Vehicle posture information generation method, apparatus, device, and computer readable medium

Abstract

Embodiments of the present disclosure disclose a vehicle pose information generation method, device, equipment and computer readable medium. A specific embodiment of the method comprises: determining a vehicle movement distance value and a ground normal vector based on a predetermined vehicle positioning information sequence; in response to determining that the vehicle movement distance value meets a preset distance condition, generating a relative pose matrix based on the ground normal vector and a preset initial unit vector; performing standardization processing on the relative pose matrix and vehicle positioning information in the vehicle positioning information sequence that meets a preset time sequence condition respectively to obtain a standardized relative pose matrix and standardized vehicle positioning information; and generating vehicle pose information based on the standardized relative pose matrix and the standardized vehicle positioning information. The embodiment can improve the accuracy of the generated vehicle pose information.

Description

Methods, apparatus, devices and computer-readable media for generating vehicle attitude information Technical Field

[0001] The embodiments disclosed herein relate to the field of computer technology, and more specifically to methods, apparatus, devices, and computer-readable media for generating vehicle attitude information. Background Technology

[0002] The generation of vehicle attitude information is of great significance to the field of autonomous driving. Currently, the common method for generating vehicle attitude information is through pre-calibration.

[0003] However, when using the above method to generate vehicle attitude information, the following technical problems often arise:

[0004] First, the actual position of the vehicle relative to the ground changes over time, while the vehicle attitude information generated in a pre-calibrated manner is fixed. Therefore, the accuracy of the generated vehicle attitude information is insufficient, which in turn leads to the insufficient accuracy of the road information generated using the vehicle attitude information.

[0005] Second, because the attitude relationship between the ground coordinate system and the initial coordinate system is not considered, the accuracy of the generated vehicle attitude information is reduced. As a result, the ability to improve vehicle control stability by using vehicle attitude information as prior information and through vehicle feedforward control is insufficient, which in turn leads to a reduction in the comfort of autonomous vehicles. Summary of the Invention

[0006] The summary portion of this disclosure is intended to provide a brief overview of the concepts, which will be described in detail in the detailed description portion. This summary portion is not intended to identify key or essential features of the claimed technical solutions, nor is it intended to limit the scope of the claimed technical solutions.

[0007] Some embodiments of this disclosure provide methods, apparatus, devices, and computer-readable media for generating vehicle attitude information to address one or more of the technical problems mentioned in the background section above.

[0008] In a first aspect, some embodiments of this disclosure provide a method for generating vehicle attitude information. The method includes: determining a vehicle movement distance value and a ground normal vector based on a predetermined vehicle positioning information sequence; in response to determining that the vehicle movement distance value satisfies a preset distance condition, generating a relative attitude matrix based on the ground normal vector and a preset initial unit vector; standardizing the relative attitude matrix and the vehicle positioning information in the vehicle positioning information sequence that satisfies a preset temporal condition to obtain a standardized relative attitude matrix and standardized vehicle positioning information; and generating vehicle attitude information based on the standardized relative attitude matrix and the standardized vehicle positioning information, wherein the vehicle attitude information includes a target attitude matrix.

[0009] Secondly, some embodiments of this disclosure provide a vehicle attitude information generation apparatus, which includes: a determining unit configured to determine a vehicle movement distance value and a ground normal vector based on a predetermined vehicle positioning information sequence; a first generation unit configured to generate a relative attitude matrix based on the ground normal vector and a preset initial unit vector in response to determining that the vehicle movement distance value satisfies a preset distance condition; a standardization processing unit configured to standardize the relative attitude matrix and the vehicle positioning information in the vehicle positioning information sequence that satisfies a preset timing condition, respectively, to obtain a standardized relative attitude matrix and standardized vehicle positioning information; and a second generation unit configured to generate vehicle attitude information based on the standardized relative attitude matrix and the standardized vehicle positioning information, wherein the vehicle attitude information includes a target attitude matrix.

