Data processing method and processing device, storage medium and electronic equipment

Abstract

The invention discloses a data processing method and device, a storage medium and electronic equipment, and the method comprises the steps: creating a development environment which comprises two threads; receiving the first point cloud data, processing the first point cloud data based on the first thread to generate second point cloud data, and storing the second point cloud data into a data queue; and creating the data queue based on a second thread, processing the second point cloud data in the data queue to obtain target point cloud data, and transmitting the target point cloud data to a data receiver. The data processing method provided by the invention can get rid of dependence on a laser radar model, shorten the project period and reduce the project cost.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data processing method, a computer-readable storage medium, an electronic device and a data processing device. Background Art

[0002] With the development of automobile intelligence, ADAS (Advanced Driver Assistance System) is being used more and more widely. The application scenarios of ADAS require that its related functions must be tested reliably enough to ensure that vehicles using ADAS functions can operate safely without risk. Therefore, the testing of ADAS systems has become a hot topic.

[0003] HIL (Hardware-in-the-loop) is a simulation test method that combines real domain control and virtual simulation environment. Compared with real vehicle testing, it has the advantages of high efficiency and low cost. HIL simulation mainly includes host computer, real-time machine, graphics workstation, video injection board, ADAS controller, which involves scene construction, sensor modeling, associated node matching, signal simulation and other modules. As the number of high-performance LiDAR sensors used in cars with ADAS systems continues to rise, how to simulate LiDAR data output as realistically as possible in HIL simulation has become a top priority.

[0004] In HIL simulation, the laser radar model is used to simulate the laser point cloud sensor, output high-precision laser radar point cloud data, extract the simulated output laser radar point cloud data through the laser radar transmission protocol, package it, and then transmit it to the ADAS controller via Ethernet. In the current related technologies, the development cycle of redeveloping a laser radar model (with many personalized parameters, such as supported bus protocols, laser point cloud packaging methods, data synchronization accuracy, and fault simulation) is long, often taking several months, and the difficulty increases, and the project progress cannot be guaranteed. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems in the related art to a certain extent. To this end, the first purpose of the present invention is to propose a data processing method, create a development environment, the development environment includes two threads; receive first point cloud data, and process the first point cloud data based on the first thread to generate second point cloud data, and store the second point cloud data in a data queue; create a data queue based on the second thread, and process the second point cloud data in the data queue to obtain target point cloud data, and transmit the target point cloud data to the data recipient, so as to get rid of the dependence on the laser radar model, shorten the project cycle, and reduce the project cost.

[0006] A second object of the present invention is to provide a computer-readable storage medium.

[0007] A third objective of the present invention is to provide an electronic device.

[0008] A fourth objective of the present invention is to provide a data processing device.

[0009] To achieve the above-mentioned purpose, the first aspect of the embodiment of the present invention proposes a data processing method, which includes: creating a development environment, the development environment includes two threads; receiving first point cloud data, and processing the first point cloud data based on the first thread to generate second point cloud data, and storing the second point cloud data in a data queue; creating the data queue based on the second thread, and processing the second point cloud data in the data queue to obtain target point cloud data, and transmitting the target point cloud data to a data recipient.

[0010] According to the data processing method of the embodiment of the present invention, a development environment is created, and the development environment includes two threads; first point cloud data is received, and the first point cloud data is processed based on the first thread to generate second point cloud data, and the second point cloud data is stored in a data queue; a data queue is created based on the second thread, and the second point cloud data in the data queue is processed to obtain target point cloud data, and the target point cloud data is transmitted to the data recipient. Therefore, the method can get rid of the dependence on the laser radar model, shorten the project cycle, and reduce the project cost.

[0011] In addition, the data processing method according to the above embodiment of the present invention may also have the following additional technical features:

[0012] According to one embodiment of the present invention, the receiving of first point cloud data and processing of the first point cloud data based on a first thread to generate second point cloud data includes: acquiring the first point cloud data generated by a preset type of laser radar based on the first thread; and performing packet patching on the first point cloud data according to point cloud data required by a target type laser radar to generate second point cloud data.

[0013] According to one embodiment of the present invention, the second point cloud data in the data queue is processed to obtain target point cloud data, including: processing the second point cloud data according to the data format of the target type laser radar to obtain the target point cloud data corresponding to the target type laser radar.

