Two-wheeled vehicle control method and device, electronic equipment and readable storage medium

Abstract

The invention relates to the technical field of two-wheeled vehicle unmanned driving, and provides a two-wheeled vehicle control method and device, electronic equipment and a readable storage medium. The method comprises the steps that target tasks of candidate two-wheeled vehicles are acquired, and the target tasks comprise a space trajectory task, a complete constraint task and a non-complete constraint task; obtaining a current vehicle state of the candidate two-wheeled vehicle, and calculating a target feedback value of the target task according to the current vehicle state; calculating a target acceleration of the target task according to the target feedback value; constructing a quadratic programming problem according to the target task and the target acceleration; the quadratic programming problem is solved, the control torque of the candidate two-wheel vehicle is calculated based on the calculation result of the quadratic programming problem, and the control torque comprises the handlebar steering torque and the rear wheel driving torque. According to the technical scheme provided by one or more implementation modes, the motion mode of the two-wheeled vehicle can be accurately controlled, and unmanned driving tasks of various two-wheeled vehicles are achieved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of two-wheeled vehicle unmanned driving, in particular to a two-wheeled vehicle control method and device, electronic equipment and readable storage medium. BACKGROUND

[0002] A two-wheeled vehicle (such as a bicycle, a motorcycle, a balance car, etc.) is a ground vehicle supported by two wheels. The unmanned driving technology of a two-wheeled vehicle is essentially a multi-task control technology, which needs to realize different control tasks such as vehicle body balance and trajectory tracking. In application scenarios such as logistics distribution, shared transportation and special operation, the research on the unmanned driving technology of a two-wheeled vehicle can significantly improve the working efficiency of the two-wheeled vehicle and reduce the use cost of the two-wheeled vehicle.

[0003] In the prior art, the vehicle body balance and trajectory tracking of a two-wheeled vehicle can be realized by an external or internal model decomposition method. However, this method usually relies on a simplified kinematics and dynamics model, and is difficult to be used for motion control of an actual two-wheeled vehicle.

[0004] In addition, the trajectory tracking problem in the unmanned driving technology of a two-wheeled vehicle is complex, which may involve various trajectory tracking tasks such as trajectory tracking of a contact point between a rear wheel of the two-wheeled vehicle and the ground, trajectory tracking of a contact point between a front wheel of the two-wheeled vehicle and the ground, and trajectory tracking of a mass center of the two-wheeled vehicle. Therefore, the multi-task control method of a two-wheeled vehicle needs to have a certain universality. SUMMARY

[0005] Therefore, one or more embodiments of the present disclosure provide a two-wheeled vehicle control method and device, electronic equipment and readable storage medium, which can accurately control the motion mode of a two-wheeled vehicle and realize various unmanned driving tasks of the two-wheeled vehicle.

[0006] In a first aspect, the present disclosure provides a control method for a two-wheeled vehicle, the method comprising: obtaining a target task of a candidate two-wheeled vehicle, the target task comprising a spatial trajectory task, a holonomic constraint task, and a non-holonomic constraint task; the spatial trajectory task comprising at least one of a position parameter, an attitude parameter, and a turning angle parameter of the candidate two-wheeled vehicle, the holonomic constraint task comprising a height parameter of a wheel-ground contact point of the candidate two-wheeled vehicle, and the non-holonomic constraint task comprising a tangential velocity parameter of the wheel-ground contact point of the candidate two-wheeled vehicle; obtaining a current vehicle state of the candidate two-wheeled vehicle, and calculating a target feedback value of the target task according to the current vehicle state; calculating a target acceleration of the target task according to the target feedback value; constructing a quadratic programming problem according to the target task and the target acceleration, the quadratic programming problem comprising a target variable, a target function, and a target constraint; solving the quadratic programming problem, and calculating a control torque of the candidate two-wheeled vehicle based on a calculation result of the target variable, the control torque comprising a handlebar steering torque and a rear wheel driving torque, the control torque being used to control a motion mode of the candidate two-wheeled vehicle.