[0010] Thirdly, some embodiments of this disclosure provide an electronic device, including: one or more processors; and a storage device having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation of the first aspect above.

[0011] Fourthly, some embodiments of this disclosure provide a computer-readable medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect above.

[0012] The various embodiments of this disclosure have the following beneficial effects: the vehicle attitude information generation method of some embodiments of this disclosure can improve the accuracy of the generated vehicle attitude information. Specifically, the reason for the insufficient accuracy of the generated vehicle attitude information is that the actual positional relationship between the vehicle and the ground changes over time, while the vehicle attitude information generated in a pre-calibrated manner is fixed. Based on this, the vehicle attitude information generation method of some embodiments of this disclosure first determines the vehicle movement distance value and the ground normal vector based on a pre-determined vehicle positioning information sequence. By generating the vehicle movement distance value and the ground normal vector, coordinate systems representing the vehicle's location on the ground and the ground's current structure can be used, respectively. Then, in response to determining that the above-mentioned vehicle movement distance value meets a preset distance condition, a relative attitude matrix is ​​generated based on the above-mentioned ground normal vector and a preset initial unit vector. By introducing the preset distance condition, the accuracy of vehicle positioning can be ensured. By generating the relative pose matrix, the attitude change of the vehicle can be determined. Then, the above-mentioned relative attitude matrix and the vehicle positioning information in the above-mentioned vehicle positioning information sequence that meets the preset temporal conditions are respectively standardized to obtain a standardized relative attitude matrix and standardized vehicle positioning information. Standardization processes remove influencing factors in generating vehicle attitude information, thereby improving the accuracy of the generated information. Finally, based on the standardized relative attitude matrix and the standardized vehicle positioning information, vehicle attitude information is generated, including the target attitude matrix. Thus, some embodiments of the vehicle attitude information generation method disclosed herein avoid generating vehicle attitude information through pre-calibration. To improve the accuracy of the generated vehicle attitude information, a method different from commonly used approaches is employed, allowing the vehicle attitude information to change with vehicle movement. This improves the accuracy of the generated vehicle attitude information. Furthermore, it improves the accuracy of road information generated using vehicle attitude information, thereby enhancing driving safety. Attached Figure Description

[0013] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic, and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flowchart of some embodiments of the vehicle attitude information generation method according to the present disclosure;

[0015] Figure 2 is a flowchart of some other embodiments of the vehicle attitude information generation method according to the present disclosure;

[0016] Figure 3 is a schematic diagram of the structure of some embodiments of the vehicle attitude information generation apparatus according to the present disclosure;

[0017] Figure 4 is a schematic diagram of the structure of an electronic device suitable for implementing some embodiments of the present disclosure. Detailed Implementation

[0018] Embodiments of this disclosure will now be described in more detail with reference to the accompanying drawings. While some embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of this disclosure. It should be understood that the accompanying drawings and embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of protection of this disclosure.

[0019] It should also be noted that, for ease of description, only the parts relevant to the invention are shown in the accompanying drawings. Unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other.

[0020] It should be noted that the concepts of "first" and "second" mentioned in this disclosure are used only to distinguish different devices, modules or units, and are not used to limit the order of functions performed by these devices, modules or units or their interdependencies.

[0021] It should be noted that the terms "a" and "a plurality of" used in this disclosure are illustrative rather than restrictive, and those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0022] The names of messages or information exchanged between multiple devices in the embodiments of this disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

[0023] This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] Figure 1 illustrates a flow 100 of some embodiments of the vehicle attitude information generation method according to the present disclosure. The flow 100 of the vehicle attitude information generation method includes the following steps:

[0025] Step 101: Based on the predetermined vehicle positioning information sequence, determine the vehicle movement distance value and ground normal vector.