[0014] According to one embodiment of the present invention, the first point cloud data is packet-padded according to the point cloud data required by the target type laser radar to generate second point cloud data, including: determining the number of data packets of the first point cloud data; and packet-padded the first point cloud data based on the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data.

[0015] According to one embodiment of the present invention, the method of supplementing the first point cloud data based on the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data includes: determining the number of supplementary packets according to the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data; and supplementing the number of supplementary packets with zero content behind the data packets of the first point cloud data to generate the second point cloud data.

[0016] According to one embodiment of the present invention, the processing of the second point cloud data according to the data format of the target type laser radar includes: adding a timestamp and a check bit to the header segment of the second point cloud data according to the data format of the target type laser radar to generate the target point cloud data.

[0017] According to an embodiment of the present invention, the method further includes: adjusting the transmission rate of the target point cloud data to adapt to the receiving rate of the data receiver.

[0018] To achieve the above-mentioned purpose, a second aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which implements the above-mentioned data processing method when executed by a processor.

[0019] According to the computer-readable storage medium of the embodiment of the present invention, by implementing the above-mentioned data processing method during execution, it is possible to get rid of the dependence on the laser radar model, shorten the project cycle, and reduce the project cost.

[0020] To achieve the above-mentioned purpose, an electronic device proposed in an embodiment of the third aspect of the present invention includes a memory, a processor, and a program stored in the memory and executable on the processor, and when the processor executes the program, the above-mentioned data processing method is implemented.

[0021] The electronic device according to the embodiment of the present invention can get rid of the dependence on the laser radar model by executing the above-mentioned data processing method, shorten the project cycle and reduce the project cost.

[0022] To achieve the above-mentioned purpose, the fourth aspect of the present invention proposes a data processing device, which includes: a creation module, used to create a development environment, and the development environment includes two threads; a first processing module, used to receive first point cloud data, and process the first point cloud data based on the first thread to generate second point cloud data, and store the second point cloud data in a data queue; a second processing module, used to create the data queue based on the second thread, and process the second point cloud data in the data queue to obtain target point cloud data, and transmit the target point cloud data to a data recipient.

[0023] According to the data processing device of the embodiment of the present invention, the creation module is used to create a development environment, and the development environment includes two threads. The first processing module is used to receive the first point cloud data, and process the first point cloud data based on the first thread to generate the second point cloud data, and store the second point cloud data in the data queue. The second processing module is used to create a data queue based on the second thread, and process the second point cloud data in the data queue to obtain the target point cloud data, and transmit the target point cloud data to the data recipient. As a result, the device can get rid of the dependence on the laser radar model, shorten the project cycle, and reduce the project cost.

[0024] Additional aspects and advantages of the present invention will be given in part in the following description and in part will be obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a flow chart of a data processing method according to an embodiment of the present invention;

[0026] Figure 2 is a flow chart of a data processing method according to a specific example of the present invention;

[0027] Figure 3 is a block diagram of an electronic device according to an embodiment of the present invention;

[0028] Figure 4 FIG. 4 is a block diagram of a data processing device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0029] Embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and should not be construed as limiting the present invention.

[0030] The following describes a data processing method, a computer-readable storage medium, an electronic device, and a data processing device according to embodiments of the present invention with reference to the accompanying drawings.

[0031] In the current related technology, it is necessary to redevelop a laser radar model, and the disadvantage is that it prolongs the project cycle. For example, the existing laser radar model is the M1 laser radar, and the laser radar model used in the present invention is the M1P laser radar. The difference between the M1 laser radar model and the M1P laser radar model is that the contents of the laser point cloud data packets of the two are slightly different, and the frame rates of the laser point cloud data packets are different. These two differences can be solved by post-processing the laser point cloud data packets, so as to meet the functional requirements of the M1P laser radar model. However, if the existing technical solution is adopted, it is necessary to redevelop a set of laser radar models, which not only increases the difficulty, but also the project progress cannot be guaranteed. Based on the existing laser radar model of similar models, the embodiment of the present invention uses a post-processing method, that is, using Matlab to build a model, and the laser radar point cloud data generated after the existing laser radar model is run is received and matched with the intelligent driving domain controller, so as to achieve the purpose of shortening the project cycle on the basis of meeting the functions of the laser radar model.

[0032] Figure 1 is a flow chart of a data processing method according to an embodiment of the present invention.

[0033] like Figure 1 As shown, the data processing method of the embodiment of the present invention may include the following steps:

[0034] S1, create a development environment, the development environment includes two threads.

