned aerial vehicle in the target flight area on a three-dimensional space map, where the above three-dimensional space map is loaded with a building model;

[0034] A second determination module, configured to determine an ith yaw point between the target path point with a higher flight order and the boundary point of the obstacle when it is detected that there is an obstacle between two adjacent target path points;

[0035] An adjustment module, configured to adjust the yaw orientation of the UAV according to the ith yaw point and a preset yaw rule, where the preset yaw rule includes a yaw angle and a yaw distance determined based on a reference line;

[0036] An iteration module, configured to, after the UAV performs path planning based on the adjusted yaw orientation, in response to there being an obstacle between the current position after the path planning and the target path point with a lower flight order, continue to iteratively adjust the yaw orientation of the UAV according to the (i + 1)th yaw point and the preset yaw rule until there is no obstacle between the current position after the path planning and the target path point with a lower flight order when the UAV performs path planning based on the iteratively adjusted yaw orientation;

[0037] A generation module, configured to generate a target path between two adjacent target path points according to the two adjacent target path points and all the yaw points.

[0038] Another aspect of the embodiments of the present disclosure provides an electronic device, including: one or more processors; a memory, configured to store one or more programs, where when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method as described above.

[0039] Another aspect of the embodiments of the present disclosure provides a computer-readable storage medium, storing computer-executable instructions, where the instructions are used to implement the method as described above when executed.

[0040] Another aspect of the embodiments of the present disclosure provides a computer program product, where the computer program product includes computer-executable instructions, and the instructions are used to implement the method as described above when executed.

[0041] According to an embodiment of the present disclosure, by determining two adjacent target waypoints in a three-dimensional spatial map loaded with a building model, when performing path planning for the two target waypoints, by determining whether there is an obstacle between the current position of the drone and the target point with a later flight order, the current position of the drone is yaw-adjusted based on a preset yaw rule, so as to form multiple yaw points for bypassing the obstacle. Finally, a target path between the two target waypoints is constructed based on the multiple yaw points and the two target waypoints of the vector. Since it is only necessary to determine that there is an obstacle between the current position of the drone and the target waypoint with a later flight order on the three-dimensional spatial map to adjust the yaw direction of the next yaw point, the problem of high flight cost caused by the operator's judgment of whether there is an obstacle in the flight path of the drone in the prior art is avoided. At the same time, the drone path planning algorithm of the present disclosure has a small amount of calculation, and the yaw point is confirmed in real time according to the obstacle depending on the three-dimensional spatial map, thereby indirectly improving the performance of the computer and the execution efficiency of the drone. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Through the following description of the embodiments of the present disclosure with reference to the drawings, the above and other objects, features and advantages of the present disclosure will become clearer. In the drawings:

[0043] Figure 1 Schematically shows an exemplary system architecture to which the drone path planning method according to an embodiment of the present disclosure can be applied;

[0044] Figure 2 Schematically shows a flowchart of the drone path planning method according to an embodiment of the present disclosure;

[0045] Figure 3 Schematically shows a scenario diagram A of the drone path planning method according to an embodiment of the present disclosure;

[0046] Figure 4 Schematically shows a scenario diagram B of the drone path planning method according to an embodiment of the present disclosure;

[0047] Figure 5 Schematically shows a block diagram of the drone path planning device according to an embodiment of the present disclosure; and

[0048] Figure 6 Schematically shows a block diagram of an electronic device for implementing the drone path planning method according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] The present disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present disclosure, rather than limiting the present disclosure. Each feature described in the embodiments can be combined to form multiple alternative solutions. In addition, it should be noted that for the sake of description, only parts related to the present disclosure rather than all structures are shown in the drawings.

[0050] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary 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, it is obvious that 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.

[0051] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "including", "comprising", etc. used herein indicate the presence of the described features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0052] All terms used herein (including technical and scientific terms) 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.

[0053] In the case of using expressions such as "at least one of A, B, and C", generally, it should be interpreted according to the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include, but not be limited to, a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, and C).