[0026] In some embodiments, the entity executing the vehicle attitude information generation method can determine the vehicle movement distance value and the ground normal vector based on a pre-determined vehicle positioning information sequence. Each vehicle positioning information in the vehicle positioning information sequence can be historically generated, consecutive frame vehicle positioning information. The vehicle positioning information can be the vehicle's position coordinates. The vehicle movement distance value can be the distance the vehicle has moved within the corresponding time period of consecutive frames. The ground normal vector can be the normal vector of the ground where the vehicle is currently located, and can be used to represent the coordinate system of the ground where the vehicle is currently located.

[0027] In some optional implementations of certain embodiments, the predetermined vehicle positioning information sequence is generated in the following manner:

[0028] The first step is to acquire vehicle inertial measurement data and wheel speed data. Vehicle inertial measurement data can be obtained from the vehicle's inertial measurement unit (IMU), and wheel speed data can be obtained from the odometer.

[0029] The second step involves generating a vehicle positioning information sequence based on the aforementioned vehicle inertial measurement data and wheel speed data. This vehicle positioning information sequence can be generated using a trajectory extrapolation algorithm.

[0030] In some optional implementations of certain embodiments, the vehicle positioning information in the above-mentioned vehicle positioning information sequence may further include a rotation matrix and a translation vector. The execution entity, based on the above-mentioned vehicle positioning information sequence, determines the vehicle movement distance value and the ground normal vector, which may include the following steps:

[0031] The first step is to determine the translation distance between the translation vectors of every two adjacent vehicle positioning information in the above vehicle positioning information sequence, thus obtaining a translation distance value sequence. The translation distance between the translation vectors of every two adjacent vehicle positioning information can be the translation distance between the translation vectors of every two adjacent frames of vehicle positioning information in a continuous series of frames. By determining the translation distance between two adjacent frames, it is easier to determine the vehicle's movement distance.

[0032] The second step is to determine the sum of each translation distance value in the above translation distance value sequence as the vehicle movement distance value.

[0033] In practice, a continuous frame can refer to continuous data within a certain time period (e.g., 0.5 seconds). Therefore, determining the vehicle displacement distance value using the above method will not produce a large error.

[0034] In some optional implementations of certain embodiments, the execution entity determines the vehicle movement distance value and ground normal vector based on the vehicle positioning information sequence, and may further include the following steps:

[0035] The first step is to extract the rotation matrix included in each vehicle positioning information sequence to generate an initial normal vector, thus obtaining an initial normal vector sequence. Specifically, this extraction can be achieved by extracting the third column of the rotation matrix included in the vehicle positioning information as the initial normal vector. This yields the initial normal vector sequence.

[0036] The second step involves low-pass filtering each initial normal vector in the aforementioned initial normal vector sequence to obtain the ground normal vector. Low-pass filtering can be achieved by averaging the values ​​of all initial normal vectors in the sequence to determine the ground normal vector. This further improves the ability of the ground normal vector to represent the terrain's natural structures, thereby ensuring the accuracy of subsequent vehicle attitude information generation.

[0037] In practice, as the vehicle moves over time, its coordinate system changes accordingly. The initial coordinate system can be a world coordinate system constructed with the vehicle's position at startup or the start of vehicle attitude information generation as its origin. The vertical axis of this world coordinate system can be vertically upward, and the plane enclosed by the horizontal and vertical axes can be horizontal. Therefore, the initial normal vector can also be used to represent the vector representation of the vertical axis of the vehicle coordinate system at a given moment within the initial coordinate system. Specifically, since the vehicle's attitude is influenced by the ground structure, making the vehicle's attitude similar to the surface of the ground where the vehicle is located, the vehicle coordinate system can also be used to represent the ground current structure within the vehicle coordinate system. Thus, the ground normal vector generated from the initial normal vector has a stronger representation ability of the ground current structure. This can reduce the estimation error of the ground current structure and improve the accuracy of vehicle attitude information generation. Furthermore, since the constructed world coordinate system can remain unchanged during vehicle attitude information generation, generating vehicle attitude information based on the aforementioned world coordinate system can further improve the accuracy of the generated vehicle attitude information.