[0035] S2, receiving first point cloud data, and processing the first point cloud data based on the first thread to generate second point cloud data, and storing the second point cloud data in a data queue.

[0036] S3, creating a data queue based on the second thread, processing the second point cloud data in the data queue to obtain target point cloud data, and transmitting the target point cloud data to a data receiver.

[0037] Specifically, after running the MotionDesk software, a development environment is created. For example, a LabVIEW project can be created, and two threads are opened for parallel processing, namely, a first thread and a second thread. That is, by assigning tasks to multiple threads, multiple tasks can be executed simultaneously, thereby speeding up the overall processing speed. The first point cloud data is received, and the first point cloud data is processed based on the first thread. That is, the first thread can be used to receive the first point cloud data, and the first point cloud data can be processed, such as by packet filling, to obtain the second point cloud data, and after obtaining the second point cloud data, the second point cloud data is stored in the data queue so that the data can be read from the data queue and the second point cloud data can be processed, which helps to manage the data flow and ensure the orderly progress of the processing process.

[0038] A data queue may be created according to the second thread, for example, a UDP (User Datagram Protocol) communication socket is opened, the addresses and ports of the server and the client are determined, a queue reference is created, and it is passed to different threads so that data can be shared between threads. The second point cloud data in the data queue is processed, for example, a timestamp and a check bit are added to the header segment of the second point cloud data to obtain the target point cloud data, and after obtaining the target point cloud data, the target point cloud data may be transmitted to the data receiver, such as after setting the transmission rate, the data is transmitted to the data receiver.

[0039] In addition, in one embodiment of the present invention, the point cloud data of the laser radar also includes a device information package, such as the power supply status of the laser radar, such as the battery status or the voltage of the power adapter, the scanning frequency of the laser radar, usually in Hz (Hertz), the installation position and orientation of the laser radar on the vehicle or equipment, and other data. When sending the device information package, it can be sent to the ADAS controller at a frequency of 50ms. In summary, it can quickly respond to the simulation needs of the ADAS system, get rid of the dependence on the laser radar model, shorten the project cycle to a certain extent, and reduce the project cost.

[0040] According to one embodiment of the present invention, first point cloud data is received, and the first point cloud data is processed based on a first thread to generate second point cloud data, including: obtaining first point cloud data generated by a preset type of laser radar based on the first thread; and performing packet patching on the first point cloud data according to point cloud data required by a target type of laser radar to generate second point cloud data.

[0041] Specifically, when receiving the first point cloud data and processing the first point cloud data based on the first thread to generate the second point cloud data, the first thread can receive the first point cloud data, and first obtain the first point cloud data generated by the preset type of laser radar based on the first thread. For example, ensure that the laser radar sensor has been correctly installed and configured. The configuration usually includes setting the IP address, communication protocol, etc. The laser radar sensor manufacturer will provide the corresponding driver and software development kit, which can be used to obtain point cloud data. In addition, when obtaining the first point cloud data generated by the preset type of laser radar, the preset type of laser radar can also be compiled based on the compilation software to generate the first point cloud data. For example, the MotionDesk software can be run and the preset type of laser radar model compilation file can be loaded to generate the first point cloud data. Among them, the MotionDesk software can provide a virtual simulation environment, enabling engineers to conduct detailed testing and verification of vehicle dynamic behavior, control algorithms and sensor systems in the early stages of development, which not only improves development efficiency, but also reduces the risk and cost of testing on actual vehicles.

[0042] After determining the first point cloud data, the first point cloud data can be packetized according to the point cloud data required by the target type laser radar to generate the second point cloud data. In other words, different types of laser radars correspond to different point cloud data, such as different numbers of corresponding data packets. Through packetization, the existing data can be converted into a format that meets the target specifications, thereby improving the data compatibility between different devices. In addition, through packetization, the data of different types of laser radars can be uniformly processed and analyzed to improve the utilization rate of the data. Or when developing new technologies and algorithms, point cloud data that meets the requirements of the target laser radar can be quickly obtained without having to wait for the deployment of new hardware equipment, thereby speeding up the research and development process.

[0043] According to one embodiment of the present invention, the second point cloud data in the data queue is processed to obtain target point cloud data, including: processing the second point cloud data according to the data format of the target type laser radar to obtain target point cloud data corresponding to the target type laser radar.

