WO2022077297A1 - 数据处理方法、装置、设备及存储介质 - Google Patents

数据处理方法、装置、设备及存储介质 Download PDF

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Publication number
WO2022077297A1
WO2022077297A1 PCT/CN2020/120982 CN2020120982W WO2022077297A1 WO 2022077297 A1 WO2022077297 A1 WO 2022077297A1 CN 2020120982 W CN2020120982 W CN 2020120982W WO 2022077297 A1 WO2022077297 A1 WO 2022077297A1
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WIPO (PCT)
Prior art keywords
task
data
file
sampling
directory
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PCT/CN2020/120982
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English (en)
French (fr)
Inventor
刘渭锋
杜劼熹
孙旭斌
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深圳市大疆创新科技有限公司
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Application filed by 深圳市大疆创新科技有限公司 filed Critical 深圳市大疆创新科技有限公司
Priority to PCT/CN2020/120982 priority Critical patent/WO2022077297A1/zh
Priority to CN202080017477.4A priority patent/CN113597603A/zh
Publication of WO2022077297A1 publication Critical patent/WO2022077297A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/11—File system administration, e.g. details of archiving or snapshots
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/10—File systems; File servers
    • G06F16/16—File or folder operations, e.g. details of user interfaces specifically adapted to file systems
    • G06F16/164—File meta data generation

Definitions

  • the present application relates to the technical field of data processing, and in particular, to a data processing method, apparatus, device, and storage medium.
  • mobile platforms can be used for surveying and mapping, security, and power inspection.
  • the movable platform can be equipped with sensors such as cameras, ultrasonic rangefinders, lidars, etc. to perform corresponding tasks, such as route tasks, point cloud recording tasks, photo/video tasks, etc.
  • sensors such as cameras, ultrasonic rangefinders, lidars, etc.
  • tasks such as route tasks, point cloud recording tasks, photo/video tasks, etc.
  • different types of data for the same task are usually stored in a decentralized manner.
  • point cloud data is stored in the point cloud directory
  • photo data is stored in the camera directory, which is very inconvenient to call and view various types of data.
  • the embodiments of the present application provide a data processing method, apparatus, device, and storage medium, which can quickly call and view a variety of different types of data, and then achieve different data display effects through mutual assistance of a variety of different types of data.
  • the present application provides a data processing method, including:
  • each of the multiple mission files is determined according to the mission information, and the multiple mission files include: a state data file of the movable platform, and an image sensor mounted on the The image data file obtained by sampling the survey area, and the point cloud data file obtained by sampling the survey area by the point cloud sensor mounted on the movable platform;
  • a plurality of the task files are associated and stored according to the file directory.
  • the present application further provides a data processing apparatus, the data processing apparatus comprising a memory and a processor;
  • the memory is used to store computer programs
  • the processor is configured to execute the computer program and implement the following steps when executing the computer program:
  • each of the multiple mission files is determined according to the mission information, and the multiple mission files include: a state data file of the movable platform, and an image sensor mounted on the The image data file obtained by sampling the survey area, and the point cloud data file obtained by sampling the survey area by the point cloud sensor mounted on the movable platform;
  • a plurality of the task files are associated and stored according to the file directory.
  • the present application further provides a data processing device, where the data processing device includes the above-mentioned data processing apparatus.
  • the present application also provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the above-mentioned data processing method .
  • the data processing method, device, device and storage medium disclosed in the present application can quickly call and view a variety of different types of data, and then achieve different data display effects through mutual assistance of a variety of different types of data.
  • FIG. 1 is a schematic block diagram of a data processing device provided by an embodiment of the present application.
  • FIG. 2 is a schematic flowchart of steps of a data processing method provided by an embodiment of the present application.
  • FIG. 3 is a schematic flowchart of steps of another data processing method provided by an embodiment of the present application.
  • FIG. 4 is a schematic diagram of a generated file directory provided by an embodiment of the present application.
  • FIG. 5 is a schematic flowchart of sub-steps for generating a file directory provided by an embodiment of the present application
  • FIG. 6 is a schematic flowchart of another sub-step of generating a file directory provided by an embodiment of the present application.
  • FIG. 7 is a schematic diagram of a file directory custom setting interface provided by an embodiment of the present application.
  • FIG. 8 is a schematic block diagram of a data processing apparatus provided by an embodiment of the present application.
  • Embodiments of the present application provide a data processing method, apparatus, device, and storage medium, which are used to quickly call and view a variety of different types of data, so as to achieve different data display effects through mutual assistance of a variety of different types of data.
  • the data processing device 1000 may include a device body 100 , a power supply module 200 provided in the device body 100 , and a data processing apparatus 300 connected to the power supply module 200 .
  • the power supply module 200 is used to supply power to the data processing device 300
  • the data processing device 300 is used to organize the task data corresponding to the tasks performed by the drone and the like, and organize them into a directory structure based on tasks for intelligent storage.
  • the data processing device 1000 includes, but is not limited to, an unmanned aerial vehicle, a remote control device of the unmanned aerial vehicle, a PC (Personal Computer, personal computer) that is communicatively connected to the unmanned aerial vehicle, and the like, which is not limited in this embodiment of the present application.
  • a PC Personal Computer, personal computer
  • the data processing method provided by the embodiments of the present application will be described in detail with reference to the data processing device in FIG. 1 .
  • the data processing device in FIG. 1 is only used to explain the data processing method provided by the embodiment of the present application, but does not constitute a limitation on the application scenario of the data processing method provided by the embodiment of the present application.
  • FIG. 2 is a schematic flowchart of a data processing method provided by an embodiment of the present application.
  • the data processing method can be used in the above-mentioned data processing apparatus 1000, that is, executed by the data processing apparatus 1000 in FIG. 1, and of course can also be implemented by the data processing apparatus 300 in the above-mentioned data processing apparatus 1000, or can also be implemented by the data processing apparatus 1000. It is implemented by other control devices carried on the device 1000, and the embodiment of the present application is not limited to this.
  • the data processing method is applied to the data processing apparatus 300 as an example for description below, so as to realize quick calling and viewing of various types of data, and then realize mutual assistance through various types of data. Different data display effects.
  • the data processing method specifically includes steps S101 to S104.
  • the movable platform is equipped with cameras, lidars, etc. to perform sampling tasks in the survey area, and the corresponding task information includes one or more of the following information: device information associated with the device performing the sampling task, the The time information of the sampling task, the description information associated with the survey area, etc.
  • the acquired task information can facilitate users or devices to search for target content in task files based on different types of task information, and facilitate association between different tasks.
  • the description information of the survey area is obtained based on user input and/or based on the feature information of the survey area identified for the survey area.
  • the user inputs corresponding information such as "iron tower”, it is defined as “iron tower” in the preset name field.
  • the user input operation is flexible and targeted to distinguish, which can avoid false associations.
  • the current task is to sample an iron tower
  • the preset name field is defined as "iron tower”. That is, the description information of the survey area is obtained based on the feature information of the survey area automatically identified for the survey area, which saves the user manual input operation and improves the user experience.
  • S102 Determine the name of each of the task files in the plurality of task files according to the task information, where the plurality of task files include: a state data file of the movable platform, an image sensor mounted on the movable platform paired with The image data file obtained by sampling the survey area, and the point cloud data file obtained by sampling the survey area by the point cloud sensor mounted on the movable platform.
  • the state data file includes one or more of the following data files: GNSS (Global Navigation Satellite System) positioning data, IMU (Inertial measurement unit, inertial measurement unit) data, PTZ parameter data, sensor relative to The pose data of the movable platform body, the MRK record data, the pose correction data, and the internal reference data of the sensor.
  • sensors include but are not limited to GNSS, LIDAR (Light Detection and Ranging, laser detection), point cloud sensors, etc.
  • Image data files include one or more of the following data files: image data, video data.
  • the task file may further include: real-time display model data when the collected point cloud is displayed on the client.
  • the display model data is the point cloud (three-dimensional data), which is based on the projection imaging of the user's current observation angle FPV.
  • the projected plane is the observation plane of the movable platform and/or the FPV of the point cloud sensor, that is, according to the three-dimensional data of the sampling point and the movable platform and/or
  • the pose data of the point cloud sensor projects the sampling points on the observation plane.
  • the current collection changes can be reflected in real time when the pose of the movable platform or the point cloud sensor changes, and the collection process can also be monitored in real time;
  • the collection effect of the point cloud can be better displayed, and the interactive experience between the movable platform and the user observation can be better improved.
  • the three-dimensional data may be data in three-dimensional space, including three-dimensional position data.
  • Three-dimensional data is three-dimensional data relative to a certain coordinate system.
  • the specific data is related to the coordinate system. Different coordinate systems have different specific three-dimensional data, and the specific three-dimensional data in different coordinate systems can be converted to each other.
  • the point cloud can be a dataset of sampling points on the target surface obtained by measuring instruments; the sampling points contain rich information, including three-dimensional coordinates (XYZ), color, classification value, intensity value, time, and so on.
  • the sampling points contain rich information, including three-dimensional coordinates (XYZ), color, classification value, intensity value, time, and so on.
  • point cloud obtained according to the principle of laser measurement including three-dimensional coordinates (XYZ) and laser reflection intensity (Intensity)
  • point cloud obtained according to the principle of photogrammetry including three-dimensional coordinates (XYZ) and color information (RGB)
  • RGB color information
  • laser measurement And photogrammetry principle to get point cloud, including three-dimensional coordinates (XYZ), laser reflection intensity and color information.
