IGV fusion positioning method, device, equipment and medium

Abstract

The invention relates to the technical field of IGV positioning, in particular to an IGV fusion positioning method, device and equipment and a medium, and the IGV fusion positioning method comprises the following steps: obtaining IGV inertial measurement unit data in a preset time period, and carrying out track plotting to obtain IGV first pose data in the preset time period; obtaining point cloud data of an IGV surrounding environment in a preset time period; second pose data and a first dynamic layer of the IGV are obtained through calculation based on the point cloud data; obtaining an initial map of the IGV surrounding environment and dividing the initial map into an initial static map layer and an initial dynamic map layer; acquiring satellite positioning data of the IGV in a preset time period, updating the initial dynamic layer based on the satellite positioning data in the first dynamic layer, and generating a second dynamic layer; the second dynamic layer and the initial static layer form a real-time updated map; and based on the first pose data, the second pose data and the satellite positioning data, generating an IGV fusion pose, and realizing IGV fusion positioning. According to the invention, IGV positioning can be more accurate and reliable.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of IGV positioning, in particular to an IGV fusion positioning method, device, equipment and medium. BACKGROUND

[0002] In modern port logistics, the application of IGV (Intelligent Guided Vehicle) is increasingly popular. Its efficient and automated characteristics make it an important tool for improving port transportation efficiency. However, in actual operation, especially in the face of dynamic and complex port environment, IGV faces many challenges. Busy ports have large drawbridges, stacked containers like mountains, and various moving vehicles. These facilities and objects not only occupy a lot of space, but also may block satellite signals at different time periods, affecting the accuracy and stability of IGV positioning.

[0003] The accuracy of IGV positioning not only concerns the efficiency of operation, but also directly affects the safety. In a busy port environment, any small positioning error can cause equipment collision, cargo damage, and even personal injury. Therefore, how to accurately position IGV in the port environment has become a problem to be solved. SUMMARY

[0004] In view of the above problems of the prior art, the purpose of the present application is to provide a solution to the above problems of IGV positioning lack of stability and accuracy.

[0005] In order to solve the above problems, the present application adopts the following technical solutions:

[0006] According to the first aspect of the present application, an IGV fusion positioning method is provided, comprising the following steps:

[0007] Obtaining inertial measurement unit data of IGV in a preset period, and using the inertial measurement unit data to obtain first pose data of the IGV in the preset period by track prediction;

[0008] Obtaining point cloud data of the environment around the IGV in the preset period, and calculating second pose data of the IGV and a first dynamic layer reflecting the environment around the IGV in the preset period based on the point cloud data;

[0009] Obtaining an initial map of the environment around the IGV, and dividing the initial map into an initial static layer and an initial dynamic layer; wherein the initial map is generated based on historical map data of the IGV;

[0010] acquire satellite positioning data of the IGV in the preset period, update the initial dynamic layer based on the satellite positioning data in the first dynamic layer, and generate a second dynamic layer; the second dynamic layer and the initial static layer constitute a real-time update map of the IGV in the preset period;

[0011] Based on the first pose data, the second pose data and the satellite positioning data, a fusion pose of the IGV is generated to realize IGV fusion positioning.

[0012] Further, the method for dividing the initial map into the initial static layer and the initial dynamic layer comprises:

[0013] Time series analysis is performed on the historical map data, and map data in the same region of different time periods is compared;

[0014] Based on the feature change amount of the map data in the same region of different time periods, the initial map is divided into the initial static layer and the initial dynamic layer.

[0015] Further, the inertial measurement unit data of the IGV in the preset period is acquired, and the first pose data of the IGV in the preset period is obtained by using the inertial measurement unit data for dead reckoning, comprising:

[0016] The inertial measurement unit data includes acceleration data and angular velocity data;

[0017] The acceleration data is integrated to obtain the linear velocity at each time point, and based on the linear velocity at each time point, the displacement of the IGV in the preset period is obtained;

[0018] The angular velocity data is integrated to obtain the angular velocity at each time point, and based on the angular velocity at each time point, the attitude of the IGV in the preset period is obtained.

[0019] Further, the point cloud data is deformed based on the first pose data, and the second pose data of the IGV and the first dynamic layer reflecting the surrounding environment of the IGV in the preset period are calculated based on the deformed point cloud data.