[0044] Specifically, when the second point cloud data in the data queue is processed to obtain the target point cloud data, the second point cloud data can be processed according to the data format of the target type laser radar, so as to obtain the target point cloud data corresponding to the target type laser radar. For example, according to the resolution and sampling frequency of the target type laser radar, the point cloud data is resampled to ensure that the data format and content meet the requirements of the target device, or the point cloud data is encoded into a specific data format (such as a specific file format or data protocol, etc.) used by the target type laser radar. After the above processing, the point cloud data that meets the requirements of the target type laser radar is finally obtained, and this data can be directly used in the application scenarios of the target type laser radar, such as environmental modeling, navigation, obstacle detection, etc. The core of the whole process is to use the first point cloud data generated by the target type laser radar that has been determined, and ensure that the first point cloud data can meet the data requirements of the target type laser radar after the packet filling processing and format conversion, so as to achieve effective use of data and system compatibility. In this way, it is possible to flexibly adapt to the needs of different laser radars without changing the hardware equipment, thereby improving the utilization efficiency of data and the overall performance of the system.

[0045] According to one embodiment of the present invention, first point cloud data are packetized according to point cloud data required by a target type laser radar to generate second point cloud data, including: determining the number of data packets of the first point cloud data; and packetizing the first point cloud data based on the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data.

[0046] Specifically, when the first point cloud data is supplemented according to the point cloud data required by the target type laser radar to generate the second point cloud data, the number of data packets of the first point cloud data is first determined. For example, the point cloud data usually contains multiple data packets, and each data packet may represent data collected from the laser radar sensor within a specific time period. If the preset type of laser radar is an M1 type laser radar, a complete frame of point cloud data may include 595 data packets. After obtaining the number of data packets of the first point cloud data, the first point cloud data can be supplemented according to the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data. For example, the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data can be compared, and new point cloud data can be generated based on this difference. For example, the supplement can be achieved by copying existing data packets or generating synthetic data packets, so that the number of data packets of the point cloud data required by the target type laser radar can be obtained.

[0047] According to one embodiment of the present invention, first point cloud data are padded based on the difference between the number of data packets of point cloud data required by the target type laser radar and the number of data packets of the first point cloud data, including: determining the number of padded packets according to the difference between the number of data packets of point cloud data required by the target type laser radar and the number of data packets of the first point cloud data; and padded with the number of padded packets with zero content behind the data packet of the first point cloud data to generate second point cloud data.

[0048] Specifically, when supplementing the first point cloud data according to the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data, the number of supplementary packets can be first determined according to the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data. For example, the preset type laser radar is the M1 type laser radar, and a complete frame of point cloud data can include 595 data packets. The target type laser radar is the M1P type laser radar, and a complete frame of point cloud data can include 630 data packets. Therefore, the number of supplementary packets can be determined to be 35.

[0049] After determining the number of supplementary packets, data packets with the same number of supplementary packets as zero can be supplemented after the data packet of the first point cloud data to generate the second point cloud data. For example, taking the above-mentioned M1 laser radar and M1P laser radar as examples, the point cloud data may include information such as the spatial coordinates of each point and the reflection intensity value of each point. These data information can be set to zero and supplemented at the tail position of the data packet of the first point cloud data, and 35 data packets with zero content can be supplemented to obtain the second point cloud data.

[0050] According to one embodiment of the present invention, the second point cloud data is processed according to the data format of the target type laser radar, including: adding a timestamp and a check digit to the header segment of the second point cloud data according to the data format of the target type laser radar to generate target point cloud data.

[0051] Specifically, when the second point cloud data is processed according to the data format of the target type laser radar, a timestamp and a check digit may be added to the header segment of the second point cloud data according to the data format of the target type laser radar. That is, the data segments of the target type laser radar and the preset type laser radar are the same, and the difference is that the header segment is different. After adding the timestamp and the check digit to the header segment of the second point cloud data, it is changed to the data format of the target type laser radar, that is, the target point cloud data is generated. Among them, the timestamp can record the timestamp of the data packet, identify the sending or receiving time of the data packet, and the check digit can be used for end-to-end verification of the data packet to ensure that the data packet has not been tampered with or damaged during transmission.

[0052] According to an embodiment of the present invention, the data processing method further includes: adjusting the transmission rate of the target point cloud data to adapt to the receiving rate of the data receiver.

