Vehicle driving control method, device and equipment and storage medium

Abstract

The invention relates to a vehicle running control method, device and equipment and a storage medium, relates to the technical field of four-steering-wheel robot control, and provides a navigation control mode that a robot platform autonomously adjusts to always keep AVG driving wheels running in a groove and meanwhile keeps load balance of all motors. Comprising the steps of calculating a target vehicle body state of a vehicle body when wheels run according to a pre-issued pre-running instruction at the current moment; detecting a second linear velocity, a second angular velocity and a second steering angle of the wheel in actual operation of the vehicle; according to the second linear speed, the second angular speed and the second steering angle, the actual vehicle body state of the vehicle is obtained through calculation; calculating a vehicle state error between the target vehicle body state and the actual vehicle body state; the vehicle state error is solved with the minimum vehicle state error as the target, and the driving direction of the vehicle at the next moment is obtained; and issuing the actual driving instruction to a wheel driver.

Description

Technical Field

[0001] The present application relates to the technical field of four-steering wheel robot control, and in particular to a vehicle driving control method, device, equipment and storage medium. Background Art

[0002] In the application scenario where the four-wheeled robot (Automated Guided Vehicle, AGV) moves forward, the two left driving wheels or the two right driving wheels run in a relatively narrow groove, so it is necessary to ensure that the driving wheels of the AGV do not collide with the groove wall during operation.

[0003] In the prior art, AGVs are usually operated by manual remote control, and the operator must observe in real time whether the wheels are in the middle of the groove to avoid collisions. At the same time, the robot must be operated to move forward. The manual operation efficiency of large and heavy-loaded AGVs is low, and the operation technology requirements are very high. It is difficult to ensure that the wheels are in the middle of the groove, which is prone to collisions and dangers. At the same time, the four-wheel robot is prone to load imbalance during movement, causing mutual pulling problems, which can cause serious consequences, especially for heavy-duty AGVs. Summary of the invention

[0004] The embodiments of the present application propose a vehicle driving control method, device, equipment and storage medium, which provide a navigation control method for the robot platform to autonomously adjust and always keep the AVG driving wheel running in the middle of the groove while maintaining the load balance of each motor.

[0005] In a first aspect, an embodiment provides a vehicle driving control method, the method comprising: Calculate the target body state of the vehicle body when the wheels are traveling according to the pre-issued pre-driving instructions at the current moment; the pre-driving instructions include a first linear velocity of the wheels, a first angular velocity of the wheels, and a first steering angle of the wheels; detect a second linear velocity of the wheels, a second angular velocity of the wheels, and a second steering angle of the wheels during actual operation of the vehicle; calculate the actual body state of the vehicle according to the second linear velocity, the second angular velocity, and the second steering angle; calculate a vehicle state error between the target body state and the actual body state; solve the vehicle state error with the goal of minimizing the vehicle state error to obtain a driving direction of the vehicle at the next moment; the driving direction includes a third linear velocity of the vehicle and a third angular velocity of the vehicle at the next moment; generate an actual driving instruction based on the driving direction of the vehicle at the next moment, and issue the actual driving instruction to the wheel driver.

[0006] In one embodiment, calculating the vehicle state error between the target vehicle body state and the actual vehicle body state includes: The vehicle state error is calculated as: (1) Wherein, A represents the first parameter matrix related to the state variables, B represents the second parameter matrix related to the state variables, the state variables include the angle between the vehicle orientation and the obstacle wall, the distance between the wheel and the obstacle wall, and the steering angle of the wheel; X is the error input variable, which is the difference between the first input and the second input; the first input is the orientation angle and the distance between the vehicle in the actual vehicle body state, and the second input is the orientation angle and the distance between the vehicle in the target vehicle body state; U is related to the linear speed of the wheel and the angle of the four steering motors during the vehicle's movement; The vehicle state error is solved with the goal of minimizing the vehicle state error, including: Setting up a state feedback controller for a state-space linear system ; Substituting the state feedback controller into the vehicle state error yields: (2) The vehicle state error is optimized by using a state space linear system to minimize the vehicle state error, and the error minimum optimization equation is obtained: (3) Among them, Q and R represent the weight matrices in the state space linear system. The vehicle state error is solved by using the error minimum optimization equation to obtain the driving direction of the vehicle at the next moment.

