Unmanned aerial vehicle control method, intelligent device and storage medium

Abstract

The application provides a UAV control method, an intelligent device and a storage medium, and is applied to an intelligent device in a task coordination system, the intelligent device comprising a mechanical arm, the task coordination system further comprising a unmanned ground vehicle and at least one UAV carried on the unmanned ground vehicle, and the method comprises the following steps: in response to a UAV release task, after the unmanned ground vehicle reaches a target operation position and parks, obtaining environment information of the target operation position; determining a take-off position and a take-off attitude of a target UAV based on the environment information; grabbing the target UAV carried on the unmanned ground vehicle through the mechanical arm; moving the target UAV to the take-off position through the mechanical arm, and adjusting the target UAV to the take-off attitude; sending a first take-off instruction to the target UAV, and releasing the clamping of the target UAV by the mechanical arm, so that the target UAV takes off from the take-off position in the take-off attitude in response to the first take-off instruction. The embodiment of the application can realize the autonomous release of the UAV.

Description

Technical Field

[0001] This application relates to the field of unmanned aerial vehicle (UAV) control technology, and more particularly to UAV control methods, intelligent devices, and storage media. Background Technology

[0002] With the development of intelligent security and low-altitude defense technologies, unmanned ground vehicles (UGVs) and drones are increasingly being used in scenarios such as industrial park inspections, border security patrols, deployment in key urban areas, and low-altitude defense in high-risk areas. Mobile security systems in these technologies typically employ a combination of UGVs and drones. The UGV carries the drone and related security equipment to the work area, and the drone is automatically launched from a fixed onboard bay, or by on-site operators using handheld assistance.

[0003] However, vehicle-mounted fixed hangars make it difficult to adjust the takeoff position and attitude of drones according to the on-site environment, while manual assisted launch requires operators to enter the work site. As a result, the existing drone launch methods are not adaptable to complex working environments and it is difficult to achieve autonomous drone launch. Summary of the Invention

[0004] This application provides a method for controlling unmanned aerial vehicles (UAVs), intelligent devices, and storage media, which aim to enable autonomous flight of UAVs.

[0005] In a first aspect, a method for controlling a drone is provided, applied to an intelligent device in a mission collaboration system. The intelligent device includes a robotic arm, and the mission collaboration system further includes an unmanned ground vehicle and at least one drone mounted on the unmanned ground vehicle. The method includes: In response to the drone launch mission, after the unmanned ground vehicle arrives at the target work location and parks, it acquires the environmental information of the target work location; The takeoff position and takeoff attitude of the target UAV are determined based on the environmental information. The robotic arm grasps the target drone mounted on the unmanned ground vehicle; The robotic arm moves the target drone to the takeoff position and adjusts the target drone to the takeoff attitude. A first takeoff command is sent to the target drone, and the robotic arm releases its grip on the target drone, so that the target drone responds to the first takeoff command and takes off from the takeoff position in the takeoff attitude.

[0006] This technical solution can adjust the takeoff position and attitude of the target UAV according to the on-site environment of the target operation location, without relying on a vehicle-mounted fixed parking bay or on-site operators to assist in flight, thus improving the adaptability of the UAV flight method to complex operating environments and realizing the autonomous flight of the target UAV.

[0007] In conjunction with the first aspect, in one possible implementation, the unmanned ground vehicle includes a universal chassis and a functional module detachably mounted on the universal chassis, wherein the at least one unmanned aerial vehicle is carried on the functional module; The functional module includes a first transport module or a second transport module. The first transport module is used to carry at least one first drone, and the second transport module is used to carry one second drone. The volume of the first drone is smaller than the volume of the second drone. Prior to the drone launch mission, the method further includes: Identify the module type of the functional modules currently installed on the unmanned ground vehicle; Based on the module type, the target drone is determined from the at least one drone, and the drone type of the target drone is determined; Load the drone capture program and drone launch program that match the drone type of the target drone.

[0008] In conjunction with the first aspect, in one possible implementation, before acquiring the environmental information of the target work location, the method further includes: The robotic arm operates the steering wheel and vehicle control components of the unmanned ground vehicle to control the vehicle to reach the target work location and park; or, The unmanned ground vehicle's onboard bus interface is connected via an electronic control connector located at the end of the robotic arm. Driving control commands are sent to the unmanned ground vehicle through the onboard bus interface to control the unmanned ground vehicle to reach the target work position and park.