  • a point cloud sensor (that is, a measuring instrument) can be a sensor that can be used to collect sampling points on the target surface at least to obtain three-dimensional data of the sampling points.
  • Point cloud sensors include but are not limited to: lidar, visible light camera, multispectral camera, millimeter Wave radar, ultrasonic radar, etc., or a combination of these sensors.
  • the currently collected point cloud is displayed according to the pose changes of the movable platform and/or the point cloud sensor in real time.
  • the projection plane is recalculated, and a projected image is generated. Since the 3D data of the sampling point is collected by the mounted point cloud sensor during the movement of the movable platform, according to the 3D data of the sampling point and the pose data of the movable platform and/or the point cloud sensor when the sampling point is collected, the The sampling points are projected on the observation plane, and the point cloud picture is generated according to the sampling points projected on the observation plane.
  • the point cloud picture is displayed on the user equipment of the mobile platform, the user can observe the point cloud sensor on the mobile platform in real time.
  • the 3D data of the sampling point can be directly calculated from the measurement data of the sampling point, or it can be reconstructed in 3D through a 2D image.
  • the computing resources that need to be used in obtaining the 3D data of the sampling points can be the computing resources of the mobile platform or the load of the mobile platform, or the relevant data can be transmitted to the ground terminal equipment (such as PC, tablet, mobile platform, etc.) in real time. equipment, etc.) or the cloud, use the computing resources of the ground-end equipment or the cloud to perform real-time computing, or you can also use the local computing resources to perform computing. That is, to obtain the three-dimensional data of the sampling points, it may be obtained from a movable platform, or obtained from a ground terminal device or the cloud, or obtained by computing using local computing resources, and so on.
  • the three-dimensional data of the sampling point is collected by the point cloud sensor mounted on the movable platform during the movement of the movable platform.
  • the position and attitude of the movable platform change during the movement process, and the position of the point cloud sensor And the posture is also changing, the sampling point is changing, and the three-dimensional data of the sampling point is also changing.
  • the pose data may be position data and pose data.
  • the pose data may be the pose data of the movable platform and/or the point cloud sensor when sampling points are collected.
  • the point cloud sensor is mounted on the movable platform, the pose of the point cloud sensor can change with the change of the pose of the movable platform, and the pose of the point cloud sensor can also change by itself.
  • the pose data when the sampling point is collected may be the pose data of the movable platform (the point cloud sensor changes with the change of the pose of the movable platform), or the pose data of the point cloud sensor ( The pose of the point cloud sensor is variable, and the pose of the movable platform remains unchanged), or the pose data of the movable platform and the point cloud sensor (the pose of the movable platform is variable, and the pose of the point cloud sensor is variable). pose is also variable).
  • the pose data can be used to determine the FPV of the movable platform and/or the point cloud sensor for determining the projection plane.
  • the pose data corresponding to multiple sampling points may be the same or different.
  • the pose data of the movable platform can be obtained through the pose capture system and positioning system on the movable platform. If the pose of the point cloud sensor remains unchanged relative to the movable platform, the pose data of the movable platform is the sampling point collected. when the pose data of the point cloud sensor; if the pose of the point cloud sensor is variable relative to the movable platform, it is necessary to combine the pose data of the movable platform and the point cloud sensor to determine the pose data.
  • Projection is a method of projecting a line through an object, projecting it to a selected projection plane, and obtaining a figure on the projection plane.
  • Projection can be divided into orthographic projection and oblique projection.
  • Orthographic projection means that the center line of the projection line is perpendicular to the projection plane, and the projection center line is not perpendicular to the projection plane, which is called oblique projection.
  • the projection plane in this embodiment is an observation plane, and the observation plane may be a plane projected from the first-person main perspective of the movable platform and/or the point cloud sensor, so that subsequent users can observe the acquisition situation on the user equipment.
  • the sources of 3D data are different, and the process of projecting sampling points on the observation plane is not the same. It is necessary to convert the 3D data in different coordinate systems, and finally convert them to the camera coordinate system, and project the 3D points in the camera coordinate system to the observation plane. point in the plane.
  • the picture of the point cloud may refer to a picture including at least the corresponding points where the sampling points are projected on the observation plane, and may include color information (eg RGB), height value, reflectivity, and the like of the corresponding points.
  • the picture of the point cloud is used to be displayed on the user equipment of the movable platform. In this way, the user can view the acquisition situation on the user equipment, as if he were in the scene.
  • the FPV formation is adjusted according to the pose changes of the movable platform and/or the point cloud sensor.
  • the movable platform is moving and/or the pose of the point cloud sensor changes.
  • the point cloud perspective of the FPV currently displayed on the user interface also changes. .
  • the pose data is the pose data of the movable platform and/or the point cloud sensor mounted on the movable platform relative to the target scene , project the sampling points on the observation plane, and project the sampling points on the observation plane from the movable platform and/or the point cloud sensor from a certain perspective
  • the generated point cloud picture is also the movable platform and / or the point cloud image of the sampling points collected by the point cloud sensor from a certain viewing angle, so when the movable platform is moving and / or the pose of the point cloud sensor changes, with the pose of the movable platform and / or the point cloud sensor changes, the point cloud perspective of the FPV currently displayed on the user interface also changes.
  • the acquisition process of the point cloud sensor of the movable platform is monitored in real time
  • the pose of the movable platform and/or the point cloud sensor is monitored in real time
  • the user can view the real-time acquisition process on the user interface. Since the point cloud sensor controlling the movable platform collects the measurement data of the sampling points in the target scene, according to the measurement data and when the sampling points are collected, the position of the movable platform and/or the point cloud sensor in the geographic coordinate system Pose data, determine the three-dimensional data of the sampling point in the geographic coordinate system, the three-dimensional data of the sampling point is used to project on the observation plane corresponding to the pose data, and generated in the available The point cloud screen displayed by the user terminal of the mobile platform, in this way, the user can watch the real-time acquisition process of the point cloud sensor of the mobile platform on the user interface.
  • the point cloud data is online replayable data, while other data are offline data, which are used for high-precision point cloud computing processing.
  • Different task files correspond to different data types.
  • the name of each task file is determined according to the task information of the sampling task and the data type information of each task file. .
  • the name of each task file is determined, so as to be easily distinguished.
  • the name of the state data file is determined based on task information of the sampling task and data type information of the state data file, such as motion data IMU.
  • the name of the image data file is determined based on the task information of the sampling task and the data type information of the image data file, such as image JPG.
  • the name of the point cloud data file is determined based on the task information of the sampling task and the data type information of the point cloud data file, such as point cloud RTB.
  • step S101 may include sub-step S1011.
  • Step S102 may include sub-step S1021.
  • the user performs a corresponding operation for triggering a new sampling task on the mobile platform, and in response to the user's operation, executes a corresponding new sampling task, wherein the new sampling task may be related to a historical sampling task that has been executed before , Exemplarily, if the new sampling task is to sample the survey area corresponding to the historical sampling task, the new sampling task and the historical sampling task are associated.
  • the new sampling tasks include, but are not limited to, the task of resuming the flight from a breakpoint, the task of supplementary recording of point clouds, and the task of supplementary photo/video shooting, etc. for the associated historical sampling tasks.
  • the task information of the historical sampling task associated with the new sampling task is determined, wherein the task information corresponding to each sampling task has been introduced above and will not be repeated here.
  • the name of each task file in the multiple task files of the new sampling task is determined.
  • the name of each task file is determined based on the task information of the historical sampling task associated with the new sampling task and the data type information of each task file in the multiple task files of the new sampling task.
  • the task file name in the file directory corresponding to the associated historical sampling task is "DJI_202005091425_002_2 Tower”
  • determine the name of the task file corresponding to the new sampling task such as "DJI_20200509142530_002_2 Tower.IMU" .
  • the task file name corresponding to the preset file directory may be used to determine the name of the task file corresponding to the new sampling task. If the same task file name exists, it indicates the content of the existing task file. If the same task file name does not exist, the file corresponding to the new sampling task can be generated according to the determined name of the task file corresponding to the new sampling task. content.
  • the file directory includes a primary directory and a secondary directory, where the secondary directory is an expanded directory of the primary directory.
  • the multiple task files are located in the first-level directory in the file directory, and a subfile included in any one of the multiple task files is located in the second-level directory in the file directory. That is, a flat two-level directory structure is used to create a corresponding file directory, and the directory structure level corresponding to the file directory is two levels.
  • the generated file directory is shown in Figure 4, in which "DJI_202005091416_001_1 Tower”, “DJI_202005091425_002_2 Tower”, etc. are the first-level directories of the file directory, "DJI_20200509141620_001_1 Tower.IMU", “DJI_20200509141620”_00RT “DJI_20200509141620_001_1 number Tower .RTR”, “DJI_20200509141620_001_1 number Tower .RTS”, “DJI_20200509141620_001_1 number Tower .LDR", “DJI_20200509141620_001_1 number Tower .RLY", “DJI_20200509141620_001_1 number Tower .MNF", “DJI_20200509141620_001_1 number Tower .JPG”, “DJI_20200509142530_001_2 Tower No.
  • a sub-file of the image data file includes multiple images of the survey area, and the multiple images are in a secondary directory in the file directory.