[0007] In one embodiment, the method further includes: Based on the vehicle running within the rated speed, in the constant torque range, with Ti as the drive torque of the i-th wheel, the torque balance equation is obtained by direct sensor data detection: (4) Among them, size indicates the size of the optimization window.

[0008] Solving the vehicle state error with the error minimum optimization equation to obtain the vehicle's driving direction at the next moment includes: The vehicle state error is solved by using the error minimization optimization equation and the torque balance equation to obtain the driving direction of the vehicle at the next moment.

[0009] In one embodiment, calculating the actual body state of the vehicle according to the second linear velocity and the second angular velocity includes: Establish the forward kinematics model of the vehicle: (5) Where θ represents the second angular velocity, Indicates The second steering angle of the wheels, Indicates The second linear speed of the wheel; The vehicle linear speed is The weight of the axis, The vehicle linear speed is The components of the axis; ω represents the angular velocity of the vehicle; The second linear velocity, the second angular velocity and the second steering angle are brought into the forward kinematics model of the vehicle to calculate the actual vehicle body state; the actual vehicle body state is based on the actual linear velocity of the vehicle. The components of the axle and the actual linear speed of the vehicle are The axis components and the actual linear speed of the vehicle are expressed.

[0010] In one embodiment, the method further includes: Collect the distance between the wheel and the obstacle wall and the angle between the wheel and the obstacle wall at the moment before the current moment; Convert the interval distance and the heading angle into the vehicle coordinate system to obtain the actual position of the vehicle at the previous moment; Real-time detection of the distance between the obstacle walls on both sides of the wheel, connecting multiple intermediate points to form a driving trajectory; Extending the driving trajectory to obtain a target position point of the vehicle at a next time point after the current time; Calculating the driving parameters of the vehicle from the actual position point to the target position point; Converting the driving parameters into a wheel coordinate system to obtain a first linear angle of the wheel, a first angular velocity of the wheel, and a first steering angle of the wheel; The pre-travel command is generated based on a first linear angle of the wheel, a first angular velocity of the wheel, and a first steering angle of the wheel.

[0011] In one embodiment, generating an actual driving instruction based on the driving direction of the vehicle at the next moment includes: An inverse kinematics model is established, and the driving direction of the vehicle at the next moment is sent to each wheel using the inverse kinematics model to obtain the fourth linear velocity and the fourth angular velocity of each wheel at the next moment: (6) Indicates The linear speed of the wheels is The weight of the axis, Indicates The linear speed of the wheels is The weight of the axis; Indicates the radius of the wheel; According to the output of the inverse kinematics model, the fourth linear velocity is The axis components and The components of the axis are used to calculate the resultant velocity υ vector of the fourth linear velocity and the fourth angular velocity σ; (7) Generating an actual driving instruction based on the driving direction of the vehicle at the next moment, comprising: An actual driving instruction is generated based on the resultant velocity υ vector of the fourth linear velocity and the fourth angular velocity σ.

[0012] In one embodiment, solving the vehicle state error by using the error minimum optimization equation to obtain the driving direction of the vehicle at the next moment includes: The cost function for configuring the state-space linear system is: (8) , , represents torque; Solve the error minimum optimization equation with the cost function to obtain the optimal gain ; The first linear velocity, the first angular velocity, and the first steering angle are calculated with the optimal gain to obtain a third linear velocity of the vehicle at the next moment and a third angular velocity of the vehicle.

[0013] In a second aspect, an embodiment provides a vehicle driving control device, the device comprising: a first calculation module, for calculating a target vehicle state of the vehicle body when the wheels are traveling according to a pre-travel instruction issued at a first moment before the current moment; the pre-travel instruction includes a first spacing distance of the wheels, a first linear velocity, a first angular velocity of the wheels, and a first steering angle of the wheels; A detection module, used to detect a second spacing distance, a second linear velocity, a second angular velocity of the wheels, and a second steering angle of the wheels during actual operation of the vehicle; a second calculation module, configured to calculate an actual vehicle body state of the vehicle according to the second interval distance, the second linear velocity, the second angular velocity and the second steering angle; A third calculation module, used for calculating a vehicle state error between the target vehicle body state and the actual vehicle body state; a fourth calculation module, for solving the vehicle state error with the goal of minimizing the vehicle state error, and obtaining the driving direction of the vehicle at the next moment; the driving direction includes the third linear speed of the vehicle at the next moment and the third triangular speed of the vehicle; The instruction sending module is used to generate an actual driving instruction based on the driving direction of the vehicle at the next moment, and send the actual driving instruction to the wheel driver.