[0020] Further, based on the first pose data, the second pose data and the satellite positioning data, a fusion pose of the IGV is generated, comprising:

[0021] Extract the feature points of the second pose data;

[0022] Based on the first pose data and the feature points, a residual function is constructed;

[0023] fusing the satellite positioning data into the residual function by using a state fusion algorithm, and minimizing the residual to generate a fused pose of the IGV.

[0024] Further, the state fusion algorithm adopts an extended Kalman filter algorithm.

[0025] Further, the data structure of the real-time updating map adopts an IKD-Tree form, and the nearest acquired data is queried by using a k-nearest neighbor algorithm to update the real-time updating map.

[0026] A second aspect of the present application provides an IGV fusion positioning device, comprising:

[0027] an inertial measurement data acquisition module, configured to acquire inertial measurement unit data of the IGV in a preset time period, and to obtain first pose data of the IGV in the preset time period by using the inertial measurement unit data for dead reckoning;

[0028] a point cloud data acquisition module, configured to acquire point cloud data of an environment around the IGV in the preset time period;

[0029] a satellite positioning data acquisition module, configured to acquire satellite positioning data of the IGV in the preset time period;

[0030] a map generation module, configured to calculate second pose data of the IGV and a first dynamic layer reflecting an environment around the IGV in the preset time period based on the point cloud data; acquire an initial map of the environment around the IGV, and divide the initial map into an initial static layer and an initial dynamic layer; wherein the initial map is generated based on historical map data of the IGV; update the initial dynamic layer based on the first dynamic layer and the satellite positioning data, to generate a second dynamic layer; and the second dynamic layer and the initial static layer constitute a real-time updating map of the IGV in the preset time period;

[0031] a pose generation module, configured to generate a fused pose of the IGV based on the first pose data, the second pose data and the satellite positioning data, to realize IGV fusion positioning.

[0032] A third aspect of the present application provides an electronic device, characterized in that the electronic device comprises a processor and a memory, the memory stores at least one instruction or at least one program, the at least one instruction or the at least one program is loaded and executed by the processor to realize the IGV fusion positioning method as described in any one of the above aspects.

[0033] The fourth aspect of the present application provides a computer readable storage medium, wherein at least one instruction or at least one program is stored in the computer readable storage medium, and the at least one instruction or at least one program is loaded and executed by a processor to implement the IGV fusion positioning method according to any one of the above.

[0034] Thanks to the above technical solutions, the present application has the following beneficial effects:

[0035] The IGV fusion positioning method provided by the embodiment of the present application acquires IGV inertial measurement unit data in a preset period to generate first pose data; acquires point cloud data of a surrounding environment of the IGV in the preset period to generate second pose data and a first dynamic layer; acquires an initial map of the surrounding environment of the IGV and divides the initial map into an initial static layer and an initial dynamic layer; acquires satellite positioning data of the IGV in the preset period, updates the initial dynamic layer based on the satellite positioning data in the first dynamic layer to generate a second dynamic layer; the second dynamic layer and the initial static layer constitute a real-time update map; and based on the first pose data, the second pose data and the satellite positioning data, a fusion pose of the IGV is generated to realize IGV fusion positioning. The inertial measurement unit data can accurately acquire real-time motion dynamics of the IGV, the point cloud data can reflect the relationship between the IGV and the surrounding environment in motion change, and the satellite positioning data can provide global positioning information. The three kinds of data complement each other, effectively reducing the error that may be generated by single data source positioning, and greatly improving the accuracy and reliability of IGV positioning. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained from these drawings without creative labor.

[0037] Figure 1 is a flow chart of the IGV fusion positioning method provided by an embodiment of the present application;

[0038] Figure 2 is a structural diagram of the IGV fusion positioning device provided by an embodiment of the present application;

[0039] Figure 3 is a block diagram of the electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0040] In the following, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative effort belong to the scope of the present application.

[0041] It should be noted that the terms "first", "second" and the like in the description and claims of the present application and the above drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, device, product or apparatus that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or apparatuses.

