CN112596542A - Data processing method and device, electronic equipment and storage medium - Google Patents
Data processing method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the application provides a data processing method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The data processing method comprises the following steps: firstly, point cloud data and a three-dimensional route of flight equipment are obtained, wherein the point cloud data comprises at least one target point, and the three-dimensional route comprises at least one route section; secondly, calculating the distance from each target point to at least one navigation segment to obtain a target distance; and then, calculating safety information of the flight equipment in the flight section according to the target distance. By the method, the possibility of collision on the planned path can be judged according to the point cloud data, and the problem that the reliability of collision detection is low because the reliability of the air route planning based on the digital surface model is not high and the planned path cannot be accurately judged to be collided in the prior art is solved.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a data processing method and apparatus, an electronic device, and a storage medium.
Background
With the progress of intelligent processes of life, industry, agriculture and the like, more and more automatic devices operate in scenes of daily life, factory warehouses, agriculture and the like. The inventor researches and discovers that in the prior art, information loss exists in the generation of the digital surface model, the reliability of the route planning based on the information loss is not high, the planned route cannot be accurately judged to be free from collision, and the problem of low reliability of collision detection exists.
Disclosure of Invention
In view of the above, the present application aims to provide a data processing method and apparatus, an electronic device and a storage medium, so as to at least partially improve one of the above problems in the prior art.
In a first aspect, the present invention provides a data processing method, including:
acquiring point cloud data and a three-dimensional route of flight equipment, wherein the point cloud data comprises at least one target point, and the three-dimensional route comprises at least one route section;
aiming at each target point, calculating the distance from the target point to at least one of the navigation sections to obtain a target distance;
and calculating safety information of the flight equipment in the flight section according to the target distance.
In an optional embodiment, the step of calculating safety information of the flight device in the flight segment according to the target distance includes:
invoking a first collision detection model;
and inputting the target distance into the first collision detection model, and calculating to obtain the safety information of the flight equipment in the flight section.
In an optional implementation manner, the step of calculating safety information of the flying device in the flight segment according to the collision detection model and the target distance includes:
acquiring state data of the flight equipment in real time, and determining at least one distance range according to the state data;
for each target point, comparing the target distance of the target point with the at least one distance range to obtain a target distance range of the target point, wherein the target distance range is the distance range in which the target distance is located;
and inputting the target distance range of each target point into a second collision detection model, and calculating to obtain the safety information of the flight equipment in the flight segment.
In an alternative embodiment, the data processing method further comprises the step of obtaining at least one target point, the step comprising:
projecting the point cloud data and at least two waypoints included by the three-dimensional route onto the same horizontal plane to obtain a minimum enclosing polygon of the waypoints;
and extracting the point cloud data in the preset range expanded by the minimum enclosing polygon to obtain at least one target point.
In an optional embodiment, the step of extracting point cloud data within a preset range extended by the minimum bounding polygon to obtain at least one target point includes:
obtaining a minimum enclosing polygon cylinder according to the minimum enclosing polygon and the height coordinate range of the point cloud in the minimum enclosing polygon;
and extracting the point cloud data in the preset range expanded outside the minimum enclosing polygonal cylinder to obtain at least one target point.
In an optional embodiment, the step of calculating, for each target point, a distance from the target point to at least one of the legs to obtain a target distance includes:
calculating the distance from the target point to each navigation section to obtain at least one distance value;
and sequencing the at least one distance value, and taking the minimum distance value as the target distance of the target point.
In a second aspect, the present invention provides a data processing apparatus comprising:
the system comprises a data acquisition module, a data acquisition module and a flight equipment, wherein the data acquisition module is used for acquiring point cloud data and a three-dimensional flight path of flight equipment, the point cloud data comprises at least one target point, and the three-dimensional flight path comprises at least one flight segment;
the distance calculation module is used for calculating the distance from the target point to at least one of the navigation sections aiming at each target point to obtain a target distance;
and the safety information calculation module is used for calculating the safety information of the flight equipment in the flight section according to the target distance.
In a third aspect, the present invention provides an electronic device, comprising a memory and a processor, wherein the processor is configured to execute an executable computer program stored in the memory to implement the data processing method of any one of the foregoing embodiments.