[0014] In a third aspect, an embodiment of the present application further provides a computer-readable storage medium, which stores a program executable by a processor, and the program executable by the processor is used to implement the vehicle driving control method as described above when executed by the processor.

[0015] In a fourth aspect, an embodiment of the present application further provides an electronic device, wherein the storage device is used to store computer instructions, and the processor is used to execute the program instructions to implement the vehicle driving control method as described above.

[0016] The beneficial effects of this application are: In the embodiment of the present application, a sensor is set on each wheel of the AVG to obtain the precise position of the wheel, so as to determine the position point where the wheel should be located based on the precise position of the wheel. In actual applications, each wheel encounters different scenarios in the groove. The vehicle's driving trajectory is planned based on the position point of the wheel, and then the driving parameters of the wheel are planned based on the driving trajectory and sent to the wheel. A solution is given from the endpoint where the problem occurs, that is, the problem of avoiding wheel collision is achieved by planning the vehicle's driving trajectory, and the vehicle's driving trajectory is generated based on the center point of the wheel in the groove. Therefore, when driving according to the driving trajectory, the wheel will not collide with the groove, and there is no need to manually observe whether the wheel is in the middle of the groove. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a flowchart of the vehicle driving control method steps proposed in the embodiment of the present application; Figure 2 This is a schematic diagram of a centering driving of an example four-steering wheel robot of the present application; Figure 3 It is a functional module diagram of the vehicle driving control device proposed in the embodiment of the present application.

[0018] Among them, 31 is a first calculation module, 32 is a detection module, 33 is a second calculation module, 34 is a third calculation module, 35 is a fourth calculation module, and 36 is an instruction issuing module. DETAILED DESCRIPTION

[0019] The present application is further described in detail below by specific embodiments in conjunction with the accompanying drawings. Wherein similar elements in different embodiments adopt associated similar element numbers. In the following embodiments, many detailed descriptions are intended to enable the present application to be better understood. However, those skilled in the art can easily recognize that some of the features can be omitted in different situations, or can be replaced by other elements, materials, and methods. In some cases, some operations related to the present application are not shown or described in the specification, in order to avoid the core part of the present application being overwhelmed by too much description, and for those skilled in the art, it is not necessary to describe these related operations in detail, and they can fully understand the related operations based on the description in the specification and the general technical knowledge in the art.

[0020] In addition, the features, operations or characteristics described in the specification can be combined in any appropriate manner to form various implementations. At the same time, the steps or actions in the method description can also be interchanged or adjusted in a manner that is obvious to those skilled in the art. Therefore, the various sequences in the specification and the drawings are only for the purpose of clearly describing a certain embodiment and are not meant to be a required sequence, unless otherwise specified that a certain sequence must be followed.

[0021] The serial numbers assigned to the components herein, such as "first", "second", etc., are only used to distinguish the objects described and do not have any order or technical meaning. The "connection" and "coupling" mentioned in this application, unless otherwise specified, include direct and indirect connections (couplings).

[0022] The purpose of the embodiment of the present application is to provide a load balancing navigation control method for autonomous centering driving of a four-steering-wheel driven robot, so that the robot can autonomously maintain centering driving while maintaining the load balance of each wheel driver, avoiding the complexity of manual operation and improving construction efficiency.

[0023] Figure 1 is a flow chart of the vehicle driving control method steps proposed in the embodiment of the present application, such as Figure 1 As shown, the steps include: S11: Calculate the target vehicle state when the wheels are traveling according to the pre-travel instruction issued at a first moment before the current moment; the pre-travel instruction includes a first spacing distance of the wheels, a first linear velocity, a first angular velocity of the wheels, and a first steering angle of the wheels.