[0009] In conjunction with the first aspect, in one possible implementation, after the target drone takes off, the method further includes: In response to the target drone returning to the unmanned ground vehicle and landing when its battery level is below a preset threshold, the robotic arm grabs the target drone. The robotic arm removes the depleted battery from the target drone and installs a fully charged battery into the target drone. The robotic arm moves the target drone to the takeoff position and adjusts the target drone to the takeoff attitude. A second takeoff command is sent to the target drone, and the robotic arm releases its grip on the target drone, so that the target drone responds to the second takeoff command and takes off again from the takeoff position in the takeoff attitude.

[0010] In conjunction with the first aspect, in one possible implementation, the unmanned ground vehicle further includes an onboard low-altitude detection radar, and the target drone is a security drone or an anti-drone. After the target drone takes off, the method further includes: Acquire target information obtained by the vehicle-mounted low-altitude detection radar or the target UAV from detecting the target object; Based on the target information, the target distance between the target object and the unmanned ground vehicle is determined; Based on the target distance, determine the appropriate action to take against the target object.

[0011] In conjunction with the first aspect, in one possible implementation, the disposal method includes radio frequency interference, laser decoy, or soft network interception. The step of determining the handling method for the target object based on the target distance includes: If the target distance is within the first distance range, the radio frequency interference method is determined as the handling method for the target object; If the target distance falls within the second distance range, the laser decoy method will be determined as the handling method for the target object; If the target distance falls within the third distance range, the soft net interception method will be determined as the handling method for the target object; Wherein, the distance values ​​within the first distance range are all greater than the distance values ​​within the second distance range, and the distance values ​​within the second distance range are all greater than the distance values ​​within the third distance range.

[0012] In conjunction with the first aspect, in one possible implementation, the target information is information obtained by the vehicle-mounted low-altitude detection radar scanning the airspace where the target object is located, and the target information includes the relative position vector of the target object relative to the unmanned ground vehicle; Determining the target distance between the target object and the unmanned ground vehicle based on the target information includes: Determine the magnitude of the relative position vector, and set the magnitude of the relative position vector as the target distance.

[0013] In conjunction with the first aspect, in one possible implementation, the target information is information obtained by the target UAV from detecting the target object, and the target information includes at least one of the visible light image data, infrared thermal imaging data, and radio frequency detection data of the target object; Determining the target distance between the target object and the unmanned ground vehicle based on the target information includes: The target information is subjected to target identification and position parsing to obtain the first relative position information of the target object relative to the target UAV; The pose information of the target UAV relative to the unmanned ground vehicle is obtained, and the pose information includes the position and attitude of the target UAV relative to the unmanned ground vehicle. Based on the pose information, coordinate transformation is performed on the first relative position information to obtain the second relative position information of the target object relative to the unmanned ground vehicle; The target distance is determined based on the second relative position information.

[0014] In a second aspect, a drone control device is provided, applied to an intelligent device in a mission collaboration system. The intelligent device includes a robotic arm, and the mission collaboration system further includes an unmanned ground vehicle and at least one drone mounted on the unmanned ground vehicle. The device includes: The acquisition module is used to acquire environmental information of the target work location after the unmanned ground vehicle arrives at the target work location and parks itself in response to the drone launch mission. The determination module is used to determine the takeoff position and takeoff attitude of the target UAV based on the environmental information; The grasping module is used to grasp the target drone mounted on the unmanned ground vehicle using the robotic arm; to move the target drone to the takeoff position using the robotic arm; and to adjust the target drone to the takeoff attitude. The launch module is used to send a first takeoff command to the target drone and release the robotic arm from the target drone, so that the target drone responds to the first takeoff command and takes off from the takeoff position in the takeoff attitude.

[0015] Thirdly, a smart device is provided, including a memory and a processor, the memory being connected to the processor, the processor being configured to execute one or more computer programs stored in the memory, the processor causing the smart device to implement the drone control method of the first aspect described above when executing the one or more computer programs.

[0016] Fourthly, a computer-readable storage medium is provided, which stores a computer program, the computer program including program instructions, which, when executed by a processor, cause the processor to perform the unmanned aerial vehicle control method of the first aspect.

[0017] Fifthly, a computer program product is provided that, when run on a smart device, causes any of the methods provided in the first aspect to be executed. Attached Figure Description

[0018] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments of this application will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A schematic diagram of a task collaboration system provided in an embodiment of this application; Figure 2 A flowchart illustrating the unmanned aerial vehicle (UAV) control method provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a drone control device provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a smart device provided in an embodiment of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this application. All other embodiments obtained by those skilled in the art based on the embodiments in this application without inventive effort are within the scope of protection of this application.

