Unmanned aerial vehicle accurate attitude control method, device and equipment based on vision and IMU data fusion and storage medium

Abstract

The invention discloses an unmanned aerial vehicle accurate attitude control method based on vision and IMU data fusion. The method comprises the following steps: obtaining service information in real time; collecting a data source in the service information according to the service scene; and performing streaming computation on the data of the data source, and outputting a computed result. According to the invention, service information is obtained in real time; collecting a data source in the service information according to the service scene; and performing streaming computation on the data of the data source, and outputting a computed result. The change state of the data can be sensed in real time through real-time loss calculation, and the calculation efficiency of the data when the business is changed can be greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a method, device, equipment and storage medium for precise attitude control of an unmanned aerial vehicle based on vision and IMU data fusion. Background Art

[0002] With the continuous deepening of various Internet applications, the amount of Internet data is growing rapidly, and the data structures and data types that need to be processed are becoming more and more diverse. At present, the demand for data in the application market is increasing day by day. In order to ensure the timeliness and quality of data services, clients usually need to call data from third-party databases.

[0003] With the rapid development of the Internet, the era of big data has arrived. Data is growing explosively, and traditional data processing models are no longer suitable for analyzing massive data. Summary of the invention

[0004] The main purpose of the present invention is to provide a method, device, equipment and storage medium for precise attitude control of unmanned aerial vehicles based on vision and IMU data fusion, aiming to solve the problems of inaccurate position perception, attitude perception and unstable control.

[0005] To achieve the above objectives, the present invention provides a method for precise attitude control of a UAV based on the fusion of vision and IMU data.

[0006] The method for precise attitude control of a UAV based on vision and IMU data fusion comprises the following steps: Get business information in real time; Collect data sources within business information based on business scenarios; Perform streaming calculation on the data of the data source and output the calculated results.

[0007] Preferably, after the step of acquiring business information in real time and before the step of collecting the data source in the business information according to the business scenario, the method for precise attitude control of the drone based on vision and IMU data fusion further includes: Clean and preprocess the data sources in the business information to obtain the data to be calculated.

[0008] Preferably, the step of cleaning the data source in the business information includes: Perform cluster analysis on the data sources to be cleaned; The clustered data sources are classified according to preset rules to obtain multiple cluster classifications.

[0009] Preferably, the cluster classification includes message queue data, database, cache and file.

[0010] Preferably, the step of performing streaming calculation on the data of the data source and outputting the calculated result includes: Different clustering classifications are calculated in real time and deployed as multiple instances.

[0011] Preferably, after the step of performing streaming calculation on the data of the data source and outputting the calculated result, the method further comprises: Verify the validity of data before entering it into the database.

[0012] In addition, to achieve the above-mentioned purpose, the present invention further provides a data computing device based on business changes, the data computing device based on business changes comprising: Acquisition module, used to obtain business information in real time; The collection module is used to collect data sources in business information according to business scenarios; The computing module is used to perform streaming computing on the data of the data source and output the computed results.

[0013] In addition, to achieve the above-mentioned purpose, the present invention also provides a method for precise attitude control of an unmanned aerial vehicle based on the fusion of vision and IMU data. The method for precise attitude control of an unmanned aerial vehicle based on the fusion of vision and IMU data includes: a memory, a processor, and a data calculation program stored in the memory and executable on the processor. When the data calculation program is executed by the processor, the steps of the data calculation method described above are implemented.

[0014] In addition, to achieve the above object, the present invention also provides a computer-readable storage medium, wherein a data calculation program is stored on the computer-readable storage medium, and when the data calculation program is executed by a processor, the steps of the data storage method described above are implemented. Beneficial effects that can be achieved by the present invention: The embodiment of the present invention proposes a method for precise attitude control of a drone based on the fusion of vision and IMU data, which obtains business information in real time; collects data sources in the business information according to business scenarios; performs streaming calculations on the data of the data sources and outputs the calculated results. The real-time loss calculation can perceive the change state of data in real time, which can greatly improve the calculation efficiency of data when the business changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of the structure of a device in a hardware operating environment involved in an embodiment of the present invention; Figure 2 It is a flow chart of the first embodiment of the method for precise attitude control of a UAV based on vision and IMU data fusion of the present invention; Figure 3It is a flow chart of the second embodiment of the method for precise attitude control of a UAV based on vision and IMU data fusion of the present invention; Figure 4 It is a flow chart of a third embodiment of a method for precise attitude control of a UAV based on vision and IMU data fusion according to the present invention; Figure 5 This is a flow chart of the fourth embodiment of the method for precise attitude control of a UAV based on vision and IMU data fusion of the present invention.