[0007] In a second aspect, the present disclosure provides a control device for a two-wheeled vehicle, the device comprising: a task determination unit configured to obtain a target task of a candidate two-wheeled vehicle, the target task comprising a spatial trajectory task, a holonomic constraint task, and a non-holonomic constraint task; the spatial trajectory task comprising at least one of a position parameter, an attitude parameter, and a turning angle parameter of the candidate two-wheeled vehicle, the holonomic constraint task comprising a height parameter of a wheel-ground contact point of the candidate two-wheeled vehicle, and the non-holonomic constraint task comprising a tangential velocity parameter of the wheel-ground contact point of the candidate two-wheeled vehicle; a state determination unit configured to obtain a current vehicle state of the candidate two-wheeled vehicle, and calculate a target feedback value of the target task according to the current vehicle state; an acceleration determination unit configured to calculate a target acceleration of the target task according to the target feedback value; a planning determination unit configured to construct a quadratic programming problem according to the target task and the target acceleration, the quadratic programming problem comprising a target variable, a target function, and a target constraint; and a control determination unit configured to solve the quadratic programming problem, and calculate a control torque of the candidate two-wheeled vehicle based on a calculation result of the target variable, the control torque comprising a handlebar steering torque and a rear wheel driving torque, the control torque being used to control a motion mode of the candidate two-wheeled vehicle.

[0008] In a third aspect, the present disclosure provides an electronic device, the electronic device comprising a memory and a processor, the memory being configured to store a computer program, the computer program being configured to be executed by the processor to implement the control method for a two-wheeled vehicle.

[0009] In a fourth aspect, the disclosure provides a computer readable storage medium for storing a computer program, which, when executed by a processor, implements the two-wheeled vehicle control method described above.

[0010] The technical solution provided by one or more embodiments of the disclosure can complete the motion mode control of the two-wheeled vehicle by using the handlebar steering torque and the rear wheel driving torque, without the need for auxiliary equipment such as a control torque gyroscope, and has low energy consumption and strong maneuverability in the control process.

[0011] The technical solution provided by one or more embodiments of the disclosure constructs a quadratic programming problem according to a target task and a target acceleration. Since the target task includes a spatial trajectory task, a complete constraint task and a non-complete constraint task, the quadratic programming problem is implemented based on a complete dynamics model. The deviation of the planning result of the quadratic programming problem from the actual motion mode of the two-wheeled vehicle is small, thereby ensuring high-precision control of the two-wheeled vehicle. Moreover, the target acceleration is determined according to a target feedback value, and the target feedback value is determined according to a current vehicle state, thereby ensuring the real-time performance and reliability of the planning result and further ensuring the precision of the control torque.

[0012] The technical solution provided by one or more embodiments of the disclosure establishes a quadratic programming problem based on a target task to solve a control torque. According to different actual application scenarios, the target task can be adaptively adjusted. In this way, the control method has high versatility and can be applied to various unmanned driving tasks such as tracking, formation, tracking and obstacle avoidance under the condition of keeping the vehicle body balanced. BRIEF DESCRIPTION OF DRAWINGS

[0013] The features and advantages of the embodiments of the disclosure will be more clearly understood through reference to the accompanying drawings, which are schematic and should not be understood as limiting the disclosure in any way, in which: Figure 1 a step schematic diagram of a two-wheeled vehicle control method in one embodiment of the disclosure is shown; Figure 2 a functional module schematic diagram of a two-wheeled vehicle control device in one embodiment of the disclosure is shown; Figure 3 a structural schematic diagram of an electronic device in one embodiment of the disclosure is shown. DETAILED DESCRIPTION

[0014] In order to make the purposes, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by a person of ordinary skill in the art without creative work fall within the protection scope of the present disclosure.

[0015] The double-wheeled vehicle control method provided by one of the embodiments of the present disclosure can be applied to a double-wheeled vehicle control device. The double-wheeled vehicle control device can be an electronic device with data processing capability. For example, the double-wheeled vehicle control device can be a vehicle-mounted computing device, a field control device (such as a personal computer, a mobile phone, a tablet for ordering), a remote control center, etc. In addition, the method can also be applied to software running in the above-mentioned double-wheeled vehicle control device.