  • the secondary directory where the plurality of images are located is set according to a preset directory structure of panoramic photos. Multiple such images do not need to appear in the playback list.
  • the step S103 may include a sub-step S1031.
  • the preset trigger event includes but is not limited to: detecting that the movable platform is powered on, or detecting that a task trigger instruction is generated.
  • the task triggering instructions include at least one of the following: point cloud task triggering instructions, shooting task triggering instructions, and the like.
  • a point cloud task trigger instruction is generated, and when the generated point cloud task trigger instruction is detected, a corresponding file directory is generated, such as "DJI_202005091416_001_1 Tower".
  • the point cloud task trigger command is generated, and when the generated point cloud task trigger command is detected, the corresponding file directory is generated, such as "DJI_202005091425_002_2 Tower".
  • a shooting task trigger instruction is generated, and when the generated shooting task trigger instruction is detected, a corresponding file directory is generated.
  • the photographing operation includes photographing and/or video recording. That is, when a photographing operation such as a photographing operation and/or a video recording operation is detected, the generation of a corresponding file directory is triggered.
  • a file directory can be generated at the current time, or a folder can be generated, and the folder can preferably be distinguished from the folder corresponding to the point cloud recording task. Or follow the DCF naming rules to determine the name of the folder to distinguish.
  • the removable platform system can still work normally, and when it is detected that the removable platform is powered on, a corresponding file directory is generated.
  • the step S103 may include a sub-step S1032.
  • a unified default setting method for file directories is preset.
  • the default setting method is a flat two-level directory structure setting method.
  • a file directory is generated, a file with a corresponding two-level directory structure is generated according to the default setting method. content.
  • a file directory custom setting function is provided.
  • the corresponding file directory custom setting interface is displayed.
  • the user can customize settings based on the file directory.
  • the interface performs custom settings for files and directories such as directory name and directory level, and saves the user's custom settings.
  • the file directory is generated, the corresponding file directory is generated according to the user-defined setting method.
  • S104 Associate and store a plurality of the task files according to the file directory.
  • multiple task files corresponding to the collection task are associated and stored according to the generated file directory.
  • a complete 3D point cloud scene can be reconstructed. For example, based on the point cloud data included in the associated storage task file, as well as the pose data of the movable platform, the PTZ pose data, etc., modeling is performed to realize the 3D point cloud scene.
  • the file directory can be displayed on the user interface; alternatively, the file directory can also be stored as the index information of the internal data, so that the subsequent retrieval of the stored file directory is quick and convenient. obtain relevant data.
  • a plurality of the task files are associated and stored in the same folder. That is, the task data corresponding to a single complete sampling task is stored in a folder.
  • a plurality of the task files are at the same directory level in the file directory.
  • each task file in the plurality of task files is located in a first-level directory in the file directory.
  • the data processing method may further include: buffering data of a first preset type within a first preset time period before executing the sampling task, and/or a second preset type after executing the sampling task
  • the cached data of the second preset type within the set duration is stored in association with the task file corresponding to the sampling task according to the description.
  • first preset duration and the second preset duration may be the same or different, and the first preset duration and the second preset duration may be flexibly set according to actual conditions, which are not specifically limited herein.
  • the cached data of the first preset type and the cached data of the second preset type may also be the same type of data, or may also be different types of data.
  • the cached data of the first preset type is state data of the movable platform within the first preset time period before the sampling task is executed, such as IMU data.
  • Data convergence is facilitated by buffering the buffered data for a period of time before the sampling task is performed, and/or buffering the buffered data for a period of time after the execution of the sampling task. For example, a relatively accurate state data of a movable platform can be obtained, so as to achieve a more accurate measurement of the survey area.
  • the cached data of the first preset type within the first preset duration before the sampling task is executed is stored in association with the task file corresponding to the sampling task. For example, taking IMU data as an example, using memory buffering, the IMU data has been cached in the memory before the sampling task is executed, and the cache is obtained within the first preset time period (such as 10 minutes) before the sampling task is executed.
  • the IMU data is stored in association with the task file corresponding to the sampling task according to the description. For example, the IMU data is stored in association with the "DJI_20200509141620_001_1 Tower.IMU" task file.
  • the IMU data within a period of time before the sampling task starts is used as auxiliary data to perform operations such as high-precision point cloud computing and processing, thereby improving the accuracy of data processing.
  • cache data of a second preset type within a second preset time period after the sampling task is executed is stored in association with the task file corresponding to the sampling task.
  • the memory buffering method is used to continue to cache the IMU data in the memory after the sampling task is executed, and the cache is obtained within a second preset time period (such as 5 minutes) after the sampling task is executed.
  • the IMU data is stored in association with the task file corresponding to the sampling task according to the description.
  • cache data of a first preset type within a first preset duration before executing the sampling task and cache data of a second preset type within a second preset duration after executing the sampling task
  • the cached data is stored in association with the task file corresponding to the sampling task according to the description. For example, still taking the IMU data as an example, using the memory buffering method, the IMU data has been cached in the memory before the sampling task is executed, and the IMU data continues to be cached in the memory after the sampling task is executed.
  • the IMU data cached within the first preset time period such as 10 minutes
  • the IMU data cached within the second preset time period such as 5 minutes
  • the storage is associated with the task file corresponding to the sampling task.
  • the IMU data for a period of time before the sampling task starts and the IMU data for a period of time after the sampling task are used as auxiliary data to perform operations such as high-precision point cloud computing processing to further improve the accuracy of data processing.
  • the task information of the sampling task performed by the movable platform on the survey area is obtained, and the state data file of the mobile platform and the image data obtained by sampling the survey area by the image sensor mounted on the mobile platform are determined according to the obtained task information.
  • file, the name of each task file in multiple task files such as point cloud data files sampled by the point cloud sensor mounted on the mobile platform, and then generate the file directory corresponding to the sampling task according to the names of the multiple task files.
  • the multiple task files are stored in association with the generated file directory.
  • different data display effects can be achieved through the mutual assistance of a variety of different types of data.
  • FIG. 8 is a schematic block diagram of a data processing apparatus provided by an embodiment of the present application.
  • the data processing apparatus 300 includes a processor 301 and a memory 302, and the processor 301 and the memory 302 are connected through a bus, such as an I2C (Inter-integrated Circuit) bus.
  • I2C Inter-integrated Circuit
  • the processor 301 may be a micro-controller unit (Micro-controller Unit, MCU), a central processing unit (Central Processing Unit, CPU) or a digital signal processor (Digital Signal Processor, DSP) or the like.
  • MCU Micro-controller Unit
  • CPU Central Processing Unit
  • DSP Digital Signal Processor
  • the memory 302 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) magnetic disk, an optical disk, a U disk, a mobile hard disk, and the like.
  • ROM Read-Only Memory
  • the memory 302 may be a Flash chip, a read-only memory (ROM, Read-Only Memory) magnetic disk, an optical disk, a U disk, a mobile hard disk, and the like.
  • the processor is used for running the computer program stored in the memory, and implements the following steps when executing the computer program:
  • each of the multiple mission files is determined according to the mission information, and the multiple mission files include: a state data file of the movable platform, and an image sensor mounted on the The image data file obtained by sampling the survey area, and the point cloud data file obtained by sampling the survey area by the point cloud sensor mounted on the movable platform;
  • a plurality of the task files are associated and stored according to the file directory.
  • the task information includes one or more of the following information: device information associated with a device performing the sampling task, time information associated with the sampling task, and a description associated with the survey area information.
  • the description information of the survey area is obtained based on user input and/or based on the feature information of the survey area identified for the survey area.
  • the processor when implementing the determining the name of each of the multiple task files according to the task information, is configured to:
  • the name of each task file in the plurality of task files is determined.
  • the processor when implementing the acquiring task information of the movable platform performing the sampling task on the survey area, the processor is configured to:
  • determining task information of historical sampling tasks associated with the new sampling task In response to a user's operation for triggering a new sampling task, determining task information of historical sampling tasks associated with the new sampling task;
  • the processor When implementing the determining of the name of each of the task files in the plurality of task files according to the task information, the processor is configured to:
  • the name of each task file in the plurality of task files corresponding to the new sampling task is determined.
  • the processor is further configured to:
  • the new sampling task is to sample the survey area corresponding to the historical sampling task, the new sampling task and the historical sampling task are associated.
  • the new sampling task includes a breakpoint re-flying task, a point cloud supplementary recording task, and a photo/video supplementary shooting task for the associated historical sampling task.
  • the processor when implementing the storing the plurality of task files in association with the file directory, the processor is configured to implement:
  • a plurality of the task files are associated and stored in the same folder according to the file directory.
  • a plurality of the task files are at the same directory level in the file directory.
  • the processor is further configured to:
  • the cached data of the first preset type is state data of the movable platform within the first preset time period before the sampling task is executed.
  • the processor when implementing the generating of the file directory corresponding to the sampling task, is configured to implement:
  • the file directory is generated when a preset trigger event is detected.
  • the preset trigger event includes:
  • the processor when implementing the generating of the file directory, is configured to implement:
  • the file directory is generated.
  • the processor when implementing the generating of the file directories corresponding to the multiple tasks, is configured to implement:
  • the file directory is generated.
  • the file directory is generated according to the user-defined setting method.
