Unmanned aerial vehicle landing method and apparatus, device and storage medium

Abstract

An unmanned aerial vehicle landing method, comprising: acquiring a ground image within a visual range of an unmanned aerial vehicle (S101); performing scene seg mentation on the ground image, and on the basis of a scene segmentation result, acquiring a plurality of candidate alternate landing areas from a ground range corresponding to the ground image (S102); on the basis of the current position of the unmanned aerial vehicle and the positions of the candidate alternate landing areas, planning candidate flight paths for the unmanned aerial vehicle to land at the candidate alternate landing areas (S103); on the basis of the candidate flight paths, determining a target flight path and a target alternate landing area corresponding to the target flight path (S104); and landing at the target alternate landing area on the basis of the target flight path (S105).

Description

UAV landing method, device, equipment and storage medium Technical Field

[0001] The present application relates to the field of drone technology, and in particular to a drone landing method, device, equipment, and storage medium. Background Art

[0002] Unmanned aerial vehicles (UAVs), also known as drones, are unmanned aircraft controlled by radio remote control and self-contained programmable controls, or operated fully or intermittently autonomously by an onboard computer. With the advancement of UAV technology, UAVs have been widely used in a variety of fields, including aerial photography, agriculture, rescue operations, and plant protection. Landing a UAV is a crucial step in its operation, but current methods for landing UAVs lack sufficient intelligence.

[0003] Therefore, how to improve the intelligence of drone landing is an urgent problem that needs to be solved.

[0004] Summary of the Invention

[0005] The present application provides a drone landing method, device, equipment and storage medium to solve the problem of low drone landing intelligence in the prior art.

[0006] In a first aspect, the present application provides a method for landing a drone, comprising:

[0007] Acquiring ground images within the visual range of the UAV;

[0008] performing scene segmentation on the ground image, and acquiring a plurality of candidate alternate areas from a ground range corresponding to the ground image based on the scene segmentation result;

[0009] Planning a candidate flight path for the drone to land in the candidate alternate landing area based on the current location of the drone and the location of the candidate alternate landing area;

[0010] determining a target flight path and a target alternate landing area corresponding to the target flight path based on the candidate flight path;

[0011] Land at the target alternate landing area according to the target flight path.

[0012] Optionally, performing scene segmentation on the ground image and obtaining multiple candidate alternate areas from a ground range corresponding to the ground image based on the scene segmentation result includes:

[0013] Inputting the ground image into a trained semantic segmentation model based on the Farseg algorithm to obtain a segmentation result of the ground image; the semantic segmentation model is used to segment the ground image; and the segmentation result is used to characterize the category of the area included in the ground range;

[0014] According to the pre-equipment alternate landing area category and the segmentation result, a candidate alternate landing area is obtained from a ground range corresponding to the ground image.

[0015] Optionally, determining a target flight path and a target alternate area corresponding to the target flight path based on the candidate flight path includes:

[0016] Obtaining the flight distance and / or estimated flight duration corresponding to the candidate flight path;

[0017] selecting the target flight path from the candidate flight paths according to the flight distance and / or the expected flight duration;

[0018] Determine a target alternate landing area corresponding to the target flight path.

[0019] Optionally, obtaining the estimated flight duration corresponding to the candidate flight path includes:

[0020] Obtaining flight parameters of the UAV and environmental parameters of the area where the candidate flight path is located;

[0021] An estimated flight duration corresponding to the candidate flight path is determined based on the flight parameters, the environmental parameters, and the flight distance of the candidate flight path.

[0022] Optionally, selecting the target flight path from the candidate flight paths according to the flight distance and / or the expected flight duration includes:

[0023] Obtain the remaining flight endurance of the drone;

[0024] Selecting a target flight path to be determined from the candidate flight paths, the flight distance of which is less than or equal to the remaining flight endurance;

[0025] The target flight path is selected from the target flight paths to be determined according to the flight distance of the target flight paths to be determined and / or the estimated flight duration.

[0026] Optionally, planning a candidate flight path for the drone to land in the candidate alternate landing area based on the current location of the drone and the location of the candidate alternate landing area includes:

[0027] Detecting whether there are any obstacles on the flight path of the UAV landing to the candidate alternate landing area;

[0028] If the obstacle exists, obtaining the obstacle avoidance strategy of the UAV;

[0029] Plan a candidate flight path for the drone to land in the candidate alternate landing area based on the obstacle avoidance strategy of the drone, the position of the drone, and the position of the candidate alternate landing area.

[0030] Optionally, if the obstacle exists, the method further includes:

[0031] Acquiring environmental parameters of an area where the flight path is located, wherein the environmental parameters include wind direction;

[0032] Determining, based on the wind direction, a direction around the obstacle where the wind direction is smaller;

[0033] Obstacle avoidance planning is performed in a direction where the wind direction is smaller around the obstacle.