[0024] The vehicle described in this embodiment is a four-steering-wheel robot (Automated Guided Vehicle, AGV).

[0025] The first spacing distance is the distance between the wheel and the groove wall from the previous moment to the current moment when the vehicle travels according to the pre-travel instruction.

[0026] Step S11 is to calculate the vehicle body state that the vehicle should be in after the vehicle has driven according to the directly calculated instruction in the historical time before the vehicle actually drives according to the instruction.

[0027] Step S12 detects the actual body state of the vehicle at the current time, that is, the actual body state of the vehicle after the vehicle drove according to the driving instruction at the first moment before the current moment.

[0028] By comparing the results of executing step S11 and executing step S12, the error caused by load imbalance and deviation of the vehicle center during the actual driving process can be obtained. Since the AGV is a heavy-loaded machine, if the AGV deviates from the driving trajectory, the AGV wheels cannot be kept in the center of the groove, the AGV wheels collide with the groove, or the torque of each AGV wheel is unbalanced, causing a large force on the vehicle body, which will cause serious damage to the vehicle.

[0029] In response to the above situation, the embodiment of the present application calculates the body state of the vehicle after driving according to the driving instructions obtained by conventional calculations, and then calculates the difference between the body state of the vehicle and the actual body state of the vehicle, quantifies the deviation caused by various forces in the AVG climbing process, and then uses actual steps to calculate the driving parameters that can compensate for the deviation.

[0030] In order to achieve real-time correction of the driving trajectory, the embodiment of the present application periodically detects the vehicle position, plans the vehicle's target position point at the next moment, forms a real-time driving trajectory, and then generates a pre-driving instruction with the goal of controlling the vehicle to drive to the target position point at the next moment.

[0031] The steps to generate pre-driving instructions are as follows: S001: Collect the distance between the wheel and the obstacle wall and the orientation angle between the wheel and the obstacle wall at the moment before the current moment.

[0032] 3D laser radars are installed on the wheel sides of the vehicle to detect the front left, front right, rear left, and rear right positions of the vehicle. In one example, after collecting the 3D laser radar point cloud data, the point cloud data can be filtered to remove high-frequency interference.

[0033] S002: Convert the interval distance and the heading angle into the vehicle body coordinate system to obtain the actual position of the vehicle at the previous moment.

[0034] Other coordinate system conversion methods in the art can be used to convert the corresponding spacing distances and orientation angles of different wheels into the vehicle body coordinate system to obtain the actual position of the vehicle body. This application will not go into details about the coordinate system conversion method.

[0035] The data of each wheel may be subjected to Kalman filtering to remove interference information, or the wheel data may be converted to the geometric center of the vehicle body and then subjected to Kalman filtering to remove interference information.

[0036] S003: Detect the distance between the obstacle walls on both sides of the wheel in real time, and connect multiple intermediate points to form a driving trajectory.

[0037] The laser radar can also collect the distance between the obstacle walls on both sides of the vehicle's current location while collecting the interval distance and direction angle. Figure 2 This is a schematic diagram of a four-wheel robot driving in the center of the present application. Figure 2 As shown, the distance between the obstacle walls on both sides is used as the drivable width W of the current wheel, the middle position of the drivable width information is the center point, and the center points corresponding to each moment are connected to form a driving trajectory.

[0038] When the vehicle is running, set the laser radar collection of the left front wheel Collect the distance between the wheel and the obstacle wall at all times , the angle between the wheel and the obstacle wall is Similarly, the laser radar installed on the right front wheel The data collected at all times are: the distance between the wheel and the obstacle wall , the angle between the wheel and the obstacle wall , the laser radar placed on the left rear wheel The data collected at all times are: the distance between the left rear wheel and the obstacle wall , the angle between the wheel and the obstacle wall , the laser radar placed on the right rear wheel The data collected at all times are: the distance between the right rear wheel and the obstacle wall , the angle between the wheel and the obstacle wall .

[0039] S004: Extending the driving trajectory to obtain a target position point of the vehicle at a next time point after the current time.