[0054] Embodiments of the present disclosure provide a method for unmanned aerial vehicle (UAV) path planning, a UAV path planning device, and an electronic device. The method includes determining two adjacent target path points of the UAV in a target flight area on a three-dimensional space map, where the three-dimensional space map is loaded with a building model; determining an i-th yaw point between the target path point with a higher flight order and the boundary point of the obstacle when an obstacle is detected between the two adjacent target path points; adjusting the yaw orientation of the UAV according to the i-th yaw point and a preset yaw rule, where the preset yaw rule includes a yaw angle and a yaw distance determined based on a reference line; after the UAV performs path planning based on the adjusted yaw orientation, in response to an obstacle existing between the current position after path planning and the target path point with a lower flight order, continuously iteratively adjusting the yaw orientation of the UAV according to the (i + 1)-th yaw point and the preset yaw rule until there is no obstacle between the current position after path planning based on the iteratively adjusted yaw orientation of the UAV and the target path point with a lower flight order; generating a target path between the two adjacent target path points according to the two adjacent target path points and all the yaw points.

[0055] Figure 1 FIG. 1 schematically shows an exemplary system architecture 100 to which the UAV path planning method according to embodiments of the present disclosure can be applied. It should be noted that Figure 1 The figure shown is only an example of the system architecture to which embodiments of the present disclosure can be applied to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0056] As Figure 1 shown, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, a server 105, and a UAV 106. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0057] Users can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. For example, the target path points for the UAV 106 to perform a flight mission can be determined through the terminal devices 101, 102, 103. Various communication client applications may be installed on the terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, and / or social platform software, etc. (only as examples).

[0058] The terminal devices 101, 102, and 103 can be various electronic devices with a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop computers, desktop computers, etc.

[0059] The server 105 can be a server that provides various services. For example, it can be a background management server (only an example) that supports the websites browsed by users using the terminal devices 101, 102, and 103. The background management server can analyze and process data such as user requests for UAV path planning received, and feedback the processing results (such as target paths, web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0060] It should be noted that the UAV path planning method provided by the embodiments of the present disclosure can generally be executed by the terminal devices 101, 102, or 103 or the UAV 106, or can also be executed by other terminal devices different from the terminal devices 101, 102, or 103. Correspondingly, the UAV path planning device provided by the embodiments of the present disclosure can also be set in the terminal devices 101, 102, or 103 or the UAV 106, or set in other terminal devices different from the terminal devices 101, 102, or 103. Or, the UAV path planning method provided by the embodiments of the present disclosure can also be executed by the server 105. Correspondingly, the UAV path planning device provided by the embodiments of the present disclosure can also be set in the server 105. The UAV path planning method provided by the embodiments of the present disclosure can also be executed by a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and / or the server 105. Correspondingly, the UAV path planning device provided by the embodiments of the present disclosure can also be set in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and / or the server 105.

[0061] It should be understood that Figure 1 the numbers of terminal devices, networks, servers, and UAVs in

[0062] Figure 2 are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, networks, servers, and UAVs.

[0063] As Figure 2 shown, the UAV path planning method can include operations S201 to S203.

[0064] In operation S201, two adjacent target waypoints of the drone in the target flight area are determined on the three-dimensional space map, where the three-dimensional space map is loaded with a building model.

[0065] In operation S202, when an obstacle is detected between two adjacent target waypoints, the i-th yaw point is determined between the target waypoint with a higher flight order and the boundary point of the obstacle.

[0066] In operation S203, the yaw orientation of the drone is adjusted according to the i-th yaw point and a preset yaw rule, where the preset yaw rule may include a yaw angle and a yaw distance determined based on a reference line.

[0067] In operation S204, after the drone performs path planning based on the adjusted yaw orientation, in response to an obstacle existing between the current position after path planning and the target waypoint with a lower flight order, the yaw orientation of the drone is continuously iteratively adjusted according to the (i + 1)-th yaw point and the preset yaw rule until there is no obstacle between the current position after path planning based on the iteratively adjusted yaw orientation and the target waypoint with a lower flight order.

[0068] In operation S205, a target path between two adjacent target waypoints is generated according to the two adjacent target waypoints and all the yaw points.

[0069] According to an embodiment of the present disclosure, a target waypoint may refer to a defined location where the drone needs to fly or patrol. The building model refers to a model with corresponding external dimensions. The reference line may refer to a horizontal line constructed based on the current position.

[0070] According to an embodiment of the present disclosure, the distance between any yaw point and the obstacle satisfies the safety distance for the drone to fly, so as to avoid the drone colliding with the obstacle.

