WO2022061880A1 - Movable platform and online data processing method and apparatus therefor, and storage medium - Google Patents

Abstract

A movable platform and an online data processing method and apparatus therefor, and a storage medium. The movable platform comprises multiple sensors. The method comprises: obtaining, online and in real time, first data generated by sensors, so as to determine an attribute of the first data (S110); performing, on the basis of the attribute of the first data, real-time compression on the first data by using a corresponding compression parameter, wherein the first data having different attributes corresponds to different compression parameters (S120); and storing the compressed first data (S130). Real-time compression is performed when data is acquired online, such that the storage volume of online data is greatly reduced, the storage space is saved, and the data transmission rate and the data processing efficiency are improved.

Description

Removable platform and online data processing method, device and storage medium technical field

The present invention relates to the technical field of mobile platforms, in particular to the processing of online data of the mobile platforms.

Background technique

Existing intelligent machines (such as robots) are equipped with many different types of sensors. These different types of sensors collect corresponding data when the intelligent machine is working, especially the image sensor collects image data, which makes the amount of collected and stored data more and more. come bigger. However, the current relatively low-cost storage media, such as solid-state drives with SATA ports, cannot actually use the speed bandwidth to collect large amounts of data, and the transmission efficiency is low when the large amounts of collected data are transferred to other storage devices. It is time-consuming and labor-intensive, and takes up a lot of storage space at the same time.

SUMMARY OF THE INVENTION

Embodiments of the present invention provide a movable platform and a method, device, and storage medium for processing online data thereof, so as to solve at least one of the above problems.

According to a first aspect of the embodiments of the present invention, a method for processing online data of a mobile platform is provided, the mobile platform includes a plurality of sensors, and the method includes:

Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

The compressed first data is stored.

According to a second aspect of the embodiments of the present invention, a method for processing online data of a mobile platform is provided, wherein the method includes:

The online data of the movable platform is obtained offline, wherein the online data of the movable platform includes compressed first data; wherein, the compressed first data is obtained by compressing the first data through corresponding compression parameters, and different attributes The first data corresponding to different compression parameters;

Decompressing the compressed first data to obtain decompressed data;

Offline processing is performed based on the decompressed data.

According to a third aspect of the embodiments of the present invention, a method for processing online data of a mobile platform is provided, the mobile platform includes a plurality of sensors, and the method includes:

Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

storing the compressed first data;

obtaining the compressed first data offline;

Decompressing the compressed first data to obtain decompressed data;

Offline processing is performed based on the decompressed data.

According to a fourth aspect of the embodiments of the present invention, there is provided an apparatus for processing online data of a mobile platform, the apparatus comprising:

memory;

processor;

one or more programs stored in the memory and configured to be executed by the processor, the processor performing the following steps when executing the one or more programs:

Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

The compressed first data is stored.

According to a fifth aspect of the embodiments of the present invention, an apparatus for processing online data of a mobile platform is provided, and the apparatus includes:

memory;

processor;

one or more programs stored in the memory and configured to be executed by the processor, the processor performing the following steps when executing the one or more programs:

The online data of the movable platform is obtained offline, wherein the online data of the movable platform includes compressed first data; wherein, the compressed first data is obtained by compressing the first data through corresponding compression parameters, and different attributes The first data corresponding to different compression parameters;

Decompressing the compressed first data to obtain decompressed data;

Offline processing is performed based on the decompressed data.

According to a sixth aspect of the embodiments of the present invention, there is provided an apparatus for processing online data of a mobile platform, the apparatus comprising:

memory;

processor;

one or more programs stored in the memory and configured to be executed by the processor, the processor performing the following steps when executing the one or more programs:

Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

storing the compressed first data;

Obtaining the compressed first data offline; decompressing the compressed first data to obtain decompressed data;

Offline processing is performed based on the decompressed data.

According to a seventh aspect of the embodiments of the present invention, there is provided a computer-readable storage medium, comprising: a program that can be executed by a processor to implement the first to third aspects of the embodiments of the present invention method.

According to an eighth aspect of an embodiment of the present invention, there is provided a movable platform, comprising: the apparatus according to the fourth aspect to the sixth aspect of the embodiment of the present invention.

The movable platform and the online data processing method, device, and storage medium according to the embodiments of the present invention greatly reduce the storage amount of online data, save storage space, and improve the efficiency of data transmission by performing real-time compression when collecting data online. speed and efficiency of data processing.

Description of drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the following briefly introduces the accompanying drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained according to these drawings without creative efforts.

1 is a schematic flowchart of a method for processing online data of a mobile platform according to an embodiment of the present invention;

2 is an example of a method for processing online data of a mobile platform according to an embodiment of the present invention;

3 is a schematic flowchart of a method for processing online data of a mobile platform according to an embodiment of the present invention;

4 is an example of a method for processing online data of a mobile platform according to an embodiment of the present invention;

5 is a schematic flowchart of a method for processing online data of a mobile platform according to an embodiment of the present invention;

FIG. 6 is a schematic block diagram of an apparatus for processing online data of a mobile platform according to an embodiment of the present invention.

detailed description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Due to the limitation of the storage speed and storage space of the existing storage medium, the efficiency of data processing such as data collection and storage is greatly limited. With the continuous increase of the amount of data, the speed bandwidth actually used by the existing storage media cannot meet the data collection of large amounts of data. The storage capacity of the intelligent machine itself is limited, and sometimes it cannot realize the data collection of a large amount of data, or when the collected data is transferred to other storage devices, it is time-consuming and laborious, and it also occupies a huge storage space.

Wherein, the intelligent machine can be a movable platform, including an air vehicle (such as an unmanned aerial vehicle), a ground vehicle (such as a gimbal vehicle, an autonomous vehicle), or other suitable mobile devices (such as a handheld gimbal, a driving recorder) instrument). During the use of the above-mentioned intelligent machine, when the aerial vehicle moves in the air, it may be necessary to collect image data in at least one direction, distance data from other objects, moving position data, sound data, machine internal temperature data, machine One or more of ambient temperature data, machine operating parameters, etc.; when ground vehicles move on the ground, such as PTZ vehicles and autonomous vehicles, it may be necessary to collect image data and/or sound data in at least one direction; Among them, the self-driving vehicle may also need to collect distance data between itself and other objects, movement position data, etc.; while other suitable mobile devices may also need to collect image data and/or image data in at least one direction when working. or sound data, etc. Therefore, the amount of data that needs to be collected by smart machines continues to increase, especially the sharp increase in the amount of data such as image data and sound data, which brings enormous pressure to the data collection and storage of smart machines. Data collection and/storage of large amounts of data cannot be achieved.