[0016] Please refer to Figure 1 The double-wheeled vehicle control method of the landing page provided by one of the embodiments of the present disclosure can include the following steps.

[0017] S1: Obtain a target task of a candidate double-wheeled vehicle, the target task including a spatial trajectory task, a complete constraint task and an incomplete constraint task; the spatial trajectory task including at least one of a position parameter, an attitude parameter and a steering angle parameter of the candidate double-wheeled vehicle, the complete constraint task including a height parameter of a wheel-ground contact point of the candidate double-wheeled vehicle, and the incomplete constraint task including a tangential velocity parameter of the wheel-ground contact point of the candidate double-wheeled vehicle.

[0018] In the embodiment, the generalized coordinates of the candidate double-wheeled vehicle can be defined as wherein is the coordinate of the mass center of the rear frame of the double-wheeled vehicle in the world coordinate system, is the yaw angle of the double-wheeled vehicle, is the roll angle of the double-wheeled vehicle, is the pitch angle of the double-wheeled vehicle, is the handlebar steering angle of the double-wheeled vehicle, are the rear wheel and front wheel steering angles of the double-wheeled vehicle, respectively.

[0019] In the embodiment, a series of spatial trajectory tasks of the candidate double-wheeled vehicle can be determined according to different unmanned tasks to be performed . Wherein, The spatial trajectory task is usually related to at least one of a position parameter (for example, one or more coordinates of the rear axle center of mass in a world coordinate system), an attitude parameter (for example, one or more of a yaw angle, a roll angle, and a pitch angle), and a steering angle parameter (for example, one or more of a handlebar steering angle, a rear wheel steering angle, and a front wheel steering angle).

[0020] In the embodiment, for different unmanned tasks, complete constraint tasks and non-complete constraint tasks of the candidate two-wheeled vehicle can be determined to ensure the completeness of the dynamic model in the subsequent calculation process.

[0021] In some embodiments, the complete constraint task includes a height parameter of the rear wheel and ground contact point and a height parameter of the front wheel and ground contact point; and the non-complete constraint task includes a tangential velocity parameter of the rear wheel and ground contact point in a first tangential direction, a tangential velocity parameter of the front wheel and ground contact point in the first tangential direction, a tangential velocity parameter of the rear wheel and ground contact point in a second tangential direction, and a tangential velocity parameter of the front wheel and ground contact point in the second tangential direction.

[0022] In an actual application example, the heights (z coordinates) of the rear wheel and the front wheel and ground contact points of the candidate two-wheeled vehicle are respectively , wherein That is, the complete constraint task of the candidate two-wheeled vehicle can be The x and y direction velocity components of the rear wheel and ground contact point of the candidate two-wheeled vehicle and the x and y direction velocity components of the front wheel and ground contact point are respectively , wherein That is, the non-complete constraint task of the candidate two-wheeled vehicle can be In particular, it is defined that , which represents the generalized velocity of the candidate two-wheeled vehicle.

[0023] S2: obtaining a current vehicle state of the candidate two-wheeled vehicle, and calculating a target feedback value of the target task according to the current vehicle state.

[0024] In the embodiment, the current vehicle state of the candidate two-wheeled vehicle can be estimated by using an inertial measurement unit (IMU) and an encoder (equivalent to a wheel speed sensor), to determine the current generalized coordinates and the generalized velocity of the candidate two-wheeled vehicle.

[0025] In the embodiment, according to the current generalized coordinates and the generalized velocity of the candidate two-wheeled vehicle, the spatial trajectory feedback of the candidate two-wheeled vehicle can be calculated as , , that is, the target feedback value of the spatial trajectory task is calculated; the current generalized coordinates and the generalized velocity of the candidate two-wheeled vehicle are obtained , , that is, the target feedback value of the complete constraint task is calculated; the current generalized coordinates and the generalized velocity of the candidate two-wheeled vehicle are obtained , , that is, the target feedback value of the non-complete constraint task is calculated.