  • the file directory includes a primary directory and a secondary directory; the secondary directory is an expanded directory of the primary directory;
  • the multiple task files are located in the first-level directory in the file directory, and a subfile included in any one of the multiple task files is located in the second-level directory in the file directory.
  • the sub-file of the image data file includes a plurality of images of the survey area
  • the secondary directory where the plurality of images are located is set according to a preset directory structure of panoramic photos.
  • the state data file includes one or more of the following data files: GNSS positioning data, IMU data, PTZ parameter data, sensor position and attitude data relative to the fuselage, MRK record data, and position and attitude correction data, the internal parameter data of the sensor.
  • the task file further includes:
  • An embodiment of the present application further provides a data processing device, where the data processing device includes the data processing apparatus 300 in the above embodiment.
  • the data processing equipment obtains the task information of the sampling task performed by the movable platform on the survey area, and determines the status data file of the mobile platform and the image data file obtained by sampling the survey area by the image sensor mounted on the mobile platform according to the acquired task information.
  • the point cloud sensor mounted on the mobile platform samples the name of each task file in multiple task files such as point cloud data files obtained from the survey area, and then generates a file directory corresponding to the sampling task according to the names of the multiple task files, and
  • the multiple task files are associated and stored according to the generated file directory.
  • the embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium stores a computer program, the computer program includes program instructions, and the processor executes the program instructions to implement the embodiments of the present application Provides the steps of the data processing method.
  • the computer-readable storage medium may be an internal storage unit of the data processing apparatus or data processing apparatus described in the foregoing embodiments, such as a hard disk or memory of the data processing apparatus or data processing apparatus.
  • the computer-readable storage medium can also be an external storage device of the data processing apparatus or data processing equipment, such as a plug-in hard disk equipped on the data processing apparatus or data processing equipment, a smart memory card (Smart Media Card, SMC), Secure Digital (SD) card, Flash Card (Flash Card), etc.
  • a data processing method a data processing apparatus, a data processing apparatus, and a computer-readable storage medium are provided.
  • the task information of the movable platform performing the sampling task on the survey area the status data file of the mobile platform, the image data file obtained by sampling the survey area by the image sensor mounted on the mobile platform, and the movable platform are determined according to the acquired task information.
  • the point cloud sensor mounted on the platform samples the name of each task file in multiple task files such as point cloud data files obtained from the survey area, and then generates a file directory corresponding to the sampling task according to the names of the multiple task files, and stores multiple task files.
  • Task files are stored in association with the generated file directory.

Abstract

一种数据处理方法、数据处理装置、数据处理设备及计算机可读存储介质，所述方法包括：获取可移动平台对测区执行采样任务的任务信息(S101)；根据所述任务信息确定多个任务文件中每一所述任务文件的名称，多个所述任务文件包括：所述可移动平台的状态数据文件，所述可移动平台搭载的图像传感器对所述测区采样得到的图像数据文件，所述可移动平台搭载的点云传感器对所述测区采样得到的点云数据文件(S102)；根据多个所述任务文件的所述名称，生成对应所述采样任务的文件目录(S103)；将多个所述任务文件按照所述文件目录关联存储(S104)。

Description

数据处理方法、装置、设备及存储介质 技术领域
本申请涉及数据处理技术领域，尤其涉及一种数据处理方法、装置、设备及存储介质。
背景技术
随着如无人机等可移动平台技术的快速发展，可移动平台的应用越来越广泛，例如，可以通过可移动平台进行测绘、安防、电力巡检等方面的应用。可移动平台可以搭载相机，超声波测距仪，激光雷达等等传感器，以执行相应任务，如航线任务、记录点云任务、拍照/录像任务等。目前，对于同一任务不同类型的各数据，通常是分散存储的，比如点云数据存储在点云目录下，照片数据存储在相机目录下，非常不便于多种不同类型数据的调用和查看。
发明内容
基于此，本申请实施例提供一种数据处理方法、装置、设备及存储介质，可以实现快捷调用和查看多种不同类型数据，进而通过多种不同类型数据相互辅助实现不同的数据展示效果。
第一方面，本申请提供了一种数据处理方法，包括：
获取可移动平台对测区执行采样任务的任务信息；
根据所述任务信息确定多个任务文件中每一所述任务文件的名称，多个所述任务文件包括：所述可移动平台的状态数据文件，所述可移动平台搭载的图像传感器对所述测区采样得到的图像数据文件，所述可移动平台搭载的点云传感器对所述测区采样得到的点云数据文件；