Moreover, after the data collected by the smart machine, users often want to play or process it on other electronic devices (for example, personal computers, mobile phones, display devices and other suitable devices), which in turn needs to convert such a large amount of data From smart machines to storage devices of other electronic devices, the traditional data collection and storage methods of smart machines also limit the efficiency of data transmission due to the huge amount of data during data transmission. Or the process of processing data is inefficient and wastes huge time and energy. Based on the above considerations, according to an embodiment of the present invention, a method for processing online data of a mobile platform is provided. Referring to FIG. 1 , FIG. 1 shows a schematic flow of the method for processing online data of a mobile platform according to an embodiment of the present invention. picture. As shown in FIG. 1, the movable platform includes a plurality of sensors, and the method 100 includes:

Step S110, acquiring the first data generated by the sensor online in real time to determine the attribute of the first data;

Step S120, based on the attributes of the first data, using corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

Step S130, storing the compressed first data.

Among them, after the data generated by the sensors of the movable platform are obtained online, the first data is compressed in real time with corresponding compression parameters according to the attributes of the data, which not only reduces the space used for storing data, but also improves the rate of data transmission and data. processing efficiency. Suitable for any data processing occasions such as online data acquisition and/or storage.

Optionally, the plurality of sensors may include a variety of different types of sensors.

Further, the various types of sensors include: image sensors, sound sensors, inertial measurement sensors (Inertial Measurement Unit, IMU), positioning sensors (Global Positioning System, GPS), temperature sensors, or a variety of distance sensors. Wherein, different types of sensors generate different first data; different first data have different properties.

In some embodiments, an image sensor may acquire image information around the movable platform to generate image data. The image data may include one or more consecutive or consecutive image frames. The acquisition of the image information may be acquired by the user controlling the image sensor, for example, acquisition according to an image acquisition program preset by the user, or acquisition according to the current trigger operation of the user.

In some embodiments, sound sensors may collect sound information around the movable platform to generate sound data. In some embodiments, the inertial measurement sensor may collect at least one of acceleration data, tilt data, shock data, vibration data, rotation data, and multi-degree-of-freedom motion data of the movable platform.

In some embodiments, a positioning sensor may collect position information of the movable platform to generate position data.

In some embodiments, a temperature sensor may collect temperature information and/or ambient temperature information inside the movable platform to generate interior temperature data and/or ambient temperature data.

In some embodiments, a distance sensor may collect distance information from the movable platform to the target to generate target distance data.

According to an embodiment of the present invention, in step S110, the attribute of the first data may be determined according to at least one of the following: data type, data importance, data volume, or data source.

Wherein, different first data have their own different characteristics. According to the characteristics of different first data, the attribute of the first data can be determined, and it is convenient to determine the corresponding compression parameter based on the attribute, thereby improving data collection, storage, and transmission. , processing efficiency, etc.

Optionally, attributes may include multiple pre-sorted different categories.

In some embodiments, different categories of the same attribute may correspond to different compression parameters, or at least some of the categories may have the same compression parameters at least partially.

In some embodiments, different categories of different attributes may correspond to different compression parameters respectively, and the corresponding compression parameters may be at least partially the same.

Wherein, the first data may include a variety of different attributes, therefore, based on the categories of different attributes of the first data, the first data may correspond to a variety of different compression parameters.

Optionally, the compression parameters include at least one of the following: compression ratio, compression speed, or compression quality. The compression rate may refer to the ratio of the size of the compressed data to the size of the data before compression; the compression speed may refer to the time used to compress the data of a unit size; and the compression quality may include lossy compression or lossless compression.

In some embodiments, categories of data types may include: image data and non-image data. Further, the category of non-image data may further include: at least one of sound data, temperature data, target distance data, and location data.

Correspondingly, in some embodiments, the first data of different attributes corresponds to different compression parameters, which may include:

When the first data is image data, it corresponds to at least one of the following compression parameters: a first compression rate and lossy compression;

When the first data is non-image data, no compression is performed, or corresponds to at least one of the following compression parameters: a second compression rate, lossless compression; wherein, the first compression rate is smaller than the second compression rate.

Among them, the data volume of image data is usually much larger than that of non-image data, but the data quality requirements are relatively low, so a smaller first compression rate and/or lossy compression can be used to compress the image data in real time, Thus, the storage space of the entire online data is reduced to store more data; the amount of non-image data is generally small, and a larger second compression rate and/or lossless compression can be used for real-time compression, or even no compression.

It should be understood that data types can also be divided into more categories, and each category can correspond to at least one of the following: different compression rates, different compression speeds, or different compression qualities; in other embodiments, the data types Different categories of , may also correspond to at least one compression parameter of the same compression ratio, compression speed, or compression quality, which is not limited herein.

In some embodiments, the categories of data importance may include: important data and unimportant data. In some embodiments, the category of the data importance level can also be set with multiple different importance levels; for example, the first importance level, the second importance level, ..., the nth importance level, where n is a positive integer, the data importance level can be From the first importance level to the nth importance level, it increases or decreases sequentially, which is not limited here.

Correspondingly, in some embodiments, the first data of different attributes corresponds to different compression parameters, which may include:

When the first data is important data, no compression is performed, or corresponds to at least one of the following compression parameters: a third compression rate, lossless compression;

When the first data is unimportant data, it corresponds to at least one of the following compression parameters: a fourth compression ratio and lossy compression; wherein, the fourth compression ratio is smaller than the third compression ratio.

Among them, for the more important data, the precision of the data is required to be higher, and more original data information needs to be retained, so a larger compression rate and/or lossless compression can be used to compress the important data in real time, or even not The comprehensiveness of data information is guaranteed; for unimportant data, a smaller compression rate and/or lossy compression can be used to minimize the storage space occupied by unimportant data.