[0071] According to an embodiment of the present disclosure, both the yaw angle and the yaw distance can be set according to the actual situation and are not fixed values. For example, the yaw angle can be 5°, the yaw distance can be 2m, and the yaw orientation may include a real-time yaw angle and a yaw distance. Among them, the real-time yaw angles corresponding to different yaw points may be different. The above specific values are all examples and are not a limitation to the present disclosure, and other values are also possible.

[0072] According to an embodiment of the present disclosure, a plurality of patrol points are determined on a three-dimensional space map as target path points of a drone. For two adjacent target path points, first, it is determined whether there is an obstacle between the two target path points on the three-dimensional space map. If it is confirmed that there is an obstacle, a first yaw point can be determined between the target path point with a higher flight order and the boundary point of the obstacle. At the first yaw point, the yaw direction is adjusted based on a preset yaw rule to obtain a second yaw point. A path is planned between the first yaw point and the second yaw point, and it is determined whether there is such an obstacle between the second yaw point and the target path point with a lower flight order. If there is, the yaw direction is iteratively adjusted at the newly determined yaw point to determine the next yaw point until there is no obstacle between the current position after the path is planned based on the iteratively adjusted yaw direction and the target path point with a lower flight order. At this time, the target path between the two adjacent target path points can be generated according to the two adjacent target path points and all the yaw points.

[0073] According to an embodiment of the present disclosure, by determining two adjacent target path points in a three-dimensional space map loaded with a building model, when planning a path between the two target path points, it is determined whether there is an obstacle between the current position of the drone and the target point with a lower flight order, so as to adjust the yaw of the current position of the drone based on a preset yaw rule, thereby forming a plurality of yaw points for bypassing the obstacle. Finally, the target path between the two target path points is constructed according to the plurality of yaw points and the two target path points of the vector. Since it is only necessary to determine that there is an obstacle between the current position of the drone and the target path point with a lower flight order on the three-dimensional space map to adjust the yaw direction of the next yaw point, the problem of high flight cost caused by an operator judging whether there is an obstacle in the flight path of the drone in the prior art is avoided. At the same time, the drone path planning algorithm of the present disclosure has a small amount of calculation, and the yaw point is confirmed in real time according to the obstacle depending on the three-dimensional space map, thereby indirectly improving the performance of the computer and the execution efficiency of the drone.

[0074] According to an embodiment of the present disclosure, adjusting the yaw direction of the drone according to the i-th yaw point and a preset yaw rule may include the following operations:

[0075] Determine the yaw direction according to the i-th yaw point, the reference line, and a preset yaw angle.

[0076] Determine the adjusted yaw direction according to the i-th yaw point, the yaw direction, and a preset yaw distance.

[0077] According to an embodiment of the present disclosure, during the path planning process, assuming that the UAV is located at the i-th yaw point and there is an obstacle between this yaw point and a target path point with a later flight order, first, a line is connected between this yaw point and the target path point with a later flight order. Combining with the reference line, the yaw direction of the next yaw point is determined using a preset yaw angle. The next yaw point (i.e., the adjusted yaw azimuth) is determined in this yaw direction, and the distance between the next yaw point and the current yaw point is a preset yaw distance.

[0078] According to an embodiment of the present disclosure, according to the (i + 1)-th yaw point and a preset yaw rule, the yaw azimuth of the UAV is continuously iteratively adjusted, which may include the following operations:

[0079] The yaw angle is corrected using an iterative change amount to obtain a new yaw angle;

[0080] Iteratively, according to the (i + 1)-th yaw point, the reference line, the new yaw angle, and the yaw distance, the iteratively adjusted yaw azimuth is determined, where during the iteration process, the difference between two new yaw angles corresponding to two adjacent yaw points is the iterative change amount.

[0081] According to an embodiment of the present disclosure, the iterative change amount can be adjusted according to the actual situation. For example, it can be set to 1°. In an exemplary embodiment, the yaw angle corresponding to the latter yaw point is 1° smaller than the yaw angle corresponding to the former yaw point.

[0082] According to an embodiment of the present disclosure, assuming that when the UAV is located at the (i + 1)-th yaw point and there is an obstacle between the (i + 1)-th yaw point and a target path point with a later flight order, at this time, the yaw angle is corrected using the iterative change amount to obtain a new yaw angle. Using this new yaw angle, in combination with the (i + 1)-th yaw point, the reference line, and the yaw distance, the (i + 2)-th yaw point is determined. Repeat the above process until there is no obstacle between the confirmed (i + m)-th yaw point and the target path point with a later flight order. Then, according to multiple yaw points and two adjacent target path points, the target path between the two adjacent target path points is generated.