In an optional implementation manner, the electronic device is a plant protection unmanned aerial vehicle with an image acquisition module, and the plant protection unmanned aerial vehicle acquires image data through the image acquisition module and processes the image data to obtain point cloud data.
In a fourth aspect, the present invention provides a storage medium having stored thereon a computer program which, when executed, implements the steps of the data processing method of any one of the preceding embodiments.
According to the data processing method and device, the electronic device and the storage medium, the target distance is obtained by calculating the distance between the target point of the point cloud data and the flight segment of the flight device, the safety information of the flight device in the flight segment is calculated according to the target distance, the possibility of collision on the planned path is judged according to the point cloud data, and the problems that in the prior art, the reliability of course planning based on a digital surface model is low, the planned path cannot be accurately judged to be collided, and the reliability of collision detection is low are solved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a block diagram of a data processing system according to an embodiment of the present disclosure.
Fig. 2 is a block diagram of an electronic device according to an embodiment of the present disclosure.
Fig. 3 is a schematic flowchart of a data processing method according to an embodiment of the present application.
Fig. 4 is another schematic flow chart of the data processing method according to the embodiment of the present application.
Fig. 5 is another schematic flow chart of the data processing method according to the embodiment of the present application.
Fig. 6 is another schematic flow chart of the data processing method according to the embodiment of the present application.
Fig. 7 is another schematic flow chart of a data processing method according to an embodiment of the present application.
Fig. 8 is another schematic flow chart of a data processing method according to an embodiment of the present application.
Fig. 9 is a block diagram of a data processing apparatus according to an embodiment of the present application.
Icon: 10-a data processing system; 100-an electronic device; 110-a network port; 120-a first processor; 130-a communication bus; 140-a first storage medium; 150-interface; 200-a flying apparatus; 900-a data processing apparatus; 910-a data acquisition module; 920-a distance calculation module; 930-security information calculation module.
Detailed Description
The defects of the above solutions are the results of the inventor after practice and careful study, and therefore, the discovery process of the above problems and the solution proposed by the present application to the above problems should be the contribution of the inventor to the present application in the process of the present application.
For purposes of making the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions of the embodiments of the present application will be described in detail below with reference to the drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for illustrative and descriptive purposes only and are not used to limit the scope of the present application. Additionally, it should be understood that the schematic drawings are not necessarily drawn to scale. The flowcharts used in this application illustrate operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be performed out of order, and steps without logical context may be performed in reverse order or simultaneously. One skilled in the art, under the guidance of this application, may add one or more other operations to, or remove one or more operations from, the flowchart.
In addition, the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
In order to enable a person skilled in the art to make use of the present disclosure, the following embodiments are given. It will be apparent to those skilled in the art that the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the application. Applications of the system or method of the present application may include web pages, plug-ins for browsers, client terminals, customization systems, internal analysis systems, or artificial intelligence robots, among others, or any combination thereof.
It should be noted that in the embodiments of the present application, the term "comprising" is used to indicate the presence of the features stated hereinafter, but does not exclude the addition of further features.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
Fig. 1 is a block diagram of a data processing system 10 provided in an embodiment of the present application, which provides a possible implementation manner of the data processing system 10, and referring to fig. 1, the data processing system 10 may include one or more of an electronic device 100 and an in-flight device 200.
The electronic device 100 is in communication connection with the flying device 200 in the target scene, and the electronic device 100 can acquire point cloud data in the target scene and a three-dimensional route of the flying device 200 and calculate safety information of the flying device 200 in a route section.
It should be noted that the electronic device 100 may be a device different from the flight device 200, or may be a part of the flight device 200, and the electronic device 100 may also be a cloud server.
Optionally, the specific type of the flight device 200 is not limited, and may be set according to the actual application requirements. For example, in one alternative example, the flying apparatus 200 may be a drone.
In detail, when the electronic device 100 and the flight device 200 are the same device, the electronic device 100 may be a plant protection unmanned aerial vehicle with an image acquisition module, and the plant protection unmanned aerial vehicle acquires image data through the image acquisition module and processes the image data to obtain point cloud data.