It should be understood that, in the above-mentioned embodiment, when the categories of data importance levels include multiple different importance levels, the different importance levels may respectively correspond to at least one of the following: different compression rates, different compression speeds, or different compression qualities . For example, the ith importance level may correspond to at least one of the following compression parameters: the ith _1st compression rate, the ith _2nd compression rate, and the ith _3rd compression quality; if i is less than n, the ith _3rd compression quality includes lossy compression or lossless compression; The i-1 th importance level may correspond to at least one of the following compression parameters: i-1 _1st compression rate, i-1 _2nd compression rate, i-1 _3rd compression quality; i-1 _3rd compression quality includes lossy compression or lossless compression. Among them, when the importance of the i-th importance level is greater than the i-1-th importance level, the i- _1th compression rate is greater than the i- ₁ -th compression rate; when the i-th importance level is less important than the i-1th importance level, The i ₁ th compression ratio is smaller than the i-1 ₁ th compression ratio.

In some embodiments, the categories of data sources may include: a first sensor and a second sensor. Further, the category of the data source may also include other sensors in the mobile platform, which is not limited here.

Correspondingly, in some embodiments, the first data of different attributes corresponds to different compression parameters, which may include:

When the data source of the first data is the first sensor, no compression is performed, or corresponding to at least one of the following compression parameters: fifth compression ratio, lossless compression;

When the data source of the first data is the second sensor, it corresponds to at least one of the following compression parameters: a sixth compression ratio and lossy compression; wherein the sixth compression ratio is smaller than the fifth compression ratio.

It should be understood that, in the foregoing embodiment, when the categories of data sources include multiple different sensors, they may correspond to at least one of the following: different compression rates, different compression speeds, or different compression qualities. In other embodiments, different categories of data sources may also correspond to at least one compression parameter of the same compression ratio, compression speed, or compression quality, which is not limited herein.

In some embodiments, the categories of the size of the data volume may include: greater than or equal to a data volume threshold and less than a data volume threshold.

Correspondingly, in some embodiments, the first data of different attributes corresponds to different compression parameters, which may include:

When the data volume of the first data is less than the data volume threshold, no compression is performed, or corresponding to at least one of the following compression parameters: seventh compression ratio, lossless compression;

When the data volume of the first data is greater than or equal to the data volume threshold, it corresponds to at least one of the following compression parameters: the eighth compression ratio, lossy compression; the eighth compression ratio is smaller than the seventh compression ratio.

Among them, the first data with a large amount of data may occupy a large storage space, and a smaller compression rate can be used to reduce the storage space occupied by the first data, while the storage space occupied by the first data with a small amount of data Not much, larger compression ratios and/or lossless compression can be used.

In some embodiments, multiple different data volume thresholds may also be set for the category of the size of the data volume, so as to divide multiple data volume levels; for example, the first data volume threshold, ..., the mth data volume threshold, where m is positive integer.

Wherein, when the first data volume threshold to the mth data volume threshold increase sequentially, the larger the data volume level is, the larger the data volume of the first data is, and the categories of the data volume size may include: the first data volume level, which is smaller than the first data volume level a data volume threshold; a second data volume level, greater than or equal to the first data volume threshold and less than the second data volume threshold; ...; the mth data volume level, greater than or equal to the m-1th data volume threshold and less than the mth data volume threshold Data volume threshold; the m+1th data volume level, greater than or equal to the mth data volume threshold.

When the first data volume threshold to the mth data volume threshold decrease in sequence, the larger the data volume level, the smaller the data volume of the first data. volume threshold; the second data volume level, less than or equal to the first data volume threshold and greater than the second data volume threshold; ...; the mth data volume level, less than or equal to the m-1th data volume threshold and greater than the mth data volume Threshold; the m+1th data volume level, less than or equal to the mth data volume threshold.

It should be understood that, in the above embodiment, when the category of the size of the data volume includes multiple data volume levels, the different data volume levels may respectively correspond to at least one of the following: different compression rates, different compression speeds, or different compression rates quality. For example, the pth data volume level may correspond to at least one of the following compression parameters: the _p1th compression rate, the _p2th compression rate, and the _p3th compression quality; if p is less than m, the _p3th compression quality includes lossy compression or lossless compression ; The p-1 data volume level may correspond to at least one of the following compression parameters: the p-1 _1st compression rate, the p-1 _2nd compression rate, the p-1 _3rd compression quality; the p-1 _3rd compression quality includes: lossy or lossless compression. Wherein, when the first data volume threshold to the mth data volume threshold increase in sequence, a larger data volume level indicates a larger data volume of the first data, and the p1th compression rate is smaller than the p _{− 11th} compression rate. When the first data volume threshold to the mth data volume threshold decrease in sequence, the larger the data volume level is, the smaller the data volume of the first data is, and the p1th compression rate is greater than the p _{- 11th} compression rate.

According to an embodiment of the present invention, in step S120, based on the attributes of the first data, the first data is compressed in real time by using corresponding compression parameters, including:

The first data is compressed in real time using different compression parameters based on different categories of attributes.

Among them, in practical applications, users have different degrees of attention to data in different scenarios, and the compression parameters are determined according to different attributes of the first data, which can meet the user's data requirements from different angles. For example, when a user uses a mobile platform to take images or record videos, he wants to collect image data for as long as possible. At this time, according to the data type, a compression parameter with a smaller compression ratio can be determined under the premise of satisfying the image quality requirements. In order to save the storage space as much as possible, the image data can be collected for a longer period of time; when the user pays less attention to some data of the mobile platform, such as when the user is using the hand-held PTZ or driving recorder, the user may not pay much attention to the hand-held camera. The location information, temperature information and other data in the PTZ and driving recorder, or even do not need these data at all, you can use these data as unimportant data, use compression parameters with a smaller compression rate, and compress as much as possible, so that you can More or more accurate storage of relatively important data (such as image data, sound data); when the user may pay less attention to the data content of the mobile platform itself, and hope to collect as many and comprehensive data of each sensor as possible. data, the data with a large amount of data can be compressed using the compression parameters with a small compression rate to release the storage space as much as possible, so that the first data generated by each sensor can be stored more and comprehensively; at that time, the user may The performance of some devices of the movable platform is more concerned, such as the accuracy and sensitivity of the positioning sensors and inertial measurement sensors of unmanned aerial vehicles, and the accuracy and sensitivity of distance sensors and positioning sensors of unmanned vehicles, which require accurate data from these sensors. Therefore, it can be determined according to the data source that these sensors can use a larger compression rate or lossless compression, or even no compression, to ensure the integrity and accuracy of the first data generated by these sensors, and it is convenient for users to monitor the performance of these sensors. .