[0026] S3: According to the target feedback value, the target acceleration of the target task is calculated.

[0027] In the embodiment, the target acceleration is determined according to the target feedback value, and the target feedback value is determined according to the current vehicle state, which ensures the real-time and reliability of the subsequent planning result, and guarantees the accuracy of the finally generated control torque.

[0028] In some embodiments, the target acceleration of the target task is calculated according to the target feedback value, including: obtaining a target reference value of the target task; determining a target error according to the target feedback value and the target reference value; and calculating the target acceleration of the target task based on the target error.

[0029] Specifically, if the target task is a spatial trajectory task, a spatial trajectory reference value of the spatial trajectory task and a spatial trajectory feedback value are obtained, and then a target error is calculated ; if the target task is a complete constraint task, a reference value of the complete constraint task and a feedback value are obtained, and then a target error is calculated ; if the target task is a non-complete constraint task, a reference value of the non-complete constraint task and a feedback value are obtained, and then a target error ， is calculated

[0030] In some embodiments, if the target task is the spatial trajectory task, the target acceleration is calculated based on the proportional and differential control operation result of the target error. For example, the target acceleration of the spatial trajectory task is , and are the proportional and differential coefficients respectively, .

[0031] In some embodiments, if the target task is the holonomic task, the target acceleration is calculated based on the proportional-derivative control operation result of the target error. For example, the target acceleration of the holonomic task is , and are the proportional and differential coefficients respectively, .

[0032] In some embodiments, if the target task is the nonholonomic constraint task, the target acceleration is calculated based on the differential control operation result of the target error. For example, the target acceleration of the nonholonomic constraint task is , is the differential coefficient, .

[0033] S4: Construct a quadratic programming problem according to the target task and the target acceleration, where the quadratic programming problem includes a target variable, an target function, and a target constraint.

[0034] In this implementation, the quadratic programming (QP) problem is a convex optimization problem. Its advantages include: convex optimization, which guarantees a globally optimal solution; mature solution algorithms (such as the interior point method and the active set method), which ensure efficient solutions; and the ability to handle multiple coupled variables simultaneously, making it suitable for real-time decision-making scenarios.

[0035] In this implementation, the target variable is the variable to be optimized; the objective function is a quadratic polynomial; and the target constraints include linear equations (such as dynamic equations) and inequalities (such as acceleration limits and torque limits). The target variable, objective function, and target constraints together constitute a standard quadratic programming problem.

[0036] In this embodiment, the quadratic programming problem can be constructed based on the first kind of Lagrange equation. The target variable can include the generalized acceleration of the candidate two-wheeled vehicle. , and the Lagrange multiplier The Lagrange multiplier is used to determine the influencing factor (equivalent to the weight) of the target constraint. The target task and target acceleration are mainly used to construct the objective function.

[0037] In some embodiments, the objective function construction process includes: determining the quadratic operator of the target task based on the target acceleration and the second-order derivative of the target task; and determining the objective function according to the quadratic operator and the target weight of the target task.

[0038] In some embodiments, the objective function formula includes:

[0039] in, represents the second-order derivative of the target task, represents the target acceleration, represents the target weight, Indicates the total number of target tasks. This objective function has fully considered the comprehensive planning of spatial trajectory tasks, complete constraint tasks, and non-complete constraint tasks, and is a complete dynamic model for candidate two-wheeled vehicles.

[0040] It should be noted that It can be expressed as The linear relationship: , Among them, the Jacobi matrix ,satisfy , for Derivative with respect to time.

[0041] In some implementations, the target constraints include dynamic constraints, ground reaction force constraints, and joint torque constraints.

[0042] Specifically, the dynamic constraint is the underactuated dynamic equation of the two-wheeled vehicle, which is obtained according to the first-kind Lagrange equation, that is,

[0043] in, They represent the mass matrix, Coriolis force and gravity terms, and first-order linear constraint coefficient matrix of the underactuated component in generalized coordinates, respectively.