[0034] In a second aspect, the present application provides a drone landing device, comprising:

[0035] An acquisition module, configured to acquire ground images within the visual range of the drone;

[0036] a processing module configured to perform scene segmentation on the ground image and, based on the scene segmentation results, obtain a plurality of candidate alternate areas from a ground range corresponding to the ground image; plan a candidate flight path for the UAV to land in the candidate alternate areas based on the current position of the UAV and the positions of the candidate alternate areas; and determine a target flight path and a target alternate area corresponding to the target flight path based on the candidate flight paths;

[0037] An execution module is used to land at the target alternate landing area according to the target flight path.

[0038] In a third aspect, the present application provides an electronic device, comprising: a processor, a communication interface, and a memory; the processor is communicatively connected to the communication interface and the memory respectively;

[0039] The memory stores computer-executable instructions;

[0040] The communication interface communicates and interacts with external devices;

[0041] The processor executes the computer-executable instructions stored in the memory to implement the method as described in any one of the first aspects.

[0042] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement the drone landing method as described in any one of the first aspects.

[0043] In a fifth aspect, the present application provides a computer program product, which, when executed by a processor, is used to implement the drone landing method as described in any one of the first aspects.

[0044] The drone landing method, apparatus, device, and storage medium provided in this application obtain a ground image within the visual range of the drone, perform scene segmentation on the ground image, and obtain multiple candidate alternate landing areas from the ground range corresponding to the ground image based on the scene segmentation results. Based on the current position of the drone and the location of the candidate alternate landing area, a candidate flight path for the drone to land in the candidate alternate landing area is planned. Based on the candidate flight path, a target flight path and a target alternate landing area corresponding to the target flight path are determined, and the drone lands in the target alternate landing area according to the target flight path. This allows the drone to automatically determine an alternate landing area that is convenient for landing and automatically land in the alternate landing area, thereby improving the intelligence, stability, and safety of the drone landing. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the application.

[0046] FIG1 is a schematic diagram of a flow chart of a method for landing a drone provided in an embodiment of the present application;

[0047] FIG2 is a schematic diagram of a flow chart of another method for landing a drone provided in an embodiment of the present application;

[0048] FIG3 is a schematic diagram of a flow chart of another method for landing a drone provided in an embodiment of the present application;

[0049] FIG4 is a schematic diagram of a flow chart of another method for landing a drone according to an embodiment of the present application;

[0050] FIG5 is a schematic diagram of a scenario of obstacle avoidance planning provided in an embodiment of the present application;

[0051] FIG6 is a schematic structural diagram of a UAV landing device provided in an embodiment of the present application;

[0052] FIG7 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.

[0053] The above drawings illustrate specific embodiments of the present application, which will be described in more detail below. These drawings and the textual description are not intended to limit the scope of the present application in any way, but rather to illustrate the concepts of the present application to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0054] Exemplary embodiments will be described in detail herein, with examples illustrated in the accompanying drawings. In the following description, when referring to the drawings, identical numerals in different figures represent identical or similar elements, unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

[0055] Currently, drone landing is primarily achieved through manual control or automatic landing. In the manual control method, the drone typically receives control commands from a user's handheld remote control terminal, lowers its altitude, and controls its flight direction accordingly, thereby achieving the landing function. This landing method requires high user control. Any operational errors can lead to poor flight stability during landing, resulting in collisions and damage.

[0056] In order to provide a more stable and safe landing function, it is currently possible to control the drone to achieve the landing function through automatic landing. In this implementation method, the user can send an automatic landing command to the drone through a handheld remote control terminal, and the drone will automatically land with one click according to the automatic landing command. However, after the existing drone triggers the one-click landing, the drone will enter the automatic landing mode. At this time, the drone will no longer receive the flight operation command from the handheld remote control terminal, so the user cannot set the parameters of the drone's horizontal dimension. When the user wants to perform a one-click landing operation on the drone at a certain moment, it is found that the current position of the drone is not suitable for landing. The only option is to perform flight operations on the drone first, and then perform one-click landing on the drone when the drone flies to a relatively ideal position. Therefore, the current drone landing method has the problem of low intelligence.

[0057] In view of this, the present application provides a drone landing method, which automatically obtains candidate alternate landing areas where the drone can land by performing scene segmentation on ground images acquired by the drone, and selects a target alternate landing area that meets the landing strategy from the candidate alternate landing areas, and controls the drone to automatically land in the target alternate landing area according to the flight path to the target alternate landing area, thereby improving the intelligence of the drone landing method.