It should be understood that the different compression parameters used by the above-mentioned various attributes are only examples and are not intended to limit the compression parameters of the attributes. In different cases, the compression parameters can be set according to user needs, which is not limited here. .

In some embodiments, the attribute includes a data type, and the categories of the data type include: image data and non-image data, and based on the attribute of the first data, the first data is compressed in real time using corresponding compression parameters, including:

When the first data is image data, use the first compression rate and/or lossy compression to perform real-time compression;

When the first data is non-image data, real-time compression is performed using a second compression rate and/or lossless compression, or no compression is performed; wherein the first compression rate is smaller than the second compression rate.

In some embodiments, the first compression rate is used to make the compression quality of the image data meet a preset standard and also meet a preset compression time. In one embodiment, the image data may be compressed at a minimum compression rate that enables the compression quality of the image data to reach a preset standard, so as to compress the image data as much as possible to save storage space.

In some embodiments, the movable platform can be an unmanned aerial vehicle, a gimbal vehicle, a handheld gimbal, or a driving recorder. The user controls the operation of the movable platform, and the movable platform can pass an image sensor (such as a camera) during the movement process. Taking pictures or recording videos to generate image data, according to multiple pre-classified different categories of each attribute, it can be determined that the image data can belong to: image data category in the data type attribute, non-important data category in the data importance attribute, and data volume The category of the size attribute is greater than or equal to the data volume threshold, or the camera category in the data source attribute; different categories of the above attributes correspond to different compression parameters, and the mobile platform can use the corresponding compression parameters to perform real-time processing on the first data. Compression, for example, compressing the image data in real time with a first compression rate and/or a lossy compression manner to obtain compressed image data, and storing the compressed image data locally on the mobile platform. In this way, compared with the traditional method of directly storing the collected image data, according to the method of the embodiment of the present invention, the collected image data is compressed in real time, the storage space of the collected data is reduced, and more image data can be collected , take more photos or record more videos. After the mobile platform finishes running, the user may wish to view the captured photos or videos on the computer device, and the compressed image data stored in the mobile platform can be moved to the computer device, because the compressed image data is moved. Image data, compared to moving uncompressed image data in the traditional method, has a faster transmission rate, which greatly shortens the user's waiting time.

In some embodiments, the first data may include image data and/or sound data, and the method may further include:

Designate the terminal to acquire image data and/or sound data online in real time to determine the attributes of the image data and/or sound data;

The designated terminal uses different compression parameters to compress the image data and/or the sound data based on the attributes of the image data and/or the sound data, and stores the compressed image data and/or the sound data.

Optionally, the designated terminal may be a ground control terminal, for example, a ground controller, a control base station, etc.; it may also be a designated server. Among them, the ground control terminal is used for communication connection with the movable platform, and the user can send control instructions to the movable platform through the ground control terminal.

In some embodiments, the manner in which the movable platform can communicate with the ground control terminal may be line-of-sight communication or non-line-of-sight communication. The line-of-sight communication method may be WIFI, Bluetooth, and the like. The non-line-of-sight communication method can be 2G, 3G, 4G, 5G and other communication networks.

Specifically, after the sensor in the movable platform generates the first data, the first data can be sent to the designated terminal through line-of-sight communication or non-line-of-sight communication, and the designated terminal receives the first data online in real time, and determines The attribute of the first data; if the first data includes image data and/or sound data, then the designated terminal obtains the image data and/or sound data in real time online, and it can be determined that the image data and/or sound data can belong to the data type attribute image data category and/or sound data category; the image data category and/or sound data category may correspond to different compression parameters, or may correspond to the same compression parameters, and the corresponding compression parameters perform real-time on the image data and/or sound data Compression; and then store the compressed image data and/or sound data in the designated terminal. In this way, not only the storage space occupied by the online data of the mobile platform is saved, but also the time for moving the online data from the mobile platform to the designated terminal can be saved, which further improves the efficiency of data processing.

It should be understood that image data and/or sound data may also belong to categories in attributes such as data importance, data volume, or data source. Similarly, the designated terminal may also compress image data based on compression parameters corresponding to other attribute categories. and/or sound data is compressed, which is not limited here.

In some embodiments, the attribute includes data importance, and the categories of the importance include: important data and non-important data. Based on the attribute of the first data, the first data is compressed in real time using corresponding compression parameters, including:

When the first data is important data, use the third compression rate and/or lossless compression to perform real-time compression, or not compress;

When the first data is unimportant data, real-time compression is performed using a fourth compression rate and/or lossy compression, wherein the fourth compression rate is smaller than the third compression rate.

In some embodiments, the movable platform may be a handheld gimbal. When the user can hold the handheld gimbal to work, he may wish to have strong followability and stability of the handheld gimbal, and the followability and stability can be achieved through inertial If the measurement data is reflected, the inertial measurement data is important data for the user, and a large compression rate and/or lossless compression, or even no compression can be used to ensure the comprehensiveness and accuracy of the inertial measurement data and facilitate accurate judgment by the user. The performance of the handheld gimbal; for other unimportant data, a smaller compression ratio and/or lossy compression can be used to provide more storage space for important data. Compared with the traditional method of directly storing all sensor data, according to the method of the embodiment of the present invention, the storage space occupied by non-important data can be reduced in a targeted manner, more important data can be collected, and the data efficiency can be greatly improved. The efficiency of data processing such as collection and storage also meets the user's personalized needs for data and improves the user experience. In some embodiments, the attribute includes a data source, the category of the data source includes: a first sensor and a second sensor, and based on the attribute of the first data, the first data is compressed in real time using corresponding compression parameters, including:

When the data source of the first data is the first sensor, use the fifth compression rate and/or lossless compression to perform real-time compression, or not to compress;

When the data source of the first data is the second sensor, a sixth compression rate and/or lossy compression are used to perform real-time compression, wherein the sixth compression rate is smaller than the fifth compression rate.

In the traditional debugging process of the mobile platform, it is usually necessary to collect the data of the mobile platform online, and then move the collected online data to the computer equipment for processing. For example, the existing software platform Ros (Robot Operating System) Rosbag (Robot Operating System Bag) tool can realize the collection of online data, and store the collected data in the storage medium in the form of standard messages according to time stamps. In view of the increasing number of specific camera sensors on the mobile platform, the generated The data volume of image data is even more huge, which makes the existing online data acquisition tools unable to collect and store large data volumes.