Fig. 2 illustrates a schematic diagram of exemplary hardware and software components of an electronic device 100 that may implement the concepts of the present application, according to some embodiments of the present application. The electronic device 100 may include a network port 110 connected to a network, one or more first processors 120 for executing program instructions, a communication bus 130, and a first storage medium 140 of a different form, such as a disk, ROM, or RAM, or any combination thereof. Illustratively, the electronic device 100 may also include program instructions stored in ROM, RAM, or other types of non-transitory storage media, or any combination thereof, according to which the methods of the present application may be implemented. The electronic device 100 may also include an Input/Output (I/O) interface 150 with other Input/Output devices (e.g., keyboard, display screen).
In some embodiments, the first processor 120 may process information and/or data related to data processing to perform one or more functions described herein. In some embodiments, the first processor 120 may include one or more processing cores (e.g., a single-core processor (S) or a multi-core processor (S)). Merely by way of example, the first Processor 120 may include a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), an Application Specific Instruction Set Processor (ASIP), a Graphics Processing Unit (GPU), a Physical Processing Unit (PPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), a Programmable Logic Device (PLD), a controller, a microcontroller Unit, a Reduced Instruction Set computer (Reduced Instruction Set Computing, RISC), a microprocessor, or the like, or any combination thereof.
The first processor 120 in the electronic device 100 may be a general purpose computer or a set purpose computer, both of which may be used to implement the methods of the present application. Although only a single computer is shown, for convenience, the functions described herein may be implemented in a distributed fashion across multiple similar platforms to balance processing loads.
For ease of illustration, only one processor is depicted in electronic device 100. However, it should be noted that the electronic device 100 in the present application may also comprise a plurality of processors, and thus the steps performed by one processor described in the present application may also be performed by a plurality of processors in combination or individually. For example, if the processor of the electronic device 100 executes steps a and B, it should be understood that steps a and B may also be executed by two different processors together or separately in one processor. For example, a first processor performs step A and a second processor performs step B, or both a first processor and a second processor perform steps A and B.
The network may be used for the exchange of information and/or data. In some embodiments, one or more components in electronic device 100 may send information and/or data to other components. For example, the electronic device 100 may acquire the signal via a network. Merely by way of example, the Network may include a Wireless Network, a telecommunications Network, an intranet, the internet, a Local Area Network (LAN), a Wide Area Network (WAN), a Wireless Local Area Network (WLAN), a Metropolitan Area Network (MAN), a Wide Area Network (WAN), a bluetooth Network, a ZigBee Network, or a Near Field Communication (NFC) Network, among others, or any combination thereof.
In some embodiments, the network may include one or more network access points. For example, the network may include wired or wireless network access points, such as base stations and/or network switching nodes, through which one or more components of electronic device 100 may connect to the network to exchange data and/or information.
Fig. 3 shows one of flowcharts of a data processing method provided in an embodiment of the present application, where the method is applicable to the electronic device 100 shown in fig. 1 and is executed by the electronic device 100 in fig. 1. It should be understood that, in other embodiments, the order of some steps in the data processing method of this embodiment may be interchanged according to actual needs, or some steps may be omitted or deleted. The flow of the data processing method shown in fig. 3 is described in detail below.
Step S310, point cloud data and a three-dimensional route of the flight device 200 are acquired.
The point cloud data comprises at least one target point, and the three-dimensional route comprises at least one route segment.
Step S320, calculating a distance from each target point to at least one leg to obtain a target distance.
In detail, after the target point and the leg are obtained in step S310, the target distance from the target point to the leg may be calculated.
And step S330, calculating safety information of the flight equipment 200 in the flight segment according to the target distance.
In detail, after the target distance is obtained in step S320, the safety information of the flight segment can be calculated according to the target distance.
According to the method, the target distance is obtained by calculating the distance between the target point of the point cloud data and the flight segment of the flight equipment, and the safety information of the flight equipment in the flight segment is calculated according to the target distance, so that the possibility of collision on the planned path is judged according to the point cloud data, and the problems that in the prior art, the reliability of route planning based on a digital surface model is not high, the planned path cannot be collided, and the reliability of collision detection is low are solved.