[0044] The ground reaction force constraint includes normal unilateral constraint and tangential friction cone constraint, namely

[0045]

[0046] in, are the components of the contact force between the rear wheel and the ground in the three coordinate directions, for the three coordinate directions of the front wheel contact force, for the friction coefficient.

[0047] the joint torque constraint is

[0048]

[0049] wherein, respectively represent the mass matrix in the generalized coordinates with respect to the driving components, the Coriolis force and gravity term, the first order linear constraint coefficient matrix, and respectively represent the lower limit and the upper limit of the driving torque, and respectively represent the lower limit and the upper limit of the generalized acceleration.

[0050] S5: solving the quadratic programming problem, and calculating the control torque of the candidate two-wheeled vehicle based on the calculation result of the target variable, the control torque including a handlebar steering torque and a rear wheel driving torque, the control torque being used to control the motion mode of the candidate two-wheeled vehicle.

[0051] In the embodiment, the target variable includes the generalized acceleration of the candidate two-wheeled vehicle, and the Lagrange multiplier of the quadratic programming problem. The Lagrange multiplier is used to determine the influence factor of the target constraint.

[0052] In the embodiment, the parameter adjustment determines a set of suitable control parameters (including the proportional coefficient , the differential coefficient and the target weight ), and then the QP problem can be solved. Solving the quadratic programming problem includes: solving the target variable group that makes the target function reach the minimum value under the constraint condition of the target constraint. According to the solved target variable group , the control torque of the candidate two-wheeled vehicle can be further calculated.

[0053] In some embodiments, the calculation of the control torque of the candidate two-wheeled vehicle based on the calculation result of the target variable includes: determining a first operator based on the generalized acceleration and the mass matrix of the candidate two-wheeled vehicle; determining a second operator based on the Lagrange multiplier and the first order linear constraint coefficient matrix of the candidate two-wheeled vehicle; and determining the control torque according to the first operator, the second operator, and the Coriolis force and gravity term of the candidate two-wheeled vehicle.

[0054] In one practical application example, the formula of the control torque includes: , wherein, denotes a mass matrix, denotes a Coriolis force and gravity term, denotes the first-order linear constraint coefficient matrix, denotes the generalized acceleration, denotes the Lagrange multiplier, denotes the control torque.

[0055] The control torque can be specifically denoted as , is a handlebar steering torque, is a rear wheel driving torque. The control torque is input to the two-wheeled vehicle control device, so as to complete accurate control of the two-wheeled vehicle motion mode, and realize various actual unmanned driving tasks of the two-wheeled vehicle.

[0056] The technical scheme provided by one or more embodiments of the present disclosure can complete motion mode control of the two-wheeled vehicle by using the handlebar steering torque and the rear wheel driving torque, without the need for auxiliary equipment such as a control torque gyro, and the control process has low energy consumption and strong maneuverability.

[0057] The technical scheme provided by one or more embodiments of the present disclosure constructs a quadratic programming problem according to a target task and a target acceleration. Since the target task includes a spatial trajectory task, a complete constraint task and a non-complete constraint task, the quadratic programming problem is implemented based on a complete dynamics model. The planning result of the quadratic programming problem has a small deviation from the actual motion mode of the two-wheeled vehicle, thereby ensuring high-precision control of the two-wheeled vehicle. Moreover, the target acceleration is determined according to a target feedback value, and the target feedback value is determined according to a current vehicle state, thereby ensuring real-time performance and reliability of the planning result, and further ensuring precision of the control torque.

[0058] The technical scheme provided by one or more embodiments of the present disclosure establishes a quadratic programming problem based on a target task, and solves a control torque. According to different actual application scenarios, the target task can be adaptively adjusted. In this way, the control method has high versatility and can be applied to various unmanned driving tasks such as tracking, formation, tracking and obstacle avoidance under the condition of keeping the vehicle body balanced.