[0042] An IGV (Intelligent Guided Vehicle) has significant advantages in various production environments due to its high flexibility and intelligent handling. The positioning accuracy of the IGV is an important factor affecting its work efficiency. Some more complex production environments, such as open ports with a large number of dynamically changing objects, challenge the reliability and accuracy of IGV positioning. Specifically, large facilities such as cargo ships, drawbridges, and containers in the port change in real time, which can block satellite positioning of the IGV, and the high similarity of the port environment affects the accuracy of laser point cloud feature extraction and matching. Therefore, embodiments of the present application propose an IGV fusion positioning method to ensure the accuracy and reliability of IGV positioning, as shown in Figure 1 The method includes the following steps S1-S5:

[0043] Step S1: Obtain inertial measurement unit data of the IGV within a preset period, and use the inertial measurement unit data to perform dead reckoning to obtain first pose data of the IGV within the preset period.

[0044] The inertial measurement unit data can be measured and collected by various sensors built into the IGV, which typically include accelerometers and gyroscopes. The inertial measurement unit data can also be measured and collected by an electronic device that integrates the above-mentioned various sensors, i.e., a device commonly referred to as an inertial measurement unit. The inertial measurement unit can refer to the prior art, and embodiments of the present application will not be described here.

[0045] The inertial measurement unit data includes linear acceleration of the IGV in X, Y, and Z axes, angular velocity of the IGV rotating around the X, Y, and Z axes, and heading information of the IGV. Further, the inertial measurement unit data is used to obtain first pose data of the IGV in a preset period through dead reckoning. The pose refers to the position and attitude of the IGV, the position can be expressed in an ENU (East-North-Up) coordinate system, and the attitude can be expressed in the form of a rotation matrix, Euler angles, quaternions, etc.

[0046] It should be noted that the X axis refers to the forward axis of the IGV movement direction, the Y axis refers to the lateral axis of the IGV movement direction, and the Z axis refers to the vertical axis of the IGV movement direction. The above concepts can refer to the known concepts of the prior art, and the embodiments of the present application will not be described here.

[0047] Step S2: Obtain point cloud data of the environment around the IGV in a preset period, and calculate second pose data of the IGV and a first dynamic layer reflecting the environment around the IGV in the preset period based on the point cloud data.

[0048] The method for obtaining the point cloud data can be obtained by a laser radar device arranged on the IGV, or can be obtained by a multi-view camera. The device for obtaining the point cloud data is not limited in the embodiment.

[0049] The method for calculating the second pose data can be calculated based on the point cloud data by using a laser radar odometer. The laser radar odometer refers to an algorithm for recursively estimating the pose state by using a laser radar. It estimates the pose change of the sensor (equivalent to the carrier IGV carrying the sensor in the embodiment) in real time by analyzing the geometric feature matching of the continuous frames of point cloud. The laser radar odometer belongs to the prior art, and the embodiments of the present application will not be described here.

[0050] Based on the point cloud data, the first dynamic layer of the environment around the IGV in the preset period can be generated. The point cloud can be divided into object clusters by a clustering algorithm, and then the dynamic objects can be marked according to the displacement speed of the object clusters in the continuous frames, and the trajectory of the dynamic objects is stored to generate the first dynamic layer. The dynamic object trajectory includes timestamp, position, and speed data, wherein the timestamp is used for alignment with the IGV pose data. The first dynamic layer can be converted into a coordinate system consistent with the pose data to assist the spatial alignment of the IGV and the dynamic objects in the surrounding environment at the same time.

[0051] Step S3: Obtain an initial map of the environment around the IGV, and divide the initial map into an initial static layer and an initial dynamic layer; wherein the initial map is generated based on historical map data of the IGV.

[0052] The initial static layer is used to determine objects that are long-term stable and unchanged in the surrounding environment, and the initial dynamic layer is used to determine objects that move and change in the surrounding environment. Dividing the initial map can improve the accuracy of positioning, enable the IGV to accurately know the surrounding environment, avoid obstacles, and improve the efficiency of updating and loading the map, and reduce the algorithmic cost of updating the map.

[0053] Step S4: acquiring satellite positioning data of the IGV within a preset period, updating the initial dynamic layer based on the satellite positioning data in the first dynamic layer, and generating a second dynamic layer; the second dynamic layer and the initial static layer constitute a real-time updated map of the IGV within the preset period.

[0054] The satellite positioning data can be GNSS (Global Navigation Satellite System) data, i.e., a data set provided by a satellite navigation system (such as GPS, Beidou, GLONASS, Galileo, etc.) to determine the geographic coordinates and time information of any position on the earth's surface or near-earth space. The satellite positioning data includes position information, time information, and motion information of the IGV.