[0021] It should be noted that, unless there is a conflict, the various features in the embodiments of this application can be combined with each other, all of which are within the protection scope of this application. Furthermore, although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than the module division in the device or the order in the flowchart. Moreover, the terms "first," "second," and "third" used in this application do not limit the data or execution order, but only distinguish identical or similar items with essentially the same function and effect.

[0022] The technical solution of this application is described in detail below.

[0023] See Figure 1 , Figure 1 This is a schematic diagram of a task collaboration system provided in an embodiment of this application, such as... Figure 1 As shown, the mission collaboration system includes intelligent devices, unmanned ground vehicles, and at least one drone mounted on the unmanned ground vehicle.

[0024] In this context, "intelligent device" refers to a device within a task collaboration system that possesses environmental perception, information processing, and mechanical operation capabilities. In one implementation, the intelligent device is a humanoid intelligent robot, comprising a sensing unit, a computing unit, two multi-degree-of-freedom mechanical execution arms (i.e., two robotic arms), and a humanoid walking chassis. The sensing unit includes at least one of a binocular camera, an infrared thermal imaging device, and a millimeter-wave radar. The sensing unit is used to acquire environmental information. The computing unit is used to process the environmental information acquired by the sensing unit. The robotic arms are used to grasp / move / adjust drones, operate unmanned ground vehicles, etc. The humanoid walking chassis supports the sensing unit, computing unit, and robotic arms.

[0025] An unmanned ground vehicle refers to a vehicle in a mission collaboration system used for ground movement and carrying at least one unmanned aerial vehicle (UAV). In one implementation, the unmanned ground vehicle includes a universal chassis and functional modules detachably mounted on the universal chassis. The functional modules include a robotic cockpit module and either a first or second transport module. The first transport module carries at least one first UAV, and the second transport module carries one second UAV. The first UAV is smaller than the second UAV. The robotic cockpit module carries intelligent equipment. The unmanned ground vehicle may also include an onboard high-capacity power battery storage compartment, an onboard fast-charging battery compartment, an onboard low-altitude detection radar, and an onboard low-altitude reconnaissance and strike defense module.

[0026] A drone is a flying device mounted on an unmanned ground vehicle and capable of performing aerial operations. Drones are equipped with a quick-release battery interface adapted to the robotic arm of intelligent devices, and may include a visible light inspection module, an infrared thermal imaging module, a radio frequency detection module, and an electronic jamming payload.

[0027] See Figure 2 , Figure 2 This is a flowchart illustrating a drone control method provided in an embodiment of this application, as shown below. Figure 2 As shown, this method is applied to smart devices and includes the following steps: S201, in response to the drone launch mission, after the unmanned ground vehicle arrives at the target work location and parks, acquires the environmental information of the target work location.

[0028] Among them, the drone launch mission refers to the task of instructing intelligent devices to perform launch operations on drones mounted on unmanned ground vehicles.

[0029] There is a correspondence between drone launch missions and target operation locations. The target operation location refers to the location where the unmanned ground vehicle needs to arrive and park when carrying out the drone launch mission.

[0030] In one implementation, the smart device further includes a sensing unit, which includes at least one of a binocular camera, an infrared thermal imaging device, and a millimeter-wave radar. The step of obtaining environmental information of the target work location includes: collecting environmental information of the target work location through the sensing unit, wherein the environmental information includes at least one of terrain information, wind direction information and obstacle information of the target work location.

[0031] Among them, the terrain information of the target operation location refers to the information used to characterize the ground morphology and its changes at the target operation location.

[0032] In one embodiment, when the environmental information includes the terrain information, the method further includes: The intelligent device can acquire ground images of the target work location through the binocular camera, obtain ground depth information of the target work location based on the ground images, and determine the terrain information based on the ground depth information; Alternatively, the intelligent device can use the millimeter-wave radar to detect the ground at the target operation location and determine the terrain information based on the distance information obtained by the millimeter-wave radar.

[0033] Among them, the wind direction information of the target operation location refers to the information used to characterize the direction of air flow at the target operation location.

[0034] In one embodiment, when the environmental information includes the wind direction information, the method further includes: The intelligent device continuously acquires environmental images of the target work location through the binocular camera, determines the image features affected by wind in the environmental images, and determines the wind direction information of the target work location based on the movement direction of the image features in the continuously acquired environmental images.

[0035] Among them, obstacle information at the target operation location refers to information used to characterize whether there are obstacles at the target operation location that affect the movement of the robotic arm drone or the take-off of the drone, as well as the location of the obstacle.

