Tandem bicycle control method and device, electronic equipment and readable storage medium

Abstract

The present disclosure relates to the technical field of two-wheeled vehicle unmanned driving, and proposes a two-wheeled vehicle control method, device, electronic equipment and readable storage medium. The method comprises: obtaining a target task of a candidate two-wheeled vehicle, the target task comprising a spatial 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; solving the quadratic programming problem, and calculating a control torque of the candidate two-wheeled vehicle based on the calculation result of the quadratic programming problem, the control torque comprising a handlebar steering torque and a rear wheel driving torque. The technical scheme provided by one or more embodiments of the present disclosure can accurately control the motion mode of the two-wheeled vehicle, and realize various two-wheeled vehicle unmanned driving tasks.

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 high 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 an incomplete 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 the 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 any limitation to the disclosure, in which:

[0014] Figure 1 A step schematic diagram of a two-wheeled vehicle control method in one embodiment of the disclosure is shown;

[0015] Figure 2 A functional module schematic diagram of a two-wheeled vehicle control device in one embodiment of the disclosure is shown;

[0016] Figure 3 A structure schematic diagram of an electronic device in one embodiment of the disclosure is shown. DETAILED DESCRIPTION

[0017] 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.

[0018] 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.

[0019] 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.

[0020] S1: Obtain a target task of a candidate double-wheeled vehicle, wherein the target task includes a spatial trajectory task, a complete constraint task and an incomplete constraint task; the spatial trajectory task includes at least one of a position parameter, an attitude parameter and a turning angle parameter of the candidate double-wheeled vehicle, the complete constraint task includes a height parameter of a wheel-ground contact point of the candidate double-wheeled vehicle, and the incomplete constraint task includes a tangential velocity parameter of the wheel-ground contact point of the candidate double-wheeled vehicle.

[0021] 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 turning angle of the double-wheeled vehicle, are the rear wheel and front wheel turning angles of the double-wheeled vehicle, respectively.

[0022] 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 . Among them, 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).

[0023] 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.

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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, calculating the target feedback value of the spatial trajectory task; according to the current generalized coordinates and generalized velocities of the candidate two-wheeled vehicle , , that is, calculating the target feedback value of the complete constraint task; according to the current generalized coordinates and generalized velocities of the candidate two-wheeled vehicle , , that is, calculating the target feedback value of the non-complete constraint task.

[0029] S3: calculating the target acceleration of the target task according to the target feedback value.

[0030] 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.

[0031] In some embodiments, the calculating the target acceleration of the target task according to the target feedback value comprises: 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.

[0032] Specifically, if the target task is a spatial trajectory task, a spatial trajectory reference value and a spatial trajectory feedback value of the spatial trajectory task can be obtained, and then a target error is calculated ; if the target task is a complete constraint task, a reference value and a feedback value of the complete constraint task can be obtained, and then a target error is calculated ; if the target task is a non-complete constraint task, a reference value and a feedback value of the non-complete constraint task can be obtained, and then a target error ， .

[0033] In some embodiments, if the target task is the spatial trajectory task, the target acceleration is calculated based on a proportional-differential control operation result of the target error. For example, the target acceleration of the spatial trajectory task is are proportional and differential coefficients, respectively,

[0034] In some embodiments, if the target task is the holonomic constraint task, the target acceleration is calculated based on a proportional-differential control operation result of the target error. For example, the target acceleration of the holonomic constraint task is are proportional and differential coefficients, respectively,

[0035] In some embodiments, if the target task is the non-holonomic constraint task, the target acceleration is calculated based on a differential control operation result of the target error. For example, the target acceleration of the non-holonomic constraint task is is a differential coefficient,

[0036] S4: constructing a quadratic programming problem based on the target task and the target acceleration, the quadratic programming problem including a target variable, a target function, and a target constraint.

[0037] In the present embodiment, the quadratic programming (QP) problem is a convex optimization problem. The quadratic programming problem has the following advantages: convex optimization, ensuring a global optimal solution; mature solving algorithm (such as interior point method, active set method, etc.), ensuring high efficiency of solving; and being able to handle multi-variable coupling relationship at the same time, suitable for real-time decision-making scenarios.