[0055] Step S5: generating a fusion pose of the IGV based on the first pose data, the second pose data, and the satellite positioning data to realize fusion positioning of the IGV.

[0056] Further, in step S1, inertial measurement unit data of the IGV within a preset period is acquired, and the inertial measurement unit data is used to perform dead reckoning to obtain first pose data of the IGV within the preset period, including:

[0057] 1) The inertial measurement unit data includes acceleration data and angular velocity data;

[0058] 2) The acceleration data is integrated to obtain the linear velocity at each time point, and based on the linear velocity at each time point, the displacement of the IGV within the preset period is obtained;

[0059] 3) The angular velocity data is integrated to obtain the angular velocity at each time point, and based on the angular velocity at each time point, the attitude of the IGV within the preset period is obtained.

[0060] Further, in step S2, the point cloud data is deformed based on the first pose data, and the second pose data of the IGV and the first dynamic layer reflecting the surrounding environment of the IGV within the preset period are calculated based on the deformed point cloud data.

[0061] The first pose data calculated by the inertial measurement unit data is aligned in time and space with the point cloud data, and the point cloud data is corrected to compensate for the motion distortion caused by the time difference.

[0062] More specifically, the distortion removal processing can adopt the following method:

[0063] 1) convert the lidar coordinate system of the point cloud data into the coordinate system corresponding to the first pose data;

[0064] 2) find the first pose data corresponding to the timestamp of each point of the point cloud data, and adjust the coordinates corresponding to each point according to the corresponding first pose data;

[0065] 3) convert the adjusted coordinates of each point back to the lidar coordinate system to obtain the point cloud data after distortion removal processing.

[0066] Further, in step S3, the initial map is divided into an initial static layer and an initial dynamic layer, which can be achieved by the following method:

[0067] 1) perform time series analysis on historical map data, and compare map data in the same region at different time periods;

[0068] 2) based on the feature change amount of the map data in the same region at different time periods, divide the initial map into an initial static layer and an initial dynamic layer.

[0069] In addition, a semantic segmentation model can also be used to identify dynamic objects and static objects in the historical data, and finally form the initial static layer and the initial dynamic layer.

[0070] Further, in step S4, the data structure of the real-time updated map adopts the IKD-Tree form, and the nearest acquired data is queried through the k-nearest neighbor algorithm to update the real-time updated map.

[0071] IKD-Tree performs incremental insertion and deletion operations, only adjusts the local tree structure for newly added or removed points, and does not need to be globally reconstructed, which can improve the efficiency of map updating and significantly reduce the computational cost in dynamic environments.

[0072] Further, in step S5, based on the first pose data, the second pose data and the satellite positioning data, a fusion pose of the IGV is generated, including:

[0073] 1) extract feature points of the second pose data;

[0074] 2) construct a residual function based on the first pose data and the feature points;

[0075] 3) The satellite positioning data is incorporated into the residual function using a state fusion algorithm, and the residual is minimized to generate the fused pose of IGV.

[0076] State fusion algorithms can combine data from three different sensors: first pose data, second pose data, and satellite positioning data. Even if one data source fails, the others can still provide valid information, improving the reliability of the positioning method and reducing errors caused by single data sources, thus further improving positioning accuracy.

[0077] More specifically, the state fusion algorithm employs the extended Kalman filter algorithm.

[0078] The Extended Kalman Filter (EKF) algorithm is a recursive filtering algorithm for state estimation of nonlinear systems. It is applicable to situations that require processing nonlinear dynamic models and observation models, and can improve the accuracy of positioning methods and increase the robustness of positioning systems.

[0079] Correspondingly, embodiments of the present invention also provide an IGV fusion positioning device, such as... Figure 2 As shown, the device includes an inertial measurement data acquisition module, a point cloud data acquisition module, a satellite positioning data acquisition module, a map generation module, and a pose generation module.

[0080] The inertial measurement data acquisition module is used to acquire the inertial measurement unit data of the IGV within a preset time period, and to use the inertial measurement unit data to calculate the first attitude data of the IGV within the preset time period.

[0081] The point cloud data acquisition module is used to acquire point cloud data of the IGV's surrounding environment within a preset time period.

[0082] The satellite positioning data acquisition module is used to acquire satellite positioning data of IGV within a preset time period.