根据多个所述任务文件的所述名称，生成对应所述采样任务的文件目录；
将多个所述任务文件按照所述文件目录关联存储。
第二方面，本申请还提供了一种数据处理装置，所述数据处理装置包括存储器和处理器；
所述存储器用于存储计算机程序；
所述处理器，用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
获取可移动平台对测区执行采样任务的任务信息；
根据所述任务信息确定多个任务文件中每一所述任务文件的名称，多个所述任务文件包括：所述可移动平台的状态数据文件，所述可移动平台搭载的图像传感器对所述测区采样得到的图像数据文件，所述可移动平台搭载的点云传感器对所述测区采样得到的点云数据文件；
根据多个所述任务文件的所述名称，生成对应所述采样任务的文件目录；
将多个所述任务文件按照所述文件目录关联存储。
第三方面，本申请还提供了一种数据处理设备，所述数据处理设备包括如上述的数据处理装置。
第四方面，本申请还提供了一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如上述的数据处理方法。
本申请公开的数据处理方法、装置、设备及存储介质，实现了快捷调用和查看多种不同类型数据，进而通过多种不同类型数据相互辅助实现不同的数据展示效果。
应当理解的是，以上的一般描述和后文的细节描述仅是示例性和解释性的，并不能限制本申请。
附图说明
为了更清楚地说明本申请实施例技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本申请的实施例提供的一种数据处理设备的示意性框图；
图2是本申请的实施例提供的一种数据处理方法的步骤示意流程图；
图3是本申请的实施例提供的另一种数据处理方法的步骤示意流程图；
图4是本申请的实施例提供的一种生成的文件目录的示意图；
图5是本申请的实施例提供的一种生成文件目录的子步骤示意流程图；
图6是本申请的实施例提供的另一种生成文件目录的子步骤示意流程图；
图7是本申请的实施例提供的一种文件目录自定义设置界面示意图；
图8是本申请的实施例提供的一种数据处理装置的示意性框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
附图中所示的流程图仅是示例说明，不是必须包括所有的内容和操作/步骤，也不是必须按所描述的顺序执行。例如，有的操作/步骤还可以分解、组合或部分合并，因此实际执行的顺序有可能根据实际情况改变。
应当理解，在此本申请说明书中所使用的术语仅仅是出于描述特定实施例的目的而并不意在限制本申请。如在本申请说明书和所附权利要求书中所使用的那样，除非上下文清楚地指明其它情况，否则单数形式的“一”、“一个”及“该”意在包括复数形式。
还应当理解，在本申请说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
下面结合附图，对本申请的一些实施方式作详细说明。在不冲突的情况下，下述的实施例及实施例中的特征可以相互组合。
本申请的实施例提供了一种数据处理方法、装置、设备及存储介质，用于实现快捷调用和查看多种不同类型数据，进而通过多种不同类型数据相互辅助实现不同的数据展示效果。
请参阅图1，图1为本申请实施例提供的一种数据处理设备的示意性框图。如图1所示，数据处理设备1000可以包括设备体100、设于设备体100内的供电模块200、以及与供电模块200连接的数据处理装置300。其中，供电模块 200用于为数据处理装置300供电，数据处理装置300用于将无人机等执行任务对应的任务数据组织在一起，整理为以任务为单位的目录结构进行智能存储。
示例性的，数据处理设备1000包括但不限于无人机、无人机的遥控设备、与无人机通信连接的PC(Personal Computer，个人计算机)等，本申请实施例对此不做限制。
可以理解的，上述对于数据处理设备1000各部件的命名仅仅出于标识的目的，并不因此对本申请实施例进行限制。
以下，将结合图1中的数据处理设备对本申请的实施例提供的数据处理方法进行详细介绍。需知，图1中的数据处理设备仅用于解释本申请实施例提供的数据处理方法，但并不构成对本申请实施例提供的数据处理方法应用场景的限定。
请参阅图2，图2是本申请的实施例提供的一种数据处理方法的示意流程图。该数据处理方法可以用于上述数据处理设备1000中，即通过图1的数据处理设备1000来执行，当然也可以由上述数据处理设备1000中的数据处理装置300来实现，或者也可以由数据处理设备1000上携带的其它控制装置来实现，本申请实施例不限于此。
为了方便对本申请的实施例作详细阐述，以下以该数据处理方法应用于数据处理装置300为例进行说明，以实现快捷调用和查看多种不同类型数据，进而通过多种不同类型数据相互辅助实现不同的数据展示效果。
如图2所示，该数据处理方法具体包括步骤S101至步骤S104。
S101、获取可移动平台对测区执行采样任务的任务信息。
示例性的，可移动平台搭载相机、激光雷达等在测区执行采样任务，对应的任务信息包括以下信息的一种或多种：关联执行所述采样任务的设备的设备信息，所述执行所述采样任务的时间信息，关联所述测区的描述信息等。通过获取的任务信息，可以便于用户或者设备，基于不同类型的任务信息进行任务文件查找目标内容，并且便于不同的任务之间进行关联。
示例性的，所述测区的描述信息是基于用户输入，和/或，基于对所述测区识别到的测区特征信息获取的。
例如，用户输入如“铁塔”的相应信息，则在预设的名称字段定义为“铁 塔”。用户输入操作灵活，有针对性区别，可以避免误关联。
又如，基于图像识别、点云识别，确定当前任务是对一铁塔进行采样，则在预设的名称字段定义为“铁塔”。也即，基于对所述测区自动识别到的测区特征信息获取到测区的描述信息，省去了用户手动输入操作，提升了用户体验。
S102、根据所述任务信息确定多个任务文件中每一所述任务文件的名称，多个所述任务文件包括：所述可移动平台的状态数据文件，所述可移动平台搭载的图像传感器对所述测区采样得到的图像数据文件，所述可移动平台搭载的点云传感器对所述测区采样得到的点云数据文件。
其中，状态数据文件包括以下一种或多种数据文件：GNSS(Global Navigation Satellite System，全球导航卫星系统)定位数据，IMU(Inertial measurement unit，惯性测量单元)数据，云台参数数据，传感器相对于可移动平台机身的位姿数据，MRK记录数据，位姿矫正数据，传感器的内参数据。其中，传感器包括但不限于GNSS、LIDAR(Light Detection and Ranging，激光探测)、点云传感器等。
图像数据文件包括以下一种或多种数据文件：图像数据，视频数据。
在一些实施例中，任务文件还可以包括：采集的点云在用户端显示时的实时展示模型数据。
其中，所述展示模型数据为所述点云(三维数据)，基于用户当前的观测视角FPV的投影成像。
示例性的，在将点云对应的三维数据进行投影时，投影到的平面是可移动平台和/或点云传感器的FPV的观测平面，即根据采样点的三维数据和可移动平台和/或点云传感器的位姿数据，将采样点投影在观测平面上，通过这种方式，能够实时反映可移动平台或点云传感器的位姿变动时当前采集的变化，也能够实时监控采集过程；在将采样点投影在观测平面上的基础上，能够更好地展示点云的采集效果，能够更好地提升可移动平台与用户观测的交互体验。
其中，三维数据可以是三维空间的数据，包括三维位置数据。三维数据是相对某个坐标系的三维数据，具体数据与坐标系有关，不同的坐标系，具体的三维数据不同，不同坐标系下具体的三维数据可以相互转换。
点云可以是通过测量仪器得到的目标表面的采样点的数据集；采样点包含 丰富的信息，包括三维坐标(XYZ)、颜色、分类值、强度值、时间等等。例如：根据激光测量原理得到的点云，包括三维坐标(XYZ)和激光反射强度(Intensity)，根据摄影测量原理得到的点云，包括三维坐标(XYZ)和颜色信息(RGB)，结合激光测量和摄影测量原理得到点云，包括三维坐标(XYZ)、激光反射强度和颜色信息。在获取目标表面的采样点的空间坐标后，得到的是一个点的集合，称之为“点云”(Point Cloud)。
点云传感器(即测量仪器)，可以是能够用于采集目标表面的采样点至少以得到采样点的三维数据的传感器，点云传感器包括但不限于：激光雷达、可见光相机、多光谱相机、毫米波雷达、超声波雷达，等等，或者这些传感器的组合。
例如，根据可移动平台和/或点云传感器姿态实时变动显示当前采集的点云，每次采集点云，都重新算投影平面，并生成投影后的画面。由于采样点的三维数据是在可移动平台运动过程中通过搭载的点云传感器采集得到的，根据采样点的三维数据和采集采样点时可移动平台和/或点云传感器的位姿数据，将采样点投影在观测平面上，根据投影到观测平面上的采样点生成点云画面，当可移动平台的用户设备上展示点云画面时，用户能够观测到实时反映可移动平台上的点云传感器采集采样点时的位姿下对应的采样点的情况；当可移动平台和/或点云传感器位姿实时变动，由于每次采集点云，都重新确定投影平面，并生成投影后的画面，当可移动平台的用户设备上展示投影后的画面时，用户能够观测到可移动平台和/或点云传感器位姿实时变动时显示当前采集的点云。
示例性的，采样点的三维数据，可以是通过采样点的测量数据直接计算出来，也可以是通过二维影像进行三维重建，在重建过程中获取采样点的三维数据，或者还可以通过三维模型来计算获取采样点的三维数据。其中，在获取采样点的三维数据中需要利用的算力资源可以是可移动平台或可移动平台的负载的算力资源，也可以把相关数据实时传输到地面端设备(如PC、平板、移动设备等)或云端，利用地面端设备或云端的算力资源实时进行计算，或者还可以利用本地的算力资源进行计算。即，获取采样点的三维数据，可以是从可移动平台获取，或者从地面端设备或云端获取，或者利用本地的算力资源进行计算得到，等等。
所述采样点的三维数据是在可移动平台运动过程中，通过所述可移动平台搭载的点云传感器采集得到的，可移动平台在运动过程中位置和姿态是变动的，点云传感器的位置和姿态也是变动的，采样点在变动，采样点的三维数据也是变动的。