[0058] The execution subject of the data processing method provided in this application can be a drone, or a processing chip of the drone, or software or program code that implements the drone landing method. When the execution subject is a drone, the drone can be deployed with software or program code that runs the drone landing method, and the landing of the drone is controlled by the software or program code. The execution subject of the method can also be the remote control terminal of the drone, or it can also be a cloud platform with drone control function. When the execution subject is a cloud platform, the control of the landing of the drone in the method can be executed in the cloud. The cloud platform can be logically divided into multiple parts according to actual needs, and each part has different functions. The various parts of the drone control platform can be deployed in any two or three of the electronic device (located on the user side), the edge environment and the cloud environment. The edge environment is an environment that includes a collection of edge electronic devices that are close to the electronic device. The edge electronic devices include: edge servers, edge stations with computing power, etc. The various parts of the drone control platform deployed in different environments or devices work together to realize the functions of the drone control platform. It should be understood that this application does not restrict the deployment of which parts of the drone control platform are deployed in what specific environment. In actual application, it can be adaptively deployed according to the computing power of the electronic equipment, the resource availability of the edge environment and the cloud environment, or the specific application requirements.

[0059] The following uses a drone as an example to illustrate the technical solution of this application and how it solves the aforementioned technical problems. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. The following embodiments of this application are described in conjunction with the accompanying drawings.

[0060] FIG1 is a flow chart of a method for landing a drone provided in an embodiment of the present application. As shown in FIG1 , the method may include:

[0061] S101. Acquire ground images within the visual range of the UAV.

[0062] Among them, the drone is currently in flight, and the drone's visual range may include the ground area around the drone, such as the ground area below the drone, the ground area in front of the drone, the ground area behind the drone, etc. This application does not impose any restrictions on this.

[0063] The ground image may be acquired by the drone itself, for example, by an image acquisition device such as a camera or a still camera on the drone. Alternatively, the ground image may be acquired by the drone from a device or network that is in communication with the drone. For example, the ground image may be acquired from a cloud platform connected to the drone based on the drone's location, or the ground image within the drone's visual range corresponding to the location may be acquired from the network.

[0064] The ground image may be a remote sensing image, for example, a high spatial resolution remote sensing image (referred to as a high-resolution image), so as to obtain richer ground information in the ground image and improve the accuracy of the ground image.

[0065] Optionally, the drone may begin capturing ground images within its visual range upon receiving an automatic landing instruction, or may periodically capture ground images within its visual range. Alternatively, the drone may automatically execute an automatic landing procedure and begin capturing ground images within its visual range when its remaining flight endurance falls below a preset endurance threshold.

[0066] S102: Perform scene segmentation on the ground image, and obtain multiple candidate alternate areas from a ground range corresponding to the ground image based on the scene segmentation result.

[0067] The candidate alternate landing area can be, for example, a baseball field, tennis court, basketball court, ground runway, or football field, which are suitable areas for drone landing. The method for performing scene segmentation on the ground image can be any image segmentation method, such as a threshold-based segmentation method, a region-based segmentation method, or an edge-based segmentation method. For example, a network such as Deeplab, Deeplabv2, Deeplabv3, or DenseASPP can be used to perform segmentation on a specific scene.

[0068] By using the image segmentation method, the ground image is divided into non-overlapping areas, and each segmented area is marked to obtain a scene segmentation result. The scene segmentation result includes the type of each segmented area, for example, it can be the aforementioned baseball field, tennis court, basketball court, etc. The present application does not limit the image segmentation method. The specific method of performing scene segmentation on the ground image by the image segmentation method can refer to the existing technology and will not be described here. After obtaining the scene segmentation result, a ground area of ​​the same type as the candidate alternate area is determined from the scene segmentation result as the candidate alternate area.

[0069] S103: Planning a candidate flight path for the drone to land in the candidate alternate landing area based on the current location of the drone and the location of the candidate alternate landing area.

[0070] The current position of the drone is obtained, for example, by a positioning device on the drone. The current position may include the position of the drone in the horizontal dimension and the flight altitude of the drone, which may be represented by an altitude. The position of the candidate alternate area may be the center of the candidate alternate area, or any position within the candidate alternate area. For example, it may be any position within the candidate alternate area within a preset distance from the edge of the candidate alternate area, and the present application does not impose any restrictions on this. The position may include the position in the horizontal dimension and the altitude of the position.

[0071] A target location is selected from the candidate alternate areas and used as the landing location. Based on the current location of the drone and the location of the candidate alternate areas, a candidate flight path is planned for the drone to land in the candidate alternate areas. For example, a candidate flight path may be selected as the shortest distance, a flight path with the fewest turns, or a flight path with the fewest obstacles. The flight path planning can refer to any existing drone flight path planning method and is not described in detail here.

[0072] S104. Determine a target flight path and a target alternate landing area corresponding to the target flight path based on the candidate flight paths.

[0073] In one possible implementation, the target flight path is determined according to the flight distances corresponding to the candidate flight paths. For example, the candidate flight path with the shortest flight distance may be used as the target flight path.

