Unmanned aerial vehicle state detection method, device and storage medium

Abstract

The present application relates to the field of vehicle-mounted unmanned aerial vehicles. Provided in the present application are an unmanned aerial vehicle state detection method, a device and a storage medium. The method comprises: acquiring a bay inside monitoring image of a vehicle-mounted bay that is collected by a camera; and performing recognition processing on the monitoring image to acquire state information of the inside of the bay. In the above process, the state information of the inside of the bay can be acquired by means of the preset camera, thereby knowing the unmanned aerial vehicle state, and improving the efficiency of acquiring unmanned aerial vehicle states.

Description

Method, device and storage medium for detecting state of unmanned aerial vehicle

[0001] The present application claims priority from the Chinese patent application No. 202410841529.X filed on June 26, 2024, and entitled "Method, device and storage medium for detecting state of unmanned aerial vehicle", the content of which is incorporated herein by reference in its entirety. TECHNICAL FIELD

[0002] The present application relates to the field of vehicle-mounted unmanned aerial vehicles, and in particular to a method, device and storage medium for detecting state of unmanned aerial vehicle. BACKGROUND

[0003] In the application scenario of vehicle-mounted unmanned aerial vehicles, by setting a cabin for takeoff and landing of unmanned aerial vehicles on a vehicle, the unmanned aerial vehicle can be closely combined with the vehicle, thereby improving the operation convenience and application range of the unmanned aerial vehicle.

[0004] In the prior art, the state of the unmanned aerial vehicle in the cabin is usually checked and confirmed by a person. However, the manual checking of the state of the unmanned aerial vehicle is time-consuming and labor-intensive, which may result in untimely information acquisition and increase the complexity and uncertainty of the operation. In particular, in an emergency, the efficiency of manual checking is difficult to guarantee. Therefore, there is an urgent need for a more automated and efficient solution to monitor the state of the unmanned aerial vehicle, reduce the labor input, and improve the efficiency of acquiring the state of the unmanned aerial vehicle. SUMMARY

[0005] The present application provides a method, device and storage medium for detecting state of unmanned aerial vehicle, which is used to monitor the state of the unmanned aerial vehicle and improve the efficiency of acquiring the state of the unmanned aerial vehicle.

[0006] In a first aspect, the present application provides a method for detecting state of unmanned aerial vehicle, comprising:

[0007] obtaining a monitoring image of the inside of the cabin of the vehicle-mounted cabin collected by a camera;

[0008] performing identification processing on the monitoring image to obtain state information of the inside of the cabin, the state information comprising whether there is an unmanned aerial vehicle at a parking position in the inside of the cabin.

[0009] In a possible implementation, if there is an unmanned aerial vehicle at the parking position, the state information further comprises whether the unmanned aerial vehicle is in a powered-on state and / or remaining power information of the unmanned aerial vehicle.

[0010] In a second aspect, the present application provides a device for detecting state of unmanned aerial vehicle, comprising:

[0011] an obtaining module configured to obtain a monitoring image of the inside of the cabin of the vehicle-mounted cabin collected by a camera;

[0012] The first processing module is configured to perform identification processing on the monitoring image to obtain state information of the inside of the cabin, wherein the state information includes whether the parking position inside the cabin has a UAV.

[0013] In a third aspect, the present application provides a computer device, comprising a processor, a memory and a communication interface.

[0014] The memory stores computer execution instructions.

[0015] The processor executes the computer execution instructions stored in the memory to implement the method for detecting the state of the UAV according to any one of the first aspect.

[0016] In a fourth aspect, the present application provides a vehicle cabin, wherein the vehicle cabin is provided with a camera, and the vehicle cabin comprises at least one parking position for a UAV.

[0017] The camera is configured to obtain a monitoring image of the inside of the cabin, and the monitoring image is used to determine state information of the inside of the cabin according to the method for detecting the state of the UAV according to any one of the first aspect, wherein the state information includes whether the parking position inside the cabin has a UAV.

[0018] In a fifth aspect, the present application provides a vehicle, comprising a vehicle body, a computer device and a vehicle cabin arranged above the vehicle body.

[0019] The computer device is configured to implement the method for detecting the state of the UAV according to any one of the first aspect.

[0020] In a sixth aspect, the present application provides a UAV control system, comprising a UAV, a vehicle cabin and a computer device.

[0021] The computer device is configured to implement the method for detecting the state of the UAV according to any one of the first aspect.

[0022] In a seventh aspect, the present application provides a computer readable storage medium, wherein the computer readable storage medium stores computer execution instructions, and the computer execution instructions are configured to implement the method for detecting the state of the UAV according to any one of the first aspect when executed by a processor.

[0023] In an eighth aspect, the present application provides a computer program product, comprising a computer program, and the computer program is configured to implement the method for detecting the state of the UAV according to any one of the first aspect when executed by a processor.

[0024] The unmanned aerial vehicle state detection method, device and storage medium provided in the application can acquire a monitoring image of the inside of the cabin of the vehicle cabin collected by a camera, perform identification processing on the monitoring image, acquire state information of the inside of the cabin, realize acquisition of the state of the unmanned aerial vehicle, and further improve the efficiency of acquisition of the state of the unmanned aerial vehicle. BRIEF DESCRIPTION OF DRAWINGS

[0025] The drawings incorporated in the specification and constituting a part of the specification illustrate embodiments consistent with the present application and, together with the specification, serve to explain the principles of the application.

[0026] Fig. 1 is a schematic diagram of an application scenario provided in an embodiment of the application;

[0027] Fig. 2 is a flowchart of an embodiment of the unmanned aerial vehicle state detection method provided in the application;

[0028] Fig. 3 is a structural schematic diagram of an example of a camera position in a vehicle cabin provided in an embodiment of the application;

[0029] Fig. 4 is a structural schematic diagram of an example of an unmanned aerial vehicle position in a vehicle cabin provided in an embodiment of the application;

[0030] Fig. 5 is a flowchart of an embodiment of the unmanned aerial vehicle state detection method provided in the application;

[0031] Fig. 6 is a flowchart of an embodiment of the unmanned aerial vehicle state detection method provided in the application;

[0032] Fig. 7 is a structural schematic diagram of an example of a camera position before and after adjustment provided in an embodiment of the application;

[0033] Fig. 8 is a structural schematic diagram of another example of a camera position before and after adjustment provided in an embodiment of the application;

[0034] Fig. 9 is a flowchart of an embodiment of the unmanned aerial vehicle state detection method provided in the application;

[0035] Fig. 10 is a structural schematic diagram of an example of an unmanned aerial vehicle hovering position provided in an embodiment of the application;

[0036] Fig. 11 is a structural schematic diagram of an embodiment of the unmanned aerial vehicle state detection device provided in the application;

[0037] Fig. 12 is a structural schematic diagram of an embodiment of the unmanned aerial vehicle state detection device provided in the application;

[0038] Fig. 13 is a structural schematic diagram of a computer device provided in an embodiment of the application;

[0039] Fig. 14 is a structural schematic diagram of a vehicle cabin provided in an embodiment of the application;

[0040] FIG. 15 is a structural schematic diagram of a vehicle according to an embodiment of the present application.