For step S310, it should be noted that the manner of acquiring the point cloud data is not limited, and may be set according to the actual application requirement. For example, in an alternative example, the flying apparatus 200 may collect point cloud data in a target scene and transmit the point cloud data to the electronic apparatus 100.
It should be noted that the three-dimensional route includes at least two waypoints, and the flight segment is a line segment (including the front point and not including the rear point) formed by two adjacent waypoints in the advancing direction of the three-dimensional route. Optionally, the three-dimensional route is not limited in acquisition mode and can be set according to actual application requirements. For example, in an alternative example, two-dimensional route data and a Digital Surface Model (DSM) input by a user or transmitted by the flight device 200 may be obtained, and the altitude of each point in the two-dimensional route may be determined from the Digital Surface Model to obtain three-dimensional route data. In detail, the digital surface model comprises a ground elevation model of the height of ground surface obstacles such as ground surface buildings, bridges, trees and the like, the height coordinates of the same two-dimensional coordinate point in the digital surface model can be obtained according to the two-dimensional coordinates of each point in the two-dimensional air route, the height of each point in the two-dimensional air route can be obtained by adding the height coordinates to a preset height, and therefore the three-dimensional air route is obtained. The preset height represents the distance from the highest point of the earth surface obstacle in the flying process of the flying device 200, the specific numerical value of the preset height is not limited, and the preset height can be set according to actual application requirements. For example, in an alternative example, the specific value of the pre-height may be 100 meters.
For another example, in another alternative example, the three-dimensional route sent by the other device may be directly obtained, and is generally set by the user on the client of the other device and generated through a preset algorithm on the device.
In order to reduce the amount of calculation of collision detection, the data processing method may further include a step of acquiring a target point before step S320. Therefore, on the basis of fig. 3, fig. 4 is a schematic flowchart of another data processing method provided in the embodiment of the present application, and referring to fig. 4, the data processing method may further include:
and step S340, cutting the point cloud data according to the three-dimensional route to obtain at least one target point.
In detail, the three-dimensional routes are generally gathered into a cluster in three dimensions, the outer wrapping edge in the horizontal direction is in a polygonal structure, and the area usually only occupies a small area in the whole point cloud, so that only the point cloud surrounding the whole three-dimensional route area can be taken. That is to say, the point cloud in the three-dimensional route preset range can be extracted to perform cutting processing on the point cloud data, and at least one target point is obtained.
For step S340, it should be noted that the specific step of performing the clipping process is not limited, and may be set according to the actual application requirement. For example, in an alternative example, step S340 may include a step of projecting onto a horizontal plane to extract point cloud data. Therefore, on the basis of fig. 4, fig. 5 is a schematic flowchart of another data processing method provided in the embodiment of the present application, and referring to fig. 5, step S340 may include:
step S341, projecting the point cloud data and at least two waypoints included in the three-dimensional route onto the same horizontal plane, and obtaining a minimum bounding polygon of the waypoints.
In detail, the specific manner of obtaining the minimum bounding polygon is not limited, and may be set according to the requirements of practical applications. For example, in an alternative example, after at least two waypoints included in the three-dimensional route are projected on a horizontal plane, the polygon boundaries of the waypoints may be searched by an algorithm such as Alpha Shape to obtain a minimum bounding polygon.
Step S342, extracting point cloud data within a preset range of the minimum bounding polygon extension to obtain at least one target point.
In detail, after the minimum enclosing polygon is obtained, the minimum enclosing polygon may be expanded outward on a horizontal plane and point cloud data within a preset range may be taken to obtain at least one target point. It should be noted that the point cloud data projected onto the horizontal plane does not include the height coordinate, but the obtained target point includes the height coordinate, and the projection operation is only to perform the clipping process on the point cloud data according to the minimum bounding polygon. Optionally, the specific value of the preset range is not limited, and may be set according to the actual application requirement. For example, in an alternative example, in order to reduce the amount of calculation of collision detection while ensuring the reliability of data, the specific value of the preset range may be 5 m.
For another example, in another alternative example, the point cloud data may be further subjected to a clipping process by a minimum bounding polygon cylinder, and step S342 may include the following sub-steps:
obtaining a minimum enclosing polygon cylinder according to the minimum enclosing polygon and the height coordinate range of the point cloud in the minimum enclosing polygon;
and extracting the point cloud data in the preset range expanded outside the minimum enclosing polygonal cylinder to obtain at least one target point.