[0083] According to an embodiment of the present disclosure, according to the i-th yaw point, the reference line, and a preset yaw angle, to determine the yaw direction, the following operations may be included:

[0084] Determine the acute angle region between the target connection line between the i-th yaw point and the target path point with a later flight order and the reference line.

[0085] The target connection line is processed using the yaw angle to obtain the yaw direction, where the yaw direction of the i-th yaw point is located in the acute angle region.

[0086] According to an embodiment of the present disclosure, a connection line (for example, a line segment or a ray can be constructed) is made between the i-th yaw point and a target path point with a later flight order to obtain a target connection line. Combining with a reference line, an acute angle region can be obtained. In this acute angle region, the target connection line is offset by a preset yaw angle to determine the yaw direction of the next yaw point. In the case where the yaw direction is determined, the position of the (i + 1)-th yaw point can be determined in combination with the yaw distance.

[0087] According to an embodiment of the present disclosure, before path planning, the following operations may also be included:

[0088] When it is detected that there is no obstacle between the adjusted (i + 1)-th yaw point and the i-th yaw point, path planning is performed.

[0089] When it is detected that there is an obstacle between the adjusted (i + 1)-th yaw point and the i-th yaw point, the yaw angle is adjusted to obtain a first transitional yaw angle.

[0090] A new (i + 1)-th yaw point is determined according to the first transitional yaw angle and the i-th yaw point, so that the unmanned aerial vehicle can perform path planning based on the new (i + 1)-th yaw point.

[0091] According to an embodiment of the present disclosure, path planning may refer to performing a flight simulation test after determining two yaw points, or making a connection line between two yaw points on a three-dimensional space map to determine the flight path of the unmanned aerial vehicle between these two yaw points.

[0092] According to an embodiment of the present disclosure, since there may be an obstacle between the determined (i + 1)-th yaw point and the i-th yaw point, it is necessary to judge whether there is an obstacle in the path between the two yaw points to avoid the unmanned aerial vehicle colliding with the obstacle during actual flight. If it is determined that there is an obstacle between the two yaw points, at this time, the yaw angle used to determine the (i + 1)-th yaw point needs to be adjusted. For example, if the original yaw angle is 30°, it can be adjusted to 35° at this time, and then the first transitional yaw angle obtained after adjustment is used to re-determine the (i + 1)-th yaw point.

[0093] In an exemplary embodiment, when i = 1, the i-th yaw point is located on the connection line between two adjacent target path points, and the (i + 1)-th yaw point is the first position deviating from the connection line between two adjacent target path points. At this time, it is necessary to judge whether there is an obstacle on the connection line between the i-th yaw point and the (i + 1)-th yaw point. If there is an obstacle, the (i + 1)-th yaw point needs to be re-determined to avoid the unmanned aerial vehicle colliding with the obstacle on the connection line during actual flight.

[0094] According to an embodiment of the present disclosure, the method for constructing a three-dimensional space map may include the following operations:

[0095] Load the image data of the target flight area in the initial coordinate system to generate a transition space map.

[0096] Load the building models of the target flight area on the transition space map to generate a three-dimensional space map, where the building models may include the three-dimensional layout structure and geographical location of the buildings.

[0097] According to an embodiment of the present disclosure, the initial coordinate system may adopt the WGS84 coordinate system. The image data may refer to 2D map data containing longitude and latitude information, on which the roads and building names of each area may be included. The building models may refer to the three-dimensional layout structures of different buildings, such as the geographical location and external shape dimensions of a certain building. The external shape dimensions may include the length, width, height, etc. under the 3D view of the building.

[0098] According to an embodiment of the present disclosure, first load the image data containing 2D map data in the initial coordinate system to obtain a transition space map, and then load the corresponding 3dTiles building models on each corresponding building on the transition space map, so as to obtain a three-dimensional space map, and then the drone path can be planned on the three-dimensional space map.

[0099] It should be noted that when loading the image data, the image data can be loaded in the initial coordinate system under the front-end cesium framework, but it is not limited that only the cesium framework can be used for loading, and it can also be other web frameworks.