[0059] Referring to Figure 2 , the present disclosure further provides a two-wheeled vehicle control device, which comprises: The task determination unit 100 is configured to obtain a target task for a candidate two-wheeled vehicle, wherein the target task includes a spatial trajectory task, a holonomic constraint task, and a nonholonomic constraint task; the spatial trajectory task includes at least one of a position parameter, a posture parameter, and a rotation angle parameter of the candidate two-wheeled vehicle; the holonomic constraint task includes a height parameter of a contact point between the candidate two-wheeled vehicle's wheel and the ground; and the nonholonomic constraint task includes a tangential velocity parameter of a contact point between the candidate two-wheeled vehicle's wheel and the ground. a state determination unit 200 for obtaining a current vehicle state of the candidate two-wheeled vehicle and calculating a target feedback value of the target task based on the current vehicle state; an acceleration determination unit 300, configured to calculate a target acceleration of the target task according to the target feedback value; A planning determination unit 400 is configured to construct a quadratic programming problem according to the target task and the target acceleration, wherein the quadratic programming problem includes a target variable, an objective function, and a target constraint; The control determination unit 500 is used to solve the quadratic programming problem and calculate the control torque of the candidate two-wheeled vehicle based on the calculation result of the target variable. The control torque includes the handlebar steering torque and the rear wheel drive torque. The control torque is used to control the motion mode of the candidate two-wheeled vehicle.

[0060] In one embodiment, the complete constraint task includes a height parameter of the rear wheel contact point with the ground, and a height parameter of the front wheel contact point with the ground; the non-complete constraint task includes a tangential velocity parameter of the rear wheel contact point with the ground in a first tangential direction, a tangential velocity parameter of the front wheel contact point with the ground in a first tangential direction, a tangential velocity parameter of the rear wheel contact point with the ground in a second tangential direction, and a tangential velocity parameter of the front wheel contact point with the ground in a second tangential direction.

[0061] In one embodiment, the acceleration determination unit 300 is specifically configured to obtain a target reference value of the target task; determine a target error according to the target feedback value and the target reference value; and calculate the target acceleration of the target task based on the target error.

[0062] In one embodiment, the target acceleration of the target task is calculated based on the target error, including at least one of the following: if the target task is the spatial trajectory task, the target acceleration is calculated based on the proportional differential control operation result of the target error; if the target task is the complete constraint task, the target acceleration is calculated based on the proportional differential control operation result of the target error; if the target task is the non-complete constraint task, the target acceleration is calculated based on the differential control operation result of the target error.

[0063] In one embodiment, the process of constructing the objective function by the planning determination unit 400 includes: determining a quadratic operator of the target task based on the target acceleration and a second derivative of the target task; and determining the objective function according to the quadratic operator and a target weight of the target task.

[0064] In one embodiment, the target constraints include a dynamics constraint, a ground reaction force constraint, and a joint torque constraint.

[0065] In one embodiment, the formula of the objective function includes:

[0066] wherein, denotes a second derivative of the target task, denotes the target acceleration, denotes the target weight, denotes a total number of the target tasks.

[0067] In one embodiment, the target variables include a generalized acceleration of the candidate two-wheeled vehicle and a Lagrange multiplier of the quadratic programming problem, the Lagrange multiplier being used to determine an influence factor of the target constraints. The control determination unit 500 solves the quadratic programming problem, including: solving the target variables under the constraint conditions of the target constraints so that the objective function reaches a minimum value.

[0068] In one embodiment, the control determination unit 500 calculates the control torque of the candidate two-wheeled vehicle based on the calculation results of the target variables, including: determining a first operator based on the generalized acceleration and a mass matrix of the candidate two-wheeled vehicle; determining a second operator based on the Lagrange multiplier and a first-order linear constraint coefficient matrix of the candidate two-wheeled vehicle; and determining the control torque according to the first operator, the second operator, and a Coriolis force and gravity term of the candidate two-wheeled vehicle.

[0069] In one embodiment, the formula of the control torque includes: , wherein, denotes the mass matrix, denotes the Coriolis force and gravity term, denotes the first-order linear constraint coefficient matrix, denotes the generalized acceleration, denotes the Lagrange multiplier, denotes the control torque.