[0041] The specific embodiments of the present application have been shown through the above drawings, and will be described in more detail hereinafter. These drawings and detailed description are not intended to limit the scope of the concept of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0042] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work fall within the scope of protection of the present application.

[0043] FIG. 1 is a schematic diagram of an application scenario according to an embodiment of the present application. Referring to FIG. 1, the application scenario includes a UAV 101, a vehicle cabin 102, a camera 103, and a computer device 104. The camera 103 is arranged on the vehicle cabin 102, and can capture and collect monitoring images of the inside of the cabin and send the monitoring images to the computer device 104. The computer device 104 can identify and process the monitoring images, so as to determine whether the UAV 101 is parked in the inside of the cabin.

[0044] In the prior art, the state of the UAV in the cabin is usually checked and confirmed by a person. However, this method has the problems of time-consuming and labor-consuming, and may cause information acquisition to be not timely, and increase the complexity and uncertainty of operation. In particular, in an emergency, the efficiency of relying on manual checking is difficult to guarantee.

[0045] In view of the above problems, the inventors have found, in the process of researching the state of the UAV in the cabin, that the main function of the cabin is to provide support for the take-off and landing of the UAV, and to protect the UAV from the influence of the external environment, objects or personnel. Accordingly, the inventors consider whether an image collection device can be arranged in the cabin to obtain state information of the inside of the cabin by using the image collection device, so as to improve the efficiency of obtaining the state of the UAV. Specifically, the inventors have found, through many experiments, that a camera can be arranged in the cabin, the monitoring images of the inside of the cabin of the vehicle cabin collected by the camera are identified and processed, the state information of the inside of the cabin is obtained, and the state of the UAV is obtained. Based on this, the present application provides a method for detecting the state of a UAV, which is used to improve the efficiency of obtaining the state of the UAV.

[0046] FIG. 2 is a flowchart of a first embodiment of a method for detecting the state of a UAV according to the present application. Referring to FIG. 2, the method can include the following steps.

[0047] S201, acquire a monitoring image of an inside of the cabin of the vehicle cabin collected by a camera.

[0048] The execution subject of the embodiment of the present application can be a computer device, or a device for detecting the state of the unmanned aerial vehicle arranged in the computer device. The computer device can be arranged in the vehicle cabin, or arranged outside the vehicle cabin, for example, arranged in the vehicle. The device for detecting the state of the unmanned aerial vehicle can be realized by software, or realized by the combination of software and hardware. The device for detecting the state of the unmanned aerial vehicle can be a processor in the computer device. For the convenience of understanding, the computer device is taken as an example in the following description.

[0049] In this step, the computer device is in communication connection with the vehicle cabin, and can acquire the monitoring image of the inside of the cabin of the vehicle cabin collected by the camera arranged in the inside of the vehicle cabin.

[0050] The vehicle cabin is a special container installed on a movable platform, such as a vehicle, a robot, or a ship, for storing and protecting devices such as unmanned aerial vehicles. For the convenience of understanding, the vehicle cabin in the present application takes the cabin arranged on the top of the vehicle, or in the trunk of the vehicle, for parking the unmanned aerial vehicle as an example.

[0051] Optionally, the camera can be arranged on any one of the top cover, the side plate, or the bottom plate of the cabin; or in the internal space of the cabin, for collecting the monitoring image of the inside of the cabin. In addition, the number of cameras arranged in the cabin is not limited in the present application.

[0052] FIG. 3 is a structural schematic diagram of an example of the arrangement position of the camera in the vehicle cabin according to the embodiment of the present application. Please refer to FIG. 3, the camera can be arranged in any one or more of region 1, region 2, or region 3. Wherein, region 1 can be any position in the top cover, the bottom plate, or the side plate; region 2 can be the region in any one of the included angle between the top cover and the side plate, or the included angle between the bottom plate and the side plate of the cabin; region 3 can be the internal space of the cabin. For example, the camera can be arranged at the center position of the top cover of the vehicle.

[0053] Optionally, the arrangement position of the camera in the vehicle cabin can be adjusted according to the structure of the cabin and the position of the unmanned aerial vehicle in the cabin.

[0054] For example, the vehicle cabin includes a top cover and a bottom plate, the internal space of the cabin is formed between the top cover and the bottom plate, the parking position of the unmanned aerial vehicle is arranged on the bottom plate, and the top cover can be provided with a camera for shooting towards the bottom plate. The computer device can acquire the monitoring image of the inside of the cabin of the vehicle cabin collected by the camera.

[0055] FIG. 4 is a structural schematic diagram of an example of a UAV setting position in a vehicle cabin according to an embodiment of the present application. Referring to FIG. 4, taking a vehicle cabin as an example, the vehicle cabin includes a top cover 11, a bottom plate 12, and a side plate 13. Four UAV parking positions, i.e., a parking position P1, a parking position P2, a parking position P3, and a parking position P4, can be arranged on the bottom plate 12. In other embodiments, the vehicle cabin can include an arc-shaped top cover and an arc-shaped bottom plate, which are combined to form a UAV parking space. The UAV parking space can also be arranged to include one parking position.

[0056] S202, performing recognition processing on the monitoring image to obtain state information of the cabin interior.

[0057] In this step, the computer device can perform recognition processing on the obtained monitoring image according to a preset image processing algorithm to obtain state information of the cabin interior, including whether the parking position in the cabin interior has a UAV.

[0058] Optionally, since the cabin interior is usually a dark environment, when the camera collects the monitoring image of the cabin interior, the ambient brightness can be increased by enabling a fill light, thereby improving the clarity and quality of the image shooting.

[0059] For example, at least one fill light can be arranged on the top cover or the bottom plate of the cabin. When the camera needs to obtain the monitoring image of the cabin interior, the fill light can be automatically turned on to provide sufficient illumination for the camera and improve the quality of the shooting image.

[0060] For another example, the fill light can be integrated in the camera. When the camera detects that the light intensity in the environment is weak, the fill light is automatically turned on to increase the shooting quality of the monitoring image.

[0061] Optionally, the number of parking positions, i.e., parking spaces, for parking UAVs in the cabin can be customized according to user needs. The area in the cabin is divided into different parking spaces for parking UAVs, which can ensure that each UAV has its own independent space and can be easily managed and maintained. By dividing the parking spaces, interference and collision between UAVs can be effectively avoided, and a safe and orderly environment can be provided, thereby realizing adjustment according to the size and type of the UAV to adapt to different types and scales of UAVs.

[0062] For example, for a vehicle cabin in a vehicle, one parking space can be designed for parking a UAV.

[0063] For example, in order to maintain the continuity of the work of the unmanned aerial vehicle, avoid the interruption of the work due to the failure of an unmanned aerial vehicle, the parking position 1 and the parking position 2 can be arranged in the cabin for parking the unmanned aerial vehicle 1 and the unmanned aerial vehicle 2. The parking positions of the unmanned aerial vehicle 1 and the unmanned aerial vehicle 2 can be changed, that is, the unmanned aerial vehicle 1 and the unmanned aerial vehicle 2 can be parked in the parking position 1 or the parking position 2.

[0064] Optionally, for the cabin, two, three or more parking positions for parking the unmanned aerial vehicle can be arranged, and each parking position in the monitoring image can be identified by the image processing algorithm to determine whether the unmanned aerial vehicle is in each parking position. In a specific implementation, a trained image processing algorithm can be used to detect the target in each parking position in the monitoring image to determine whether the unmanned aerial vehicle is in the parking position.