[0100] According to an embodiment of the present disclosure, the drone path planning method may further include the following operations:

[0101] Generate a total path according to multiple target paths, where different target paths correspond to different adjacent pairs of target path points.

[0102] Transmit the total path to the drone so that the drone executes the flight mission according to the total path.

[0103] According to an embodiment of the present disclosure, when the drone is executing a mission, if the number of target path points of the drone is greater than two, determine multiple groups of adjacent pairs of target path points according to the flight order, and for each group of adjacent pairs of target path points, use the drone path planning method of the present disclosure to determine its target path, generate the total path for the drone to execute the mission according to multiple target paths, and transmit the total path to the drone so that the drone executes the flight mission according to the total path.

[0104] Figure 3 Schematically shows a scenario schematic diagram A of the drone path planning method according to an embodiment of the present disclosure. Figure 4Schematically shows a scenario schematic diagram B of an unmanned aerial vehicle path planning method according to an embodiment of the present disclosure.

[0105] In an exemplary embodiment, as Figure 3 shown, four target path points A, B, C, and D are determined on a three-dimensional space map as the patrol mission of the unmanned aerial vehicle this time. When determining the target path between two target path points A and B, first confirm whether there are obstacles between A and B. In Figure 3 , there is an obstacle 1 (building 1) between A and B. Referring to Figure 4 , the first yaw point E is determined between the boundary point M of A and the obstacle 1 1 , according to the first yaw point and a preset yaw rule (such as the acute angle θ 1 between the target connection line AB and the horizontal reference line is reduced by 1° as the yaw angle, and the yaw distance is set to 3 m), the yaw orientation of the unmanned aerial vehicle is adjusted, so as to obtain the second yaw point E 2 . As can be seen from the figure, there is an obstacle 1 between the second yaw point and B. Therefore, the subsequent third yaw point... the xth yaw point E can be iteratively determined at the current yaw point x , until there is no obstacle between the xth yaw point and B. Among them, when determining the yaw orientation of E x , the used yaw angle θ x-1 ' is smaller than the yaw angle θ x-1 used to determine E x-2 ' by an iterative change amount in sequence. At this time, the line A→E 1 →E 2 →...→E x →B can be determined as the target path between the two target path points A and B. Figure 3 And Figure 4 the horizontal line at point A is the reference line of the present disclosure. The area where θ 1 is located at point A is the acute angle area described above. λ is the maximum value of the safety distance, and the distance between the yaw point closest to the obstacle and the obstacle shall not be less than the minimum value of the safety distance.

[0106] It should be noted that the determination methods of the target paths between B and C and between C and D are the same as those of the target path between A and B, and will not be elaborated here.

[0107] Figure 5 Schematically shows a block diagram of an unmanned aerial vehicle path planning device according to an embodiment of the present disclosure.

[0108] As Figure 5 shown, the unmanned aerial vehicle path planning device 500 may include a first determination module 501, a second determination module 502, an adjustment module 503, an iteration module 504, and a generation module 505.

[0109] The first determination module 501 is configured to determine two adjacent target waypoints of the unmanned aerial vehicle in the target flight area on the three-dimensional space map, where the three-dimensional space map is loaded with a building model.

[0110] The second determination module 502 is configured to determine the i-th yaw point between the target waypoint with a higher flight order and the boundary point of the obstacle when it is detected that there is an obstacle between two adjacent target waypoints.

[0111] The adjustment module 503 is configured to adjust the yaw orientation of the unmanned aerial vehicle according to the i-th yaw point and a preset yaw rule, where the preset yaw rule may include a yaw angle and a yaw distance determined based on a reference line.

[0112] The iteration module 504 is configured to, after the unmanned aerial vehicle performs path planning based on the adjusted yaw orientation, in response to there being an obstacle between the current position after path planning and the target waypoint with a lower flight order, continue to iteratively adjust the yaw orientation of the unmanned aerial vehicle according to the (i + 1)-th yaw point and the preset yaw rule until there is no obstacle between the current position after path planning and the target waypoint with a lower flight order when the unmanned aerial vehicle performs path planning based on the iteratively adjusted yaw orientation.

[0113] The generation module 505 is configured to generate a target path between two adjacent target waypoints according to the two adjacent target waypoints and all the yaw points.