[0016] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0017] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0018] The main solutions of the embodiments of the present invention are: Get business information in real time; Collect data sources within business information based on business scenarios; Perform streaming calculation on the data of the data source and output the calculated results.

[0019] With the continuous deepening of various Internet applications, the amount of Internet data is growing rapidly, and the data structures and data types that need to be processed are becoming more and more diverse. At present, the demand for data in the application market is increasing day by day. In order to ensure the timeliness and quality of data services, clients usually need to call data from third-party databases.

[0020] With the rapid development of the Internet, the era of big data has arrived. Data is growing explosively, and traditional data processing models are no longer suitable for analyzing massive data.

[0021] The present invention provides a solution that can perceive the changing state of data in real time through real-time loss calculation, and can greatly improve the calculation efficiency of data when the business changes.

[0022] like Figure 1 As shown, Figure 1 It is a schematic diagram of the terminal structure of the hardware operating environment involved in the embodiment of the present invention.

[0023] The terminal of the embodiment of the present invention can be a PC, or it can be a smart phone, a tablet computer, an e-book reader, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a portable computer, or other portable terminal devices with display function.

[0024] like Figure 1 As shown, the terminal may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0025] Optionally, the terminal may also include a camera, an RF (Radio Frequency) circuit, a sensor, an audio circuit, a WiFi module, and the like. Among them, sensors include light sensors, motion sensors, and other sensors. Specifically, the light sensor may include an ambient light sensor and a proximity sensor, wherein the ambient light sensor may adjust the brightness of the display screen according to the brightness of the ambient light, and the proximity sensor may turn off the display screen and / or backlight when the mobile terminal is moved to the ear. As a type of motion sensor, the gravity acceleration sensor can detect the magnitude of acceleration in each direction (generally three axes), and can detect the magnitude and direction of gravity when stationary. It can be used for applications that identify the posture of the mobile terminal (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; of course, the mobile terminal can also be equipped with other sensors such as gyroscopes, barometers, hygrometers, thermometers, infrared sensors, etc., which will not be repeated here.

[0026] Those skilled in the art will understand that Figure 1 The terminal structure shown in the figure does not constitute a limitation on the terminal, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0027] like Figure 1 As shown, the memory 1005 as a computer storage medium may include an operating system, a network communication module, a user interface module, and a data calculation program.

[0028] exist Figure 1 In the terminal shown, the network interface 1004 is mainly used to connect to the backend server and perform data communication with the backend server; the user interface 1003 is mainly used to connect to the client (user end) and perform data communication with the client; and the processor 1001 can be used to call the data calculation program stored in the memory 1005 and perform the following operations: Get business information in real time; Collect data sources within business information based on business scenarios; Perform streaming calculation on the data of the data source and output the calculated results.

[0029] Furthermore, the processor 1001 may call the data calculation program stored in the memory 1005, and further perform the following operations: Clean and preprocess the data sources in the business information to obtain the data to be calculated.

[0030] Furthermore, the processor 1001 may call the data calculation program stored in the memory 1005, and further perform the following operations: Perform cluster analysis on the data sources to be cleaned; The clustered data sources are classified according to preset rules to obtain multiple cluster classifications.

[0031] Furthermore, the processor 1001 may call the data calculation program stored in the memory 1005, and further perform the following operations: Different clustering classifications are calculated in real time and deployed as multiple instances.

[0032] Furthermore, the processor 1001 may call the data calculation program stored in the memory 1005, and further perform the following operations: Check the validity of data before entering it into the database The specific embodiments of the data storage device of the present invention are basically the same as the embodiments of the data storage method described below, and will not be described in detail here.