[0065] Specifically, the image processing algorithm adopts a convolutional neural network algorithm (CNN). The CNN algorithm is a neural network structure for processing image data. By introducing convolutional layers, pooling layers and fully connected layers and other hierarchical structures, the local and global features of the monitoring image can be effectively extracted and analyzed to obtain the state information of the inside of the cabin.

[0066] For example, if there is only one parking position in the cabin, the computer device can identify and process the obtained monitoring image according to the preset convolutional neural network algorithm to obtain whether the unmanned aerial vehicle is in the parking position in the inside of the cabin.

[0067] In an optional implementation, if the unmanned aerial vehicle is in the parking position, the state information further includes whether the unmanned aerial vehicle is in the start state and / or the remaining power information of the unmanned aerial vehicle.

[0068] Optionally, the start state of the unmanned aerial vehicle can be obtained by the state of the start signal light or according to the position of the start switch of the unmanned aerial vehicle.

[0069] For example, if the start signal light of the unmanned aerial vehicle is red or the start switch of the unmanned aerial vehicle is in the on position, it indicates that the unmanned aerial vehicle is in the start state. If the start signal light of the unmanned aerial vehicle is not on or the start switch of the unmanned aerial vehicle is in the off position, it indicates that the unmanned aerial vehicle is in the stop state.

[0070] Optionally, the remaining power information of the UAV can be obtained according to the color of the power indicator light. For example, the power indicator light can be provided on the UAV. If the power indicator light displays green, it means that the power of the UAV is sufficient. If the power indicator light displays yellow, it means that the power of the UAV is insufficient. If the power indicator light displays red, it means that the power of the UAV is severely insufficient. If the power indicator light does not display any color, it means that the UAV has run out of power.

[0071] Optionally, the remaining power information of the UAV can also be obtained according to the flashing frequency of the power indicator light. For example, the power indicator light can be provided on the UAV. If the power indicator light is on and does not flash, it means that the power of the UAV is sufficient. If the power indicator light is on and flashes slowly, such as once per second, it means that the power of the UAV is insufficient. If the power indicator light is on and flashes at medium speed, such as twice per second, it means that the power of the UAV is severely insufficient. If the power indicator light is on and flashes rapidly, such as three times per second or more, or the power indicator light is not on, it means that the UAV has run out of power.

[0072] Optionally, the remaining power information of the UAV can also be obtained according to the number of power indicator lights that are on. For example, four power indicator lights can be provided on the UAV. If all four power indicator lights are on, it means that the power of the UAV is sufficient. If three power indicator lights are on, it means that the power of the UAV is insufficient. If two power indicator lights are on, it means that the power of the UAV is severely insufficient. If only one power indicator light is on, it means that the UAV has run out of power.

[0073] Optionally, the indication range of the remaining power information of the UAV can be pre-set according to specific needs. For example, sufficient power of the UAV can mean that the remaining power of the UAV is equal to 60%. Insufficient power of the UAV can mean that the remaining power of the UAV is less than 60% and greater than 40%. Severely insufficient power of the UAV can mean that the remaining power of the UAV is less than or equal to 40% and greater than 3%. The UAV has run out of power can mean that the remaining power of the UAV is less than or equal to 3%. The power of the UAV when fully charged is 100%.

[0074] For example, the computer device can perform recognition processing on the obtained monitoring image to obtain state information of the cabin interior, including whether the UAV is parked at the parking position, whether the UAV is in the powered-on state, and the remaining power information of the UAV with sufficient power.

[0075] It should be noted that when it is determined that the UAV is parked at the parking position, state information of whether the UAV has a fault can also be obtained. The fault of the UAV can include at least one of a system fault and structural damage.

[0076] Optionally, for system failure of the UAV, the failure signal light of the UAV can be used to determine the system failure, and the image processing algorithm can be used to determine whether the failure signal light of the UAV is on, to determine whether the UAV has a system failure. For structural damage of the UAV, the image processing algorithm can be used to determine the appearance structure of the UAV in the monitoring image. In other embodiments, the UAV has a failure, and the alarm sound of the UAV can be used to determine the failure; the sound detection device arranged in the cabin can be used to determine the alarm sound.

[0077] In the embodiments of the present application, the computer device can acquire the monitoring image of the inside of the vehicle cabin collected by the camera, and identify and process the image, to acquire the state information of the inside of the cabin. In the above process, the presence of the UAV in the parking position of the cabin can be determined according to the acquired state information of the inside of the cabin, and the efficiency of acquiring the state of the UAV is further improved.

[0078] FIG. 5 is a flowchart of a second embodiment of the method for detecting the state of the UAV provided by the present application. Referring to FIG. 5, the method can include the following steps:

[0079] S501, receiving the monitoring image sent by the camera arranged in the inside of the cabin; or, in response to the operation of the user, sending an image acquisition request to the camera arranged in the inside of the cabin; and receiving the monitoring image of the inside of the cabin returned by the camera.

[0080] In this step, the computer device can acquire the monitoring image of the inside of the cabin in any one of the following ways.

[0081] Method 1: receiving the monitoring image sent by the camera arranged in the inside of the cabin.

[0082] The camera arranged in the inside of the cabin can monitor the inside of the cabin in real time or periodically, and actively transmit the captured monitoring image to the computer device through wireless (such as Wi-Fi, Bluetooth) or wired (such as Ethernet) network.

[0083] Method 2: in response to the operation of the user, sending an image acquisition request to the camera arranged in the inside of the cabin, and receiving the monitoring image of the inside of the cabin returned by the camera.

[0084] The computer device can send an image acquisition request to the camera arranged in the inside of the cabin in response to the operation of the user. After receiving the request, the camera can perform corresponding operations, and return the monitoring image of the inside of the cabin to the computer device.

[0085] Optionally, the computer device can send an image acquisition request to the camera arranged inside the cabin in response to a click operation of the user on the graphical user interface, or in response to a voice control instruction input by the user. For example, the computer device can send an image acquisition request to the camera arranged inside the cabin in response to a click operation of the user on the graphical user interface, or in response to a voice control instruction input by the user.

[0086] For example, the computer device can send an image acquisition request to the camera arranged inside the cabin in response to a voice control instruction input by the user. After receiving the request, the camera can start the image acquisition function, adjust the angle or parameters of the camera, monitor the inside of the cabin in real time, and return the monitoring image of the inside of the cabin to the computer device.

[0087] Option 3: In response to an operation of the user on the vehicle-mounted application (APP), an image acquisition request is sent to the camera arranged inside the cabin, and the monitoring image of the inside of the cabin returned by the camera is received.

[0088] For example, the computer device can be installed with an APP, and the user can control the takeoff and landing of the unmanned aerial vehicle through the APP. When the user clicks a one-key takeoff button in the APP, the computer device can send an image acquisition request to the camera arranged inside the cabin in response to the click operation of the user on the APP.

[0089] S502. According to a preset image processing algorithm, at least one of the unmanned aerial vehicle parking position, the unmanned aerial vehicle power-on indication area, and the battery power indication area in the monitoring image is identified and processed to obtain the state information of the inside of the cabin.