[0074] Another possible implementation is to determine the target flight path according to the estimated flight durations corresponding to the candidate flight paths. For example, the candidate flight path with the shortest estimated flight duration may be used as the target flight path.

[0075] Another possible implementation method is to determine the target flight path based on the flight distance and expected flight time corresponding to the candidate flight paths. For example, the score of each candidate flight path can be determined based on the flight distance, flight distance weight, expected flight time, and expected flight time weight, and the target flight path can be determined based on the scoring result.

[0076] S105. Land at the target alternate landing area according to the target flight path.

[0077] One possible implementation method is that the end point of the target flight path is above the landing position of the target alternate landing area. After the drone flies along the target flight path to the landing position, it lowers its flight altitude until it lands in the target alternate landing area.

[0078] Another possible implementation is that the end point of the target flight path is the ground where the landing position of the target alternate landing area is located, and the UAV flies along the target flight path and lands in the target alternate landing area.

[0079] The drone landing method provided in an embodiment of the present application obtains a ground image within the visual range of the drone, performs scene segmentation on the ground image, and obtains multiple candidate alternate landing areas from the ground range corresponding to the ground image based on the scene segmentation results. Based on the current position of the drone and the location of the candidate alternate landing area, a candidate flight path for the drone to land in the candidate alternate landing area is planned. Based on the candidate flight path, a target flight path and a target alternate landing area corresponding to the target flight path are determined, and the drone lands in the target alternate landing area according to the target flight path. This allows the drone to automatically determine an alternate landing area that is convenient for landing and automatically land in the alternate landing area, thereby improving the intelligence, stability, and safety of the drone landing.

[0080] Below, taking the ground image as a high-resolution image and improving the accuracy of the ground image as an example, a detailed explanation is given on how to perform scene segmentation on the ground image in step S102, and obtain multiple candidate alternate landing areas from the ground range corresponding to the ground image based on the scene segmentation result.

[0081] At present, high-resolution images always face problems such as large scale changes, large background intra-class variance, and unbalanced distribution between foreground and background. As a result, there are problems such as a small proportion of pixels in the UAV emergency landing area, inconsistency in edge information, and irregular distribution of feature deformation. The existing image segmentation algorithm is not sufficient to effectively deal with the above problems caused by the large background intra-class variance and unbalanced distribution between foreground and background, resulting in low accuracy and efficiency of scene segmentation for the above-mentioned ground images.

[0082] FIG2 is a flow chart of another method for landing a drone according to an embodiment of the present application. As shown in FIG2 , the aforementioned step S102 may include:

[0083] S201: Input the ground image into a trained semantic segmentation model based on the Farseg algorithm to obtain a segmentation result of the ground image.

[0084] Among them, the semantic segmentation model is used to segment the ground image, and the segmentation result is used to characterize the category of the area included in the ground range. The trained semantic segmentation model based on the Farseg algorithm can utilize the symbiotic relationship between geospatial scenes and geospatial objects, associate context related to the foreground, and improve the model's recognition ability for foreground features. In addition, the semantic segmentation model includes a foreground-aware optimization function, which includes three steps: difficult sample estimation, dynamic weighting, and backpropagation, thereby suppressing a large number of simple background samples and allowing the entire network to focus on foreground and difficult samples for balanced optimization, thereby reducing the contribution of a large number of simple samples to the gradient to alleviate the problem of imbalance between foreground and background. The specific architecture and training method of the semantic segmentation model based on the Farseg algorithm can refer to the existing technology and will not be repeated here.

[0085] The trained semantic segmentation model based on the Farseg algorithm can accurately segment the high-resolution image of the ground range corresponding to the ground image into different areas, and generate a segmentation result of the ground image.

[0086] S202: Acquire candidate alternate landing areas from a ground range corresponding to the ground image according to the pre-equipped alternate landing area category and the segmentation result.

[0087] Based on the segmentation result, each region in the ground image data and the type of each region are obtained. Based on the type of each region and the pre-equipment landing area category, areas within the ground range corresponding to the ground image that belong to the pre-equipment landing area category are determined and designated as candidate alternate landing areas.

[0088] The method provided in the embodiment of the present application obtains the segmentation result of the ground image by inputting the ground image into a trained semantic segmentation model based on the Farseg algorithm, and obtains the candidate alternate landing area from the ground range corresponding to the ground image according to the pre-equipment landing area category and the segmentation result, thereby reducing the problems caused by the large background intra-class variance and unbalanced foreground and background distribution of high-resolution images, and improving the accuracy and efficiency of scene segmentation of the above-mentioned ground images.

[0089] The following describes in detail how to determine the target flight path and the target alternate landing area corresponding to the target flight path based on the candidate flight paths in the aforementioned step S104.