[0038] In the present embodiment, the target variable is a variable to be optimized and solved; the target function is a quadratic form (quadratic polynomial); and the target constraint includes linear equations (such as dynamic equations) and inequalities (such as acceleration amplitude limiting and torque amplitude limiting). The target variable, the target function, and the target constraint together constitute a standard form of quadratic programming problem.

[0039] In the present embodiment, the quadratic programming problem can be constructed based on the first type of Lagrange equation. The target variable can include the generalized acceleration of the candidate double-wheeled vehicle and the Lagrange multiplier . The Lagrange multiplier is used to determine the influence factor (equivalent to the weight) of the target constraint. The target task and the target acceleration are mainly used to construct the target function.

[0040] ​​​​​​​​In some embodiments, the constructing process of the target function comprises: determining a quadratic operator of the target task based on the target acceleration and the second derivative of the target task; and determining the target function according to the quadratic operator and a target weight of the target task.

[0041] In some embodiments, the formula of the target function comprises:

[0042]

[0043] wherein, denotes the second derivative of the target task, denotes the target acceleration, denotes the target weight, denotes the total number of the target tasks. is a quadratic operator. The target function has fully considered the comprehensive planning of the spatial trajectory task, the complete constraint task and the non-complete constraint task, and is a complete dynamic model for the candidate double-wheeled vehicle.

[0044] It should be noted that, can be represented as a linear relationship:

[0045] ,

[0046] wherein, a Jacobi matrix satisfies , is a derivative with respect to time.

[0047] In some embodiments, the target constraints comprise dynamic constraints, ground reaction force constraints and joint torque constraints.

[0048] Specifically, the dynamic constraints are underactuated dynamic equations of the double-wheeled vehicle, which are obtained according to the first type of Lagrange equation, i.e.

[0049]

[0050] wherein, respectively represent a mass matrix, a Coriolis force and a gravity term about the underactuated component in the generalized coordinates, and a first-order linear constraint coefficient matrix.

[0051] The ground reaction force constraints comprise normal unilateral constraints and tangential friction cone constraints, i.e.

[0052]

[0053] ​

[0054] wherein, are components of the contact force of the rear wheel in three coordinate directions, are components of the contact force of the front wheel in three coordinate directions, is a friction coefficient.

[0055] The joint torque constraint is

[0056]

[0057]

[0058] wherein, respectively represent a mass matrix in the generalized coordinates with respect to the driving components, Coriolis force and gravity terms, a first-order linear constraint coefficient matrix, and respectively are lower and upper limits of the driving torque, and respectively are lower and upper limits of the generalized acceleration.

[0059] S5: solving the quadratic programming problem, and based on the calculation results of the target variables, calculating the control torque of the candidate two-wheeled vehicle, 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.

[0060] In the embodiment, the target variables include the generalized acceleration of the candidate two-wheeled vehicle, and the Lagrange multipliers of the quadratic programming problem. The Lagrange multipliers are used to determine the influence factors of the target constraints.

[0061] In the embodiment, the parameter adjustment determines a set of suitable control parameters (including proportional coefficients , differential coefficients and target weights ) and then the QP problem can be solved. Solving the quadratic programming problem includes: under the constraint condition of the target constraints, solving a target variable group that makes the target function reach the minimum value. According to the solved target variable group , the control torque of the candidate two-wheeled vehicle can be further calculated.

[0062] In some embodiments, the calculation of the control torque of the candidate two-wheeled vehicle based on the calculation results of the target variables 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 multipliers 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 terms of the candidate two-wheeled vehicle.

[0063] In one practical application example, the formula of the control torque includes:

[0064]

[0065] M represents a mass matrix, G represents a Coriolis force and gravity term, A represents the first-order linear constraint coefficient matrix, a represents the generalized acceleration, λ represents the Lagrange multiplier, τ represents the control torque.

[0066] The control torque can be specifically represented as θ represents a handlebar steering torque, F represents a rear wheel driving torque. The control torque τ is input to a two-wheeled vehicle control device, so as to complete accurate control of the motion mode of the two-wheeled vehicle, and realize various actual unmanned driving tasks of the two-wheeled vehicle.

[0067] The technical solution provided by one or more embodiments of the present 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 the control process has low energy consumption and strong maneuverability.

[0068] The technical solution 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 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 accuracy of the control torque.