[0090] In this step, the received monitoring image can be identified and processed according to a preset image processing algorithm to obtain the state information of the inside of the cabin. In a specific implementation, at least one of the unmanned aerial vehicle parking position, the unmanned aerial vehicle power-on indication area, and the battery power indication area in the monitoring image can be identified and processed to obtain the state information of the inside of the cabin.

[0091] The state information of the inside of the cabin includes whether the unmanned aerial vehicle is parked in the parking position of the cabin. When it is determined that the unmanned aerial vehicle is parked in the parking position of the cabin, the state information of the inside of the cabin further includes whether the unmanned aerial vehicle is in a power-on state and / or the remaining power information of the unmanned aerial vehicle.

[0092] For example, the preset convolutional neural network algorithm can be used to identify the UAV parking position, the power-on indication area of the UAV, and the battery power indication area in the monitoring image, so as to obtain the state information of the cabin interior, including whether the UAV is parked in the cabin interior, whether the UAV is in the power-on state, and the residual power information of the UAV with sufficient power.

[0093] S503, according to the state information, pushing the first prompt information, the first prompt information is used to prompt the power condition of the UAV.

[0094] In this step, the computer device can push the first prompt information to the terminal device or the user according to the state information identified from the monitoring image, to prompt the user about the power condition of the UAV in the vehicle cabin.

[0095] The terminal device can include a vehicle terminal, a user's mobile phone, and a user's smart computer, etc.

[0096] Optionally, if the terminal device is a vehicle terminal, the computer device can be a device arranged in the vehicle interior and different from the vehicle terminal; if the terminal device is a user's mobile phone or a user's smart computer, the computer device can be a terminal device arranged in the vehicle interior.

[0097] For example, if the monitoring image includes a green UAV power indicator light, or the power indicator light is on and not flashing, or all four power indicator lights of the UAV are on, the first prompt information of the UAV with sufficient power can be sent to the vehicle terminal according to the state information identified from the monitoring image, including the residual power information of the UAV with sufficient power.

[0098] Optionally, if the state information identified from the monitoring image includes that the parking position in the cabin interior is empty and there is no UAV, the first prompt information of the empty parking position in the cabin interior and the absence of the UAV can also be sent to the vehicle terminal.

[0099] Optionally, if the state information identified from the monitoring image includes the residual power information of the UAV with insufficient power, the first prompt information of the UAV with insufficient power can be sent to the vehicle terminal. If the state information identified from the monitoring image includes the residual power information of the UAV with severely insufficient power, the first prompt information of the UAV with severely insufficient power can be sent to the vehicle terminal. If the state information identified from the monitoring image includes the residual power information of the UAV with no power, the first prompt information of the UAV with no power can be sent to the vehicle terminal.

[0100] In an optional embodiment, after receiving the first prompt information, the terminal device can remind the user of the power condition of the UAV through at least one of voice, text, and icon.

[0101] For example, the vehicle terminal can voice "the drone has run out of power, please pay attention to charging" to the user after receiving the first prompt information that the drone has run out of power, to remind the user.

[0102] For another example, the vehicle terminal can show an icon indicating that the drone has run out of power to the user through the graphical user interface of the vehicle terminal after receiving the first prompt information that the drone has run out of power, to remind the user that the drone has run out of power. The icon indicating that the drone has run out of power can be a red exclamation mark.

[0103] Optionally, the computer device can also push the first prompt information to the user directly according to the state information identified from the monitoring image, prompting the user about the power status of the drone in the vehicle cabin. For example, if the state information identified from the monitoring image by the computer device includes the remaining power information that the power of the drone is severely insufficient, the computer device can send the first prompt information that the power of the drone is severely insufficient to the user through voice. The voice content can be "the power of the drone is severely insufficient, please pay attention to charging".

[0104] Optionally, the state information identified from the monitoring image by the computer device can include information about whether the drone is malfunctioning, and the first prompt information can be pushed according to the identified information about whether the drone is malfunctioning, prompting that the drone is malfunctioning. Optionally, the prompt information can be sent in the form of text or voice.

[0105] In an optional embodiment, the user can charge the drone after receiving the first prompt information that the power of the drone is insufficient, the power of the drone is severely insufficient, or the drone has run out of power. The charging method can include replacing the battery of the drone, or charging the drone using a charging connector. Replacing the battery of the drone can include setting a battery replacement structure in the cabin, such as using a mechanical hand to remove the old battery of the drone and grabbing a new battery from a battery compartment provided in the cabin to install it on the drone. Charging the drone using a charging connector can include providing a charging port (such as a charging contact or a charging interface) on the drone, providing a charging connector (such as a charging contact or a charging head) in the cabin, and using the charging contact to contact the charging contact, or using a traditional method to insert the charging connector into the charging interface of the drone to charge the battery of the drone.

[0106] S504, according to the state information, control the charging circuit in the cabin to charge the drone.

[0107] In this step, the charging circuit in the cabin can be controlled according to the state information identified from the monitoring image to charge the drone.

[0108] Optionally, the charging circuit can be connected with the power supply, and can charge the unmanned aerial vehicle through wired or wireless mode. In a specific implementation, after the unmanned aerial vehicle and the cabin charging circuit are connected through the above-mentioned charging port and the charging head contact mode, the unmanned aerial vehicle can be charged through the charging circuit; or a charging coil can be arranged on the unmanned aerial vehicle and connected to the battery of the unmanned aerial vehicle. At the same time, another charging coil is arranged in the cabin and connected to the power supply through the charging circuit. Energy is transmitted between the two coils through a wireless mode, thereby realizing wireless charging of the battery of the unmanned aerial vehicle.

[0109] For example, the state information identified according to the monitoring image can include remaining power information indicating that the power of the unmanned aerial vehicle is seriously insufficient, and the charging circuit in the cabin is controlled to charge the unmanned aerial vehicle in a wireless mode.

[0110] It should be noted that in the technical solution of the present application, step S503 and step S504 are in an and / or relationship, that is, step S503 can be executed without executing step S504; or step S504 can be executed without executing step S503; or step S503 and step S504 can be executed. In the case where both step S503 and step S504 are executed, the execution of step S503 and step S504 does not distinguish the order.

[0111] In the embodiment of the present application, when the monitoring image sent by the camera is received, at least one of the unmanned aerial vehicle parking position, the unmanned aerial vehicle starting indication area and the battery power indication area in the monitoring image can be identified and processed according to the preset image processing algorithm, to obtain the state information inside the cabin. According to the state information, the first prompt information for prompting the power condition of the unmanned aerial vehicle can be pushed to the terminal device; and / or according to the state information, the charging circuit in the cabin is controlled to charge the unmanned aerial vehicle. In the above process, the state of the unmanned aerial vehicle can be further determined through the identified state information inside the cabin, and the efficiency of obtaining the state of the unmanned aerial vehicle is improved.

[0112] FIG. 6 is a flowchart of an embodiment of a method for detecting the state of an unmanned aerial vehicle provided by the present application. Referring to FIG. 6, on the basis of any of the above-mentioned embodiments, the method for detecting the state of the unmanned aerial vehicle further comprises:

[0113] S601, in response to a take-off instruction of the unmanned aerial vehicle, controlling the camera to take a picture of the outside of the cabin to obtain an environmental image of the outside of the cabin.