Based on the above considerations, in some embodiments, referring to FIG. 2 , FIG. 2 shows an example of a method for processing online data of a mobile platform according to an embodiment of the present invention. As shown in Figure 2, the camera sensor in the mobile platform collects image data, and the data source of the image data is the camera sensor; other sensors such as inertial measurement sensors collect motion data, positioning sensors collect position data, and the data source of the motion data is Inertial measurement sensor, the data source of the position data is the positioning sensor; the movable platform can determine that the image data belongs to the camera sensor category of the data source attribute, and compress the image data in real time with the corresponding compression parameters, and the image data is compressed after compression. After image data, the data volume can be reduced to several times (such as 10 times), while the data collected by other sensors, such as motion data and position data, is relatively small and does not need to be compressed; the mobile platform will compress the data. The resulting image data and uncompressed data collected by other sensors are stored in the storage medium of the removable platform. Then, it can not only solve the problem that the mobile platform cannot collect data due to the huge amount of data, but also the amount of data stored after compression is smaller, which saves the storage space and the time for users to move the data, and greatly improves the data processing efficiency. effectiveness.

In some embodiments, the attribute includes the size of the data amount, and the category of the size of the data amount includes: greater than or equal to the data amount threshold and less than the data amount threshold, and based on the attribute of the first data, the first data is processed by using corresponding compression parameters. Real-time compression, including:

When the data volume of the first data is less than the data volume threshold, use the seventh compression ratio and/or lossless compression to perform real-time compression, or not compress;

When the data volume of the first data is greater than or equal to the data volume threshold, real-time compression is performed using an eighth compression ratio and/or lossy compression, wherein the eighth compression ratio is smaller than the seventh compression ratio.

In some embodiments, the movable platform may be an autonomous vehicle, and the autonomous vehicle may generate various types of image data, distance data to other objects, inertial measurement data, position data, temperature data, etc. However, the safe operation of autonomous vehicles requires comprehensive consideration of multiple types of data. Users want to store multiple types of data comprehensively, and the accuracy requirements for each type of data are relatively low, such as image data. Since the autonomous vehicle collects a large amount of image data in multiple directions, it occupies a large storage space, and the user wants to store more types of sensor data, the image data can meet the image quality requirements. Image data with a data volume threshold is compressed with a smaller compression rate, and other sensor data whose data volume does not exceed the data volume threshold are compressed with a larger compression rate or lossless compression, or even no compression; compared with the traditional method All sensor data are directly stored, and the method according to the embodiment of the present invention can reduce the storage space occupied by data with a large amount of data, enable users to obtain more comprehensive sensor data, and improve the efficiency of data processing such as data collection and storage .

It should be noted that the sensor data corresponding to various attributes and categories according to the embodiments of the present invention are only examples, and are not intended to limit the various attributes and categories of the first data.

According to an embodiment of the present invention, in step S130, storing the compressed first data may include: storing the compressed first data locally on the mobile platform.

According to an embodiment of the present invention, the movable platform includes at least one of: an unmanned aerial vehicle, a car, a remote control car, and a robot.

In practical applications, after the mobile platform obtains the compressed online data at runtime, the user may need to obtain the online data on other devices; and/or perform data processing on the online data on other devices. Then, the compressed online data can be moved (eg, copied) to other devices (eg, computer devices) for data processing.

Therefore, according to an embodiment of the present invention, a method for processing online data of a mobile platform is provided. Referring to FIG. 3 , FIG. 3 shows a schematic flowchart of a method for processing online data of a mobile platform according to an embodiment of the present invention. As shown in FIG. 3, method 300 includes:

Step S310, obtain the online data of the movable platform offline, wherein the online data of the movable platform includes compressed first data; wherein, the compressed first data is obtained by compressing the first data through corresponding compression parameters, and the first data of different attributes is obtained. The data corresponds to different compression parameters;

Step S320, decompress the compressed first data to obtain decompressed data;

Step S330, offline processing is performed based on the decompressed data.

Wherein, the compressed first data is obtained offline, and is decompressed for offline processing. Compared with directly obtaining the uncompressed first data in the traditional method, the data volume of the compressed first data is smaller, which greatly improves the data transmission rate.

Optionally, the offline processing includes: offline simulation, or offline playback.

In some embodiments, the offline simulation includes:

In a simulation environment corresponding to the movable platform, the movable platform is simulated and operated based on at least part of the decompressed data.

Among them, the decompressed data is played according to the time stamp in the simulation environment corresponding to the mobile platform, so as to simulate the actual operation of the mobile platform, so as to realize the function of offline simulation. Users can adjust the parameters of the movable platform in the offline simulation process to continuously improve and perfect the performance of the movable platform.

According to an embodiment of the present invention, in step S330, offline processing is performed based on the decompressed data, including:

Filter the decompressed data based on the filtering strategy to obtain the filtered data;

Offline processing based on filtered data.

Optionally, the decompressed data is screened based on a screening strategy to obtain filtered data, including one of the following:

In the decompressed data, data within a preset time period, interval preset period, preset type, preset data source, or data quality that meets preset requirements is selected as the filtered data.

In the process of offline processing, users sometimes do not use all the collected data. Therefore, after filtering the decompressed data as needed, the required data can be selected for offline processing to reduce the amount of calculation for data processing. , save computing resources and further improve the efficiency of data processing. It should be understood that the filtering of the decompressed data based on the filtering strategy may be performed manually or based on a machine, which is not limited herein.

In some embodiments, filtering the data within a preset time period in the decompressed data as the filtered data may be obtaining data of one or more preset time periods in the decompressed data as the filtered data. data. For example, it takes a certain period of time for the mobile platform to start to run stably. The sensor data during this period may not necessarily be stable data, or it is less useful to the user. Data is removed, and the sensor data after stable operation is screened as the data basis for subsequent processing, thereby further reducing the amount of data processed, saving computing resources, and improving the efficiency of data processing.

In some embodiments, the data in the decompressed data at intervals of a preset period is selected as the filtered data, which may be a certain amount of data or data of a certain period of time obtained at every preset period, or may be obtained at every preset period. Periodically obtain the data at this moment as the filtered data. For example, if the sensor data collected by the mobile platform does not change much with time, based on the sampling principle, one frame or a certain amount of data or data in a certain period of time can be screened at a certain interval to reduce the amount of data processed. , save computing resources and improve the efficiency of data processing.