[0114] According to an embodiment of the present disclosure, by determining two adjacent target waypoints in a three-dimensional space map loaded with a building model, when performing path planning for the two target waypoints, by determining whether there is an obstacle between the current position of the unmanned aerial vehicle and the target point with a lower flight order, the yaw of the current position of the unmanned aerial vehicle is adjusted based on a preset yaw rule, so as to form multiple yaw points for bypassing the obstacle. Finally, a target path between the two target waypoints is constructed according to the multiple yaw points and the two target waypoints of the vector. Since it is only necessary to determine that there is an obstacle between the current position of the unmanned aerial vehicle and the target waypoint with a lower flight order on the three-dimensional space map to adjust the yaw orientation of the next yaw point, the problem of high flight cost caused by an operator judging whether there is an obstacle in the flight path of the unmanned aerial vehicle in the prior art is avoided. At the same time, the unmanned aerial vehicle path planning algorithm of the present disclosure has a small amount of calculation, and the yaw point is confirmed in real time according to the obstacle depending on the three-dimensional space map, thereby indirectly improving the performance of the computer and the execution efficiency of the unmanned aerial vehicle.

[0115] According to an embodiment of the present disclosure, the adjustment module 503 may include a first determination unit and a second determination unit.

[0116] A first determination unit, configured to determine the yaw direction of the i-th yaw point according to the i-th yaw point, a reference line, and a preset yaw angle.

[0117] A second determination unit, configured to determine an adjusted yaw azimuth according to the i-th yaw point, the yaw direction, and a preset yaw distance.

[0118] According to an embodiment of the present disclosure, the iteration module 504 may include a correction unit and an iteration unit.

[0119] The correction unit is configured to correct the yaw angle by using an iterative variation amount to obtain a new yaw angle.

[0120] The iteration unit is configured to iteratively determine an iteratively adjusted yaw azimuth according to the (i + 1)-th yaw point, the reference line, the new yaw angle, and the yaw distance, wherein, during the iteration process, the difference between two new yaw angles corresponding to two adjacent yaw points is the iterative variation amount.

[0121] According to an embodiment of the present disclosure, the first determination unit may include a determination subunit and an obtaining subunit.

[0122] The determination subunit is configured to determine an acute angle region between a target connection line between the i-th yaw point and a target path point with a later flight order and the reference line.

[0123] The obtaining subunit is configured to process the target connection line by using the yaw angle to obtain the yaw direction, wherein the yaw direction of the i-th yaw point is located in the acute angle region.

[0124] According to an embodiment of the present disclosure, the UAV path planning device 500 may further include a first judgment module.

[0125] The first judgment module is configured to perform path planning when it is detected that there is no obstacle between the adjusted (i + 1)-th yaw point and the i-th yaw point.

[0126] According to an embodiment of the present disclosure, the UAV path planning device 500 may further include a second judgment module and a third determination module.

[0127] The second judgment module is configured to adjust the yaw angle to obtain a first transition yaw angle when it is detected that there is an obstacle between the adjusted (i + 1)-th yaw point and the i-th yaw point.

[0128] The third determination module is configured to determine a new (i + 1)-th yaw point according to the first transition yaw angle and the i-th yaw point, so as to facilitate the UAV to perform path planning based on the new (i + 1)-th yaw point.

[0129] According to an embodiment of the present disclosure, the three-dimensional space map is constructed by using a first generation unit and a second generation unit.

[0130] The first generation unit is configured to load the image data of the target flight area in the initial coordinate system and generate a transition space map.

[0131] The second generation unit is configured to load the building model of the target flight area on the transition space map and generate a three-dimensional space map, where the building model may include the three-dimensional layout structure and geographical location of the building.

[0132] According to an embodiment of the present disclosure, the drone path planning device 500 may further include a second generation module and a transmission module.

[0133] The second generation module is configured to generate a total path according to a plurality of target paths, where different target paths correspond to different adjacent two target path points.

[0134] The transmission module is configured to transmit the total path to the drone so that the drone performs a flight mission according to the total path.

[0135] According to an embodiment of the present disclosure, any plurality of modules, units, and sub-units, or at least part of the functions of any of them, may be implemented in one module. Any one or more of the modules, units, and sub-units according to the embodiments of the present disclosure may be split into multiple modules for implementation. Any one or more of the modules, units, and sub-units according to the embodiments of the present disclosure may 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 may 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, units, and sub-units according to the embodiments of the present disclosure may be at least partially implemented as a computer program module, and when the computer program module is run, the corresponding functions may be executed.