[0083] The map generation module is used to calculate the second pose data of the IGV based on point cloud data and the first dynamic layer reflecting the surrounding environment of the IGV within a preset time period; to obtain the initial map of the surrounding environment of the IGV and divide the initial map into an initial static layer and an initial dynamic layer; wherein, the initial map is generated based on the historical map data of the IGV; the initial dynamic layer is updated based on the satellite positioning data in the first dynamic layer to generate the second dynamic layer; the second dynamic layer and the initial static layer constitute the real-time updated map of the IGV within the preset time period.

[0084] The pose generation module is used to generate the fused pose of IGV based on the first pose data, the second pose data, and satellite positioning data, so as to achieve IGV fusion positioning.

[0085] In summary, the IGV fusion positioning method of the embodiment of the application comprises: acquiring IGV inertial measurement unit data in a preset period to generate first pose data; acquiring point cloud data of a surrounding environment of the IGV in the preset period to generate second pose data and a first dynamic map layer; acquiring an initial map of the surrounding environment of the IGV and dividing the initial map into an initial static map layer and an initial dynamic map layer; acquiring satellite positioning data of the IGV in the preset period, updating the initial dynamic map layer based on the satellite positioning data and the first dynamic map layer to generate a second dynamic map layer; the second dynamic map layer and the initial static map layer constitute a real-time updated map; and generating a fusion pose of the IGV based on the first pose data, the second pose data and the satellite positioning data, to realize IGV fusion positioning. The inertial measurement unit data can accurately acquire real-time motion dynamics of the IGV, the point cloud data can reflect the relationship between the IGV and the surrounding environment in motion change, and the satellite positioning data can provide global positioning information. The three kinds of data complement each other, effectively reducing errors that may be generated by single data source positioning, and greatly improving the accuracy and reliability of IGV positioning.

[0086] It should be noted that the device provided in the above embodiment is only used as an example to illustrate the division of the above functional modules in realizing its functions. In actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions. In addition, the device provided in the above embodiment and the corresponding method embodiment belong to the same concept, and the specific implementation process is detailed in the corresponding method embodiment, which will not be described here.

[0087] An embodiment of the application further provides an electronic device, which comprises a processor and a memory, the memory storing at least one instruction or at least one program, the at least one instruction or the at least one program being loaded and executed by the processor to realize the IGV fusion positioning method provided in the above method embodiment.

[0088] The memory can be used to store software programs and modules, and the processor can execute various functional applications and data processing by running the software programs and modules stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, application programs required by functions, etc.; and the data storage area can store data created according to the use of the device, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage device. Accordingly, the memory can also include a memory controller to provide access of the processor to the memory.

[0089] In combination with the drawings attached Figure 3, shown is a block diagram of an apparatus 300 according to one embodiment of the application. Apparatus 300 can include one or more processors 302, system control logic 308 connected to at least one of processors 302, system memory 304 connected to system control logic 308, non-volatile memory (NVM) 306 connected to system control logic 308, and network interface 310 connected to system control logic 308.

[0090] Processors 302 can include one or more single core or multicore processors. Processors 302 can include any combination of general-purpose processors and dedicated processors (e.g., graphics processors, application processors, baseband processors, etc.). In embodiments herein, processors 302 can be configured to perform one or more embodiments of various embodiments as shown in Figure 1

[0091] In some embodiments, system control logic 308 can include any suitable interface controllers to provide for any suitable interface to at least one of processors 302 and / or any suitable device or component in communication with system control logic 308.

[0092] In some embodiments, system control logic 308 can include one or more memory controllers to provide an interface to system memory 304. System memory 304 can be used to load and store data and / or instructions. In some embodiments, system memory 304 of apparatus 300 can include any suitable volatile memory, such as suitable dynamic random access memory (DRAM).

[0093] NVM / memory 306 can include one or more tangible, non-transitory computer readable media for storage of data and / or instructions. In some embodiments, NVM / memory 306 can include any suitable non-volatile memory, such as flash memory, and / or any suitable non-volatile storage device, such as at least one of a Hard Disk Drive (HDD), a Compact Disc (CD) drive, a Digital Versatile Disc (DVD) drive.

[0094] NVM / memory 306 can include a portion of storage resident on a device of apparatus 300, or it can be accessible by the apparatus but not necessarily part of the apparatus. For example, NVM / memory 306 can be accessed over a network via network interface 310.