[0069] The technical solution 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 universality 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.

[0070] Referring to Figure 2 the present disclosure also provides a two-wheeled vehicle control device, which comprises:

[0071] ​​​​​​​​​​​​​​​​​​​The task determination unit 100 is configured to obtain a target task of a candidate two-wheeled vehicle, the target task including a spatial trajectory task, a full constraint task, and a non-full constraint task; the spatial trajectory task including at least one of a position parameter, an attitude parameter, and a turning angle parameter of the candidate two-wheeled vehicle, the full constraint task including a height parameter of a wheel-ground contact point of the candidate two-wheeled vehicle, and the non-full constraint task including a tangential velocity parameter of the wheel-ground contact point of the candidate two-wheeled vehicle.

[0072] The state determination unit 200 is 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.

[0073] The acceleration determination unit 300 is configured to calculate a target acceleration of the target task according to the target feedback value.

[0074] The planning determination unit 400 is configured to construct a quadratic programming problem according to the target task and the target acceleration, the quadratic programming problem including a target variable, a target function, and a target constraint.

[0075] The control determination unit 500 is 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 including 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.

[0076] In an embodiment, the full constraint task includes a height parameter of a rear wheel-ground contact point and a height parameter of a front wheel-ground contact point, and the non-full constraint task includes a tangential velocity parameter of the rear wheel-ground contact point in a first tangential direction, a tangential velocity parameter of the front wheel-ground contact point in the first tangential direction, a tangential velocity parameter of the rear wheel-ground contact point in a second tangential direction, and a tangential velocity parameter of the front wheel-ground contact point in the second tangential direction.

[0077] In an 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.

[0078] In an embodiment, the calculating the target acceleration of the target task based on the target error comprises at least one of: if the target task is the spatial trajectory task, calculating the target acceleration based on a proportional-derivative control operation result of the target error; if the target task is the full-constrained task, calculating the target acceleration based on the proportional-derivative control operation result of the target error; if the target task is the non-full-constrained task, calculating the target acceleration based on a derivative control operation result of the target error.

[0079] In an embodiment, the process of constructing the target function by the planning determination unit 400 comprises: determining a quadratic operator of the target task based on the target acceleration and a second derivative of the target task; and determining the target function according to the quadratic operator and a target weight of the target task.

[0080] In an embodiment, the target constraint comprises a dynamics constraint, a ground reaction force constraint, and a joint torque constraint.

[0081] In an embodiment, the formula of the target function comprises:

[0082]

[0083] wherein, denotes the second derivative of the target task, denotes the target acceleration, denotes the target weight, denotes a total number of the target tasks.

[0084] In an embodiment, the target variable comprises 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 constraint. The control determination unit 500 solves the quadratic programming problem by solving the target variable under the constraint condition of the target constraint so as to minimize the target function.

[0085] In an embodiment, the control determination unit 500 calculates the control torque of the candidate two-wheeled vehicle based on the calculation result of the target variable, comprising: 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.

[0086] In an embodiment, the formula of the control torque comprises:

[0087] ,

[0088] wherein, denotes the mass matrix, denotes the Coriolis and gravitational terms, denotes the first order linear constraint coefficient matrix, denotes the generalized acceleration, denotes the Lagrange multipliers, denotes the control torques.

[0089] Each unit illustrated in the above embodiments can be implemented by a computer chip, or by a product with certain function. 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.

[0090] For the convenience of description, the above device is described in various units by function. Of course, the functions of the units can be implemented in one or more software and / or hardware in the implementation of the present application.

[0091] 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 double-wheeled vehicle control method when executed by the processor.

[0092] 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 double-wheeled vehicle control method when executed by a processor.

[0093] 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 device, discrete gate or transistor logic device, discrete hardware component, or a combination of the above-mentioned chips or components.

[0094] The memory, as a non-transitory computer readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs and modules, such as program instructions / modules corresponding to the method 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, that is, implements the method in the above method embodiments.

[0095] The memory can include a program storage area and a data storage area, wherein the program storage area can store an operating system and application programs required by at least one function; and 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 also 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 remotely arranged with respect to the processor, and these remote memories can be connected to the processor through a network. Examples of the above network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0096] 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, and the program can be stored in a computer readable storage medium. When the program is executed, it can include the processes of the above-mentioned embodiments of each method. 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.