位姿数据可以是位置数据和姿态数据。位姿数据可以是采集采样点时可移动平台和/或所述点云传感器的位姿数据。点云传感器搭载在可移动平台上，点云传感器的位姿可以跟随可移动平台的位姿的变化而变化，点云传感器的姿态也可以自己变化。采集所述采样点时的位姿数据可以是所述可移动平台的位姿数据(点云传感器随可移动平台的位姿的变化而变化)，可以是所述点云传感器的位姿数据(点云传感器的位姿可变，可移动平台的位姿不变)，也可以是可移动平台和所述点云传感器的位姿数据(可移动平台的位姿可变，点云传感器的位姿也可变)。位姿数据可以用于确定可移动平台和/或点云传感器的FPV，用于确定投影平面。多个采样点对应的位姿数据可以相同，也可以不同。
通过可移动平台上的姿态捕捉系统和定位系统即可得到可移动平台的位姿数据，如果点云传感器的姿态相对可移动平台不变，可移动平台的位姿数据即为采集所述采样点时所述点云传感器的位姿数据；如果点云传感器的姿态相对可移动平台可变，则需要结合可移动平台和点云传感器的位姿确定位姿数据。
投影是投射线通过物体，向选定的投影平面投射，并在该投影平面上得到图形的方法。投影可分为正投影和斜投影。正投影即是投射线的中心线垂直于投影平面，其投射中心线不垂直于投影平面的称为斜投影。本实施例的投影平面为观测平面，观测平面可以是以可移动平台和/或点云传感器的第一人称主视角进行投影的平面，这样后续用户能够在用户设备上观测采集情况。三维数据的来源不同，将采样点投影在观测平面的过程不太相同，需要将不同的坐标系中的三维数据进行转换，最后转换至相机坐标系，将相机坐标系中的三维点投影到观测平面中的点。
点云的画面可以是指至少包括采样点投影到观测平面上的对应的点的画面，可以包括对应的点的颜色信息(例如RGB)、高度值、反射率，等等。点云的画面用于在所述可移动平台的用户设备上展示，通过这种方式，能够使用户在用户设备上观看到采集情况，如同身临其境的感觉。
又如，根据可移动平台和/或点云传感器位姿变化，调整FPV形成。简单说就是：可移动平台在移动和/或点云传感器位姿变化，随着可移动平台和/或点云传感器的位姿变化，当前展示在用户界面上的FPV的点云视角也发生变化。由于采样点的三维数据是目标场景的三维模型的采样点的三维数据，位姿数据是可移动平台和/或所述可移动平台搭载的点云传感器的相对于所述目标场景的位姿数据，据此将所述采样点投影在观测平面上，投影在观测平面上的是可移动平台和/或点云传感器某个视角下所采集的采样点，生成的点云画面也是可移动平台和/或点云传感器某个视角下所采集的采样点的点云画面，因此当可移动平台在移动和/或点云传感器位姿变化，随着可移动平台和/或点云传感器的位姿变化，当前展示在用户界面上的FPV的点云视角也发生变化。
又如，实时监控可移动平台的点云传感器的采集过程，实时监控可移动平台和/或所述点云传感器的位姿，用户能够在用户界面观看到实时采集过程。由于控制可移动平台的点云传感器采集目标场景中采样点的测量数据，根据测量数据和采集所述采样点时所述可移动平台和/或所述点云传感器的在所述地理坐标系的位姿数据，确定所述采样点的在所述地理坐标系下的三维数据，采样点的所述三维数据用于投影在与所述位姿数据相应的观测平面上，并生成在所述可移动平台的用户终端展示的点云画面，通过这种方式，能够使用户在用户界面观看到可移动平台的点云传感器的实时采集过程。
在采样任务对应的多个任务文件中，点云的数据为在线可回放数据，而其他数据都属于离线数据，用于进行高精度点云计算处理。
不同的任务文件对应不同的数据类型，对于采样任务对应的多个任务文件，示例性的，根据采样任务的所述任务信息、以及每一个任务文件的数据类型信息，确定每一个任务文件的名称。示例性的，按照EDCF命名规则，确定每一个任务文件的名称，从而便于区分。
比如，对于状态数据文件，基于采样任务的任务信息以及状态数据文件的数据类型信息，如运动数据IMU，确定状态数据文件的名称。
又如，对于图像数据文件，基于采样任务的任务信息以及图像数据文件的数据类型信息，如图像JPG，确定图像数据文件的名称。
又如，对于点云数据文件，基于采样任务的任务信息以及点云数据文件的 数据类型信息，如点云RTB，确定点云数据文件的名称。
在一些实施例中，如图3所示，步骤S101可以包括子步骤S1011。
S1011、响应于用户用于触发新的采样任务的操作，确定与所述新的采样任务关联的历史采样任务的任务信息。
步骤S102可以包括子步骤S1021。
S1021、基于所述历史采样任务的任务信息，确定对应所述新的采样任务的多个任务文件中每一所述任务文件的名称。
用户执行相应的用于触发可移动平台新的采样任务的操作，对用户的该操作进行响应，执行相应的新的采样任务，其中，该新的采样任务可能与之前已经执行的历史采样任务有关，示例性的，若所述新的采样任务为对所述历史采样任务对应的测区进行采样，则关联所述新的采样任务和所述历史采样任务。新的采样任务包括但不限于对关联的历史采样任务的断点续飞任务、点云补录任务、照片/视频补拍任务等。
若新的采样任务与历史采样任务有关，则确定该新的采样任务所关联的历史采样任务的任务信息，其中，关于每个采样任务对应的任务信息在上面已经介绍，在此不再赘述。并基于新的采样任务关联的历史采样任务的任务信息，确定新的采样任务的多个任务文件中每一任务文件的名称。示例性的，基于新的采样任务关联的历史采样任务的任务信息，以及新的采样任务的多个任务文件中每一个任务文件的数据类型信息，确定每一个任务文件的名称。
例如，若关联的历史采样任务对应的文件目录中的任务文件名称为“DJI_202005091425_002_2号铁塔”，基于该任务文件名称，确定新的采样任务对应的任务文件的名称，比如“DJI_20200509142530_002_2号铁塔.IMU”。
示例性的，对于点云补录任务，可以采用预先设置好的文件目录对应的任务文件名称，确定新的采样任务对应的任务文件的名称。若存在相同的任务文件名称，说明已有任务文件的内容，若不存在相同的任务文件名称，则可根据所确定的新的采样任务对应的任务文件的名称，生成新的采样任务对应的文件目录。
S103、根据多个所述任务文件的所述名称，生成对应所述采样任务的文件目录。
示例性的，文件目录包括一级目录和二级目录，其中，二级目录为一级目录的展开目录。多个任务文件在文件目录中处于所述一级目录，多个任务文件中任一个任务文件包括的子文件在文件目录中处于所述二级目录。也即，采用扁平的两级目录结构，创建相应的文件目录，文件目录对应的目录结构层级为两级。
例如，生成的文件目录如图4所示，其中，"DJI_202005091416_001_1号铁塔"、"DJI_202005091425_002_2号铁塔"等为文件目录的一级目录，"DJI_20200509141620_001_1号铁塔.IMU"、"DJI_20200509141620_001_1号铁塔.RTB"、"DJI_20200509141620_001_1号铁塔.RTR"、"DJI_20200509141620_001_1号铁塔.RTS"、"DJI_20200509141620_001_1号铁塔.LDR"、"DJI_20200509141620_001_1号铁塔.RLY"、"DJI_20200509141620_001_1号铁塔.MNF"、"DJI_20200509141620_001_1号铁塔.JPG"、"DJI_20200509142530_001_2号铁塔.IMU"、"DJI_20200509142530_001_2号铁塔.RTB"、"DJI_20200509142530_001_2号铁塔.MNF"、"DJI_20200509142530_001_2号铁塔.JPG"、"DJI_20200510151025_002_2号铁塔.IMU"、"DJI_20200510151025_002_2号铁塔.RTB"、"DJI_20200510151025_002_2号铁塔.MNF"、"DJI_20200510151025_002_2号铁塔.JPG"等为文件目录的二级目录。
示例性的，以图像数据文件为例，图像数据文件的子文件包括所述测区的多张图像，多张所述图像在文件目录中处于二级目录。其中，多张所述图像所在的所述二级目录是按照预设的全景照片的目录结构设置的。多张所述图像不需要出现在回放列表。
在一些实施例中，如图5所示，所述步骤S103可以包括子步骤S1031。
S1031、当检测到预设触发事件时，生成所述文件目录。
示例性的，预设触发事件包括但不限于：检测到所述可移动平台上电，或者，检测到生成的任务触发指令。
其中，任务触发指令包括以下至少一种：点云任务触发指令、拍摄任务触发指令等。
例如，当用户基于开始录制点云按键执行相应的点击操作时，生成点云任 务触发指令，当检测到生成的点云任务触发指令时，生成对应的文件目录，如"DJI_202005091416_001_1号铁塔"。
又如，当检测到用户使用waypoint mission进行点云录制时，生成点云任务触发指令，当检测到生成的点云任务触发指令时，生成对应的文件目录，如"DJI_202005091425_002_2号铁塔"。
又如，当用户执行拍摄操作时，生成拍摄任务触发指令，当检测到生成的拍摄任务触发指令时，生成对应的文件目录。
其中，拍摄操作包括拍照和/或录像。也即，当检测到拍照操作、和/或录像操作等拍摄操作时，触发生成对应的文件目录。
示例性的，对于相机非点云录制任务相关的图像和视频，可以以当前时间生成文件目录，也可以生成文件夹，该文件夹最好能跟点云录制任务对应的文件夹有所区分，或按照DCF命名规则确定文件夹的名称以进行区分。
示例性的，用户上电格式化sd卡后，可移动平台系统仍然可正常工作，当检测到可移动平台上电时，生成对应的文件目录。
在一些实施例中，如图6所示，所述步骤S103可以包括子步骤S1032。
S1032、按照统一的默认设置方式，生成所述文件目录；或者，按照用户自定义设置方式，生成所述文件目录。
示例性的，预先设置统一的文件目录默认设置方式，例如，默认设置方式为扁平的两级目录结构设置方式，在生成文件目录时，按照该默认设置方式，生成对应的两级目录结构的文件目录。
示例性的，提供文件目录自定义设置功能，当用户打开文件目录自定义设置功能时，显示对应的文件目录自定义设置界面，例如，如图7所示，用户可以基于该文件目录自定义设置界面进行目录名称、目录层级等文件目录自定义设置，并保存用户的自定义设置方式。在生成文件目录时，按照用户的自定义设置方式，生成对应的文件目录。
S104、将多个所述任务文件按照所述文件目录关联存储。
通过所生成的文件目录，将采集任务对应的多个任务文件按照所生成的文件目录关联存储。通过该按照文件目录关联存储的任务文件，可以实现重建完整的三维点云场景。比如，基于关联存储的任务文件包括的点云数据，以及可 移动平台的位姿数据、云台位姿数据等进行建模，实现三维点云场景。