[0090] FIG3 is a flow chart of another method for landing a drone provided in an embodiment of the present application. As shown in FIG3 , the aforementioned step S104 may include:

[0091] S301: Obtain the flight distance and / or estimated flight duration corresponding to the candidate flight path.

[0092] One possible implementation method is to obtain the flight distance based on the path length of the flight path, and obtain the estimated flight time of the candidate flight path based on the flight speed of the UAV. For example, the estimated flight time of the flight path can be obtained by dividing the flight distance by the flight speed.

[0093] Another possible implementation method is to consider the environmental parameters of the area where the candidate flight path is located to determine the estimated flight duration. The environmental parameters may include wind speed and direction in the area, as well as parameters of obstacles in the area. This implementation method can be achieved by the following steps:

[0094] S3011. Obtain the flight parameters of the UAV and the environmental parameters of the area where the candidate flight path is located.

[0095] The flight parameters of the UAV may include the flight speed, turning speed, etc. of the UAV, or other flight parameters that determine the flight speed and turning speed, such as the speed and output power of the UAV's drive motor.

[0096] When the environmental parameters include wind speed and direction within the area, the current wind speed and direction within the area can be obtained from the network, or the wind speed and direction at the drone's location can be used as the wind speed and direction within the area. When the environmental parameters include parameters of obstacles within the area, map data for the area can be obtained based on the area's location, or the presence of obstacles on the candidate flight path can be determined from the map data, as well as the size of the obstacles. For example, if the obstacle is a high-rise building, the width, length, and height of the building can be obtained to represent the size of the obstacle.

[0097] S3012. Determine an estimated flight duration corresponding to the candidate flight path based on the flight parameters, environmental parameters, and the flight distance of the candidate flight path.

[0098] When the flight parameters include flight speed and the environmental parameters include wind speed and wind direction, the actual flight speed of the drone is calculated based on the flight speed, wind speed, and wind direction. The estimated flight duration is calculated based on the actual flight speed and the flight distance of the candidate flight path.

[0099] Furthermore, when the flight parameters also include turning speed, the estimated flight duration can be modified based on the number of turns in the candidate flight path. In this implementation, the duration of the drone's turns calculated based on turning speed is replaced by the duration of the drone's flight speed through these turns, resulting in a more accurate estimated flight duration.

[0100] Furthermore, when the environmental parameters also include parameters of obstacles in the area, the actual time it takes for the drone to execute the obstacle avoidance strategy to avoid the obstacle can be determined based on the drone's obstacle avoidance strategy, and the above-mentioned estimated flight time can be corrected according to the actual time to obtain a more accurate estimated flight time.

[0101] S302: Select a target flight path from candidate flight paths based on the flight distance and / or the estimated flight duration.

[0102] Implementation A: Determine the target flight path according to the flight distances corresponding to the candidate flight paths. For example, the candidate flight path with the shortest flight distance may be used as the target flight path.

[0103] Implementation method B: Determine the target flight path according to the estimated flight durations corresponding to the candidate flight paths. For example, the candidate flight path with the shortest estimated flight duration may be used as the target flight path.

[0104] Implementation method C: Determine the target flight path based on the flight distance and expected flight time corresponding to the candidate flight paths. For example, the score of each candidate flight path can be determined based on the flight distance, flight distance weight, expected flight time, and expected flight time weight, and the target flight path can be determined based on the scoring result.

[0105] Optionally, in the above implementations AC, the remaining flight endurance of the drone may be further considered to select a target flight path from the candidate flight paths. This implementation may be achieved by the following steps:

[0106] S3021. Get the remaining flight time of the drone.

[0107] The remaining flight endurance of the drone can be calculated by calculating the remaining energy of the drone, and the remaining flight endurance of the drone is determined based on the remaining energy and the operating status of the drone. For example, for an electric drone, the remaining energy is the remaining battery power of the drone. Alternatively, the remaining flight endurance can be calculated by calculating the remaining flight time of the drone. Based on the remaining flight time of the drone and the flight speed of the drone, the distance that the drone can fly at the remaining flight time at the flight speed is calculated, and the distance is used as the remaining flight endurance of the drone.

[0108] S3022. Select a target flight path to be determined from the candidate flight paths, whose flight distance is less than or equal to the remaining flight endurance.

[0109] One possible implementation is to use a candidate flight path whose flight distance is less than or equal to the remaining flight endurance as the target flight path to be determined.

[0110] Another possible implementation involves setting a flight range protection margin to prevent the drone from running out of energy. This ensures that the drone's remaining flight range after landing is greater than or equal to the flight range protection margin, thereby improving landing safety. Candidate flight paths with a flight distance less than or equal to the remaining flight range minus the flight range protection margin are selected as the target flight path to be determined.

[0111] S3023: Select a target flight path from the target flight paths to be determined based on the flight distance and / or the estimated flight duration of the target flight paths to be determined.