[0038] Step 102: In response to determining that the vehicle movement distance value meets the preset distance condition, a relative attitude matrix is ​​generated based on the ground normal vector and the preset initial unit vector.

[0039] In some embodiments, the execution entity may, in response to determining that the vehicle movement distance value meets a preset distance condition, generate a relative attitude matrix in various ways based on the ground normal vector and a preset initial unit vector. The preset distance condition may be that the vehicle movement distance value is within a preset distance interval. The initial unit vector may be the vertical axis of an initial coordinate system. The relative attitude matrix can be used to characterize the attitude relationship between the coordinate system corresponding to the vehicle's location and the initial coordinate system. Since the current structure of the ground where the vehicle is located changes at each moment, the ground normal vector changes accordingly. Therefore, the coordinate system corresponding to the ground also changes.

[0040] In some optional implementations of certain embodiments, the execution entity generates a relative attitude matrix based on the ground normal vector and a preset initial unit vector, which may include the following steps:

[0041] The first step is to determine the rotation vector by multiplying the ground normal vector and the initial unit vector. The rotation vector can be the axis representation of the vehicle coordinate system at the current moment relative to the initial coordinate system. The current moment can be the moment corresponding to the last frame in a consecutive frame.

[0042] The second step is to determine the arccosine of the product of the dot product between the ground normal vector and the initial unit vector as the rotation angle. The rotation angle can be the range of angles by which the vehicle coordinate system changes relative to the initial coordinate system around the aforementioned rotation vector at the current moment.

[0043] The third step is to generate a relative attitude matrix based on the aforementioned rotation vector and rotation angle. This can be achieved by using a pre-defined identity matrix and an exponential mapping method to convert the rotation vector and rotation angle into a rotation matrix. The relative attitude matrix represents the relative change between the rotation matrix in the current vehicle positioning information and the rotation matrix when the vehicle was at the origin of the initial coordinate system.

[0044] As an example, the identity matrix mentioned above could be a 3×3 identity matrix.

[0045] Step 103: Standardize the relative attitude matrix and the vehicle positioning information that meet the preset timing conditions in the vehicle positioning information sequence to obtain the standardized relative attitude matrix and standardized vehicle positioning information.

[0046] In some embodiments, the execution entity can standardize the relative attitude matrix and the vehicle positioning information in the vehicle positioning information sequence that meet preset timing conditions to obtain a standardized relative attitude matrix and standardized vehicle positioning information. The preset timing conditions can be the last frame of vehicle positioning information in the vehicle positioning information sequence, i.e., the vehicle positioning information at the current moment. Standardization can be performed as follows: First, the rotation matrices in the relative attitude matrix and vehicle positioning information can be represented using Euler angles to obtain the relative attitude heading angle matrix, relative attitude pitch angle matrix, relative attitude roll angle matrix, rotation heading angle matrix, rotation pitch angle matrix, and rotation roll angle matrix. Then, one term of the heading angle can be deleted from the Euler angles (i.e., the relative heading angle matrix and rotation heading angle matrix can be deleted). Finally, the product of the relative attitude pitch angle matrix and the relative attitude roll angle matrix can be determined as the standardized relative attitude matrix. The product of the rotation pitch angle matrix and the rotation roll angle matrix can be determined as the standardized vehicle positioning matrix, which serves as the standardized vehicle positioning information.

[0047] Step 104: Generate vehicle attitude information based on the standardized relative attitude matrix and standardized vehicle positioning information.

[0048] In some embodiments, the executing entity may generate vehicle attitude information in various ways based on the standardized relative attitude matrix and the standardized vehicle positioning information. The vehicle attitude information may include a target attitude matrix.