[0095] ​In particular, system memory 304 and NVM / memory 306 can include, respectively, a temporary copy and a permanent copy of instructions 320. Instructions 320 can include instructions that, when executed by at least one of processors 302, cause device 300 to implement the IGV fusion positioning method as shown in FIG. 1. In some embodiments, instructions 320, hardware, firmware, and / or software components thereof can additionally / alternatively be placed in system control logic 308, network interface 310, and / or processors 302. Figure 1

[0096] Network interface 310 can include a transceiver to provide a radio interface for device 300 to communicate with any other suitable device (e.g., a front-end module, an antenna, etc.) over one or more networks. In some embodiments, network interface 310 can be integrated with other components of device 300. For example, network interface 310 can be integrated with a communication module of processors 302, system memory 304, NVM / memory 306, and firmware devices (not shown) having instructions that, when executed by at least one of processors 302, cause device 300 to implement one or more embodiments of the various embodiments as shown in FIG. 1. Figure 1

[0097] Network interface 310 can further include any suitable hardware and / or firmware to provide a multiple-input multiple-output radio interface. For example, network interface 310 can be a network adapter, a wireless network adapter, a telephone modem, and / or a wireless modem.

[0098] In one embodiment, at least one of processors 302 can be packaged with logic for one or more controllers of system control logic 308 to form a system-in-a-package (SiP). In one embodiment, at least one of processors 302 can be integrated on the same die with logic for one or more controllers of system control logic 308 to form a system-on-a-chip (SoC).

[0099] Device 300 can further include input / output (I / O) devices 312. I / O devices 312 can include a user interface to enable a user to interact with device 300; a peripheral component interface to enable peripheral components to also interact with device 300. In some embodiments, device 300 also includes sensors to determine at least one of environmental conditions and location information related to device 300.

[0100] In some embodiments, the user interface can include, but is not limited to, a display (e.g., a liquid crystal display, a touch screen display, etc.), a speaker, a microphone, one or more cameras (e.g., a still image camera and / or a video camera), a flashlight (e.g., a light emitting diode flash), and a keypad. ​​

[0101] In some embodiments, the peripheral component interfaces can include, but are not limited to, a non-volatile memory port, an audio jack, and a power interface.

[0102] In some embodiments, the sensors can include, but are not limited to, a gyroscope sensor, an accelerometer, a proximity sensor, an ambient light sensor, and a positioning unit. The positioning unit can also be part of or interact with the network interface 310 to communicate with components of a positioning network (e.g., Global Positioning System (GPS) satellites).

[0103] It can be understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the device 300. In other embodiments of the present application, the device 300 can include more or fewer components than illustrated, or combine certain components, or split certain components, or different arrangement of components. The illustrated components can be implemented in hardware, software, or a combination of software and hardware.

[0104] An embodiment of the present application further provides a computer readable storage medium, which can be arranged in an electronic device to save at least one instruction or at least one program related to the method for implementing the IGV fusion positioning method provided by the above-mentioned method embodiments, and the at least one instruction or the at least one program is loaded and executed by the processor to implement the IGV fusion positioning method provided by the above-mentioned method embodiments.

[0105] Optionally, in the embodiments of the present application, the storage medium can include, but is not limited to: a U disk, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0106] An embodiment of the present application further provides a computer program product or a computer program, which includes computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device executes the IGV fusion positioning method provided in the various optional implementation examples.

[0107] It should be noted that the above-mentioned embodiments of the present application are merely intended to describe the present application and are not intended to limit the present application. The above-mentioned embodiments of the present application are described in a progressive manner, and the same or similar parts among the embodiments can be mutually referred to. Each embodiment focuses on the difference from other embodiments. In particular, the device embodiments are described simply because they are basically similar to the method embodiments, and the relevant parts can be referred to the description of the method embodiments.

[0108] The embodiments in the present specification are described in a progressive manner, and the same or similar parts among the embodiments can be mutually referred to. Each embodiment focuses on the difference from other embodiments. In particular, the device embodiments are described simply because they are basically similar to the method embodiments, and the relevant parts can be referred to the description of the method embodiments.

[0109] A person of ordinary skill in the art can understand that all or part of the above-mentioned embodiments can be completed by hardware, or a program instructing relevant hardware, and the program can be stored in a computer readable storage medium, such as a read-only memory, a magnetic disk or an optical disk.