In some embodiments, filtering data of a preset type in the decompressed data as the filtered data may be obtaining data of one or more data types. For example, when the user pays more attention to some types of data, such as the user may want to watch the image data collected by the gimbal vehicle, the hand-held gimbal, and the unmanned aerial vehicle, the mobile platform compresses at least part of the first data online in real time, and obtains For the compressed first data, the image data and/or sound data in the decompressed first data can be filtered, and the filtered data can be played offline in any suitable display device.

In some embodiments, the preset data sources in the filtered decompressed data may be data obtained from one or more data sources. For example, filtering data derived from inertial measurement sensors, and/or positioning sensors, as filtered data.

In some embodiments, filtering the decompressed data whose data quality meets a preset requirement may include: acquiring data whose image resolution reaches a preset resolution in the image data, as the filtered data. The image resolution may be determined based on a machine learning algorithm. For example, a user may wish to view image data with better image quality collected by a gimbal vehicle, a handheld gimbal, or an unmanned aerial vehicle. , the image data that meets the preset resolution is directly provided to the user, which saves the user's manual screening time and improves the efficiency of data processing.

According to an embodiment of the present invention, the method 300 may further include:

For the remaining data in the decompressed data that do not meet the screening strategy, offline processing is not performed.

In some embodiments, referring to FIG. 4 , FIG. 4 shows an example of a method for processing online data of a mobile platform according to an embodiment of the present invention. As shown in FIG. 4 , the online data stored locally on the mobile platform includes compressed first data, where the compressed first data may include camera data compressed with corresponding compression parameters and other uncompressed sensor data ; The user can obtain the online data of the mobile platform offline based on any suitable electronic device (for example, personal computer, notebook computer, tablet computer, smart phone or other suitable electronic device), and decompress the compressed camera data to obtain the decompressed camera. data; and offline processing of decompressed camera data and other sensor data.

According to an embodiment of the present invention, a method for processing online data of a mobile platform is also provided. Referring to FIG. 5 , FIG. 5 shows a schematic flowchart of a method for processing online data of a mobile platform according to an embodiment of the present invention. As shown in FIG. 5, the movable platform includes a plurality of sensors, and the method 500 includes:

Step S510, obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

Step S520: Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

Step S530, storing the compressed first data;

Step S540, obtain the compressed first data offline;

Step S550, decompress the compressed first data to obtain decompressed data;

Step S560, offline processing is performed based on the decompressed data.

Among them, the sensor collects parameters online to generate the first data during the operation of the movable platform, and the first data can have different attributes and correspond to one category in each attribute; each category in each attribute has Corresponding compression parameters, these compression parameters may be the same or different, and are not limited here; the movable platform may compress the first data in real time according to the compression parameters corresponding to the category of one of the attributes of the first data, and obtain The compressed first data; and the compressed first data is stored locally on the mobile platform. The user can obtain the compressed first data offline on other terminals, such as computer equipment, and decompress the compressed first data to obtain decompressed data; and then perform offline processing on the decompressed data.

It should be understood that the steps in method 500 can be combined or replaced with any steps in method 100 and/or method 300 for the same, equivalent or similar purpose.

According to an embodiment of the present invention, an apparatus for processing online data of a mobile platform is also provided. Referring to FIG. 6, FIG. 6 shows a schematic block diagram of an apparatus for processing online data of a mobile platform according to an embodiment of the present invention. Apparatus 600 includes:

memory 610;

processor 620;

One or more programs, the one or more programs are stored in the memory 610 and are configured to be executed by the processor 620, and the processor 620, when executing the one or more programs, implements the mobile platform online data according to embodiments of the present invention Some or all of the steps or any combination of the steps in the processing method.

The memory 610 may be loaded with various computer programs such as an operating system and application programs for the processor 620 to execute, and data required for executing the computer programs.

In some embodiments, memory 210 may be volatile memory or non-volatile memory, and may include both volatile and non-volatile memory. Among them, the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-only memory) Only Memory), Electrically Erasable Programmable Read-Only Memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), Magnetic Random Access Memory (FRAM, ferromagnetic random access memory), Flash Memory (Flash Memory), Magnetic Surface Memory , CD-ROM, or CD-ROM (Compact Disc Read-Only Memory); magnetic surface memory can be disk memory or tape memory. Volatile memory may be Random Access Memory (RAM), which acts as an external cache. By way of example but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory Memory (DRAM, Dynamic Random Access Memory), Synchronous Dynamic Random Access Memory (SDRAM, Synchronous Dynamic Random Access Memory), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM, Double Data Rate Synchronous Dynamic Random Access Memory), Enhanced Type Synchronous Dynamic Random Access Memory (ESDRAM, Enhanced Synchronous Dynamic Random Access Memory), Synchronous Link Dynamic Random Access Memory (SLDRAM, SyncLink Dynamic Random Access Memory), Direct Memory Bus Random Access Memory (DRRAM, Direct Rambus Random Access Memory) ). The memory 610 described in the embodiments of the present invention is intended to include these and any other suitable types of memory.

In some embodiments, the processor 620 may be implemented by software, hardware, firmware, or a combination thereof, and may use circuits, single or multiple application-specific integrated circuits (ASICs), digital signal processors (Digital Signal Processors) Processor, DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (Programmable Logic Device, PLD), Field Programmable Gate Array (Field Programmable Gate Array, FPGA), Central Processing Unit (Central Processing) At least one of Unit, CPU), controller, microcontroller, and microprocessor, so that the processor 620 can execute part of the steps in the method for processing online data of the mobile platform in the various embodiments of the present application or All or any combination of steps.

According to an embodiment of the present invention, a computer-readable storage medium is also provided. The computer-readable storage medium stores a plurality of program instructions. After the plurality of program instructions are called and executed by a processor, the program instructions in the various embodiments of the present invention can be executed. Part or all of the steps or any combination of the steps in the method for processing the online data of the mobile platform.

According to an embodiment of the present invention, a mobile platform is also provided, including: an online data processing apparatus based on the mobile platform according to the embodiment of the present invention.

To sum up, the movable platform and the online data processing method, device and storage medium of the embodiment of the present invention greatly reduce the storage capacity of online data, save storage space and improve the performance of online data by performing real-time compression when collecting data online. The rate of data transmission and the efficiency of data processing.