[0097] Each of the embodiments in the specification is described in a progressive manner, and the same or similar parts between each embodiment can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, the equipment and the storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the part of the method embodiments.

[0098] 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.

[0099] While embodiments of the present disclosure have been described in conjunction with the accompanying drawings, various modifications and changes can be suggested by those skilled in the art, and it is intended that the present disclosure encompass such modifications and changes as fall within the scope of the appended claims.

Claims

1. A control method of a two-wheeled vehicle, characterized by, The method comprises: obtaining a target task of a candidate two-wheeled vehicle, the target task comprising a spatial trajectory task, a full constraint task and a non-full 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 full constraint task comprising a height parameter of a wheel-ground contact point of the candidate two-wheeled vehicle, and the non-full 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.

2. The method of claim 1, wherein, The full constraint task comprises a height parameter of a rear wheel-ground contact point and a height parameter of a front wheel-ground contact point, and the non-full constraint task comprises a tangential velocity parameter of the rear wheel-ground contact point in a first tangential direction, a tangential velocity parameter of the front wheel-ground contact point in the first tangential direction, a tangential velocity parameter of the rear wheel-ground contact point in a second tangential direction, and a tangential velocity parameter of the front wheel-ground contact point in the second tangential direction.

3. The method of claim 1, wherein, The calculation of the target acceleration of the target task according to the target feedback value comprises: obtaining a target reference value of the target task; determining a target error according to the target feedback value and the target reference value; calculating the target acceleration of the target task based on the target error.

4. The method of claim 3, wherein, The calculation of the target acceleration of the target task based on the target error comprises at least one of: 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 full constraint task, calculating the target acceleration based on a proportional-differential control operation result of the target error; if the target task is the non-full constraint task, calculating the target acceleration based on a differential control operation result of the target error.

5. The method of claim 1, wherein, The construction process of the target function comprises: determining a quadratic operator of the target task based on the target acceleration and a second derivative of the target task; determining the target function according to the quadratic operator and a target weight of the target task.

6. The method of claim 5, wherein, The target constraint comprises a dynamics constraint, a ground reaction force constraint and a joint torque constraint.

7. The method of claim 5, wherein, The formula of the target function comprises: 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.

8. The method of claim 1, wherein, The target variable comprises 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 constraint; The solving of the quadratic programming problem comprises: Solve the target variable under the constraint condition of the target constraint, so that the target function reaches a minimum value.

9. The method of claim 8, wherein, The control torque of the candidate two-wheeled vehicle is calculated based on the calculation result of the target variable, including: Determine a first operator based on the generalized acceleration and a mass matrix of the candidate two-wheeled vehicle; Determine a second operator based on the Lagrange multiplier and a first-order linear constraint coefficient matrix of the candidate two-wheeled vehicle; Determine the control torque according to the first operator, the second operator, and the Coriolis force and gravity term of the candidate two-wheeled vehicle.

10. The method of claim 9, wherein, The formula of the control torque includes: ， denotes the mass matrix, denotes the Coriolis and gravitational terms, denotes the first order linear constraint coefficient matrix, denotes the generalized accelerations, denotes the Lagrange multipliers, denotes the control torques.

11. A control device for a two-wheeled vehicle, characterized by The device includes: A task determination unit is configured to obtain a target task of a candidate two-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 turning angle parameter of the candidate two-wheeled vehicle, the complete constraint task including a height parameter of a wheel-ground contact point of the candidate two-wheeled vehicle, and the incomplete constraint task including a tangential velocity parameter of the wheel-ground contact point of the candidate two-wheeled vehicle; A state determination unit is 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 is configured to calculate a target acceleration of the target task according to the target feedback value; A planning determination unit is configured to construct a quadratic programming problem according to the target task and the target acceleration, the quadratic programming problem including a target variable, a target function, and a target constraint; A control determination unit is 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 including 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.

12. An electronic device, comprising: The electronic device includes a memory and a processor, the memory being configured to store a computer program, the computer program being executed by the processor to implement the method in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that, The computer readable storage medium is configured to store a computer program, the computer program being executed by a processor to implement the method in any one of claims 1 to 10.

Images