That is to say, after the minimum enclosing polygon is obtained, the minimum enclosing polygon may be stretched according to the height coordinate range of the point cloud within the minimum enclosing polygon to obtain a minimum enclosing polygon cylinder, and the point cloud data within the preset range expanded outside the minimum enclosing polygon cylinder is extracted to obtain at least one target point. It should be noted that the point cloud data within the preset range extending from the minimum enclosing polygonal cylinder includes a height coordinate.
For step S320, it should be noted that the specific step of calculating the target distance is not limited, and may be set according to the actual application requirement. For example, in an alternative example, step S320 may include the step of obtaining the target distance from at least one distance value. Therefore, on the basis of fig. 3, fig. 6 is a schematic flowchart of another data processing method provided in the embodiment of the present application, and referring to fig. 6, step S320 may include:
step S321, calculating a distance from the target point to each flight leg to obtain at least one distance value.
In detail, the calculation of the distance from the target point to the flight segment is only performed when the target point is within the vertical range of the flight segment, the distance from the point to the line segment is calculated, otherwise, the distance from the target point to the nearest point of the flight segment is calculated.
Step S322, performing sorting processing on at least one distance value, and taking the minimum distance value as the target distance of the target point.
In detail, the target point may be attributed to the leg with the minimum distance, and the minimum distance may be used as the target distance.
For step S330, it should be noted that the safety information may represent the collision probability of the flight device in the flight segment, and the specific step of calculating the safety information is not limited, and may be set according to the actual application requirement. For example, in an alternative example, when the collision detection model is prestored in the electronic apparatus 100, step S330 may include a step of calculating safety information from the collision detection model. Therefore, on the basis of fig. 3, fig. 7 is a schematic flowchart of another data processing method provided in the embodiment of the present application, and referring to fig. 7, step S330 may include:
and step S331, calculating to obtain the safety information of the flight equipment 200 in the flight segment according to the collision detection model and the target distance.
In detail, the type of the collision detection model may include a linear regression model or a non-linear regression model, the model training may be performed according to the manual labeling data, the feature vector may be input into the model, and the result output by the model may be whether each leg will collide (collision possibility).
For step S331, it should be noted that step S331 may include different sub-steps according to different types of collision detection models. According to different training data, the collision detection model can comprise a first collision detection model and a second collision detection model, the first collision detection model can be obtained directly through training according to the target distance from a target point to a flight segment, a target distance range can be obtained through comparing a distance range determined according to state data of the flight equipment with the target distance, and the second collision detection model can be obtained through training according to the target distance range of the target point.
Optionally, the specific step of calculating the safety information according to the collision detection model is not limited, and may be set according to the actual application requirements. For example, in an alternative example, when the collision detection model includes a first collision detection model, step S331 may include a step of calculating safety information directly from the target distance, and step S331 may include the sub-steps of:
invoking a first collision detection model;
and inputting the target distance into the first collision detection model, and calculating to obtain the safety information of the flight equipment 200 in the flight segment.
In detail, in order to retain the most original data information, the target distance of each target point may be directly input into the first collision detection model as a feature vector, and the safety information is obtained.
For another example, in another alternative example, when the collision detection model includes the second collision detection model, step S331 may include a step of calculating safety information from a target distance range obtained by the target distance. Therefore, on the basis of fig. 7, fig. 8 is a schematic flowchart of another data processing method provided in the embodiment of the present application, and referring to fig. 8, step S331 may include:
step S3311, obtaining the state data of the flight device 200 in real time, and determining at least one distance range according to the state data.
Wherein the distance range is used to characterize the area in which the flying apparatus 200 may collide. Optionally, the specific type of the distance range is not limited, and may be set according to the actual application requirements. For example, in an alternative example, three distance ranges (x) may be set according to the distance from the center point of the flying apparatus 200, the farthest distance range being a safety zone (e.g., x ≧ 5m) indicating a low possibility of collision, the middle distance range being a warning zone (e.g., 1m ≦ x <5m) indicating a medium possibility of collision, and the closest distance range being a danger zone (e.g., x <1m) indicating a high possibility of collision.