[0036] In one embodiment, where the environmental information includes the obstacle information, the method further includes: The intelligent device acquires environmental images of the target work location using the binocular camera; The intelligent device collects infrared thermal imaging data of the target work location through the infrared thermal imaging device, or detects the target work location through the millimeter-wave radar; The intelligent device determines whether the obstacle exists at the target work location and the location of the obstacle based on the environmental image and the infrared thermal imaging data, or based on the environmental image and the detection results of the millimeter-wave radar, thereby obtaining the obstacle information.

[0037] S202, determine the takeoff position and takeoff attitude of the target UAV based on the environmental information.

[0038] The takeoff position refers to the spatial location where the target UAV takes off.

[0039] The takeoff attitude refers to the spatial attitude of the target UAV when it performs a takeoff operation at that takeoff position. The spatial attitude includes the orientation and tilt of the target UAV.

[0040] In one implementation, the intelligent device further includes a local computing unit, and the step of determining the takeoff position and takeoff attitude of the target UAV based on the environmental information includes: The local computing unit processes the environmental information to obtain the takeoff position and takeoff attitude of the target UAV.

[0041] The local computing unit processes the environmental information according to the types of information included in the environmental information. When the environmental information includes terrain information, the local computing unit processes the terrain information to determine the ground spatial distribution at the target work location. When the environmental information includes obstacle information, the local computing unit processes the obstacle information to determine the obstacle spatial distribution at the target work location. When the environmental information includes wind direction information, the local computing unit processes the wind direction information to determine the airflow direction at the target work location.

[0042] The local computing unit determines a spatial position that does not interfere with the ground and obstacles at the target operating position based on at least one of the ground spatial distribution and the obstacle spatial distribution, and determines the spatial position as the take-off position of the target UAV; the local computing unit determines the orientation and tilt state of the target UAV at the take-off position based on at least one of the airflow direction, the ground spatial distribution and the obstacle spatial distribution, and determines the orientation and tilt state as the take-off attitude of the target UAV.

[0043] S203, the robotic arm grabs the target drone mounted on the unmanned ground vehicle.

[0044] Specifically, intelligent devices control robotic arms to grip target drones mounted on unmanned ground vehicles, thereby establishing a gripping relationship between the robotic arm and the target drone.

[0045] S204, the target drone is moved to the takeoff position by the robotic arm, and the target drone is adjusted to the takeoff attitude.

[0046] Specifically, while the robotic arm holds the target drone, the intelligent device controls the robotic arm to move the target drone so that its spatial position is consistent with the takeoff position. The device also controls the robotic arm to adjust the target drone's orientation and tilt so that its spatial attitude is consistent with the takeoff attitude. After completing the movement and attitude adjustment, the robotic arm continues to hold the target drone, keeping it in the takeoff position and attitude.

[0047] S205, send a first takeoff command to the target drone and release the robotic arm from the target drone, so that the target drone responds to the first takeoff command and takes off from the takeoff position in the takeoff attitude.

[0048] Specifically, the first takeoff command instructs the target drone to take off from the takeoff position and in the takeoff attitude. With the robotic arm holding the target drone in the takeoff position and attitude, the intelligent device sends the first takeoff command to the target drone and controls the robotic arm to release its grip on the target drone. After the robotic arm releases its grip, the target drone is no longer constrained by the robotic arm and, in response to the received first takeoff command, takes off from the takeoff position and in the takeoff attitude.

[0049] In one implementation, the task coordination system further includes a local coordination scheduling bus, through which the intelligent device communicates with the unmanned ground vehicle and the at least one UAV respectively; Sending the takeoff command to the target UAV includes: sending the takeoff command to the flight control unit of the target UAV via the local cooperative scheduling bus.

[0050] In this embodiment, the take-off position and attitude of the target UAV can be adjusted according to the on-site environment of the target operation location, without relying on a vehicle-mounted fixed parking bay or on-site operators to assist in flight, which improves the adaptability of the UAV flight method to complex operation environments and realizes the autonomous flight of the target UAV.

[0051] In one implementation, the unmanned ground vehicle includes a universal chassis and a functional module detachably mounted on the universal chassis, wherein at least one unmanned aerial vehicle is mounted on the functional module; The functional module includes a first transport module or a second transport module. The first transport module is used to carry at least one first drone, and the second transport module is used to carry one second drone. The volume of the first drone is smaller than the volume of the second drone. Prior to the drone launch mission, the method further includes: Identify the module type of the functional modules currently installed on the unmanned ground vehicle; Based on the module type, the target drone is determined from the at least one drone, and the drone type of the target drone is determined; Load the drone capture program and drone launch program that match the drone type of the target drone.