[0040] For example, time, time, Time to The center points of the corresponding collection times are , , ,…… ;connect , , ,…… Forming a driving trajectory , extending according to the extension trend of the driving trajectory ,get The center point corresponding to the moment As the vehicle's target location, and The time interval is long enough. Be accurate The center position that the vehicle should reach at the moment.

[0041] S005: Calculate the driving parameters of the vehicle from the actual position point to the target position point.

[0042] The driving parameter of the vehicle from the actual position point to the target position point refers to the vehicle and During the period of time, from The linear speed, angular velocity and steering angle that should be used to drive to the target position at the corresponding position at the moment.

[0043] S006: Convert the driving parameters into a wheel coordinate system to obtain a first linear angle of the wheel, a first angular velocity of the wheel, and a first steering angle of the wheel.

[0044] S007: Generate the pre-driving instruction based on the first linear angle of the wheel, the first angular velocity of the wheel and the first steering angle of the wheel.

[0045] Pre-travel instructions are used to control the wheels and During the time period, the vehicle travels according to the parameters of a first linear angle, a first angular velocity, and a first steering angle.

[0046] In view of the fact that the key to controlling the driving of the AVG is to keep the wheels in the grooves and not collide with the groove walls, the embodiment of the present application sets a sensor on each wheel of the AVG to obtain the precise position of the wheel, so as to determine the position point where the wheel should be located based on the precise position of the wheel. In actual applications, each wheel encounters different scenarios in the groove. The vehicle's driving trajectory is planned based on the position point of the wheel, and then the driving parameters of the wheel are planned based on the driving trajectory and sent to the wheel. A solution is given from the endpoint where the problem occurs, that is, the problem of avoiding wheel collision is achieved by planning the vehicle's driving trajectory, and the vehicle's driving trajectory is generated based on the center point of the wheel in the groove. Therefore, when driving according to the driving trajectory, the wheel will not collide with the groove, and there is no need to manually observe whether the wheel is in the middle of the groove.

[0047] Step S12: Detecting a second spacing distance, a second linear velocity, a second angular velocity of the wheels, and a second steering angle of the wheels during actual operation of the vehicle.

[0048] The second spacing distance is the actual spacing distance between the wheel and the groove wall at the current moment detected by the sensor.

[0049] Step S13: Calculate the actual body state of the vehicle according to the second interval distance, the second linear velocity, the second angular velocity and the second steering angle.

[0050] For example, step S11 is executed to calculate the vehicle Always follow the pre-driving instructions to The target vehicle state should be maintained at all times. Steps S12 and S13 are executed to detect and calculate the vehicle The actual vehicle state reached at any moment.

[0051] The AGV climbing process is affected by factors such as gravity and the imbalance of each driving load. When driving according to the driving parameters of the driving instruction, position deviation will occur. Based on the fact that when the time interval is long enough, the force of the corresponding position in the relevant adjacent time period is not much different, this application first calculates Time to The displacement offset of the vehicle in the time period is corrected based on the pre-driving instruction to generate the actual driving instruction, and then the actual driving instruction is sent to the driver of each wheel. Since the displacement offset caused by the outside world and vehicle load is corrected, the vehicle can run according to the actual driving instruction. The wheel is automatically controlled to avoid collision with the groove wall by reaching the pre-marked target position point at all times, which is the center position point of the groove where the wheel is located.

[0052] Step S14: Calculate the vehicle state error between the target vehicle body state and the actual vehicle body state.

[0053] The vehicle state error is a quantification of the deviation of the vehicle due to external influences based on historical data.

[0054] Step S15: With the goal of minimizing the vehicle state error, solve the vehicle state error to obtain the driving direction of the vehicle at the next moment; the driving direction includes the third linear velocity of the vehicle at the next moment and the third triangular velocity of the vehicle.

[0055] Step S16: Generate an actual driving instruction based on the driving direction of the vehicle at the next moment, and send the actual driving instruction to the wheel driver.

[0056] The wheel driver responds to the actual driving command and drives the motor to generate a torque with a third linear velocity and a third angular velocity.