It should be noted that the center point of the flying apparatus 200 can be regarded as a waypoint in a three-dimensional flight path, however, in practical cases, the flying apparatus 200 has a volume, the distance range cannot be determined directly according to the center point, and at least one distance range needs to be determined according to the state data of the flying apparatus 200.
Optionally, the specific type of the status data is not limited, and may be set according to the actual application requirement. For example, in an alternative example, the state data may include an appearance state of the flying device 200, which may specifically include distances from a center point of the flying device 200 to various points of the surface. For example, the distance from the center point of the flying device 200 to the surface point of the left wing may be 2m, and when the distance range is considered, 2m needs to be added in the direction from the center point of the flying device 200 to the surface point of the left wing, so as to avoid collision of the left wing of the flying device 200. That is, the distance range of the safety zone in this direction may be x ≧ 7m, the distance range of the warning zone may be 3m ≦ x <7m, and the distance range of the hazard zone may be x <3 m.
For another example, in another alternative example, the state data may include an appearance state and an operation state of the flying apparatus 200, and the operation state represents various states of the flying apparatus 200 during the movement process, and specifically may include, but is not limited to, takeoff, acceleration, uniform speed, deceleration, landing, and the like, when the distance range is considered, not only the distance from the center point of the flying apparatus 200 to each point of the surface needs to be considered, but also the distance range may be increased or decreased according to the operation state of the flying apparatus 200. For example, when the distance from the center point of the flying device 200 to the surface point of the left wing is 2m, a larger distance range is required when the flying device 200 is in the takeoff state, so as to avoid collision of the left wing of the flying device 200 when the flying device 200 bumps in the takeoff state. That is, the distance range of the safety zone in this direction may be x ≧ 9m, the distance range of the warning zone may be 5m ≦ x <9m, and the distance range of the hazard zone may be x <5 m.
Step S3312, for each target point, compares the target distance of the target point with at least one distance range to obtain a target distance range of the target point.
In detail, one end of the distance range is the center point of the flying apparatus 200, and the target distance is the minimum distance from the point cloud to the flight segment (which may be considered as the distance from the point cloud to the center point of the flying apparatus 200 on the three-dimensional route), so the target distance and the distance range may be compared. For example, when the target distance of the target point is 7m, the distance range from the point cloud to the safety area in the connecting line direction of the flight segment is x ≧ 9m, the distance range of the warning area is 5m ≦ x <9m, and the distance range of the danger area is x <5m, the target distance range of the target point is the distance range of the warning area.
Step S3313, the target distance range of each target point is input into the second collision detection model, and the safety information of the flight device 200 in the flight segment is calculated.
In detail, in order to more intuitively represent the possibility of collision when facing the user, the target distance range of each target point may be input as a feature vector to the second collision detection model, and the collision possibility may be obtained.
With reference to fig. 9, an embodiment of the present application further provides a data processing apparatus 900, where the functions implemented by the data processing apparatus 900 correspond to the steps executed by the foregoing method. The data processing apparatus 900 may be understood as a processor of the electronic device 100, or may be understood as a component that is independent of the electronic device 100 or a processor and implements the functions of the present application under the control of the electronic device 100. The data processing apparatus 900 may include a data acquisition module 910, a distance calculation module 920, and a security information calculation module 930, among others.
The data acquisition module 910 is configured to acquire point cloud data and a three-dimensional route of the flying apparatus 200, where the point cloud data includes at least one target point, and the three-dimensional route includes at least one route segment. In the embodiment of the present application, the data obtaining module 910 may be configured to perform step S310 shown in fig. 3, and for relevant contents of the data obtaining module 910, reference may be made to the foregoing description of step S310.
And a distance calculating module 920, configured to calculate, for each target point, a distance from the target point to at least one leg, so as to obtain a target distance. In this embodiment of the application, the distance calculating module 920 may be configured to perform step S320 shown in fig. 3, and reference may be made to the foregoing description of step S320 for relevant contents of the distance calculating module 920.
And a safety information calculation module 930, configured to calculate safety information of the flight device 200 in the flight segment according to the target distance. In the embodiment of the present application, the safety information calculating module 930 may be configured to perform step S330 shown in fig. 3, and the related content of the safety information calculating module 930 may refer to the description of step S330.