将多个任务文件按照所生成的文件目录关联存储，也便于快捷调用和查看多种不同类型数据，并且，在同一文件目录下，多种不同类型数据可以相互辅助实现不同的数据展示效果。例如，点云数据结合图像数据，可以实现上色点云展示效果。又如，点云数据结合IMU数据，可以实现点云模型展示效果。
示例性的，生成对应的文件目录后，可以将该文件目录在用户界面上展示；或者，也可以将文件目录作为内部数据的索引信息进行存储，以便于后续通过调取存储的文件目录快捷方便地获取到相关数据。
在一些实施例中，按照生成的所述文件目录，将多个所述任务文件关联存储至同一文件夹下。也即，实现将单次完整的采样任务对应的任务数据存储至一个文件夹下。
示例性的，多个所述任务文件在所述文件目录中处于同一目录级。比如，多个所述任务文件中的每一个任务文件均在所述文件目录中处于一级目录。
在一些实施例中，所述数据处理方法还可以包括：将执行所述采样任务之前第一预设时长内的第一预设类型的缓存数据，和/或执行所述采样任务之后第二预设时长内的第二预设类型的缓存数据，按照所述与对应所述采样任务的所述任务文件关联存储。
其中，第一预设时长与第二预设时长可以相同，也可以不同，第一预设时长与第二预设时长可根据实际情况进行灵活设置，在此不作具体限制。第一预设类型的缓存数据与第二预设类型的缓存数据也可以是相同类型数据，或者也可以是不同类型数据。
示例性的，所述第一预设类型的缓存数据为所述采样任务执行前所述第一预设时长内所述可移动平台的状态数据，比如IMU数据。
通过缓存执行所述采样任务之前一段时间内的缓存数据，和/或缓存执行所述采样任务之后一段时间内的缓存数据，有助于数据收敛。比如能够获得一个较为准确的可移动平台的状态数据，从而实现对测区的测量更准确。
在一实施方式中，将执行所述采样任务之前第一预设时长内的第一预设类型的缓存数据，按照所述与对应所述采样任务的所述任务文件关联存储。例如，以IMU数据为例，采用内存缓冲的方式，在执行所述采样任务之前已经开始将 IMU数据缓存在内存中，获取执行所述采样任务之前第一预设时长内(如10分钟)缓存的IMU数据，将该IMU数据按照所述与对应所述采样任务的所述任务文件关联存储。例如，将该IMU数据与"DJI_20200509141620_001_1号铁塔.IMU"任务文件关联存储。从而实现将所述采样任务开始之前一段时间内的IMU数据作为辅助数据，进行高精度点云计算处理等操作，提高数据处理的精准性。
在另一实施方式中，将执行所述采样任务之后第二预设时长内的第二预设类型的缓存数据，按照所述与对应所述采样任务的所述任务文件关联存储。例如，仍以IMU数据为例，采用内存缓冲的方式，在执行所述采样任务之后继续将IMU数据缓存在内存中，获取执行所述采样任务之后第二预设时长内(如5分钟)缓存的IMU数据，将该IMU数据按照所述与对应所述采样任务的所述任务文件关联存储。将所述采样任务之后一段时间内的IMU数据作为辅助数据，进行高精度点云计算处理等操作，同样也能提高数据处理的精准性。
在另一实施方式中，将执行所述采样任务之前第一预设时长内的第一预设类型的缓存数据，以及执行所述采样任务之后第二预设时长内的第二预设类型的缓存数据，按照所述与对应所述采样任务的所述任务文件关联存储。例如，仍以IMU数据为例，采用内存缓冲的方式，在执行所述采样任务之前已经开始将IMU数据缓存在内存中，并在执行所述采样任务之后继续将IMU数据缓存在内存中，获取执行所述采样任务之前第一预设时长内(如10分钟)缓存的IMU数据以及执行所述采样任务之后第二预设时长内(如5分钟)缓存的IMU数据，将两组IMU数据按照所述与对应所述采样任务的所述任务文件关联存储。将所述采样任务开始之前一段时间内的IMU数据、以及所述采样任务之后一段时间内的IMU数据作为辅助数据，进行高精度点云计算处理等操作，进一步提高数据处理的精准性。
上述实施例中通过获取可移动平台对测区执行采样任务的任务信息，根据所获取到的任务信息确定可移动平台的状态数据文件、可移动平台搭载的图像传感器对测区采样得到的图像数据文件、可移动平台搭载的点云传感器对测区采样得到的点云数据文件等多个任务文件中每一任务文件的名称，然后根据多个任务文件的名称，生成对应采样任务的文件目录，并将多个任务文件按照所生 成的文件目录关联存储。从而便于多个任务文件中不同类型数据的调用和查看。并且，在同一文件目录下，通过多种不同类型数据相互辅助实现不同的数据展示效果。
请参阅图8，图8是本申请实施例提供的一种数据处理装置的示意性框图。如图8所示，该数据处理装置300包括处理器301和存储器302，处理器301和存储器302通过总线连接，该总线比如为I2C(Inter-integrated Circuit)总线。
具体地，处理器301可以是微控制单元(Micro-controller Unit，MCU)、中央处理单元(Central Processing Unit，CPU)或数字信号处理器(Digital Signal Processor，DSP)等。
具体地，存储器302可以是Flash芯片、只读存储器(ROM，Read-Only Memory)磁盘、光盘、U盘或移动硬盘等。
其中，所述处理器用于运行存储在存储器中的计算机程序，并在执行所述计算机程序时实现如下步骤：
获取可移动平台对测区执行采样任务的任务信息；
根据所述任务信息确定多个任务文件中每一所述任务文件的名称，多个所述任务文件包括：所述可移动平台的状态数据文件，所述可移动平台搭载的图像传感器对所述测区采样得到的图像数据文件，所述可移动平台搭载的点云传感器对所述测区采样得到的点云数据文件；
根据多个所述任务文件的所述名称，生成对应所述采样任务的文件目录；
将多个所述任务文件按照所述文件目录关联存储。
在一些实施例中，所述任务信息包括以下信息的一种或多种：关联执行所述采样任务的设备的设备信息，所述执行所述采样任务的时间信息，关联所述测区的描述信息。
在一些实施例中，所述测区的描述信息是基于用户输入，和/或，基于对所述测区识别到的测区特征信息获取的。
在一些实施例中，所述处理器在实现所述根据所述任务信息确定多个任务文件中每一所述任务文件的名称时，用于实现：
根据所述任务信息和任务文件的数据类型信息，确定多个任务文件中每一所述任务文件的名称。
在一些实施例中，所述处理器在实现所述获取可移动平台对测区执行采样任务的任务信息时，用于实现：
响应于用户用于触发新的采样任务的操作，确定与所述新的采样任务关联的历史采样任务的任务信息；
所述处理器在实现所述根据所述任务信息确定多个任务文件中每一所述任务文件的名称时，用于实现：
基于所述历史采样任务的任务信息，确定对应所述新的采样任务的多个任务文件中每一所述任务文件的名称。
在一些实施例中，所述处理器还用于实现：
若所述新的采样任务为对所述历史采样任务对应的测区进行采样，则关联所述新的采样任务和所述历史采样任务。
在一些实施例中，所述新的采样任务包括对关联的所述历史采样任务的断点续飞任务、点云补录任务、照片/视频补拍任务。
在一些实施例中，所述处理器在实现所述将多个所述任务文件按照所述文件目录关联存储时，用于实现：
按照所述文件目录将多个所述任务文件关联存储至同一文件夹下。
在一些实施例中，多个所述任务文件在所述文件目录中处于同一目录级。
在一些实施例中，所述处理器还用于实现：
将执行所述采样任务之前第一预设时长内的第一预设类型的缓存数据，和/或执行所述采样任务之后第二预设时长内的第二预设类型的缓存数据，按照与对应所述采样任务的所述任务文件关联存储。
在一些实施例中，所述第一预设类型的缓存数据为所述采样任务执行前所述第一预设时长内所述可移动平台的状态数据。
在一些实施例中，所述处理器在实现所述生成对应所述采样任务的文件目录时，用于实现：
当检测到预设触发事件时，生成所述文件目录。
在一些实施例中，所述预设触发事件包括：
检测到所述可移动平台上电，或者，检测到生成的任务触发指令。
在一些实施例中，所述处理器在实现所述生成所述文件目录时，用于实现：
当检测到生成的点云任务触发指令或者拍摄任务触发指令，生成所述文件目录。
在一些实施例中，所述处理器在实现所述生成所述多个任务对应的文件目录时，用于实现：
按照统一的默认设置方式，生成所述文件目录；或者
按照用户自定义设置方式，生成所述文件目录。
在一些实施例中，所述文件目录包括一级目录和二级目录；所述二级目录为所述一级目录的展开目录；
多个所述任务文件在所述文件目录中处于所述一级目录，多个所述任务文件中任一所述任务文件包括的子文件在所述文件目录中处于所述二级目录。
在一些实施例中，所述图像数据文件的子文件包括所述测区的多张图像；
多张所述图像所在的所述二级目录是按照预设的全景照片的目录结构设置的。
在一些实施例中，所述状态数据文件包括以下一种或多种数据文件：GNSS定位数据，IMU数据，云台参数数据，传感器相对于机身的位姿数据，MRK记录数据，位姿矫正数据，传感器的内参数据。
在一些实施例中，所述任务文件还包括：
采集的点云在用户端显示时的实时展示模型数据。
本申请的实施例中还提供一种数据处理设备，该数据处理设备包括上述实施例中的数据处理装置300。数据处理设备通过获取可移动平台对测区执行采样任务的任务信息，根据所获取到的任务信息确定可移动平台的状态数据文件、可移动平台搭载的图像传感器对测区采样得到的图像数据文件、可移动平台搭载的点云传感器对测区采样得到的点云数据文件等多个任务文件中每一任务文件的名称，然后根据多个任务文件的名称，生成对应采样任务的文件目录，并将多个任务文件按照所生成的文件目录关联存储，具体操作可参考本申请实施例提供的数据处理方法的步骤，在此不再赘述。
本申请的实施例中还提供一种计算机可读存储介质，所述计算机可读存储介质存储有计算机程序，所述计算机程序中包括程序指令，处理器执行所述程序指令，实现本申请实施例提供的数据处理方法的步骤。
其中，所述计算机可读存储介质可以是前述实施例所述的数据处理装置或数据处理设备的内部存储单元，例如所述数据处理装置或数据处理设备的硬盘或内存。所述计算机可读存储介质也可以是所述数据处理装置或数据处理设备的外部存储设备，例如所述数据处理装置或数据处理设备上配备的插接式硬盘，智能存储卡(Smart Media Card，SMC)，安全数字(Secure Digital，SD)卡，闪存卡(Flash Card)等。