[0053] Specifically, after determining the target point cloud data, the target point cloud data can be sent to the data receiver, for example, the data receiver is an ADAS controller, and the ADAS controller can be used to receive the target point cloud data and process the target point cloud data to use these data for a variety of real-time analysis and decision-making. When sending to the ADAS controller, the transmission rate of the target point cloud data can be adjusted according to the requirements of the ADAS controller's receiving rate. For example, the target point cloud data can be slowed down and the transmission rate can be set to 160μs per data packet to adapt to the receiving rate of the data receiver. This ensures that the data can be sent normally. That is to say, if the data transmission rate exceeds the processing capacity of the receiver, the data packet may be lost in the network, resulting in incomplete or inaccurate data. Adjusting the transmission rate of the target point cloud data can ensure that all transmitted data packets can be processed and stored by the receiver, ensuring the integrity and accuracy of the data, which is crucial for the data analysis and decision-making process.

[0054] Combine the following Figure 2 The processing method of the present invention will be described below.

[0055] As a specific example, the data processing method of the present invention may include the following steps:

[0056] S101, compile a preset type of laser radar based on compilation software to generate first point cloud data.

[0057] S102, determining the number of data packets of the first point cloud data.

[0058] S103, determining the number of supplementary packets according to the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of the first point cloud data.

[0059] S104, append a data packet with a number of zero appended packets after the data packet of the first point cloud data to generate second point cloud data.

[0060] S105, adding a timestamp and a check digit to the header segment of the second point cloud data according to the data format of the target type laser radar to generate target point cloud data.

[0061] S106, adjusting the transmission rate of the target point cloud data to adapt to the receiving rate of the data receiver.

[0062] In summary, according to the data processing method of the embodiment of the present invention, a development environment is created, and the development environment includes two threads; the first point cloud data is received, and the first point cloud data is processed based on the first thread to generate the second point cloud data, and the second point cloud data is stored in the data queue; the data queue is created based on the second thread, and the second point cloud data in the data queue is processed to obtain the target point cloud data, and the target point cloud data is transmitted to the data recipient. Therefore, the method can get rid of the dependence on the laser radar model, shorten the project cycle, and reduce the project cost.

[0063] Corresponding to the above embodiment, the present invention also proposes a computer-readable storage medium.

[0064] The computer-readable storage medium of the embodiment of the present invention stores a program, and the program implements the above-mentioned data processing method when executed by a processor.

[0065] According to the computer-readable storage medium of the embodiment of the present invention, by executing the above-mentioned data processing method, it is possible to get rid of the dependence on the laser radar model, shorten the project cycle, and reduce the project cost.

[0066] Corresponding to the above embodiment, the present invention further provides an electronic device.

[0067] like Figure 3 As shown, the electronic device 200 of the embodiment of the present invention may include: a memory 210, a processor 220, and a program stored in the memory 210 and executable on the processor 220. When the processor 220 executes the program, the above-mentioned data processing method is implemented.

[0068] The electronic device according to the embodiment of the present invention can get rid of the dependence on the laser radar model by executing the above-mentioned data processing method, shorten the project cycle and reduce the project cost.

[0069] Corresponding to the above embodiment, the present invention also proposes a data processing device.

[0070] like Figure 4 As shown, the data processing device 100 according to the embodiment of the present invention includes: a creation module 110 , a first processing module 120 and a second processing module 130 .

[0071] The creation module 110 is used to create a development environment, which includes two threads. The first processing module 120 is used to receive the first point cloud data, and process the first point cloud data based on the first thread to generate the second point cloud data, and store the second point cloud data in the data queue. The second processing module 130 is used to create a data queue based on the second thread, and process the second point cloud data in the data queue to obtain the target point cloud data, and transmit the target point cloud data to the data recipient.

[0072] According to one embodiment of the present invention, the first processing module 120 receives first point cloud data, and processes the first point cloud data based on the first thread to generate second point cloud data, and is specifically used for: acquiring first point cloud data generated by a preset type of laser radar based on the first thread; and performing packet patching on the first point cloud data according to the point cloud data required by the target type laser radar to generate second point cloud data.

[0073] According to one embodiment of the present invention, the second processing module 130 processes the second point cloud data in the data queue to obtain target point cloud data, and is specifically used to: process the second point cloud data according to the data format of the target type laser radar to obtain target point cloud data corresponding to the target type laser radar.