[0057] The embodiment of the present application also provides a method for calculating a vehicle state error, setting a first error input variable X, X= , It is the distance between the wheel and the groove wall in the actual vehicle body state. It is the steering angle between the wheel and the groove wall under the actual vehicle body state. The distance between the wheel and the groove wall and the direction angle are detected by the sensor installed on the specific wheel and converted into the vehicle body coordinate system. is the separation distance between vehicles in the target vehicle state, is the steering angle of the vehicle in the target body state.

[0058] The steering angle between the wheel and the groove wall refers to the angle between the wheel direction and the groove wall.

[0059] Let the state variable ζ = , enter u= ; It is the linear speed of the left front wheel under the actual vehicle state detected during the vehicle's movement. It is the linear speed of the left rear wheel under the actual vehicle state detected during the vehicle's movement. is the angle of the left front wheel steering motor during vehicle movement, It is the angle of the left rear wheel steering motor when the vehicle is moving, and so on.

[0060] Set up the state-space equations: .

[0061] is the actual state linear velocity The component in the axial direction, is the actual state linear velocity Component in the direction of the axis. The value of is 1, 2, 3, or 4.

[0062] make , linearization is performed, then A B .

[0063] , Indicates the target vehicle state and u.

[0064] Among them, A and B are obtained by finding the Jacobian matrix; , .

[0065] r is the radius of rotation of the wheel angular velocity, i.e., the distance from the wheel to the center of the vehicle body, and β is the angle between the wheel position and the x-axis of the vehicle body coordinate axis. The wheels are installed symmetrically in a rectangular position, and r and β are equal.

[0066] Let the error state variable X = ,U= , we get the vehicle state error, that is, the error state space equation between the vehicle in the actual vehicle state and the vehicle in the target vehicle state: (1) A represents the first parameter matrix related to the state variables, B represents the second parameter matrix related to the state variables, the state variables include the angle between the vehicle's orientation and the obstacle wall, the distance between the wheel and the obstacle wall, and the steering angle of the wheel; X is the error input variable, the error input variable is the difference between the first input and the second input; the first input is the orientation angle and the distance between the vehicle in the actual vehicle body state, and the second input is the orientation angle and the distance between the vehicle in the target vehicle body state; U is related to the linear speed of the wheel and the angle of the four steering motors during the vehicle's movement.

[0067] Solving the vehicle state error calculated in the above manner, the process of executing step S15 includes: Setting up a state feedback controller for a state-space linear system ; Substituting the state feedback controller into the vehicle state error yields: (2) The vehicle state error is optimized by using a state space linear system to minimize the vehicle state error, and the error minimum optimization equation is obtained: (3) Among them, Q and R represent the weight matrix in the state space linear system and the artificially set experience value matrix; LQR is also an optimal control; the basic idea of ​​optimal control is to design a performance indicator so that the indicator is optimal (usually minimum) to obtain the required control rate.

[0068] The vehicle state error is solved by using the error minimum optimization equation to obtain the driving direction of the vehicle at the next moment.

[0069] In addition, the embodiment of the present application establishes a torque balance equation. By solving the torque balance equation, the optimal torque of the steering motor corresponding to each wheel is obtained to achieve load balance of each motor.

[0070] Based on the vehicle running within the rated speed, in the constant torque range, As the driver torque of the i-th wheel, the torque balance equation is obtained by direct sensor data detection: The torque optimization objective of the torque balance equation can be to minimize the cumulative sum of all torques in Size moments: , heavy-load AGV runs at low speed, always running within the rated speed, constant torque range, can be simplified as The drive torque is detected directly from sensor data.

[0071] (4) The vehicle state error is then solved using the error minimization optimization equation and the torque balance equation to obtain the vehicle's driving direction at the next moment.

[0072] In one example, the torque balance equation and the vehicle state error can be combined to solve the combined equation to obtain better driving parameters: the third linear speed and the third triangular speed of the vehicle.

[0073] The final optimization problem is described as: , Optimization goal solution: According to the usage of the ceres library, the main steps are to construct an optimization problem and then configure the optimizer to solve the optimization problem. Write the cost function as =e, , the quadratic residual block form is , select automatic differentiation for optimization and solution. Get the solution to the optimization problem. e means using the ceres library, write the cost function.