根据本发明实施方式，提出了数据处理方法、数据处理装置、数据处理设备及计算机可读存储介质。通过获取可移动平台对测区执行采样任务的任务信息，根据所获取到的任务信息确定可移动平台的状态数据文件、可移动平台搭载的图像传感器对测区采样得到的图像数据文件、可移动平台搭载的点云传感器对测区采样得到的点云数据文件等多个任务文件中每一任务文件的名称，然后根据多个任务文件的名称，生成对应采样任务的文件目录，并将多个任务文件按照所生成的文件目录关联存储。从而便于多个任务文件中不同类型数据的调用和查看。并且，在同一文件目录下，通过多种不同类型数据相互辅助实现不同的数据展示效果。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (40)

  1. 一种数据处理方法，其特征在于，包括：
    获取可移动平台对测区执行采样任务的任务信息；
    根据所述任务信息确定多个任务文件中每一所述任务文件的名称，多个所述任务文件包括：所述可移动平台的状态数据文件，所述可移动平台搭载的图像传感器对所述测区采样得到的图像数据文件，所述可移动平台搭载的点云传感器对所述测区采样得到的点云数据文件；
    根据多个所述任务文件的所述名称，生成对应所述采样任务的文件目录；
    将多个所述任务文件按照所述文件目录关联存储。
  2. 根据权利要求1所述的方法，其特征在于，所述任务信息包括以下信息的一种或多种：关联执行所述采样任务的设备的设备信息，所述执行所述采样任务的时间信息，关联所述测区的描述信息。
  3. 根据权利要求2所述的方法，其特征在于，所述测区的描述信息是基于用户输入，和/或，基于对所述测区识别到的测区特征信息获取的。
  4. 根据权利要求1-3任一项所述的方法，其特征在于，所述根据所述任务信息确定多个任务文件中每一所述任务文件的名称，包括：
    根据所述任务信息和任务文件的数据类型信息，确定多个任务文件中每一所述任务文件的名称。
  5. 根据权利要求1所述的方法，其特征在于，所述获取可移动平台对测区执行采样任务的任务信息，包括：
    响应于用户用于触发新的采样任务的操作，确定与所述新的采样任务关联的历史采样任务的任务信息；
    所述根据所述任务信息确定多个任务文件中每一所述任务文件的名称，包括：
    基于所述历史采样任务的任务信息，确定对应所述新的采样任务的多个任务文件中每一所述任务文件的名称。
  6. 根据权利要求5所述的方法，其特征在于，所述方法包括：
    若所述新的采样任务为对所述历史采样任务对应的测区进行采样，则关联所述新的采样任务和所述历史采样任务。
  7. 根据权利要求5所述的方法，其特征在于，所述新的采样任务包括对关联的所述历史采样任务的断点续飞任务、点云补录任务、照片/视频补拍任务。
  8. 根据权利要求1所述的方法，其特征在于，所述将多个所述任务文件按照所述文件目录关联存储，包括：
    按照所述文件目录将多个所述任务文件关联存储至同一文件夹下。
  9. 根据权利要求8所述的方法，其特征在于，多个所述任务文件在所述文件目录中处于同一目录级。
  10. 根据权利要求1所述的方法，其特征在于，所述方法还包括：
    将执行所述采样任务之前第一预设时长内的第一预设类型的缓存数据，和/或执行所述采样任务之后第二预设时长内的第二预设类型的缓存数据，按照与对应所述采样任务的所述任务文件关联存储。
  11. 根据权利要求10所述的方法，其特征在于，所述第一预设类型的缓存数据为所述采样任务执行前所述第一预设时长内所述可移动平台的状态数据。
  12. 根据权利要求1所述的方法，其特征在于，所述生成对应所述采样任务的文件目录，包括：
    当检测到预设触发事件时，生成所述文件目录。
  13. 根据权利要求12所述的方法，其特征在于，所述预设触发事件包括：
    检测到所述可移动平台上电，或者，检测到生成的任务触发指令。
  14. 根据权利要求13所述的方法，其特征在于，所述生成所述文件目录，包括：
    当检测到生成的点云任务触发指令或者拍摄任务触发指令，生成所述文件目录。
  15. 根据权利要求1所述的方法，其特征在于，所述生成所述多个任务对应的文件目录，包括：
    按照统一的默认设置方式，生成所述文件目录；或者
    按照用户自定义设置方式，生成所述文件目录。
  16. 根据权利要求1所述的方法，其特征在于，所述文件目录包括一级目 录和二级目录；所述二级目录为所述一级目录的展开目录；
    多个所述任务文件在所述文件目录中处于所述一级目录，多个所述任务文件中任一所述任务文件包括的子文件在所述文件目录中处于所述二级目录。
  17. 根据权利要求16所述的方法，其特征在于，所述图像数据文件的子文件包括所述测区的多张图像；
    多张所述图像所在的所述二级目录是按照预设的全景照片的目录结构设置的。
  18. 根据权利要求1所述的方法，其特征在于，所述状态数据文件包括以下一种或多种数据文件：GNSS定位数据，IMU数据，云台参数数据，传感器相对于机身的位姿数据，MRK记录数据，位姿矫正数据，传感器的内参数据。
  19. 根据权利要求1所述的方法，其特征在于，所述任务文件还包括：
    采集的点云在用户端显示时的实时展示模型数据。
  20. 一种数据处理装置，其特征在于，所述数据处理装置包括存储器和处理器；
    所述存储器用于存储计算机程序；
    所述处理器，用于执行所述计算机程序并在执行所述计算机程序时，实现如下步骤：
    获取可移动平台对测区执行采样任务的任务信息；
    根据所述任务信息确定多个任务文件中每一所述任务文件的名称，多个所述任务文件包括：所述可移动平台的状态数据文件，所述可移动平台搭载的图像传感器对所述测区采样得到的图像数据文件，所述可移动平台搭载的点云传感器对所述测区采样得到的点云数据文件；
    根据多个所述任务文件的所述名称，生成对应所述采样任务的文件目录；
    将多个所述任务文件按照所述文件目录关联存储。
  21. 根据权利要求20所述的装置，其特征在于，所述任务信息包括以下信息的一种或多种：关联执行所述采样任务的设备的设备信息，所述执行所述采样任务的时间信息，关联所述测区的描述信息。
  22. 根据权利要求21所述的装置，其特征在于，所述测区的描述信息是基于用户输入，和/或，基于对所述测区识别到的测区特征信息获取的。
  23. 根据权利要求20-22任一项所述的装置，其特征在于，所述处理器在实现所述根据所述任务信息确定多个任务文件中每一所述任务文件的名称时，用于实现：
    根据所述任务信息和任务文件的数据类型信息，确定多个任务文件中每一所述任务文件的名称。
  24. 根据权利要求20所述的装置，其特征在于，所述处理器在实现所述获取可移动平台对测区执行采样任务的任务信息时，用于实现：
    响应于用户用于触发新的采样任务的操作，确定与所述新的采样任务关联的历史采样任务的任务信息；
    所述处理器在实现所述根据所述任务信息确定多个任务文件中每一所述任务文件的名称时，用于实现：
    基于所述历史采样任务的任务信息，确定对应所述新的采样任务的多个任务文件中每一所述任务文件的名称。
  25. 根据权利要求24所述的装置，其特征在于，所述处理器还用于实现：
    若所述新的采样任务为对所述历史采样任务对应的测区进行采样，则关联所述新的采样任务和所述历史采样任务。
  26. 根据权利要求24所述的装置，其特征在于，所述新的采样任务包括对关联的所述历史采样任务的断点续飞任务、点云补录任务、照片/视频补拍任务。
  27. 根据权利要求20所述的装置，其特征在于，所述处理器在实现所述将多个所述任务文件按照所述文件目录关联存储时，用于实现：
    按照所述文件目录将多个所述任务文件关联存储至同一文件夹下。
  28. 根据权利要求27所述的装置，其特征在于，多个所述任务文件在所述文件目录中处于同一目录级。
  29. 根据权利要求20所述的装置，其特征在于，所述处理器还用于实现：
    将执行所述采样任务之前第一预设时长内的第一预设类型的缓存数据，和/或执行所述采样任务之后第二预设时长内的第二预设类型的缓存数据，按照与对应所述采样任务的所述任务文件关联存储。
  30. 根据权利要求29所述的装置，其特征在于，所述第一预设类型的缓存数据为所述采样任务执行前所述第一预设时长内所述可移动平台的状态数据。
  31. 根据权利要求20所述的装置，其特征在于，所述处理器在实现所述生成对应所述采样任务的文件目录时，用于实现：
    当检测到预设触发事件时，生成所述文件目录。
  32. 根据权利要求31所述的装置，其特征在于，所述预设触发事件包括：
    检测到所述可移动平台上电，或者，检测到生成的任务触发指令。
  33. 根据权利要求32所述的装置，其特征在于，所述处理器在实现所述生成所述文件目录时，用于实现：
    当检测到生成的点云任务触发指令或者拍摄任务触发指令，生成所述文件目录。
  34. 根据权利要求20所述的装置，其特征在于，所述处理器在实现所述生成所述多个任务对应的文件目录时，用于实现：
    按照统一的默认设置方式，生成所述文件目录；或者
    按照用户自定义设置方式，生成所述文件目录。
  35. 根据权利要求20所述的装置，其特征在于，所述文件目录包括一级目录和二级目录；所述二级目录为所述一级目录的展开目录；
    多个所述任务文件在所述文件目录中处于所述一级目录，多个所述任务文件中任一所述任务文件包括的子文件在所述文件目录中处于所述二级目录。
  36. 根据权利要求35所述的装置，其特征在于，所述图像数据文件的子文件包括所述测区的多张图像；
    多张所述图像所在的所述二级目录是按照预设的全景照片的目录结构设置的。
  37. 根据权利要求20所述的装置，其特征在于，所述状态数据文件包括以下一种或多种数据文件：GNSS定位数据，IMU数据，云台参数数据，传感器相对于机身的位姿数据，MRK记录数据，位姿矫正数据，传感器的内参数据。
  38. 根据权利要求20所述的装置，其特征在于，所述任务文件还包括：
    采集的点云在用户端显示时的实时展示模型数据。
  39. 一种数据处理设备，其特征在于，所述数据处理设备包括如权利要求20至38中任一项所述的数据处理装置。
  40. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存 储有计算机程序，所述计算机程序被处理器执行时使所述处理器实现如权利要求1至19中任一项所述的数据处理方法。
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