[0049] In some optional implementations of certain embodiments, the above-mentioned execution entity generates vehicle attitude information based on a standardized relative attitude matrix and standardized vehicle positioning information, which may include the following steps:

[0050] The first step is to generate a pose matrix to be processed based on the standardized relative attitude matrix and the standardized vehicle positioning information. Specifically, the pose matrix to be processed can be determined by multiplying the inverse of the standardized vehicle positioning matrix in the standardized vehicle positioning information with the standardized relative attitude matrix.

[0051] The second step is to standardize the aforementioned attitude matrix to obtain the target attitude matrix. Specifically, the aforementioned standardization method can be used to standardize the attitude matrix to obtain the target attitude matrix.

[0052] The third step is to determine the target attitude matrix as the vehicle attitude information.

[0053] The various embodiments of this disclosure have the following beneficial effects: the vehicle attitude information generation method of some embodiments of this disclosure can improve the accuracy of the generated vehicle attitude information. Specifically, the reason for the insufficient accuracy of the generated vehicle attitude information is that the actual positional relationship between the vehicle and the ground changes over time, while the vehicle attitude information generated in a pre-calibrated manner is fixed. Based on this, the vehicle attitude information generation method of some embodiments of this disclosure first determines the vehicle movement distance value and the ground normal vector based on a pre-determined vehicle positioning information sequence. By generating the vehicle movement distance value and the ground normal vector, coordinate systems representing the vehicle's location on the ground and the ground's current structure can be used, respectively. Then, in response to determining that the above-mentioned vehicle movement distance value meets a preset distance condition, a relative attitude matrix is ​​generated based on the above-mentioned ground normal vector and a preset initial unit vector. By introducing the preset distance condition, the accuracy of vehicle positioning can be ensured. By generating the relative pose matrix, the attitude change of the vehicle can be determined. Then, the above-mentioned relative attitude matrix and the vehicle positioning information in the above-mentioned vehicle positioning information sequence that meets the preset temporal conditions are respectively standardized to obtain a standardized relative attitude matrix and standardized vehicle positioning information. Standardization processes remove influencing factors in generating vehicle attitude information, thereby improving the accuracy of the generated information. Finally, based on the standardized relative attitude matrix and the standardized vehicle positioning information, vehicle attitude information is generated, including the target attitude matrix. Thus, some embodiments of the vehicle attitude information generation method disclosed herein avoid generating vehicle attitude information through pre-calibration. To improve the accuracy of the generated vehicle attitude information, a method different from commonly used approaches is employed, allowing the vehicle attitude information to change with vehicle movement. This improves the accuracy of the generated vehicle attitude information. Furthermore, it improves the accuracy of road information generated using vehicle attitude information, thereby enhancing driving safety.

[0054] Referring further to Figure 2, a flow 200 of another embodiment of the vehicle attitude information generation method is shown. Flow 200 of this vehicle attitude information generation method includes the following steps:

[0055] Step 201: Based on the predetermined vehicle positioning information sequence, determine the vehicle movement distance value and ground normal vector.

[0056] Step 202: In response to determining that the vehicle movement distance value meets the preset distance condition, a relative attitude matrix is ​​generated based on the ground normal vector and the preset initial unit vector.

[0057] Step 203: Standardize the relative attitude matrix and the vehicle positioning information that meet the preset timing conditions in the vehicle positioning information sequence to obtain the standardized relative attitude matrix and standardized vehicle positioning information.

[0058] Step 204: Generate vehicle attitude information based on the standardized relative attitude matrix and standardized vehicle positioning information.

[0059] In some embodiments, the specific implementation of steps 201-204 and the resulting technical effects can be referred to steps 101-104 in the embodiments corresponding to Figure 1, and will not be repeated here.

[0060] Step 205: Determine the pitch angle of the relative attitude matrix.

[0061] In some embodiments, the entity executing the vehicle attitude information generation method can determine the pitch angle of the aforementioned relative attitude matrix. Specifically, the relative attitude matrix can be represented using Euler angles to obtain the relative attitude pitch angle matrix. Thus, the pitch angle can be obtained. This pitch angle can be used to characterize the slope of the ground where the vehicle is located at the current moment.