[0033] Reference Figure 2 The first embodiment of the present invention provides a method for precise attitude control of a UAV based on vision and IMU data fusion, and the method for precise attitude control of a UAV based on vision and IMU data fusion includes: Step S10, obtaining business information in real time; Step S20, collecting data sources in the business information according to the business scenario; Step S30, performing streaming calculation on the data of the data source and outputting the calculated results.

[0034] In this embodiment, business information is acquired in real time; data sources in the business information are collected according to business scenarios; streaming calculations are performed on the data of the data sources and the calculated results are output. Real-time churn calculations can sense the changing state of data in real time, which can greatly improve the calculation efficiency of data when business changes.

[0035] Among them, the stream computing engine supports multiple types of data sources, including message queues, databases, caches, files, etc. According to the overall system architecture design, the computing service uses the message queue as an interface to meet the access standards of the stream computing engine. By subscribing to the message queue, the data change status can be perceived in real time, and the read operation of the cache database (redis and other components) can be used to achieve full access to the data required for real-time computing and analysis.

[0036] The business execution logic of real-time computing is executed in the computing job link. The job scheduling, state management, programming model, fault-tolerant mechanism and other functions provided by the stream computing engine are used to develop and submit real-time computing programs, process minute data, freeze data, report events in the data access link, and feed back the calculation results to the result output link.

[0037] According to the time response requirements of business scenarios and applications, different real-time computing and analysis logics are encapsulated into multiple instances for deployment (for example, real-time power calculation and anomaly analysis can be developed and deployed as two independent stream computing instances). Logically, the isolation between each instance is maintained, which avoids mutual interference between instances and facilitates the upgrade, operation, maintenance and management of different businesses.

[0038] The stream computing engine supports multiple types of result output, including output to message queues, databases, caches, or direct output to files, etc. Output to cache is mainly to meet the real-time access requirements of business applications; output to business libraries provides persistent storage capabilities for calculation results and can provide data access channels for business applications through data services.

[0039] Further, see Figure 3 The second embodiment of the present invention provides a method for precise attitude control of a UAV based on the fusion of vision and IMU data. Figure 2 In the embodiment shown, after the step of acquiring business information in real time and before the step of collecting the data source in the business information according to the business scenario, the method for precise attitude control of the drone based on vision and IMU data fusion further includes: Step S40, cleaning and preprocessing the data source in the business information to obtain the data to be calculated.

[0040] In this embodiment, cleaning the data source in the business information can effectively reduce the amount of calculation, remove some fixed data that does not need to be calculated, and prevent invalid calculations from occurring.

[0041] Specifically, refer to Figure 4 The third embodiment of the present invention provides a method for precise attitude control of a UAV based on vision and IMU data fusion, wherein the step of cleaning the data source in the business information comprises: Step S41, performing cluster analysis on the data source to be cleaned in the data source; Step S42, classifying the clustered data sources according to preset rules to obtain multiple cluster classifications.

[0042] In this embodiment, when executing the above method, a judgment criterion may be preset, and different keywords may be preset according to different attributes of each data. When the data stream is acquired, the data may be matched according to different keywords to perform clustering and grouping.

[0043] Specifically, please refer to Figure 5 The fourth embodiment of the present invention provides a method for precise attitude control of a drone based on vision and IMU data fusion. After the step of performing streaming calculation on the data of the data source and outputting the calculated result, the method further includes: Verify the validity of data before entering it into the database.

[0044] In this embodiment, the rationality of the data can be checked (excluding abnormal reverse running of meter codes), for example: meter reading settlement data (frozen data, etc.).

[0045] In addition, when processing power outage alarms with high real-time requirements, it is required to quickly process related alarms through real-time stream computing, such as the user's power outage event analysis, and quickly determine the location of the power outage through multiple interrelated alarm events.

[0046] In addition, an embodiment of the present invention further proposes a data calculation device based on business type, and the data calculation device based on business type includes: Acquisition module, used to obtain business information in real time; The collection module is used to collect data sources in business information according to business scenarios; The computing module is used to perform streaming computing on the data of the data source and output the computed results.