[0136] For example, any combination of the first determination module 501, the second determination module 502, the adjustment module 503, the iteration module 504, and the generation module 505 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 first determination module 501, the second determination module 502, the adjustment module 503, the iteration module 504, and the generation module 505 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 of 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 an appropriate combination of any several of them. Alternatively, at least one of the first determination module 501, the second determination module 502, the adjustment module 503, the iteration module 504, and the generation module 505 can be at least partially implemented as a computer program module, and when the computer program module runs, it can execute the corresponding functions.

[0137] It should be noted that the part of the drone path planning device in the embodiments of the present disclosure corresponds to the part of the drone path planning method in the embodiments of the present disclosure. For the description of the part of the drone path planning device, please refer to the part of the drone path planning method specifically, and details will not be repeated here.

[0138] Figure 6 A block diagram of an electronic device suitable for implementing the method described above 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 limitations on the functions and usage scope of the embodiments of the present disclosure.

[0139] Such as Figure 6As shown, the 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 can include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an Application Specific Integrated Circuit (ASIC)), and so on. The processor 601 can also include on-board memory for caching purposes. The processor 601 can 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.

[0140] 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 can also be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 can 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.

[0141] According to an embodiment of the present disclosure, the electronic device 600 can 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 system 600 can 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 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.

[0142] 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 a communication part 609, and / or installed from a removable medium 611. When the computer program is executed by a processor 601, the above 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 system, device, apparatus, module, unit, etc. can be implemented by computer program modules.

[0143] The present disclosure also provides a computer-readable storage medium, which can be included in the device / device / system described in the above embodiment; or can exist alone without being assembled into the device / device / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0144] 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 memories (RAMs), read-only memories (ROMs), erasable programmable read-only memories (EPROMs (Erasable Programmable Read Only Memory, EPROM) or flash memories), portable compact disc read-only memories (Computer Disc Read-Only Memory, CD-ROMs), optical storage devices, magnetic storage devices, or any suitable combination of the above. 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, device, or device.

[0145] 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.

[0146] An embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program includes program codes for executing the method provided by the embodiment of the present disclosure. When the computer program product runs on an electronic device, the program codes are used to cause the electronic device to implement the drone path planning method provided by the embodiment of the present disclosure.

[0147] When the computer program is executed by the processor 601, the above functions defined in the system / apparatus of the embodiments of the present disclosure are performed. According to the embodiments of the present disclosure, the systems, apparatuses, modules, units, etc. described above can be implemented by computer program modules.

[0148] In one embodiment, the computer program can rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program can also be transmitted and distributed in the form of signals on a network medium, and be downloaded and installed through the communication part 609, and / or be installed from the removable medium 611. The program code included in the computer program can be transmitted by any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0149] According to the embodiments of the present disclosure, the program code for executing the computer program provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level procedures and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include but are not limited to, such as Java, C++, python, the "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, by using an Internet service provider to connect through the Internet).

[0150] 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 that contains one or more executable instructions for implementing a 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, may 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 may 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 may be combined and / or combined in various ways. All such combinations and / or combinations fall within the scope of the present disclosure.

[0151] 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 path planning of an unmanned aerial vehicle, comprising: determining two adjacent target path points of the unmanned aerial vehicle in a target flight area on a three-dimensional space map, wherein the three-dimensional space map is loaded with a building model; when it is detected that there is an obstacle between two adjacent target path points, determining an i-th yaw point between the target path point with a higher flight order and the boundary point of the obstacle; adjusting the yaw orientation of the unmanned aerial vehicle according to the i-th yaw point and a preset yaw rule, wherein the preset yaw rule includes a yaw angle and a yaw distance determined based on a reference line; after the unmanned aerial vehicle performs path planning based on the adjusted yaw orientation, in response to the existence of an obstacle between the current position after the path planning and the target path point with a lower flight order, continuously iteratively adjusting the yaw orientation of the unmanned aerial vehicle according to the (i + 1)-th yaw point and the preset yaw rule until there is no obstacle between the current position after the path planning based on the iteratively adjusted yaw orientation of the unmanned aerial vehicle and the target path point with a lower flight order; generating a target path between two adjacent target path points according to two adjacent target path points and all yaw points; wherein, the adjusting the yaw orientation of the unmanned aerial vehicle according to the i-th yaw point and the preset yaw rule includes: determining a yaw direction according to the i-th yaw point, the reference line, and the preset yaw angle; determining the adjusted yaw orientation according to the i-th yaw point, the yaw direction, and the preset yaw distance; wherein, the continuously iteratively adjusting the yaw orientation of the unmanned aerial vehicle according to the (i + 1)-th yaw point and the preset yaw rule includes: correcting the yaw angle by using an iterative change amount to obtain a new yaw angle; iteratively determining the iteratively adjusted yaw orientation according to the (i + 1)-th yaw point, the reference line, the new yaw angle, and the yaw distance, wherein during the iteration, the difference between two new yaw angles corresponding to two adjacent yaw points is the iterative change amount.