[0074] According to one embodiment of the present invention, the first processing module 120 performs packet patching on the first point cloud data according to the point cloud data required by the target type laser radar to generate second point cloud data, and is specifically used to: determine the number of data packets of the first point cloud data; and patch the first point cloud data based on the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data.

[0075] According to one embodiment of the present invention, the first processing module 120 performs packet padding on the first point cloud data based on the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data, specifically for: determining the number of packet padding according to the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data; padding the number of packet paddings with zero content behind the data packet of the first point cloud data to generate second point cloud data.

[0076] According to one embodiment of the present invention, the second processing module 130 processes the second point cloud data according to the data format of the target type laser radar, and is specifically used to: add a timestamp and a check bit to the header segment of the second point cloud data according to the data format of the target type laser radar to generate target point cloud data.

[0077] According to an embodiment of the present invention, the second processing module 130 is further configured to adjust the transmission rate of the target point cloud data to adapt to the receiving rate of the data receiver.

[0078] It should be noted that for details not disclosed in the data processing device of the embodiment of the present invention, please refer to the details disclosed in the data processing method of the embodiment of the present invention, and the details will not be repeated here.

[0079] According to the data processing device of the embodiment of the present invention, the creation module is used to create a development environment, and the development environment includes two threads. The first processing module is used to receive the first point cloud data, and process the first point cloud data based on the first thread to generate the second point cloud data, and store the second point cloud data in the data queue. The second processing module is used to create a data queue based on the second thread, and process the second point cloud data in the data queue to obtain the target point cloud data, and transmit the target point cloud data to the data recipient. As a result, the device can get rid of the dependence on the laser radar model, shorten the project cycle, and reduce the project cost.

[0080] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0081] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0082] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0083] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0084] In the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0085] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A data processing method, characterized in that: The method comprises: Creating a development environment, wherein the development environment includes two threads; Receive first point cloud data, process the first point cloud data based on the first thread to generate second point cloud data, and store the second point cloud data in a data queue; The data queue is created based on the second thread, and the second point cloud data in the data queue is processed to obtain target point cloud data, and the target point cloud data is transmitted to a data receiver.

2. The data processing method according to claim 1, characterized in that: The receiving the first point cloud data and processing the first point cloud data based on the first thread to generate second point cloud data includes: Acquire the first point cloud data generated by a preset type of laser radar based on the first thread; The first point cloud data is packaged according to the point cloud data required by the target type laser radar to generate second point cloud data.

3. The data processing method according to claim 2, characterized in that: Processing the second point cloud data in the data queue to obtain target point cloud data includes: The second point cloud data is processed according to the data format of the target type laser radar to obtain the target point cloud data corresponding to the target type laser radar.

4. The data processing method according to claim 2, characterized in that: The step of performing packet filling processing on the first point cloud data according to the point cloud data required by the target type laser radar to generate second point cloud data includes: Determining the number of data packets of the first point cloud data; The first point cloud data is supplemented based on the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data.

5. The data processing method according to claim 4, characterized in that: The method of supplementing the first point cloud data based on the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data includes: Determine the number of supplementary packets according to the difference between the number of data packets of the point cloud data required by the target type laser radar and the number of data packets of the first point cloud data; The data packets with the number of supplementary packets and the content of which is zero are supplemented after the data packets of the first point cloud data to generate the second point cloud data.

6. The data processing method according to claim 3, characterized in that: The processing of the second point cloud data according to the data format of the target type laser radar includes: A timestamp and a check digit are added to the header segment of the second point cloud data according to the data format of the target type laser radar to generate the target point cloud data.

7. The data processing method according to claim 1, characterized in that: The method further comprises: The transmission rate of the target point cloud data is adjusted to adapt to the receiving rate of the data receiver.

8. A computer-readable storage medium, characterized in that: A program is stored thereon, and when the program is executed by a processor, the data processing method according to any one of claims 1 to 7 is implemented.

9. An electronic device, characterized in that: include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the data processing method according to any one of claims 1 to 7 is implemented.

10. A data processing device, characterized in that: The device comprises: A creation module is used to create a development environment, wherein the development environment includes two threads; A first processing module, configured to receive first point cloud data, process the first point cloud data based on a first thread to generate second point cloud data, and store the second point cloud data in a data queue; The second processing module is used to create the data queue based on the second thread, process the second point cloud data in the data queue to obtain target point cloud data, and transmit the target point cloud data to a data receiver.

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