[0070] The various units illustrated in the above embodiments can be implemented by a computer chip, or by a product with certain functions. A typical implementation device is a computer. Specifically, the computer can be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0071] For the convenience of description, the above device is described as various units respectively described in functions. Of course, the functions of the units can be implemented in one or more software and / or hardware when implementing the present application.

[0072] Referring to Figure 3 The present disclosure also provides an electronic device, which includes a memory and a processor, the memory is configured to store a computer program, and the computer program is configured to implement the above-described tandem bicycle control method when executed by the processor.

[0073] The present disclosure also provides a computer-readable storage medium, which is configured to store a computer program, and the computer program is configured to implement the above-described tandem bicycle control method when executed by a processor.

[0074] The processor can be a central processing unit (CPU). The processor can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination thereof.

[0075] The memory is a non-transitory computer-readable storage medium, which can be configured to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions / modules corresponding to the methods in the embodiments of the present disclosure. The processor executes various functions and data processing of the processor by running the non-transitory software programs, instructions and modules stored in the memory, i.e. implements the methods in the above method embodiments.

[0076] The memory can include a program storage area and a data storage area. The program storage area can store an operating system and applications required by at least one function. The data storage area can store data created by the processor and the like. In addition, the memory can include a high-speed random access memory and can further include a non-transitory memory such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid state memory device. In some embodiments, the memory can optionally include a memory that is remotely located with respect to the processor and can be connected to the processor through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0077] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium, and when the program is executed, the processes of the above-mentioned embodiments of the methods can be included. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory, a hard disk drive (HDD), or a solid-state drive (SSD), etc. The storage medium can also include a combination of the above-mentioned types of memories.

[0078] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the difference from other embodiments. In particular, the embodiments of the apparatus, device, and storage medium are described simply because they are basically similar to the method embodiments, and the relevant parts can be referred to the part of the description of the method embodiments.

[0079] The above only describes the embodiments of the present application and is not intended to limit the present application. Those skilled in the art can make various modifications and changes to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the scope of the claims of the present application.

[0080] Although the embodiments of the present disclosure are described in conjunction with the drawings, various modifications and changes can be made by those skilled in the art without departing from the spirit and scope of the present disclosure, and such modifications and changes fall within the scope defined by the appended claims.

Claims

1. A two-wheeled vehicle control method, characterized in that: The method comprises: Obtaining a target task for a candidate two-wheeled vehicle, the target task comprising a spatial trajectory task, a holonomic constraint task, and a nonholonomic constraint task; the spatial trajectory task comprising at least one of a position parameter, a posture parameter, and a rotation angle parameter of the candidate two-wheeled vehicle; the holonomic constraint task comprising a height parameter of a contact point between the candidate two-wheeled vehicle's wheel and the ground; and the nonholonomic constraint task comprising a tangential velocity parameter of a contact point between the candidate two-wheeled vehicle's wheel and the ground; Obtaining a current vehicle state of the candidate two-wheeled vehicle, and calculating a target feedback value of the target task based on the current vehicle state; Calculating the target acceleration of the target task according to the target feedback value; Constructing a quadratic programming problem according to the target task and the target acceleration, wherein the quadratic programming problem includes a target variable, an objective function, and a target constraint; Solve the quadratic programming problem and calculate the control torque of the candidate two-wheeled vehicle based on the calculation result of the target variable, wherein the control torque includes a handlebar steering torque and a rear wheel drive torque, and the control torque is used to control the motion mode of the candidate two-wheeled vehicle.

2. The method according to claim 1, characterized in that The complete constraint task includes the height parameters of the rear wheel contact point with the ground, and the height parameters of the front wheel contact point with the ground; the non-complete constraint task includes the tangential velocity parameters of the rear wheel contact point with the ground in the first tangential direction, the tangential velocity parameters of the front wheel contact point with the ground in the first tangential direction, the tangential velocity parameters of the rear wheel contact point with the ground in the second tangential direction, and the tangential velocity parameters of the front wheel contact point with the ground in the second tangential direction.