In addition, an embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program performs the steps of the data processing method.
The computer program product of the data processing method provided in the embodiment of the present application includes a computer-readable storage medium storing a program code, where instructions included in the program code may be used to execute steps of the data processing method in the above method embodiment, which may be referred to specifically in the above method embodiment, and are not described herein again.
In summary, according to the data processing method and apparatus, the electronic device, and the storage medium provided in the embodiments of the present application, the target distance is obtained by calculating the distance between the target point of the point cloud data and the flight segment of the flight device, and the safety information of the flight device in the flight segment is calculated according to the target distance, so that the possibility of collision on the planned path is determined according to the point cloud data, and the problem of low reliability of collision detection caused by the fact that the reliability of the course planning based on the digital surface model is not high, and the planned path cannot be accurately determined.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative, and for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that, in this document, the terms "comprises," "comprising," or 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 may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A data processing method, comprising:
acquiring point cloud data and a three-dimensional route of flight equipment, wherein the point cloud data comprises at least one target point, and the three-dimensional route comprises at least one route section;
aiming at each target point, calculating the distance from the target point to at least one of the navigation sections to obtain a target distance;
and calculating safety information of the flight equipment in the flight section according to the target distance.
2. The data processing method of claim 1, wherein the step of calculating safety information of the flying apparatus in the flight segment according to the target distance comprises:
invoking a first collision detection model;
and inputting the target distance into the first collision detection model, and calculating to obtain the safety information of the flight equipment in the flight section.
3. The data processing method of claim 1, wherein the step of calculating safety information of the flying apparatus in the flight segment according to the target distance comprises:
acquiring state data of the flight equipment in real time, and determining at least one distance range according to the state data;
for each target point, comparing the target distance of the target point with the at least one distance range to obtain a target distance range of the target point, wherein the target distance range is the distance range in which the target distance is located;
and inputting the target distance range of each target point into a second collision detection model, and calculating to obtain the safety information of the flight equipment in the flight segment.
4. The data processing method of claim 1, further comprising the step of obtaining at least one target point, the step comprising:
projecting the point cloud data and at least two waypoints included by the three-dimensional route onto the same horizontal plane to obtain a minimum enclosing polygon of the waypoints;
and extracting the point cloud data in the preset range expanded by the minimum enclosing polygon to obtain at least one target point.
5. The data processing method of claim 4, wherein the step of extracting the point cloud data within the preset range of the minimum bounding polygon extension to obtain at least one target point comprises:
obtaining a minimum enclosing polygon cylinder according to the minimum enclosing polygon and the height coordinate range of the point cloud in the minimum enclosing polygon;
and extracting the point cloud data in the preset range expanded outside the minimum enclosing polygonal cylinder to obtain at least one target point.
6. The data processing method of claim 1, wherein the step of calculating, for each of the target points, a distance from the target point to at least one of the legs to obtain a target distance comprises:
calculating the distance from the target point to each navigation section to obtain at least one distance value;
and sequencing the at least one distance value, and taking the minimum distance value as the target distance of the target point.
7. A data processing apparatus, characterized in that the data processing apparatus comprises:
the system comprises a data acquisition module, a data acquisition module and a flight equipment, wherein the data acquisition module is used for acquiring point cloud data and a three-dimensional flight path of flight equipment, the point cloud data comprises at least one target point, and the three-dimensional flight path comprises at least one flight segment;
the distance calculation module is used for calculating the distance from the target point to at least one of the navigation sections aiming at each target point to obtain a target distance;
and the safety information calculation module is used for calculating the safety information of the flight equipment in the flight section according to the target distance.
8. An electronic device, comprising a memory and a processor, the processor being configured to execute an executable computer program stored in the memory to implement the data processing method of any one of claims 1 to 6.
9. The electronic device of claim 8, wherein the electronic device is a plant protection drone with an image acquisition module, the plant protection drone acquires image data through the image acquisition module and processes the image data to obtain point cloud data.
10. A storage medium, characterized in that a computer program is stored thereon, which when executed performs the steps of the data processing method of any one of claims 1-6.
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