[0114] In this step, the take-off instruction of the unmanned aerial vehicle can be received in response to the operation of the user, and the camera arranged inside the cabin is controlled to adjust the position and take a picture of the outside of the cabin to obtain an environmental image of the outside of the cabin according to the received take-off instruction.

[0115] Optionally, the computer device can acquire the take-off instruction of the UAV in any of the following manners.

[0116] Manner 1: Acquiring the take-off instruction of the UAV in response to a user operating a take-off control lever or a take-off button on a UAV remote controller. For example, the computer device can acquire the take-off instruction of the UAV in response to a user tilting a take-off control lever on a UAV remote controller upward.

[0117] Manner 2: Acquiring the take-off instruction of the UAV in response to a user clicking on a graphical user interface. For example, the computer device can acquire the take-off instruction of the UAV in response to a user clicking a "take-off" button on a graphical user interface.

[0118] Manner 3: Acquiring the take-off instruction of the UAV in response to a user inputting a voice control instruction. For example, the computer device can acquire the take-off instruction of the UAV in response to a user inputting a voice "take-off".

[0119] Optionally, the position adjustment of the camera inside the cabin can include: adjusting the camera shooting area from inside the cabin to outside the cabin in a rotating manner or in an extending and retracting manner.

[0120] FIG. 7 is a structural schematic diagram of an example of the position adjustment of the camera according to an embodiment of the present application. As shown in FIG. 7, if the camera is arranged on the top cover of the cabin, the position of the camera can be adjusted from inside the cabin to outside the cabin in a rotating manner around the X axis.

[0121] In an optional implementation, when adjusting the camera, the entire camera can be adjusted, or only the gimbal or gimbal mechanism of the camera can be adjusted, so that the visual range of the camera covers outside the cabin. The gimbal is a mechanical device for controlling and adjusting the direction of the camera, which allows the camera to rotate, tilt or translate in the horizontal and vertical directions.

[0122] FIG. 8 is a structural schematic diagram of another example of the position adjustment of the camera according to an embodiment of the present application. As shown in FIG. 8, if the camera is arranged in the internal space of the cabin, the position of the camera can be adjusted from inside the cabin to outside the cabin in an extending and retracting manner. In a specific implementation, the top cover of the vehicle cabin can be provided with a hole for the camera to extend out, and the bottom of the camera can be provided with an extending and retracting device. When it is necessary to shoot images outside the cabin, the extending and retracting device can extend the camera out of the hole in the top cover to shoot outside the cabin, so as to acquire the environmental images outside the cabin.

[0123] For example, the computer device can respond to the user input voice control instruction, receive a take-off instruction of the UAV, and control a camera arranged inside the cabin to rotate and capture an image of the outside of the cabin according to the received take-off instruction.

[0124] S602, performing identification processing on the environment image to determine whether there is an obstacle on the take-off route of the UAV.

[0125] In this step, the obtained environment image can be identified according to a preset image processing algorithm to determine whether there is an obstacle on the take-off route of the UAV.

[0126] Optionally, the take-off route can be artificially preset or determined in real time after identification of the environment image.

[0127] The obstacle refers to an object or obstacle that threatens the safe flight of the UAV, including but not limited to buildings, trees, power lines, etc.

[0128] For example, the computer device can perform identification processing on the obtained environment image according to a preset convolutional neural network algorithm to determine that there is an obstacle on the take-off route of the UAV.

[0129] S603, if it is identified that there is an obstacle on the take-off route of the UAV, the UAV is controlled to pause take-off and a second prompt information is pushed, and the second prompt information is used to prompt that there is an obstacle on the take-off route of the UAV.

[0130] In this step, if it is identified that there is an obstacle on the take-off route of the UAV, the UAV can be controlled to pause take-off, and a second prompt information is pushed to the terminal device or the user to prompt that there is an obstacle on the take-off route of the UAV.

[0131] For example, after receiving the second prompt information that there is an obstacle on the take-off route of the UAV, the vehicle-mounted terminal can send a voice "there is a house on the take-off route, pay attention to take-off" to the user to remind the user.

[0132] For another example, after receiving the second prompt information that there is an obstacle on the take-off route of the UAV, the vehicle-mounted terminal can display an icon or prompt text that there is an obstacle on the take-off route of the UAV to the user through an image user interface of the vehicle-mounted terminal to remind the user. The icon that there is an obstacle on the take-off route of the UAV can be a house icon.

[0133] In an optional embodiment, after receiving the second prompt information that there is an obstacle on the take-off route of the UAV, the vehicle-mounted terminal can automatically control the vehicle to continue driving through the automatic driving system of the vehicle until it is detected that there is no obstacle on the take-off route, and the UAV takes off.

[0134] Optionally, the computer device can also directly push a second prompt information to the user, prompting that there is an obstacle on the take-off route of the UAV, according to the identification that there is an obstacle on the take-off route of the UAV. For example, if the computer device identifies that there is an obstacle house on the take-off route of the UAV according to the environment image, the computer device can send the second prompt information that there is an obstacle on the take-off route of the UAV to the user in the form of voice. The voice content can be "there is a house on the take-off route, pay attention to take-off".

[0135] In an optional embodiment, after receiving the second prompt information that there is an obstacle on the take-off route of the UAV, the user can drive the vehicle to leave the range of the obstacle, so as to ensure that the UAV can take off safely. After the UAV takes off, the position-adjusted camera can be reset to the original position.

[0136] In the embodiments of the present application, the camera can be controlled to capture the environment outside the cabin according to the take-off instruction of the UAV, to obtain and identify the environment image, so as to confirm whether there is an obstacle on the take-off route. If an obstacle is detected, the take-off of the UAV can be paused and the second prompt information can be sent to remind the user that there is an obstacle on the take-off route of the UAV. In the above process, the preset camera is used to capture and identify the image of the environment outside the cabin, so that the situation on the take-off route of the UAV can be monitored, and corresponding control measures and notifications can be taken in time, so as to improve the flight safety of the UAV and the user experience.

[0137] FIG. 9 is a flowchart of an embodiment of a method for detecting the state of a UAV provided by the present application. Referring to FIG. 9, the method for detecting the state of the UAV further includes the following steps based on the embodiments shown in FIG. 2 or FIG. 5:

[0138] S901, if the state information indicates that there is no UAV in the parking position inside the cabin and the landing instruction of the UAV is detected, the camera is controlled to capture the outside of the cabin to obtain the environment image outside the cabin.

[0139] In this step, if the computer device obtains, according to the monitoring image, that there is no UAV in the parking position inside the cabin and the landing instruction of the UAV is detected, the camera arranged inside the cabin can be controlled to adjust the position according to the detected landing instruction, to capture the outside of the cabin and obtain the environment image outside the cabin.

[0140] For the cabin with only one parking position, if there is no UAV in the parking position, it can be indicated that the UAV is performing a flight task and is not parked in the parking position of the cabin.