[0074] Solving the vehicle state error with the error minimum optimization equation to obtain the vehicle's driving direction at the next moment includes: The cost function for configuring the state-space linear system is: =e(8) , ; Solve the error minimum optimization equation with the cost function to obtain the optimal gain ; The first linear velocity, the first angular velocity, and the first steering angle are calculated with the optimal gain to obtain a third linear velocity of the vehicle at the next moment and a third angular velocity of the vehicle.

[0075] The embodiment of the present application establishes an optimization goal of minimizing deviation and load. The optimization solution (gain K) obtained through the above steps is the optimal solution under this goal, that is, the control rate The third linear velocity of the vehicle at the next moment and the third triangular velocity of the vehicle, that is, the linear velocity of the four wheel driving wheels and the angle data of the four steering wheels are obtained. The data is sent to the driver for execution through the driver communication program.

[0076] The embodiment of the present application also provides an implementation method of “calculating the actual vehicle body state of the vehicle according to the second interval distance, the second linear velocity, the second angular velocity and the second steering angle”: Establish the forward kinematics model of the vehicle: (5) Among them, θ represents the angle, the vehicle's heading angle, that is, the vehicle's direction, Indicates The second steering angle of the wheels, Indicates The second linear speed of the wheel; The vehicle linear speed is The weight of the axis, The vehicle linear speed is The components of the axis; ω represents the angular velocity of the vehicle; The second linear velocity, the second angular velocity and the second steering angle are brought into the forward kinematics model of the vehicle to calculate the actual vehicle body state; the actual vehicle body state is based on the actual linear velocity of the vehicle. The components of the axle and the actual linear speed of the vehicle are The axis components and the actual linear speed of the vehicle are expressed.

[0077] The embodiment of the present application also provides an implementation method of "generating an actual driving instruction based on the driving direction of the vehicle at the next moment, and sending the actual driving instruction to the wheel driver": In this way, the third linear velocity of the vehicle at the next moment and the third angular velocity of the vehicle are converted into each wheel coordinate system, so that the driving parameters received by the wheel driver are the linear velocity and angular velocity in the local coordinate system.

[0078] Similarly, the method of "generating the pre-driving instruction based on the first linear angle of the wheel, the first angular velocity of the wheel and the first steering angle of the wheel" can also be used to establish an inverse kinematic model and convert the first linear angle and the first angular velocity of the wheel into the wheel coordinate system.

[0079] An inverse kinematics model is established, and the driving direction of the vehicle at the next moment is sent to each wheel using the inverse kinematics model to obtain the fourth linear velocity and the fourth angular velocity of each wheel at the next moment: (6) Indicates The linear speed of the wheels is The weight of the axis, Indicates The linear speed of the wheels is The weight of the axis; Indicates the radius of the wheel; According to the output of the inverse kinematics model, the fourth linear velocity is The axis components and The components of the axis are used to calculate the resultant velocity υ vector of the fourth linear velocity and the fourth angular velocity σ; (7) Generating an actual driving instruction based on the driving direction of the vehicle at the next moment, comprising: An actual driving instruction is generated based on the resultant velocity υ vector of the fourth linear velocity and the fourth angular velocity σ.

[0080] Figure 3 is a functional module diagram of the vehicle driving control device proposed in the embodiment of the present application, such as Figure 3 As shown, the vehicle driving control device includes: A first calculation module 31 is used to calculate a target vehicle state when the wheels are traveling according to a pre-travel instruction issued at a first moment before the current moment; the pre-travel instruction includes a first spacing distance of the wheels, a first linear velocity, a first angular velocity of the wheels, and a first steering angle of the wheels; A detection module 32, used for detecting a second spacing distance, a second linear velocity, a second angular velocity and a second steering angle of the wheels of the vehicle during actual operation; A second calculation module 33, configured to calculate an actual vehicle body state of the vehicle according to the second interval distance, the second linear velocity, the second angular velocity and the second steering angle; A third calculation module 34, used to calculate a vehicle state error between the target vehicle body state and the actual vehicle body state; The fourth calculation module 35 is used to solve the vehicle state error with the goal of minimizing the vehicle state error, and obtain the driving direction of the vehicle at the next moment; the driving direction includes the third linear speed of the vehicle at the next moment and the third triangular speed of the vehicle; The instruction issuing module 36 is used to generate an actual driving instruction based on the driving direction of the vehicle at the next moment, and issue the actual driving instruction to the wheel driver.