It will be understood by those skilled in the art that all features disclosed in this specification (including the accompanying claims, abstract and drawings) and any method or apparatus so disclosed may be used in any combination, except that the features are mutually exclusive. Processes or units are combined. Each feature disclosed in this specification (including accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, it will be understood by those skilled in the art that although some of the embodiments described herein include certain features included in other embodiments and not others, combinations of features of different embodiments are meant to be within the scope of the present invention. range and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

The technical terms used in the embodiments of the present invention are only used to describe specific embodiments and are not intended to limit the present invention. As used herein, the singular forms "a," "the," and "the" are used to include the plural forms as well, unless the context clearly dictates otherwise. Further, as used in the specification for "comprising" and/or "comprising" refers to the presence of the stated features, integers, steps, operations, elements and/or components, but does not preclude the presence or addition of one or more Other features, integers, steps, operations, elements and/or components.

The corresponding structures, materials, acts, and equivalents of all means or step and function elements in the appended claims, if any, are intended to include any structure, material, or act for performing the function in combination with other explicitly claimed elements. The description of the present invention has been presented for purposes of example and description, but is not intended to be exhaustive or to limit the invention to the form disclosed. Various modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the invention. The embodiments described in the present invention can better disclose the principles and practical applications of the present invention, and enable those skilled in the art to understand the present invention.

The flowchart described in the present invention is only an embodiment, and various modifications and changes may be made to this illustration or the steps in the present invention without departing from the spirit of the present invention. For example, the steps may be performed in a different order, or certain steps may be added, deleted, or modified. Those skilled in the art can understand that all or part of the flow of the above-mentioned embodiments, and the equivalent changes made according to the claims of the present invention, still belong to the scope covered by the present invention.

Claims (42)

1. A method for processing online data of a movable platform, wherein the movable platform includes a plurality of sensors, and the method includes:

   Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

   Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

   The compressed first data is stored.
2. The method according to claim 1, wherein the attribute is determined according to at least one of the following: data type, data importance, data volume, or data source.
3. The method according to claim 1, wherein, based on the attributes of the first data, using corresponding compression parameters to perform real-time compression on the first data, comprising:

   The first data is compressed in real time using different compression parameters based on different categories of the attribute.
4. The method according to claim 1, wherein the compression parameters include at least one of the following: compression ratio, compression speed, or compression quality.
5. The method according to claim 1, wherein the attributes include data types, the categories of the data types include image data and non-image data, and based on the attributes of the first data, corresponding compression parameters are used to pair The first data is compressed in real time, including:

   When the first data is image data, use the first compression rate and/or lossy compression to perform real-time compression;

   When the first data is non-image data, real-time compression is performed using a second compression rate and/or lossless compression, or no compression is performed; wherein, the first compression rate is smaller than the second compression rate.
6. The method according to claim 5, wherein the first compression rate is used to make the compression quality of the image data meet a preset standard and also meet a preset compression time.
7. The method according to claim 1, wherein the attribute includes data importance, the categories of the importance include: important data and non-important data, and a corresponding compression parameter is adopted based on the attribute of the first data Perform real-time compression on the first data, including:

   When the first data is important data, use a third compression rate and/or lossless compression to perform real-time compression, or not compress;

   When the first data is unimportant data, real-time compression is performed using a fourth compression rate and/or lossy compression, wherein the fourth compression rate is smaller than the third compression rate.
8. The method according to claim 1, wherein the attribute includes a data source, the category of the data source includes: a first sensor and a second sensor, and a corresponding compression parameter is adopted based on the attribute of the first data Perform real-time compression on the first data, including:

   When the data source of the first data is the first sensor, use the fifth compression rate and/or lossless compression to perform real-time compression, or not to compress;

   When the data source of the first data is the second sensor, a sixth compression ratio and/or lossy compression is used to perform real-time compression, wherein the sixth compression ratio is smaller than the fifth compression ratio.
9. The method according to claim 1, wherein the attribute includes the size of the data amount, and the categories of the size of the data amount include: greater than or equal to a data amount threshold and less than a data amount threshold, based on the first data attribute, and use corresponding compression parameters to compress the first data in real time, including:

   When the data amount of the first data is less than the data amount threshold, use the seventh compression rate and/or lossless compression to perform real-time compression, or not compress;

   When the data volume of the first data is greater than or equal to the data volume threshold, real-time compression is performed using an eighth compression ratio and/or lossy compression, wherein the eighth compression ratio is smaller than the seventh compression ratio.
10. The method according to claim 1, wherein the first data comprises: image data and/or sound data, and the method further comprises:

    The designated terminal obtains the image data and/or the sound data in real time online to determine the attributes of the image data and/or the sound data;

    The designated terminal uses different compression parameters to compress the image data and/or sound data based on attributes of the image data and/or sound data, and stores the compressed image data and/or sound data.
11. The method of claim 1, wherein the attributes comprise a plurality of pre-categorized different categories.
12. The method of claim 1, wherein the plurality of sensors comprises a plurality of different types of sensors, wherein the plurality of different types of sensors include: image sensors, sound sensors, inertial measurement sensors, positioning sensors , temperature sensor, or a variety of distance sensors.
13. The method according to claim 1, wherein the movable platform comprises at least one of: an unmanned aerial vehicle, a car, a remote control car, and a robot.
14. A method for processing online data of a mobile platform, characterized in that the method comprises:

    The online data of the movable platform is obtained offline, wherein the online data of the movable platform includes compressed first data; wherein, the compressed first data is obtained by compressing the first data through corresponding compression parameters, and different attributes The first data corresponding to different compression parameters;

    Decompressing the compressed first data to obtain decompressed data;

    Offline processing is performed based on the decompressed data.
15. The method according to claim 14, wherein the offline processing comprises: offline simulation or offline playback.
16. The method according to claim 14, wherein the performing offline processing based on the decompressed data comprises:

    Screening the decompressed data based on the screening strategy to obtain screened data;

    Offline processing is performed based on the filtered data.
17. The method according to claim 16, wherein the decompressed data is screened based on a screening strategy to obtain the screened data, including one of the following:

    In the decompressed data, the data within the preset time period, the interval preset period, the preset type, the preset data source, or the data quality that meets the preset requirements is selected as the filtered data.
18. The method of claim 15, wherein the offline simulation comprises:

    In a simulation environment corresponding to the movable platform, the movable platform is simulated and operated based on at least part of the decompressed data.
19. The method of claim 14, wherein the method further comprises:

    For the remaining data in the decompressed data that does not meet the screening strategy, offline processing is not performed.
20. A method for processing online data of a movable platform, wherein the movable platform includes a plurality of sensors, and the method includes:

    Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

    Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

    storing the compressed first data;

    obtaining the compressed first data offline;

    Decompressing the compressed first data to obtain decompressed data;

    Offline processing is performed based on the decompressed data.
21. A device for processing online data of a mobile platform, characterized in that the device comprises:

    memory;

    processor;

    one or more programs stored in the memory and configured to be executed by the processor, the processor performing the following steps when executing the one or more programs:

    Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

    Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

    The compressed first data is stored.
22. The apparatus according to claim 21, wherein the attribute is determined according to at least one of the following: data type, data importance, data volume, or data source.
23. The apparatus according to claim 21, wherein the real-time compression of the first data by using corresponding compression parameters based on the attributes of the first data, comprising:

    The first data is compressed in real time using different compression parameters based on different categories of the attribute.
24. The apparatus according to claim 21, wherein the compression parameter comprises at least one of the following: compression ratio, compression speed, or compression quality.
25. The apparatus according to claim 21, wherein the attribute includes a data type, and the categories of the data type include: image data and non-image data, and different compression parameters are used for different compression parameters based on different categories of the attribute. The first data is compressed in real time, including:

    When the first data is image data, use the first compression rate and/or lossy compression to perform real-time compression;

    When the first data is non-image data, real-time compression is performed using a second compression rate and/or lossless compression, or no compression is performed; wherein, the first compression rate is smaller than the second compression rate.
26. The apparatus according to claim 25, wherein the first compression rate is used to make the compression quality of the image data meet a preset standard and also meet a preset compression time.
27. The apparatus according to claim 21, wherein the attribute includes data importance, and the categories of the importance include: important data and non-important data, and different compression parameters are used based on different categories of the attribute to The first data is compressed in real time, including:

    When the first data is important data, use a third compression rate and/or lossless compression to perform real-time compression, or not compress;

    When the first data is unimportant data, real-time compression is performed using a fourth compression rate and/or lossy compression, wherein the fourth compression rate is smaller than the third compression rate.
28. The apparatus according to claim 21, wherein the attribute includes a data source, the categories of the data source include: a first sensor and a second sensor, and different compression parameters are used for the data based on different categories of the attribute. The first data is compressed in real time, including:

    When the data source of the first data is the first sensor, use the fifth compression rate and/or lossless compression to perform real-time compression, or not to compress;

    When the data source of the first data is the second sensor, a sixth compression ratio and/or lossy compression is used to perform real-time compression, wherein the sixth compression ratio is smaller than the fifth compression ratio.
29. The apparatus according to claim 21, wherein the attribute includes a size of a data amount, and the categories of the size of the data amount include: greater than or equal to a data amount threshold and less than a data amount threshold, based on the first data attribute, and use corresponding compression parameters to compress the first data in real time, including:

    When the data amount of the first data is less than the data amount threshold, use the seventh compression rate and/or lossless compression to perform real-time compression, or not compress;

    When the data volume of the first data is greater than or equal to the data volume threshold, real-time compression is performed using an eighth compression ratio and/or lossy compression, wherein the eighth compression ratio is smaller than the seventh compression ratio.
30. The apparatus according to claim 21, wherein the first data includes image data and/or sound data, and the processor further implements the following steps when executing the one or more programs:

    The designated terminal acquires the image data and/or the sound data in real time online to determine the attributes of the image data and/or the sound data;

    The designated terminal uses different compression parameters to compress the image data and/or sound data based on attributes of the image data and/or sound data, and stores the compressed image data and/or sound data.
31. 21. The apparatus of claim 21, wherein the attributes comprise a plurality of different pre-categorized categories.
32. The apparatus of claim 21, wherein the plurality of sensors comprises a plurality of different types of sensors, wherein the plurality of different types of sensors include: image sensors, sound sensors, inertial measurement sensors, positioning sensors , temperature sensor, or a variety of distance sensors.
33. The device according to claim 21, wherein the movable platform comprises at least one of: an unmanned aerial vehicle, a car, a remote control car, and a robot.
34. A device for processing online data of a mobile platform, characterized in that the device comprises:

    memory;

    processor;

    one or more programs stored in the memory and configured to be executed by the processor, the processor performing the following steps when executing the one or more programs:

    The online data of the movable platform is obtained offline, wherein the online data of the movable platform includes compressed first data; wherein, the compressed first data is obtained by compressing the first data through corresponding compression parameters, and different attributes The first data corresponding to different compression parameters;

    Decompressing the compressed first data to obtain decompressed data;

    Offline processing is performed based on the decompressed data.
35. The apparatus according to claim 34, wherein the offline processing comprises: offline simulation or offline playback.
36. The apparatus according to claim 34, wherein the offline processing based on the decompressed data comprises:

    Screening the decompressed data based on the screening strategy to obtain screened data;

    Offline processing is performed based on the filtered data.
37. The device according to claim 36, wherein the decompressed data is screened based on a screening strategy to obtain the screened data, including one of the following:

    In the decompressed data, data within a preset time period, interval preset period, preset type, preset data source, or data quality that meets preset requirements is selected as the filtered data.
38. The apparatus of claim 35, wherein the offline simulation comprises:

    In a simulation environment corresponding to the movable platform, the movable platform is simulated and operated based on at least part of the decompressed data.
39. The apparatus of claim 34, wherein the method further comprises:

    For the remaining data in the decompressed data that does not meet the screening strategy, offline processing is not performed.
40. A device for processing online data of a mobile platform, characterized in that the device comprises:

    memory;

    processor;

    one or more programs stored in the memory and configured to be executed by the processor, the processor performing the following steps when executing the one or more programs:

    Obtain the first data generated by the sensor online in real time to determine the attribute of the first data;

    Based on the attributes of the first data, use corresponding compression parameters to compress the first data in real time; wherein, the first data of different attributes correspond to different compression parameters;

    storing the compressed first data;

    Obtaining the compressed first data offline; decompressing the compressed first data to obtain decompressed data;

    Offline processing is performed based on the decompressed data.
41. A computer-readable storage medium, comprising: a program that can be executed by a processor to implement the method according to any one of claims 1-20.
42. A movable platform, characterized by comprising: the device according to any one of claims 21-40.

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