[0052] Specifically, the module type is used to characterize whether the functional module currently installed on the unmanned ground vehicle is a first transport module or a second transport module. When the module type is the module type corresponding to the first transport module, the intelligent device determines the target drone from at least one first drone carried by the first transport module and identifies the drone type of the target drone as the drone type corresponding to the first drone; when the module type is the module type corresponding to the second transport module, the intelligent device identifies the second drone carried by the second transport module as the target drone and identifies the drone type of the target drone as the drone type corresponding to the second drone.

[0053] After determining the target drone and its drone type, the smart device loads a drone capture program and a drone launch program that match the drone type of the target drone.

[0054] Specifically, after loading a drone-grabbing program that matches the type of drone being used for the target drone, the intelligent device executes the step "grabbing the target drone mounted on the unmanned ground vehicle using the robotic arm".

[0055] After loading a drone launch program that matches the drone type of the target drone, the intelligent device executes the steps of "moving the target drone to the takeoff position via the robotic arm and adjusting the target drone to the takeoff attitude; sending a takeoff command to the target drone and releasing the robotic arm from the target drone".

[0056] In one embodiment, the intelligent device determines the target drone from at least one first drone carried by the first carrier module, including: When the first carrier module carries a first drone, the intelligent device identifies the first drone as the target drone; When the first carrier module carries multiple first drones, the intelligent device selects any one of the multiple first drones and uses the selected first drone as the target drone.

[0057] In this embodiment, the loaded drone capture and drone launch programs can be adapted to the drone type of the target drone, enabling the intelligent device to perform corresponding capture and launch operations for target drones of different sizes, thereby improving the adaptability of the task collaboration system to different functional modules and different types of drones.

[0058] In one implementation, before obtaining the environmental information of the target work location, the method further includes: The robotic arm operates the steering wheel and vehicle control components of the unmanned ground vehicle to control the vehicle to reach the target work location and park; or, The unmanned ground vehicle's onboard bus interface is connected via an electronic control connector located at the end of the robotic arm. Driving control commands are sent to the unmanned ground vehicle through the onboard bus interface to control the unmanned ground vehicle to reach the target work position and park.

[0059] Specifically, the intelligent device controls the robotic arm to operate the steering wheel and vehicle control components of the unmanned ground vehicle. By operating the steering wheel, the unmanned ground vehicle's driving direction is controlled, and by operating the vehicle control components, the unmanned ground vehicle's driving status is controlled, so that the unmanned ground vehicle reaches the target work position and parks.

[0060] The driving control command is used to instruct the vehicle to drive to the target work location and park. After receiving the driving control command, the unmanned ground vehicle executes the driving control command to drive to the target work location and park.

[0061] In the embodiments of this application, intelligent devices can be adapted to different control methods of unmanned ground vehicles and autonomously control the unmanned ground vehicles to reach the target work location and park, thereby reducing the dependence on on-site personnel during the operation of unmanned ground vehicles.

[0062] In one implementation, after the target drone takes off, the method further includes: In response to the target drone returning to the unmanned ground vehicle and landing when its battery level is below a preset threshold, the robotic arm grabs the target drone. The robotic arm removes the depleted battery from the target drone and installs a fully charged battery into the target drone. The robotic arm moves the target drone to the takeoff position and adjusts the target drone to the takeoff attitude. A second takeoff command is sent to the target drone, and the robotic arm releases its grip on the target drone, so that the target drone responds to the second takeoff command and takes off again from the takeoff position in the takeoff attitude.

[0063] The preset threshold is used to determine whether the target drone's battery level is sufficient to continue flying. For example, it could be 5%, 8%, 10%, or other values.

[0064] A depleted battery refers to the battery installed on the target drone when it returns to base.

[0065] In this embodiment of the application, a smart device can use a robotic arm to complete the grabbing, battery replacement, and re-flighting of the target drone, reducing the reliance on on-site personnel during the battery replacement and re-flighting process and improving the continuity of drone operations.

[0066] In one implementation, the unmanned ground vehicle further includes an onboard low-altitude detection radar, and the target drone is a security drone or an anti-drone. After the target drone takes off, the method further includes: Acquire target information obtained by the vehicle-mounted low-altitude detection radar or the target UAV from detecting the target object; Based on the target information, the target distance between the target object and the unmanned ground vehicle is determined; Based on the target distance, determine the appropriate action to take against the target object.

[0067] Among them, vehicle-mounted low-altitude detection radar refers to radar equipment installed on unmanned ground vehicles and used to detect targets in the low-altitude atmosphere. Vehicle-mounted low-altitude detection radar can scan the airspace where the target object is located and obtain target information about the target object.