[0112] The implementation method of selecting the target flight path from the target flight path to be determined based on the flight distance and / or the expected flight duration of the target flight path to be determined is similar to the implementation method of selecting the target flight path from the candidate flight paths based on the flight distance and / or the expected flight duration in the aforementioned step S302, and will not be repeated here.

[0113] S303: Determine the target alternate landing area corresponding to the target flight path.

[0114] The target alternate area is determined based on a mapping relationship between the target flight path and the target alternate area, as well as the target flight path. Alternatively, the location of the endpoint of the target flight path may be determined, and based on the coordinates of the location of the endpoint, the candidate alternate area including the coordinates may be determined as the target alternate area.

[0115] The method provided in the embodiments of the present application obtains the flight distance and / or estimated flight duration corresponding to candidate flight paths, and then selects a target flight path and a target alternate landing area corresponding to the target flight path from the candidate flight paths based on the flight distance and / or estimated flight duration, as well as a flight path selection strategy. Furthermore, the target alternate landing area is comprehensively determined by considering factors such as environmental parameters and remaining flight endurance, thereby improving the intelligence and efficiency of the drone's landing.

[0116] Next, taking the consideration of whether there are obstacles on the flight path of the candidate alternate landing area as an example, a detailed introduction is given to how to plan the candidate flight path for the drone to land in the candidate alternate landing area based on the current position of the drone and the position of the candidate alternate landing area in the aforementioned step S103.

[0117] FIG4 is a flow chart of another method for landing a drone provided in an embodiment of the present application. As shown in FIG4 , the aforementioned step S103 may include:

[0118] S401: Detect whether there are any obstacles on the flight path of the UAV landing in the candidate alternate landing area.

[0119] The obstacles may be buildings, trees, rocks, mountains, etc. that may hinder the flight of the UAV. The obstacles may be monitored by an image acquisition device deployed on the UAV or acquired through map data.

[0120] For example, the map data includes volume information, size information, etc. of obstacles such as buildings or mountains that can be displayed in the map data. The drone obtains the map data through a network or communication connection, and obtains the volume information, size information, etc. of the obstacle from the map data.

[0121] S402: If there is an obstacle, obtain the obstacle avoidance strategy of the UAV.

[0122] One possible implementation method is to bypass the obstacle through an existing obstacle avoidance strategy. For example, if the obstacle is on the line between the current position of the UAV and the position of the candidate alternate landing area, the obstacle avoidance strategy can be that when the UAV flies near the obstacle, it can bypass the obstacle to a position where there is no obstacle blocking it based on the volume and size information of the obstacle, pass the obstacle, and return to the line after passing the obstacle.

[0123] Another possible implementation method is to perform obstacle avoidance planning by using the obstacle to reduce the impact of wind direction on the UAV's flight. This implementation method can be achieved by the following steps:

[0124] S4021. Obtain environmental parameters of the area where the flight path is located.

[0125] The environmental parameters include wind direction. The method of obtaining the environmental parameters is the same as that in the aforementioned step S3011, and will not be repeated here.

[0126] S4022. Determine the direction of the obstacle with the smallest wind direction based on the wind direction.

[0127] The direction opposite to the wind direction is determined as the direction with the smallest wind direction around the obstacle. For example, if the wind direction is easterly, the west side of the obstacle is determined as the direction with the smallest wind direction around the obstacle.

[0128] S4023. Perform obstacle avoidance planning in the direction with lower wind direction around the obstacle.

[0129] In one possible implementation, the obstacle avoidance plan is that when the UAV flies around the obstacle, it first flies to a direction with a smaller wind direction around the obstacle, and then flies in this direction according to a flight trajectory around the obstacle.

[0130] Another possible implementation method is that the obstacle avoidance planning is that when the UAV flies around the obstacle, it first flies to a direction with smaller wind direction around the obstacle, and determines the height difference between the current position of the UAV and the position of the candidate alternate landing area based on the current position of the UAV and the position of the candidate alternate landing area, and determines the height to be lowered based on the height difference. The height to be lowered is less than the height difference, and the height to be lowered can be preset or determined based on a preset target height. For example, if the height difference is 20 meters and the preset target height is 5 meters, then the height to be lowered is 15 meters. At this direction of the obstacle, after lowering the height to be lowered, the drone flies according to the flight trajectory that bypasses the obstacle. Figure 5 is a scene diagram of an obstacle avoidance planning provided in an embodiment of the present application. As shown in Figure 5, the obstacle avoidance planning is the same as the description in the implementation method.

[0131] S403: Planning a candidate flight path for the drone to land at the candidate alternate landing area based on the drone's obstacle avoidance strategy, the drone's location, and the location of the candidate alternate landing area.