[0141] Optionally, for the cabin with multiple parking positions, i.e., parking spaces, the absence of the UAV in the parking position indicates that there is an idle parking position in the cabin, which can be used to park the UAV that is performing a flight task. For example, the cabin is provided with parking space 1 and parking space 2, and the UAV 1 is performing a flight task. According to the monitoring image, the computer device obtains that there is no UAV in the parking position inside the cabin, which indicates that one of the parking space 1 and the parking space 2 is idle, or both of the parking space 1 and the parking space 2 are idle.

[0142] Optionally, the manner in which the computer device detects the landing instruction of the UAV can include: responding to the user operating the landing control lever or the landing button on the UAV remote controller; or, responding to the user clicking on the graphical user interface; or, responding to the user inputting a voice control instruction to obtain the landing instruction of the UAV; or, responding to the UAV actively sending a landing request (such as a request for return due to insufficient power or completion of a task).

[0143] For example, according to the monitoring image, the computer device obtains that there is no UAV in the parking position inside the cabin, and detects that the user clicks on the “landing” button on the graphical user interface to obtain the landing instruction of the UAV. Then, the computer device can respond to the user clicking on the “landing” button on the graphical user interface to control the camera arranged inside the cabin to adjust the position and capture the outside of the cabin to obtain the environmental image of the outside of the cabin.

[0144] S902, performing identification processing on the environmental image to determine whether there is an obstacle on the landing route of the UAV.

[0145] Optionally, the landing route can be artificially preset, or can be determined in real time after identification of the environmental image.

[0146] In this step, the obtained environmental image can be identified according to a preset image processing algorithm to determine whether there is an obstacle on the landing route of the UAV.

[0147] For example, the computer device can identify the obtained environmental image according to a preset convolutional neural network algorithm to determine that there is an obstacle tree on the landing route of the UAV.

[0148] S903, if it is identified that there is an obstacle on the landing route of the UAV, the UAV is controlled to hover in a preset area and a third prompt information is pushed, the third prompt information being used to prompt that there is an obstacle on the landing route of the UAV.

[0149] In this step, if it is identified that there is an obstacle on the landing route of the UAV, the UAV can be controlled to hover in a preset area, and a third prompt information is pushed to the terminal device or the user to prompt that there is an obstacle on the landing route of the UAV.

[0150] For example, the vehicle terminal can send a voice "there is a tree on the landing route, pay attention to landing" to the user after receiving the third prompt information that there is an obstacle on the landing route of the UAV, to remind the user.

[0151] For another example, the vehicle terminal can display an icon of an obstacle on the take-off route of the UAV to the user through the image user interface of the vehicle terminal after receiving the third prompt information that there is an obstacle on the landing route of the UAV, to remind the user. The icon of the obstacle on the landing route of the UAV can be a tree icon.

[0152] In an optional implementation, the vehicle terminal can automatically control the vehicle to continue driving until the UAV lands after detecting that there is no obstacle on the landing route, through the automatic driving system of the vehicle, after receiving the third prompt information that there is an obstacle on the landing route of the UAV.

[0153] Optionally, the computer device can also directly push the third prompt information to the user according to the identification that there is an obstacle on the landing route of the UAV, prompting the user that there is an obstacle on the landing route of the UAV. For example, if the computer device identifies that there is an obstacle tree on the landing route of the UAV according to the environmental image, the computer device can send the third prompt information that there is an obstacle on the landing route of the UAV to the user in the form of voice. The voice content can be "there is a tree on the landing route, pay attention to landing".

[0154] FIG. 10 is a structural schematic diagram of an example of a hovering position of a UAV provided by an embodiment of the present application. Please refer to FIG. 10. If there is an obstacle on the landing route of the UAV, the preset area for the UAV to hover can be determined according to the size of the UAV, and / or the weight of the UAV.

[0155] For example, the preset area for the UAV to hover can be area 1 according to the size of the UAV, and the area 1 can be an area vertically 2 meters (m) above the top cover; or the preset area for the UAV to hover can be area 2 according to the weight of the UAV, and the area 2 can be an area vertically 2 m away from the top cover at the left upper side or the right upper side of the top cover, and having a certain angle A with the top cover.

[0156] In an optional implementation, the user can drive the vehicle out of the range of the obstacle after receiving the third prompt information that there is an obstacle on the landing route of the UAV, so as to ensure that the UAV can land safely. If the UAV is less than a preset distance from the cabin door during the landing process of the UAV, the cabin door can be controlled to be opened to realize the landing of the UAV.

[0157] Optionally, the preset distance of the UAV from the cabin door can be preset according to user demand, for example, the preset distance is 1 m, and when the UAV is less than 1 m from the cabin door, the cabin door can be opened to realize the landing of the UAV.

[0158] The distance of the UAV from the cabin door can be determined in any of the following ways:

[0159] Method 1: The camera arranged inside the cabin is controlled to rotate or stretch, the camera shooting area is adjusted from inside the cabin to outside the cabin, the image of the UAV is shot in real time, and the distance of the UAV from the cabin door is identified by a preset image processing algorithm, such as a convolutional neural network algorithm. When the UAV is less than a preset distance from the cabin door, the cabin door can be opened to realize the landing of the UAV. After the UAV lands, the position-adjusted camera can be reset to the original position.

[0160] Method 2: A distance measuring sensor or an image sensor can be arranged outside the UAV or the cabin. During the landing of the UAV, if it is detected that the distance of the UAV from the cabin door is less than a preset distance, the cabin door can be controlled to open.

[0161] Optionally, after the cabin door is opened, the camera inside the cabin can be controlled to adjust the position, the camera shooting area is adjusted from inside the cabin to outside the cabin, the image of the landing area of the UAV is shot in real time, and whether the landing area has an obstacle is identified by a preset image processing algorithm, such as a convolutional neural network algorithm, so as to assist the UAV to land and avoid collision and damage to the UAV.

[0162] In the embodiments of the present application, according to the state information indicating that there is no UAV in the parking position inside the cabin and the landing instruction of the UAV, the camera is controlled to shoot the environment outside the cabin, the environment image is acquired and identified to confirm whether there is an obstacle on the landing route. If an obstacle is detected, the UAV can be controlled to hover in a preset area and a third prompt information is sent to remind the user that there is an obstacle on the landing route of the UAV. In the above process, the camera is used to shoot and identify the image of the environment outside the cabin, which can monitor the situation on the landing route of the UAV and take corresponding control measures and notifications in time, thereby improving the flight safety of the UAV and the user experience.

[0163] FIG. 11 is a structural schematic diagram of an embodiment of a UAV state detection device provided by the present application. Referring to FIG. 11, the UAV state detection device 20 comprises:

[0164] The acquisition module 21 is configured to acquire a monitoring image of the inside of the cabin of the vehicle cabin collected by the camera.

[0165] The first processing module 22 is configured to perform identification processing on the monitoring image, and obtain state information of the inside of the cabin, wherein the state information comprises whether the parking position inside the cabin has a UAV.

[0166] The UAV state detection apparatus provided by the embodiments of the present application can implement the technical solutions shown in the method embodiments, and the implementation principles and beneficial effects are similar, which will not be repeated here.

[0167] In a possible implementation, if the parking position has a UAV, the state information further comprises whether the UAV is in a powered-on state and / or remaining power information of the UAV.

[0168] In a possible implementation, the remaining power information of the UAV is obtained according to at least one of the following: color of a power indicator, flashing frequency of the power indicator, and number of times of turning on the power indicator.