[0068] Security drones are drones used for security patrols and target detection; counter-drone drones are drones used for low-altitude defense and target detection. Security drones and counter-drone drones are two alternative types of target drones.

[0069] The target object can be an aircraft (such as a drone) that enters the low-altitude airspace around the target operation location and needs to be detected and dealt with.

[0070] In one embodiment, the handling method includes radio frequency interference, laser decoy, or soft network interception; The step of determining the handling method for the target object based on the target distance includes: If the target distance is within the first distance range, the radio frequency interference method is determined as the handling method for the target object; If the target distance falls within the second distance range, the laser decoy method will be determined as the handling method for the target object; If the target distance falls within the third distance range, the soft net interception method will be determined as the handling method for the target object; Wherein, the distance values ​​within the first distance range are all greater than the distance values ​​within the second distance range, and the distance values ​​within the second distance range are all greater than the distance values ​​within the third distance range.

[0071] Radio frequency (RF) interference refers to the method of dealing with a target object through radio frequency interference. For example, the target object might be a drone illegally flying in the low-altitude airspace surrounding a target operational location. When the target distance between the drone and the unmanned ground vehicle is determined to be within a first distance range, RF interference is applied to the target object.

[0072] Laser-based deterrence refers to the method of using lasers to drive away target objects. For example, the target object might be a drone illegally flying in the low-altitude airspace surrounding a target work location. When the distance between the target object and the unmanned ground vehicle is determined to be within the second distance range, laser deterrence is applied to the target object.

[0073] Softnet interception refers to the method of intercepting a target object using a softnet. For example, the target object is a drone illegally flying in the low-altitude airspace surrounding a target operation location. When it is determined that the target distance between the drone and the unmanned ground vehicle falls within the third distance range, a softnet is launched towards the target object to intercept it.

[0074] In one embodiment, the target information is information obtained by the vehicle-mounted low-altitude detection radar scanning the airspace where the target object is located, and the target information includes the relative position vector of the target object relative to the unmanned ground vehicle; Determining the target distance between the target object and the unmanned ground vehicle based on the target information includes: Determine the magnitude of the relative position vector, and set the magnitude of the relative position vector as the target distance.

[0075] For example, assuming the relative position vector is represented as r = (x, y, z), then the magnitude of the relative position vector = .

[0076] In another embodiment, the target information is information obtained by the target UAV from detecting the target object, and the target information includes at least one of the visible light image data, infrared thermal imaging data, and radio frequency detection data of the target object; Determining the target distance between the target object and the unmanned ground vehicle based on the target information includes: The target information is subjected to target identification and position parsing to obtain the first relative position information of the target object relative to the target UAV; The pose information of the target UAV relative to the unmanned ground vehicle is obtained, and the pose information includes the position and attitude of the target UAV relative to the unmanned ground vehicle. Based on the pose information, coordinate transformation is performed on the first relative position information to obtain the second relative position information of the target object relative to the unmanned ground vehicle; The target distance is determined based on the second relative position information.

[0077] The step of performing target identification and position parsing on the target information to obtain the first relative position information of the target object relative to the target UAV includes: The target information is used for target identification, identifying information corresponding to the target object from the target information, and the identified target object is analyzed for position to determine the position of the target object relative to the target drone. This position is then defined as the first relative position information. The first relative position information is used to characterize the relative positional relationship between the target object and the target drone when the target drone is used as a reference.

[0078] The position of the target UAV relative to the unmanned ground vehicle is used to characterize the relative positional relationship between the target UAV and the unmanned ground vehicle. The attitude of the target UAV relative to the unmanned ground vehicle is used to characterize the attitude relationship between the target UAV and the unmanned ground vehicle.

[0079] The step of performing coordinate transformation on the first relative position information based on the pose information to obtain the second relative position information of the target object relative to the unmanned ground vehicle includes: Based on the pose information, the first relative position information is oriented by a direction transformation, and based on the position information, the oriented first relative position information is oriented by a position transformation, thereby converting the first relative position information with the target UAV as a reference into a second relative position information with the unmanned ground vehicle as a reference. The second relative position information is used to characterize the position of the target object relative to the unmanned ground vehicle.

[0080] The step of determining the target distance based on the second relative position information includes: determining the magnitude of the relative position vector represented by the second relative position information, and determining the magnitude of the relative position vector as the target distance between the target object and the unmanned ground vehicle.

[0081] In this embodiment of the application, the handling method for the target object can be matched with the distance of the target object relative to the unmanned ground vehicle, thereby improving the targeting of the handling of the target object.