2. The method according to claim 1, wherein, the determining a yaw direction according to the i-th yaw point, the reference line, and the preset yaw angle includes: determining an acute angle region between a target connection line between the i-th yaw point and the target path point with a lower flight order and the reference line; processing the target connection line by using the yaw angle to obtain the yaw direction, wherein the yaw direction of the i-th yaw point is located in the acute angle region.

3. The method according to claim 1, wherein, before performing the path planning, it further includes: performing the path planning when it is detected that there is no obstacle between the adjusted (i + 1)-th yaw point and the i-th yaw point.

4. The method according to claim 3, wherein, before performing the path planning, it further includes: In the case where an obstacle is detected between the adjusted (i + 1)-th yaw point and the i-th yaw point, the yaw angle is adjusted to obtain a first transitional yaw angle; A new (i + 1)-th yaw point is determined according to the first transitional yaw angle and the i-th yaw point, so that the unmanned aerial vehicle can perform path planning based on the new (i + 1)-th yaw point.

5. The method according to claim 1, wherein, the method for constructing the three-dimensional space map includes: loading the image data of the target flight area in the initial coordinate system to generate a transitional space map; loading the building model of the target flight area on the transitional space map to generate the three-dimensional space map, wherein the building model includes the three-dimensional layout structure and geographical location of the building.

6. The method according to claim 1, further including: generating a total path according to a plurality of the target paths, wherein different target paths correspond to different adjacent two target path points; transmitting the total path to the unmanned aerial vehicle so that the unmanned aerial vehicle can execute a flight mission according to the total path.

7. A path planning device for an unmanned aerial vehicle, adopting the path planning method for an unmanned aerial vehicle according to any one of claims 1 to 6, the device includes: a first determination module, configured to determine two adjacent target path points of the unmanned aerial vehicle in the target flight area on the three-dimensional space map, wherein the three-dimensional space map is loaded with a building model; a second determination module, configured to determine an i-th yaw point between the target path point with a forward flight order and the boundary point of the obstacle in the case where an obstacle is detected between two adjacent target path points; an adjustment module, configured to adjust the yaw orientation of the unmanned aerial vehicle according to the i-th yaw point and a preset yaw rule, wherein the preset yaw rule includes a yaw angle and a yaw distance determined based on a reference line; an iteration module, configured to, after the unmanned aerial vehicle performs path planning based on the adjusted yaw orientation, in response to an obstacle existing between the current position after the path planning and the target path point with a backward flight order, continue to iteratively adjust the yaw orientation of the unmanned aerial vehicle according to the (i + 1)-th yaw point and the preset yaw rule until there is no obstacle between the current position after the path planning and the target path point with a backward flight order when the unmanned aerial vehicle performs path planning based on the iteratively adjusted yaw orientation; a generation module, configured to generate a target path between two adjacent target path points according to two adjacent target path points and all the yaw points; wherein, the adjustment module includes: a first determination unit, configured to determine the yaw direction of the i-th yaw point according to the i-th yaw point, the reference line, and a preset yaw angle; a second determination unit, configured to determine the adjusted yaw orientation according to the i-th yaw point, the yaw direction, and a preset yaw distance; wherein, the iteration module includes: a correction unit, configured to correct the yaw angle by using an iterative change amount to obtain a new yaw angle; An iterative unit for iteratively determining an iteratively adjusted yaw orientation based on the (i + 1)-th yaw point, a reference line, a new yaw angle, and a yaw distance, wherein, during the iteration process, the difference between two new yaw angles corresponding to two adjacent yaw points is an iterative variation amount.

8. An electronic device, comprising: 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 method according to any one of claims 1 to 6.

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