[0169] In a possible implementation, the first processing module 22 is specifically configured to:

[0170] According to a preset image processing algorithm, at least one of the UAV parking position, a powered-on indication region of the UAV, and a battery power indication region in the monitoring image is identified to obtain the state information of the inside of the cabin.

[0171] In a possible implementation, when the parking position has a UAV, the UAV is subjected to fault identification processing to determine whether the UAV has a UAV fault, wherein

[0172] The UAV fault comprises at least one of a system fault and structural damage.

[0173] The system fault is determined by a UAV fault signal light, and the structural damage is determined by an appearance structure of the UAV.

[0174] In a possible implementation, the acquisition module 21 is specifically configured to:

[0175] receive the monitoring image sent by the camera arranged inside the cabin;

[0176] Alternatively,

[0177] in response to an operation of a user, send an image acquisition request to the camera arranged inside the cabin;

[0178] receive the monitoring image of the inside of the cabin returned by the camera.

[0179] Fig. 12 is a structural schematic diagram of a second embodiment of the UAV state detection device provided in the present application. Based on the embodiment shown in Fig. 11, referring to Fig. 12, the UAV state detection device 20 further comprises a second processing module 23, which is configured to:

[0180] According to the state information, push a first prompt information, the first prompt information is used for prompting the power situation of the UAV or prompting the UAV failure; and / or,

[0181] According to the state information, control the charging circuit in the cabin to charge the UAV.

[0182] In a possible implementation, the method further comprises:

[0183] According to the state information, control the battery replacement structure in the cabin to replace the battery of the UAV.

[0184] In a possible implementation, the acquisition module 21 is further configured to, in response to a take-off instruction of the UAV, control the camera to capture the outside of the cabin to acquire an environment image of the outside of the cabin.

[0185] The first processing module 22 is further configured to perform identification processing on the environment image to determine whether there is an obstacle on the take-off route of the UAV.

[0186] The second processing module 23 is further configured to, if it is identified that there is an obstacle on the take-off route of the UAV, control the UAV to pause take-off and push a second prompt information, the second prompt information is used for prompting that there is an obstacle on the take-off route of the UAV.

[0187] In a possible implementation, the acquisition module 21 is further configured to, in response to a take-off instruction of the UAV, control the camera to perform position adjustment to capture the outside of the cabin to acquire an environment image of the outside of the cabin.

[0188] In a possible implementation, the camera is arranged on the top cover of the cabin; the acquisition module 21 is further configured to adjust the position of the camera by rotation, and adjust the position of the camera from inside the cabin to outside the cabin.

[0189] In a possible implementation, the camera is arranged in the internal space of the cabin; the acquisition module 21 adjusts the position of the camera by extension and retraction, and adjusts the position of the camera from inside the cabin to outside the cabin.

[0190] In a possible implementation, the acquisition module 21 is further configured to, if the state information indicates that there is no UAV in the parking position inside the cabin and a landing instruction of a UAV is detected, control the camera to capture an image of the outside of the cabin, and acquire an environment image of the outside of the cabin.

[0191] The first processing module 22 is further configured to perform identification processing on the environment image, and determine whether there is an obstacle on a landing route of the UAV.

[0192] The second processing module 23 is further configured to, if it is identified that there is an obstacle on the landing route of the UAV, control the UAV to hover in a preset area and push a third prompt information, where the third prompt information is used to prompt that there is an obstacle on the landing route of the UAV.

[0193] In a possible implementation, if it is identified that there is no obstacle on the landing route of the UAV, the apparatus is further configured to:

[0194] If the distance between the UAV and the cabin door is less than a preset distance, control the cabin door to be opened, so as to realize landing of the UAV.

[0195] The distance between the UAV and the cabin door is determined in any of the following manners:

[0196] An image of the UAV is captured by the camera, and the distance between the UAV and the cabin door is determined by using a preset image processing algorithm.

[0197] The distance between the UAV and the cabin door is determined by using a sensor, where the sensor is a distance measuring sensor or an image sensor.

[0198] The apparatus for detecting a state of a UAV provided in the embodiments of the present application can perform the technical solutions shown in the method embodiments, and the implementation principles and beneficial effects are similar, which will not be described herein again.

[0199] FIG. 13 is a structural schematic diagram of a computer device provided in the embodiments of the present application. Please refer to FIG. 13, the computer device 30 can include a processor 31, a memory 32 and a communication interface 34. Exemplarily, the processor 31, the memory 32 and the communication interface 34 are connected with each other through a bus 33.

[0200] The memory 32 stores computer execution instructions;

[0201] The processor 31 executes the computer execution instructions stored in the memory 32, so that the processor 31 performs the method for detecting a state of a UAV provided in the above method embodiments.

[0202] The computer device provided in the embodiments of the present application can be arranged in the vehicle cabin or outside the vehicle cabin, for example, in the vehicle interior, for executing the technical solutions shown in the above method embodiments, and the implementation principles and advantages are similar, which will not be repeated here.

[0203] FIG. 14 is a structural schematic diagram of a vehicle cabin provided in an embodiment of the present application. Referring to FIG. 14, the vehicle cabin 40 can include a shell, and the shell is internally arranged with a parking position for parking a UAV, and the shell is further arranged with a camera 44 for shooting an image of the parking position.

[0204] Optionally, the vehicle cabin 40 further includes a computer device, which can acquire the image collected by the camera 44 to realize the method for detecting the UAV state provided in the above method embodiments.

[0205] Optionally, the shell can be further arranged with a charging device 45, and the shell of the vehicle cabin 40 can include a top cover 41, a side plate 42, and a bottom plate 43, and the bottom plate 43 is arranged with at least one parking position for parking a UAV.

[0206] Optionally, the top cover 41 can be arranged with a light supplementing lamp and the camera 44 for shooting in the direction of the bottom plate 43, and the camera 44 can be provided with a rotating device 441 or a telescopic device 442, which can adjust the shooting area of the camera 44 from the inside of the cabin 40 to the outside of the cabin 40. The rotating device 441 can include a gimbal or a gimbal mechanism, and the telescopic device 442 can include a telescopic rod.

[0207] Optionally, the charging device 45 can be arranged on the bottom plate 43 for charging the UAV, and the charging device 45 can include a mechanical hand, a battery compartment, and a charging circuit.

[0208] In an optional embodiment, the charging device 45 can further include a charging connector or a wireless charging structure. The wireless charging structure can include a charging coil, a charging circuit, and a power supply.

[0209] The camera 44 is used to acquire a monitoring image in the cabin, and the monitoring image is used to determine state information in the cabin 40 according to the method for detecting the UAV state provided in the method embodiments, and the state information includes whether there is a UAV in the parking position in the cabin 40.

[0210] FIG. 15 is a structural schematic diagram of a vehicle provided in an embodiment of the present application. Referring to FIG. 15, the vehicle 50 includes a vehicle body 51, a computer device 52, and a vehicle cabin 53 arranged above the vehicle body 50.

[0211] The computer device 52 is configured to implement the method of detecting the state of the UAV in any of the preceding method embodiments. Optionally, the computer device 52 can be arranged in the vehicle body 51 or in the vehicle cabin 53.