[0082] In one implementation, the method further includes: Receive image data and airspace detection data collected by the target UAV during its aerial inspection mission; The image data and the spatial detection data are parsed locally on the smart device to obtain the parsing results; The analysis results, the image data, and the spatial detection data are stored together.

[0083] The analysis results include image analysis information corresponding to the image data and spatial detection analysis information corresponding to the spatial detection data.

[0084] Image analysis information is used to characterize the image content of the inspection area reflected by the image data.

[0085] Airspace detection resolution information is used to characterize the airspace status of the inspection area reflected by airspace detection data.

[0086] In this embodiment, by receiving image data and airspace detection data collected by the target UAV during aerial inspection missions, and parsing the image data and airspace detection data locally on a smart device, the reliance on remote processing and network transmission for data parsing can be reduced, improving the timeliness of data parsing. By associating and storing the parsing results, the image data, and the airspace detection data, a correlation can be established between the parsing results and the corresponding image data and airspace detection data, facilitating the retrieval of the parsing results and their corresponding image data and airspace detection data.

[0087] The method of this application has been described above; the apparatus of this application will be described below.

[0088] See Figure 3 , Figure 3 This is a schematic diagram of the structure of a drone control device provided in an embodiment of this application, as shown below. Figure 3 As shown, an intelligent device is applied to a task collaboration system. The intelligent device includes a robotic arm, and the task collaboration system also includes an unmanned ground vehicle and at least one unmanned aerial vehicle mounted on the unmanned ground vehicle. The unmanned aerial vehicle control device 30 includes: The acquisition module 301 is used to acquire environmental information of the target operation location after the unmanned ground vehicle arrives at the target operation location and parks in response to the drone launch mission. The determination module 302 is used to determine the takeoff position and takeoff attitude of the target UAV based on the environmental information; The grasping module 303 is used to grasp the target drone mounted on the unmanned ground vehicle using the robotic arm; to move the target drone to the takeoff position using the robotic arm; and to adjust the target drone to the takeoff attitude. The launch module 304 is used to send a first takeoff command to the target drone and release the robotic arm from the target drone, so that the target drone responds to the first takeoff command and takes off from the takeoff position in the takeoff attitude.

[0089] It should be noted that the aforementioned drone control device 30 can execute the drone control method provided in the embodiments of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the embodiments can be found in the drone control method provided in the embodiments of this application.

[0090] See Figure 4 , Figure 4 This is a schematic diagram of the structure of a smart device provided in an embodiment of this application. The smart device 40 includes a processor 401 and a memory 402. The memory 402 is connected to the processor 401, for example, via a bus.

[0091] Processor 401 is configured to support the intelligent device 40 in performing the corresponding functions in the methods described in the above method embodiments. The processor 301 may be a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof. The aforementioned hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The aforementioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0092] Memory 402 is used to store program code, etc. Memory 402 may include volatile memory (VM), such as random access memory (RAM); memory 402 may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid-state drive (SSD); memory 402 may also include combinations of the above types of memory.

[0093] The memory 402 is used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as the program instructions / modules corresponding to the UAV control method in the embodiments of this application. The processor executes various functional applications and data processing of the UAV control method by running the non-volatile software programs, instructions, and modules stored in the memory, thereby realizing the functions of the UAV control method provided in the above method embodiments.

[0094] Memory 402 may include a program storage area and a data storage area, wherein the program storage area may store the operating system and applications required for at least one function. The data storage area may store data created based on the use of the drone control device. In some embodiments, the memory may include memory remotely located relative to the processor, which can be connected to the drone control device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0095] The one or more modules are stored in the memory. When executed by the one or more processors, they perform the UAV control method in any of the above method embodiments. For example, they perform the method steps described in the above method embodiments to realize the functions of the modules described in the above device embodiments.

[0096] This application also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a computer, cause the computer to perform the method described in the foregoing embodiments.

[0097] This application also provides a computer program product that, when run on a smart device, causes any of the above methods to be executed.

[0098] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0099] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A method for controlling an unmanned aerial vehicle (UAV), characterized in that, A smart device applied in a task collaboration system, the smart device including a robotic arm, the task collaboration system further including an unmanned ground vehicle and at least one unmanned aerial vehicle mounted on the unmanned ground vehicle, the method comprising: In response to the drone launch mission, after the unmanned ground vehicle arrives at the target work location and parks, it acquires the environmental information of the target work location; The takeoff position and takeoff attitude of the target UAV are determined based on the environmental information. The robotic arm grasps the target drone mounted on the unmanned ground vehicle; The robotic arm moves the target drone to the takeoff position and adjusts the target drone to the takeoff attitude. A first takeoff command is sent to the target drone, and the robotic arm releases its grip on the target drone, so that the target drone responds to the first takeoff command and takes off from the takeoff position in the takeoff attitude.