[0062] Step 206: Add the pitch angle to the vehicle attitude information to obtain the target vehicle attitude information.

[0063] In some embodiments, the execution entity can add the pitch angle to the vehicle attitude information to obtain target vehicle attitude information. The target vehicle attitude information can represent the road information where the vehicle is located at the current moment.

[0064] Step 207: Send the target vehicle attitude information to the vehicle control terminal so that the vehicle control terminal can control the vehicle movement.

[0065] In some embodiments, the aforementioned executing entity may send the target vehicle attitude information to the vehicle control terminal so that the vehicle control terminal can control the movement of the vehicle.

[0066] The above embodiments and related contents, as inventive points of this disclosure, solve the second technical problem mentioned in the background section: "Because the attitude relationship between the ground coordinate system and the initial coordinate system is not considered, the accuracy of the generated vehicle attitude information is reduced, resulting in insufficient ability to improve vehicle control stability through feedforward control using vehicle attitude information as prior information, and consequently, reduced comfort of autonomous vehicles." The reason for insufficient vehicle control stability is that the accuracy of the generated vehicle attitude information is reduced because the attitude relationship between the ground coordinate system and the initial coordinate system is not considered, thus resulting in insufficient ability to improve vehicle control stability through feedforward control using vehicle attitude information as prior information. Solving the above factors can achieve the goal of improving vehicle control stability. To achieve this effect, firstly, the above embodiments can improve the accuracy of the generated vehicle attitude information. Specifically, by generating a relative attitude matrix, the attitude relationship between the ground coordinate system and the initial coordinate system can be determined. This can further improve the accuracy of the generated vehicle attitude information. Then, by generating target vehicle attitude information, the attitude relationship between the vehicle and the road surface at the current moment and the road slope can be obtained. This provides the control unit with more accurate prior information about the current road conditions. Consequently, the control unit can adjust vehicle control data promptly based on this prior information, thereby improving the stability of vehicle control. In practice, more power can be allocated to the vehicle during uphill driving to avoid instability caused by insufficient power. This, in turn, improves the comfort of autonomous vehicles.

[0067] As shown in Figure 2, compared to the description of some embodiments corresponding to Figure 1, the flow 200 of the vehicle attitude information generation method in some embodiments of Figure 2 illustrates the steps of generating target vehicle attitude information and sending the target vehicle attitude information to the vehicle control terminal. First, by generating target vehicle attitude information, the ability of the target vehicle attitude information to represent the current road surface structure of the road where the vehicle is located can be further improved. Then, by sending the target vehicle attitude information to the vehicle control terminal, prior information can be provided to the vehicle control terminal, enabling improved vehicle control stability through vehicle feedforward control. This, in turn, improves the comfort of autonomous vehicles.

[0068] Referring further to FIG3, as an implementation of the methods shown in the above figures, this disclosure provides some embodiments of a vehicle attitude information generation device, which correspond to the method embodiments shown in FIG2, and the device can be specifically applied to various electronic devices.

[0069] As shown in Figure 3, a vehicle attitude information generation device 300 in some embodiments includes: a determining unit 301, a first generation unit 302, a standardization processing unit 303, and a second generation unit 304. The determining unit 301 is configured to determine a vehicle movement distance value and a ground normal vector based on a predetermined vehicle positioning information sequence. The first generation unit 302 is configured to generate a relative attitude matrix based on the ground normal vector and a preset initial unit vector in response to determining that the vehicle movement distance value meets a preset distance condition. The standardization processing unit 303 is configured to standardize the relative attitude matrix and the vehicle positioning information in the vehicle positioning information sequence that meets a preset timing condition, respectively, to obtain a standardized relative attitude matrix and standardized vehicle positioning information. The second generation unit 304 is configured to generate vehicle attitude information based on the standardized relative attitude matrix and the standardized vehicle positioning information, wherein the vehicle attitude information includes a target attitude matrix.