[0212] Correspondingly, the embodiments of the present application provide a UAV control system, which comprises a UAV, a vehicle cabin, and a computer device.

[0213] The computer device is configured to implement the method of detecting the state of the UAV in any of the preceding method embodiments.

[0214] Correspondingly, the embodiments of the present application provide a computer readable storage medium, which stores computer execution instructions, and the computer execution instructions, when executed by a processor, are configured to implement the method of detecting the state of the UAV in the method embodiments.

[0215] Correspondingly, the embodiments of the present application can also provide a computer program product, which comprises a computer program, and the computer program, when executed by a processor, can implement the method of detecting the state of the UAV in the method embodiments.

[0216] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can be in the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code.

[0217] The present application is described with reference to flowcharts and / or block diagrams of the method, device (system), and computer program product according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of the flows and / or blocks, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce the functions specified in one or more flows in the flowcharts and / or one or more blocks in the block diagrams.

[0218] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the function specified in the flowchart or flowsheets and / or block or blocks of the block diagrams.

[0219] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart or flowsheets and / or block or blocks of the block diagrams.

[0220] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0221] The memory can include non-persistent memory and / or volatile memory, such as random access memory (RAM) and / or cache memory, non-volatile memory, such as read-only memory (ROM), EPROM, and / or flash memory, etc. The memory is an example of computer readable media.

[0222] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile discs (DVDs) or other optical storage, magnetic cassettes, magnetic disks storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to computing devices. According to the definition herein, computer readable media does not include transitory media, such as modulated data signals and carrier waves.

[0223] It is also to be noted that the terms "comprising", "including", and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises a... " does not, without more constraints, exclude the existence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0224] The above description is merely illustrative of the application, and not restrictive. Various modifications and changes can become apparent to those skilled in the art. Incorporating any modification, equivalent substitution, improvement, etc. within the spirit and principle of the application, shall be included in the scope of the claims of the application.

Claims

1. A method for detecting the status of a drone, characterized in that, include: Acquire monitoring images of the interior of the vehicle's engine compartment captured by the camera; The monitoring images are processed to obtain the status information inside the cabin, including whether there is a drone at the parking position inside the cabin.

2. The method according to claim 1, characterized in that, If there is a drone at the parking location, the status information also includes: whether the drone is powered on and / or the drone's remaining battery power.

3. The method according to claim 2, characterized in that, The unseen remaining battery power information is obtained in at least one of the following ways: the color of the battery indicator light, the flashing frequency of the battery indicator light, and the number of battery indicator lights that are lit.

4. The method according to claim 1 or 2, characterized in that, The process of recognizing and processing the monitored images to obtain the status information inside the cabin includes: Based on a preset image processing algorithm, at least one of the drone's parking position, the drone's power-on indicator area, and the battery level indicator area in the monitoring image is identified to obtain the status information inside the cabin.

5. The method according to claim 4, characterized in that, When a drone is present at its parking location, a fault identification process is performed on the drone to determine if it has any malfunctions. The drone malfunction includes at least one of system malfunction and structural damage; The system malfunction is determined by the drone's malfunction indicator lights, and the structural damage is determined by the drone's external structure.

6. The method according to claim 1 or 2, characterized in that, The acquisition of monitoring images of the cabin interior captured by the camera includes: Receive the monitoring images sent by the camera installed inside the cabin; or, In response to the user's operation, an image acquisition request is sent to the camera installed inside the cabin; Receive the monitoring images of the cabin interior returned by the camera.

7. The method according to claim 2, characterized in that, The method further includes: Based on the status information, a first prompt message is pushed, which is used to indicate the drone's battery level or a drone malfunction; and / or, Based on the status information, the charging circuit inside the cabin is controlled to charge the drone.

8. The method according to claim 7, characterized in that, The method further includes: Based on the status information, control the battery replacement structure inside the cabin to replace the drone's battery.

9. The method according to claim 1 or 2, characterized in that, The method further includes: In response to the takeoff command of the drone, the camera is controlled to take pictures of the outside of the cabin and acquire environmental images of the outside of the cabin; The environmental image is processed to identify whether there are obstacles on the takeoff route of the drone; If an obstacle is detected in the takeoff path of the drone, the drone is controlled to pause takeoff and a second prompt message is sent, which is used to indicate that there is an obstacle in the takeoff path of the drone.

10. The method according to claim 9, characterized in that, In response to the takeoff command of the drone, the camera is controlled to capture images of the exterior of the cabin, including: In response to the takeoff command of the drone, the camera is controlled to adjust its position to take pictures of the outside of the cabin and acquire environmental images of the outside of the cabin.

11. The method according to claim 10, characterized in that, The camera is mounted on the top cover of the cabin; controlling the camera's position adjustment includes: The camera position is adjusted by rotating it, moving it from inside the cabin to outside.

12. The method according to claim 10, characterized in that, The camera is installed inside the cabin; controlling the camera's position adjustment includes: The camera's position can be adjusted by extending or retracting it, moving it from inside the cabin to outside.

13. The method according to claim 1 or 2, characterized in that, The method further includes: If the status information indicates that there is no drone at the parking position inside the cabin, and a landing command for the drone is detected, then the camera is controlled to take pictures of the outside of the cabin to obtain environmental images of the outside of the cabin. The environmental image is processed to identify whether there are obstacles on the landing path of the drone; If an obstacle is detected on the drone's landing path, the drone is controlled to hover in a preset area and a third prompt message is sent, which is used to indicate that there is an obstacle on the drone's landing path.

14. The method according to claim 1 or 2, characterized in that, If it is determined that there are no obstacles on the landing path of the drone, the method further includes: If the distance between the drone and the cabin door is less than a preset distance, the cabin door is opened to allow the drone to land. The distance between the drone and the cabin door is determined using any of the following methods: The camera captures images of the drone, and a preset image processing algorithm is used to determine the distance between the drone and the cabin door. The distance between the drone and the cabin door is determined using a sensor, which can be a distance measurement sensor or an image sensor.

15. A computer device, characterized in that, include: Processor, memory, and communication interface; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method for unmanned aerial vehicle (UAV) status detection as described in any one of claims 1 to 7.

16. A vehicle-mounted engine compartment, characterized in that, The vehicle-mounted cabin is equipped with a camera, and the vehicle-mounted cabin includes at least one parking position for parking drones; The camera is used to acquire monitoring images of the cabin interior, and the monitoring images are used to determine the state information of the cabin interior by the UAV state detection method according to any one of claims 1 to 7, the state information including whether there is a UAV at the parking position inside the cabin.

17. A vehicle, characterized in that, The vehicle includes a vehicle body, computer equipment, and an onboard cabin located above the vehicle body; The computer device is used to implement the method for unmanned aerial vehicle (UAV) status detection as described in any one of claims 1-14.

18. A drone control system, characterized in that, The unmanned aerial vehicle (UAV) control system includes the UAV, the vehicle-mounted cabin, and computer equipment. The computer device is used to implement the method for unmanned aerial vehicle (UAV) status detection as described in any one of claims 1-14.

19. 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 method for unmanned aerial vehicle (UAV) state detection as described in any one of claims 1 to 14.

20. A computer program product comprising a computer program that, when executed by a processor, implements the method for detecting the state of a drone as described in any one of claims 1 to 14.

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