[0110] The above-mentioned embodiments are merely preferred embodiments of the present application, and are not intended to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. An IGV fusion mapping method, characterized by, The method comprises the following steps: acquiring inertial measurement unit data of the IGV in a preset period, and performing dead reckoning on the inertial measurement unit data to obtain first pose data of the IGV in the preset period; acquiring point cloud data of the environment around the IGV in the preset period, and calculating second pose data of the IGV and a first dynamic layer reflecting the environment around the IGV in the preset period based on the point cloud data; acquiring an initial map of the environment around the IGV, and dividing the initial map into an initial static layer and an initial dynamic layer; wherein the initial map is generated based on historical map data of the IGV; acquiring satellite positioning data of the IGV in the preset period, updating the initial dynamic layer based on the first dynamic layer and the satellite positioning data, and generating a second dynamic layer; the second dynamic layer and the initial static layer constitute a real-time update map of the IGV in the preset period; based on the first pose data, the second pose data and the satellite positioning data, generating a fusion pose of the IGV to realize IGV fusion positioning.

2. The IGV fusion mapping method of claim 1, wherein, The method for dividing the initial map into the initial static layer and the initial dynamic layer comprises: performing time series analysis on the historical map data, and comparing map data in the same region in different time periods; based on the feature change amount of the map data in the same region in different time periods, dividing the initial map into the initial static layer and the initial dynamic layer.

3. The IGV fusion mapping method of claim 1, wherein, The method for acquiring inertial measurement unit data of the IGV in a preset period, and performing dead reckoning on the inertial measurement unit data to obtain first pose data of the IGV in the preset period comprises: the inertial measurement unit data comprises acceleration data and angular velocity data; integrating the acceleration data to obtain linear velocity at each time point, and based on the linear velocity at each time point, obtaining displacement of the IGV in the preset period; integrating the angular velocity data to obtain angular velocity at each time point, and based on the angular velocity at each time point, obtaining the attitude of the IGV in the preset period.

4. The IGV fusion mapping method of claim 1, wherein, based on the first pose data, the point cloud data is deformed, and based on the deformed point cloud data, the second pose data of the IGV and the first dynamic layer reflecting the environment around the IGV in the preset period are calculated.

5. The IGV fusion mapping method of claim 1, wherein, based on the first pose data, the second pose data and the satellite positioning data, generating a fusion pose of the IGV, comprises: extracting feature points of the second pose data; based on the first pose data and the feature points, constructing a residual function; using a state fusion algorithm to fuse the satellite positioning data into the residual function, minimizing the residual to generate the fusion pose of the IGV.

6. The IGV fusion mapping method of claim 5, wherein, The state fusion algorithm adopts an extended Kalman filter algorithm.

7. The IGV fusion mapping method of claim 1, wherein, The data structure of the real-time update map adopts an IKD-Tree form, and the nearest acquired data is queried through a k-nearest neighbor algorithm to update the real-time update map.

8. An IGV fusion positioning device, characterized by, The method comprises the following steps: An inertial measurement data acquisition module is configured to acquire inertial measurement unit data of the IGV in a preset time period, and to obtain first pose data of the IGV in the preset time period by using the inertial measurement unit data for dead reckoning; A point cloud data acquisition module is configured to acquire point cloud data of an environment surrounding the IGV in the preset time period; A satellite positioning data acquisition module is configured to acquire satellite positioning data of the IGV in the preset time period; A map generation module is configured to calculate second pose data of the IGV and a first dynamic layer reflecting an environment surrounding the IGV in the preset time period based on the point cloud data, to acquire an initial map of the environment surrounding the IGV, and to divide the initial map into an initial static layer and an initial dynamic layer. The initial map is generated based on historical map data of the IGV. The initial dynamic layer is updated based on the satellite positioning data and the first dynamic layer to generate a second dynamic layer. The second dynamic layer and the initial static layer constitute a real-time updated map of the IGV in the preset time period. A pose generation module is configured to generate a fused pose of the IGV based on the first pose data, the second pose data, and the satellite positioning data, so as to realize IGV fused positioning.

9. An electronic device, comprising: The electronic device includes a processor and a memory. The memory stores at least one instruction or at least one program. The at least one instruction or the at least one program is loaded and executed by the processor to implement the IGV fused positioning method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores at least one instruction or at least one program. The at least one instruction or the at least one program is loaded and executed by the processor to implement the IGV fused positioning method according to any one of claims 1-7.

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