[0070] It is understood that the units described in the apparatus 300 correspond to the various steps in the method described with reference to FIG1. ​​Therefore, the operations, features, and beneficial effects described above for the method also apply to the apparatus 300 and the units contained therein, and will not be repeated here.

[0071] Referring now to FIG4, a schematic diagram of the structure of an electronic device 400 suitable for implementing some embodiments of the present disclosure is shown. The electronic device shown in FIG4 is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present disclosure.

[0072] As shown in Figure 4, the electronic device 400 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a storage device 408 into a random access memory (RAM) 403. The RAM 403 also stores various programs and data required for the operation of the electronic device 400. The processing unit 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0073] Typically, the following devices can be connected to I / O interface 405: input devices 406 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 407 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 408 including, for example, magnetic tapes, hard disks, etc.; and communication devices 409. Communication device 409 allows electronic device 400 to communicate wirelessly or wiredly with other devices to exchange data. Although FIG4 shows electronic device 400 with various devices, it should be understood that it is not required to implement or have all of the devices shown. More or fewer devices may be implemented or have instead. Each box shown in FIG4 may represent one device or multiple devices as needed.

[0074] In particular, according to some embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, some embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication device 409, or installed from storage device 408, or installed from ROM 402. When the computer program is executed by processing device 401, it performs the functions defined above in the methods of some embodiments of this disclosure.

[0075] It should be noted that, in some embodiments of this disclosure, the computer-readable medium described above may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In some embodiments of this disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of this disclosure, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0076] In some implementations, clients and servers can communicate using any currently known or future-developed network protocol such as HTTP (Hypertext Transfer Protocol) and can interconnect with digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”), wide area networks (“WANs”), the Internet (e.g., the Internet of Things), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future-developed networks.

[0077] The aforementioned computer-readable medium may be included in the aforementioned device or may exist independently without being assembled into the electronic device. The aforementioned computer-readable medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: determine a vehicle movement distance value and a ground normal vector based on a predetermined vehicle positioning information sequence; in response to determining that the vehicle movement distance value satisfies a preset distance condition, generate a relative attitude matrix based on the ground normal vector and a preset initial unit vector; standardize the relative attitude matrix and the vehicle positioning information in the vehicle positioning information sequence that satisfies a preset timing condition, respectively, to obtain a standardized relative attitude matrix and standardized vehicle positioning information; and generate vehicle attitude information based on the standardized relative attitude matrix and the standardized vehicle positioning information, wherein the vehicle attitude information includes a target attitude matrix.

[0078] Computer program code for performing operations of some embodiments of this disclosure can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0079] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0080] The units described in some embodiments of this disclosure can be implemented in software or hardware. The described units can also be housed in a processor; for example, a processor may be described as including a determining unit, a first generating unit, a normalization processing unit, and a second generating unit. The names of these units do not necessarily limit the specific unit; for example, the determining unit may also be described as "a unit for determining vehicle travel distance values ​​and ground normal vectors".

[0081] The functions described above in this document can be performed at least in part by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), and so on.

[0082] The above description is merely a selection of preferred embodiments of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in the embodiments of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features with similar functions disclosed in the embodiments of this disclosure.