[0132] Based on the drone's obstacle avoidance strategy, an obstacle avoidance flight path is determined for the drone to circumvent the obstacle. Based on the drone's location and the location of the candidate alternate landing area, a line is determined connecting the two. This line is divided into a first flight path before the starting point of the obstacle avoidance flight path and a second flight path after the end point of the obstacle avoidance flight path. The first flight path, the obstacle avoidance flight path, and the second flight path are concatenated to obtain a candidate flight path for the drone to land in the candidate alternate landing area.

[0133] The method provided in an embodiment of the present application detects whether there are obstacles on the flight path of a drone landing to a candidate alternate landing area. If an obstacle is present, the drone's obstacle avoidance strategy is obtained. Based on the drone's obstacle avoidance strategy, the drone's location, and the location of the candidate alternate landing area, a candidate flight path for the drone landing to the candidate alternate landing area is planned, enabling the drone to obtain a candidate flight path that avoids the obstacle. Furthermore, the obstacle blocks wind that could affect the drone's stability, and obstacle avoidance planning is performed in directions with less wind around the obstacle, further improving the stability and safety of the drone's landing.

[0134] FIG6 is a schematic diagram of the structure of a UAV landing device provided in an embodiment of the present application. As shown in FIG6 , the UAV landing device may include: an acquisition module 11 , a processing module 12 , and an execution module 13 .

[0135] The acquisition module 11 is used to acquire ground images within the visual range of the UAV.

[0136] Processing module 12 is configured to perform scene segmentation on the ground image and, based on the scene segmentation results, obtain multiple candidate alternate areas from the ground range corresponding to the ground image. Based on the current location of the UAV and the locations of the candidate alternate areas, a candidate flight path is planned for the UAV to land in the candidate alternate areas. Based on the candidate flight paths, a target flight path and a target alternate area corresponding to the target flight path are determined.

[0137] The execution module 13 is configured to land at the target alternate landing area according to the target flight path.

[0138] In one possible implementation, processing module 12 is specifically configured to input the ground image into a trained semantic segmentation model based on the Farseg algorithm to obtain a segmentation result for the ground image. Based on the pre-flight area category and the segmentation result, candidate alternate landing areas are obtained from the ground range corresponding to the ground image. The semantic segmentation model is used to segment the ground image. The segmentation result is used to characterize the category of the area included in the ground range.

[0139] In another possible implementation, the acquisition module 11 is specifically configured to acquire the flight distance and / or estimated flight duration corresponding to the candidate flight path. The processing module 12 is specifically configured to select the target flight path from the candidate flight paths based on the flight distance and / or estimated flight duration, and determine the target alternate landing area corresponding to the target flight path.

[0140] In this implementation, one possible implementation is that acquisition module 11 is specifically configured to obtain flight parameters of the UAV and environmental parameters of the area where the candidate flight path is located. Processing module 12 is specifically configured to determine an estimated flight duration corresponding to the candidate flight path based on the flight parameters, the environmental parameters, and the flight distance of the candidate flight path.

[0141] In another possible implementation, the acquisition module 11 is specifically configured to obtain the remaining flight endurance of the drone. The processing module 12 is specifically configured to select a target flight path from the candidate flight paths whose flight distance is less than or equal to the remaining flight endurance. The target flight path is selected from the candidate flight paths based on the flight distance and / or estimated flight duration of the target flight path.

[0142] In any of the above implementations, processing module 12 is specifically configured to detect whether there is an obstacle on the UAV's flight path to the candidate alternate landing area. If such an obstacle is present, the UAV's obstacle avoidance strategy is obtained. Based on the UAV's obstacle avoidance strategy, the UAV's location, and the location of the candidate alternate landing area, a candidate flight path for the UAV to land in the candidate alternate landing area is planned.

[0143] When an obstacle is present, the acquisition module 11 is optionally further configured to acquire environmental parameters of the flight path area, including wind direction. The processing module 12 is further configured to determine, based on the wind direction, a direction with lower wind direction around the obstacle. Obstacle avoidance planning is performed in the direction with lower wind direction around the obstacle.

[0144] The drone landing device provided in the embodiment of the present application can execute the drone landing method in the above method embodiment. Its implementation principle and technical effects are similar and will not be repeated here.

[0145] Figure 7 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device is configured to execute the aforementioned drone landing method, and may be, for example, the aforementioned drone. As shown in Figure 7 , the electronic device 700 may include at least one processor 701, a memory 702, and a communication interface 703.

[0146] The memory 702 is used to store programs. Specifically, the programs may include program codes, and the program codes include computer operation instructions.

[0147] The memory 702 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0148] The processor 701 is configured to execute computer-executable instructions stored in the memory 702 to implement the method described in the aforementioned method embodiment. The processor 701 may be a CPU, an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0149] The processor 701 can communicate and interact with external devices through the communication interface 703. The external device can be, for example, the remote control terminal of the drone mentioned above. In a specific implementation, if the communication interface 703, the memory 702, and the processor 701 are implemented independently, the communication interface 703, the memory 702, and the processor 701 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc., but it does not mean that there is only one bus or one type of bus.