2. The method according to claim 1, characterized in that, The unmanned ground vehicle includes a universal chassis and functional modules detachably mounted on the universal chassis, and the at least one unmanned aerial vehicle is carried on the functional modules; The functional module includes a first transport module or a second transport module. The first transport module is used to carry at least one first drone, and the second transport module is used to carry one second drone. The volume of the first drone is smaller than the volume of the second drone. Prior to the drone launch mission, the method further includes: Identify the module type of the functional modules currently installed on the unmanned ground vehicle; Based on the module type, the target drone is determined from the at least one drone, and the drone type of the target drone is determined; Load the drone capture program and drone launch program that match the drone type of the target drone.

3. The method according to claim 1, characterized in that, Before obtaining the environmental information of the target work location, the method further includes: The robotic arm operates the steering wheel and vehicle control components of the unmanned ground vehicle to control the vehicle to reach the target work location and park; or, The unmanned ground vehicle's onboard bus interface is connected via an electronic control connector located at the end of the robotic arm. Driving control commands are sent to the unmanned ground vehicle through the onboard bus interface to control the unmanned ground vehicle to reach the target work position and park.

4. The method according to claim 1, characterized in that, After the target drone takes off, the method further includes: In response to the target drone returning to the unmanned ground vehicle and landing when its battery level is below a preset threshold, the robotic arm grabs the target drone. The robotic arm removes the depleted battery from the target drone and installs a fully charged battery into the target drone. The robotic arm moves the target drone to the takeoff position and adjusts the target drone to the takeoff attitude. A second takeoff command is sent to the target drone, and the robotic arm releases its grip on the target drone, so that the target drone responds to the second takeoff command and takes off again from the takeoff position in the takeoff attitude.

5. The method according to claim 1, characterized in that, The unmanned ground vehicle also includes an onboard low-altitude detection radar, and the target drone is a security drone or an anti-drone drone. After the target drone takes off, the method further includes: Acquire target information obtained by the vehicle-mounted low-altitude detection radar or the target UAV from detecting the target object; Based on the target information, the target distance between the target object and the unmanned ground vehicle is determined; Based on the target distance, determine the appropriate action to take against the target object.

6. The method according to claim 5, characterized in that, The methods of handling include radio frequency interference, laser disengagement, or soft network interception. The step of determining the handling method for the target object based on the target distance includes: If the target distance is within the first distance range, the radio frequency interference method is determined as the handling method for the target object; If the target distance falls within the second distance range, the laser decoy method will be determined as the handling method for the target object; If the target distance falls within the third distance range, the soft net interception method will be determined as the handling method for the target object; Wherein, the distance values ​​within the first distance range are all greater than the distance values ​​within the second distance range, and the distance values ​​within the second distance range are all greater than the distance values ​​within the third distance range.

7. The method according to claim 5, characterized in that, The target information is the information obtained by the vehicle-mounted low-altitude detection radar scanning the airspace where the target object is located, and the target information includes the relative position vector of the target object relative to the unmanned ground vehicle; Determining the target distance between the target object and the unmanned ground vehicle based on the target information includes: Determine the magnitude of the relative position vector, and set the magnitude of the relative position vector as the target distance.

8. The method according to claim 5, characterized in that, The target information is information obtained by the target UAV from detecting the target object, and the target information includes at least one of the visible light image data, infrared thermal imaging data and radio frequency detection data of the target object; Determining the target distance between the target object and the unmanned ground vehicle based on the target information includes: The target information is subjected to target identification and position parsing to obtain the first relative position information of the target object relative to the target UAV; The pose information of the target UAV relative to the unmanned ground vehicle is obtained, and the pose information includes the position and attitude of the target UAV relative to the unmanned ground vehicle. Based on the pose information, coordinate transformation is performed on the first relative position information to obtain the second relative position information of the target object relative to the unmanned ground vehicle; The target distance is determined based on the second relative position information.

9. A smart device, characterized in that, The device includes a memory and a processor, the memory being connected to the processor, the processor being configured to execute one or more computer programs stored in the memory, the processor causing the smart device to implement the method as described in any one of claims 1-8 when executing the one or more computer programs.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, the computer program including program instructions that, when executed by a processor, cause the processor to perform the method as described in any one of claims 1-8.

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