Claims

1. A method for generating vehicle attitude information, comprising: Based on a predetermined sequence of vehicle positioning information, determine the vehicle's travel distance and ground normal vector; In response to determining that the vehicle movement distance value meets a preset distance condition, a relative attitude matrix is ​​generated based on the ground normal vector and a preset initial unit vector; the relative attitude matrix and the vehicle positioning information in the vehicle positioning information sequence that meets a preset temporal condition are respectively standardized to obtain a standardized relative attitude matrix and standardized vehicle positioning information; based on the standardized relative attitude matrix and the standardized vehicle positioning information, vehicle attitude information is generated, wherein the vehicle attitude information includes a target attitude matrix; wherein the predetermined vehicle positioning information sequence is generated by: acquiring vehicle inertial measurement data and wheel speed data; generating a vehicle positioning information sequence based on the vehicle inertial measurement data and wheel speed data; wherein the vehicle positioning information sequence... The vehicle positioning information in the sequence includes rotation matrices and translation vectors; and determining the vehicle movement distance value and ground normal vector based on the vehicle positioning information sequence includes: determining the translation distance value between the translation vectors of every two adjacent vehicle positioning information in the vehicle positioning information sequence to obtain a translation distance value sequence; and determining the sum of each translation distance value in the translation distance value sequence as the vehicle movement distance value; wherein, determining the vehicle movement distance value and ground normal vector based on the vehicle positioning information sequence further includes: extracting the rotation matrix included in each vehicle positioning information in the vehicle positioning information sequence to generate an initial normal vector to obtain an initial normal vector sequence; and performing low-pass filtering on each initial normal vector in the initial normal vector sequence to obtain a ground normal vector.

2. The method according to claim 1, wherein, The method further includes: determining the pitch angle of the relative attitude matrix; adding the pitch angle to the vehicle attitude information to obtain target vehicle attitude information; and sending the target vehicle attitude information to the vehicle control terminal so that the vehicle control terminal can control the vehicle movement.

3. The method according to claim 1, wherein, The step of generating a relative attitude matrix based on the ground normal vector and a preset initial unit vector includes: determining the product of the cross product between the ground normal vector and the initial unit vector as a rotation vector; determining the arccosine of the product of the dot product between the ground normal vector and the initial unit vector as a rotation angle; and generating a relative attitude matrix based on the rotation vector and the rotation angle.

4. The method according to claim 1, wherein, The step of generating vehicle posture information based on the standardized relative posture matrix and the standardized vehicle positioning information includes: generating a posture matrix to be processed based on the standardized relative posture matrix and the standardized vehicle positioning information; performing standardized processing on the posture matrix to be processed to obtain a target posture matrix; and determining the target posture matrix as the vehicle posture information.

5. A vehicle attitude information generation device, comprising: The determining unit is configured to determine the vehicle movement distance value and the ground normal vector based on a predetermined sequence of vehicle positioning information; The first generation unit is configured to generate a relative attitude matrix based on the ground normal vector and a preset initial unit vector in response to determining that the vehicle movement distance value meets a preset distance condition. A standardization processing unit is configured to standardize the relative attitude matrix and the vehicle positioning information in the vehicle positioning information sequence that meet preset timing conditions, respectively, to obtain a standardized relative attitude matrix and standardized vehicle positioning information. A second generation unit is configured to generate vehicle attitude information based on the standardized relative attitude matrix and the standardized vehicle positioning information, wherein the vehicle attitude information includes a target attitude matrix. The predetermined vehicle positioning information sequence is generated by: acquiring vehicle inertial measurement data and wheel speed data; generating a vehicle positioning information sequence based on the vehicle inertial measurement data and wheel speed data; wherein the vehicle positioning information in the vehicle positioning information sequence includes a rotation matrix. The determination of vehicle movement distance value and ground normal vector based on the vehicle positioning information sequence includes: determining the translation distance value between translation vectors in every two adjacent vehicle positioning information in the vehicle positioning information sequence to obtain a translation distance value sequence; and determining the sum of each translation distance value in the translation distance value sequence as the vehicle movement distance value; wherein, the determination of vehicle movement distance value and ground normal vector based on the vehicle positioning information sequence further includes: extracting the rotation matrix included in each vehicle positioning information in the vehicle positioning information sequence to generate an initial normal vector to obtain an initial normal vector sequence; and performing low-pass filtering on each initial normal vector in the initial normal vector sequence to obtain a ground normal vector.

6. An electronic device, comprising: One or more processors; A storage device having stored one or more programs thereon, which, when executed by the one or more processors, cause the one or more processors to implement the method as described in any one of claims 1-4.

7. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, it implements the method as described in any one of claims 1-4.

Images