[0047] The embodiment of the present invention further provides a data calculation device based on business type, and the data calculation device based on business type further includes: The cleaning module is used to clean and preprocess the data sources in the business information to obtain the data to be calculated.

[0048] The verification module is used to verify the validity of data before it is stored in the database. It should be noted that those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described device and each module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0049] In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a data calculation program is stored. When the data calculation program is executed by a processor, the following operations are implemented: Get business information in real time; Collect data sources within business information based on business scenarios; Perform streaming calculation on the data of the data source and output the calculated results.

[0050] Furthermore, when the data calculation program is executed by the processor, the following operations are also implemented: Clean and preprocess the data sources in the business information to obtain the data to be calculated.

[0051] Furthermore, when the data calculation program is executed by the processor, the following operations are also implemented: Perform cluster analysis on the data sources to be cleaned; The clustered data sources are classified according to preset rules to obtain multiple cluster classifications.

[0052] Furthermore, when the data calculation program is executed by the processor, the following operations are also implemented: Different clustering classifications are calculated in real time and deployed as multiple instances.

[0053] Furthermore, when the data calculation program is executed by the processor, the following operations are also implemented: Verify the validity of data before entering it into the database.

[0054] The specific embodiments of the computer-readable storage medium of the present invention are basically the same as the embodiments of the above-mentioned application software security vulnerability detection method, and will not be described in detail here.

[0055] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0056] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0057] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0058] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for precise attitude control of unmanned aerial vehicles based on vision and IMU data fusion, characterized in that: The method for precise attitude control of a UAV based on vision and IMU data fusion comprises the following steps: Acquire first data information of the UAV in the NWU coordinate system through the visual odometer, wherein the first data information includes relative position information and attitude information; Acquire second data information of the UAV in the ENU coordinates, where the second data information includes speed and linear acceleration data; Convert the second data information in the ENU coordinate system into the NWU coordinate system, and extract the yaw angle; Based on the first data information and the second data information of the drone, said.

2. The method for precise attitude control of unmanned aerial vehicle based on vision and IMU data fusion as claimed in claim 1, characterized in that: After the step of acquiring the business information in real time and before the step of collecting the data source in the business information according to the business scenario, the method for precise attitude control of the drone based on vision and IMU data fusion further includes: Clean and preprocess the data sources in the business information to obtain the data to be calculated.

3. The method for precise attitude control of unmanned aerial vehicle based on vision and IMU data fusion as claimed in claim 2, characterized in that: The step of cleaning the data source in the business information includes: Perform cluster analysis on the data sources to be cleaned; The clustered data sources are classified according to preset rules to obtain multiple cluster classifications.

4. The method for precise attitude control of unmanned aerial vehicle based on vision and IMU data fusion according to claim 3 is characterized in that: The clustering categories include message queue data, database, cache and file.

5. The method for precise attitude control of unmanned aerial vehicle based on vision and IMU data fusion according to claim 4 is characterized in that: The step of performing streaming calculation on the data of the data source and outputting the calculated result comprises: Different clustering classifications are calculated in real time and deployed as multiple instances.

6. The method for precise attitude control of unmanned aerial vehicle based on vision and IMU data fusion according to claim 4 is characterized in that: After the step of performing streaming calculation on the data of the data source and outputting the calculated result, the method further includes: Verify the validity of data before entering it into the database.

7. A data calculation device based on business changes, characterized in that: The data calculation device based on business change includes: Acquisition module, used to obtain business information in real time; The collection module is used to collect data sources in business information according to business scenarios; The computing module is used to perform streaming computing on the data of the data source and output the computed results.

8. A data computing device based on business changes, characterized in that: The data computing device based on business changes includes: a memory, a processor, and a data computing program stored in the memory and executable on the processor. When the data computing program is executed by the processor, the steps of the data computing method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a data calculation program, and when the data calculation program is executed by a processor, the steps of the data calculation method according to any one of claims 1 to 6 are implemented.

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