[0150] Optionally, in a specific implementation, if the communication interface 703, the memory 702 and the processor 701 are integrated on a chip, the communication interface 703, the memory 702 and the processor 701 can complete communication through an internal interface.

[0151] The present application also provides a computer-readable storage medium, which may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, and other media that can store program codes. Specifically, the computer-readable storage medium stores program instructions, and the program instructions are used for the methods in the above embodiments.

[0152] The present application also provides a program product, the program product including execution instructions stored in a readable storage medium. At least one processor of a computing device can read the execution instructions from the readable storage medium, and at least one processor executes the execution instructions so that the computing device implements the above-mentioned drone landing method.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for landing a drone, characterized in that: include: Acquire ground images within the visual range of the drone; Performing scene segmentation on the ground image, and acquiring a plurality of candidate alternate landing areas from a ground range corresponding to the ground image based on the scene segmentation result; Planning a candidate flight path for the drone to land at the candidate alternate landing area according to the current position of the drone and the position of the candidate alternate landing area; Determining a target flight path and a target alternate landing area corresponding to the target flight path according to the candidate flight path; Land at the target alternate landing area according to the target flight path.

2. The method according to claim 1, characterized in that The performing scene segmentation on the ground image, and acquiring a plurality of candidate alternate areas from a ground range corresponding to the ground image based on the scene segmentation result, includes: Inputting the ground image into a trained semantic segmentation model based on the Farseg algorithm to obtain a segmentation result of the ground image; the semantic segmentation model is used to segment the ground image; the segmentation result is used to characterize the category of the area included in the ground range; According to the category of the pre-equipped alternate landing area and the segmentation result, a candidate alternate landing area is obtained from a ground range corresponding to the ground image.

3. The method according to claim 1, characterized in that The determining, according to the candidate flight path, a target flight path and a target alternate landing area corresponding to the target flight path includes: Obtaining the flight distance and / or estimated flight duration corresponding to the candidate flight path; Selecting the target flight path from the candidate flight paths according to the flight distance and / or the estimated flight duration; Determine a target alternate landing area corresponding to the target flight path.

4. The method according to claim 3, characterized in that The obtaining of the estimated flight duration corresponding to the candidate flight path includes: Acquire the flight parameters of the UAV and the environmental parameters of the area where the candidate flight path is located; An estimated flight duration corresponding to the candidate flight path is determined according to the flight parameters, the environmental parameters, and the flight distance of the candidate flight path.

5. The method according to claim 3, characterized in that: The step of selecting the target flight path from the candidate flight paths according to the flight distance and / or the estimated flight duration includes: Obtaining the remaining flight endurance of the drone; Selecting a target flight path to be determined whose flight distance is less than or equal to the remaining flight endurance from the candidate flight paths; The target flight path is selected from the target flight paths to be determined according to the flight distance of the target flight paths to be determined and / or the estimated flight duration.

6. The method according to any one of claims 1 to 5, characterized in that: The step of planning a candidate flight path for the drone to land at the candidate alternate landing area according to the current position of the drone and the position of the candidate alternate landing area includes: Detecting whether there are obstacles on the flight path of the UAV landing to the candidate alternate landing area; If the obstacle exists, obtaining the obstacle avoidance strategy of the drone; According to the obstacle avoidance strategy of the UAV, the position of the UAV, and the position of the candidate alternate landing area, a candidate flight path for the UAV to land in the candidate alternate landing area is planned.

7. The method according to claim 6, characterized in that If the obstacles mentioned above exist, it also includes: Acquire environmental parameters of the area where the flight path is located, wherein the environmental parameters include wind direction; According to the wind direction, determining a direction around the obstacle where the wind direction is smaller; Obstacle avoidance planning is performed in a direction where the wind direction is smaller around the obstacle.

8. A drone landing device, characterized in that: include: An acquisition module, used to acquire ground images within the visual range of the drone; a processing module, configured to perform scene segmentation on the ground image, and obtain a plurality of candidate alternate landing areas from a ground range corresponding to the ground image based on the scene segmentation result; plan a candidate flight path for the drone to land at the candidate alternate landing area according to the current position of the drone and the position of the candidate alternate landing area; and determine a target flight path and a target alternate landing area corresponding to the target flight path according to the candidate flight path; An execution module is used to land at the target alternate landing area according to the target flight path.

9. An electronic device, characterized in that: include: A processor, a communication interface and a memory, wherein the processor is communicatively connected to the communication interface and the memory respectively; The memory stores computer-executable instructions; The communication interface communicates and interacts with external devices; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the drone landing method according to any one of claims 1 to 7.

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