3. The method according to claim 1, characterized in that Calculating the target acceleration of the target task according to the target feedback value includes: Obtaining a target reference value for the target task; determining a target error according to the target feedback value and the target reference value; The target acceleration of the target task is calculated based on the target error.

4. The method according to claim 3, characterized in that Calculating the target acceleration of the target task based on the target error includes at least one of the following: If the target task is the spatial trajectory task, calculating the target acceleration based on a proportional differential control operation result of the target error; If the target task is the holonomically constrained task, calculating the target acceleration based on a proportional-derivative control operation result of the target error; If the target task is the nonholonomic constrained task, the target acceleration is calculated based on a differential control operation result of the target error.

5. The method according to claim 1, wherein The objective function construction process includes: Determining a quadratic operator of the target task based on the target acceleration and a second-order derivative of the target task; The objective function is determined according to the quadratic operator and the objective weight of the objective task.

6. The method according to claim 5, characterized in that The target constraints include dynamic constraints, ground reaction force constraints and joint torque constraints.

7. The method according to claim 5, characterized in that The objective function formula includes: in, represents the second-order derivative of the target task, represents the target acceleration, represents the target weight, Indicates the total number of target tasks.

8. The method according to claim 1, characterized in that The target variable includes the generalized acceleration of the candidate two-wheeled vehicle and the Lagrange multiplier of the quadratic programming problem, wherein the Lagrange multiplier is used to determine the influencing factor of the target constraint; The solving of the quadratic programming problem comprises: Under the constraint conditions of the target constraint, the target variable is solved so that the target function reaches a minimum value.

9. The method according to claim 8, characterized in that Calculating the control torque of the candidate two-wheeled vehicle based on the calculation result of the target variable includes: Determining a first operator based on the generalized acceleration and the mass matrix of the candidate two-wheeled vehicle; Determining a second operator based on the Lagrange multiplier and the first-order linear constraint coefficient matrix of the candidate two-wheeled vehicle; The control torque is determined according to the first operator, the second operator, and the Coriolis force and gravity terms of the candidate two-wheeled vehicle.

10. The method according to claim 9, characterized in that The formula for the control torque includes: ， represents the mass matrix, represents the Coriolis force and gravity terms, represents the first-order linear constraint coefficient matrix, represents the generalized acceleration, represents the Lagrange multiplier, represents the control torque.

11. A two-wheeled vehicle control device, characterized in that: The device comprises: a task determination unit, configured to obtain a target task for a candidate two-wheeled vehicle, the target task comprising a spatial trajectory task, a holonomic constraint task, and a nonholonomic constraint task; the spatial trajectory task comprising at least one of a position parameter, a posture parameter, and a rotation angle parameter of the candidate two-wheeled vehicle; the holonomic constraint task comprising a height parameter of a contact point between the wheels of the candidate two-wheeled vehicle and the ground; and the nonholonomic constraint task comprising a tangential velocity parameter of a contact point between the wheels of the candidate two-wheeled vehicle and the ground; a state determination unit, configured to obtain a current vehicle state of the candidate two-wheeled vehicle and calculate a target feedback value of the target task based on the current vehicle state; an acceleration determination unit, configured to calculate a target acceleration of the target task according to the target feedback value; A planning determination unit, configured to construct a quadratic programming problem according to the target task and the target acceleration, wherein the quadratic programming problem includes a target variable, an objective function, and a target constraint; A control determination unit is used to solve the quadratic programming problem and calculate the control torque of the candidate two-wheeled vehicle based on the calculation result of the target variable, wherein the control torque includes a handlebar steering torque and a rear wheel drive torque, and the control torque is used to control the motion mode of the candidate two-wheeled vehicle.

12. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory is used to store a computer program, and when the computer program is executed by the processor, the method according to any one of claims 1 to 10 is implemented.

13. A computer-readable storage medium, characterized in that The computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 10 is implemented.

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