[0081] Figure 3 The implementation principle and technical effects of the vehicle driving control device provided in the illustrated embodiment may be further described with reference to the relevant description in the vehicle driving control method embodiment.

[0082] Regarding the various modules / units included in the various devices described in the above embodiments, they can be software modules / units, or hardware modules / units, or they can be partially software modules / units and partially hardware modules / units. For example, for various devices applied to or integrated in a chip, the various modules / units included therein can all be implemented in the form of hardware such as circuits, or at least some of the modules / units can be implemented in the form of software programs, which run on a processor integrated inside the chip, and the remaining modules / units can be implemented in the form of hardware such as circuits; for various devices applied to or integrated in a chip module, the various modules / units included therein can all be implemented in the form of hardware such as circuits, and different modules / units can be located in the same component of the chip module (such as a chip, circuit module, etc.) or in different components, or at least some of the modules / units can be implemented in the form of software programs. The software program may be implemented in the form of a program, which runs on a processor integrated in the chip module, and the remaining modules / units may be implemented in the form of hardware such as circuits; for each device applied to or integrated in the electronic terminal device, each module / unit contained therein may be implemented in the form of hardware such as circuits, and different modules / units may be located in the same component (for example, a chip, a circuit module, etc.) or in different components in the electronic terminal device, or at least some modules / units may be implemented in the form of a software program, which runs on a processor integrated in the electronic terminal device, and the remaining (if any) modules / units may be implemented in the form of hardware such as circuits.

[0083] The embodiment of the present application also provides an electronic device, wherein the storage device is used to store computer instructions, and the processor is used to execute the program instructions to implement the cardiac arrest prediction method as described above. The electronic device can be a vehicle-mounted computer, a server connected to a vehicle system, etc.

[0084] In one embodiment of the present application, a computer-readable storage medium is provided, on which a program is stored. The stored program includes a method that can be loaded by a processor and process any one of the above embodiments.

[0085] Those skilled in the art will appreciate that all or part of the functions of the various methods in the above-mentioned embodiments can be implemented by hardware or by computer programs. When all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can be stored in a computer-readable storage medium, and the storage medium can include: read-only memory, random access memory, disk, optical disk, hard disk, etc., and the program is executed by a computer to implement the above-mentioned functions. For example, the program is stored in the memory of the device, and when the program in the memory is executed by the processor, all or part of the above-mentioned functions can be implemented. In addition, when all or part of the functions in the above-mentioned embodiments are implemented by computer programs, the program can also be stored in a storage medium such as a server, another computer, disk, optical disk, flash disk or mobile hard disk, and can be downloaded or copied and saved in the memory of the local device, or the system of the local device is updated, and when the program in the memory is executed by the processor, all or part of the functions in the above-mentioned embodiments can be implemented.

[0086] The above specific examples are used to illustrate the present application, which is only used to help understand the present application and is not intended to limit the present application. For technicians in the technical field to which the present application belongs, they can also make some simple deductions, deformations or substitutions based on the ideas of the present application.

Claims

1. A vehicle driving control method, characterized in that: The method comprises: Calculating a target vehicle state of a vehicle body when the wheels are traveling according to a pre-travel instruction issued at a first moment before the current moment; the pre-travel instruction includes a first spacing distance of the wheels, a first linear velocity, a first angular velocity of the wheels, and a first steering angle of the wheels; Detecting a second spacing distance, a second linear velocity, a second angular velocity of the wheels, and a second steering angle of the wheels during actual operation of the vehicle; Calculate the actual body state of the vehicle according to the second interval distance, the second linear velocity, the second angular velocity and the second steering angle; Calculating a vehicle state error between the target vehicle body state and the actual vehicle body state; With the goal of minimizing the vehicle state error, the vehicle state error is solved to obtain the driving direction of the vehicle at the next moment; the driving direction includes the third linear velocity of the vehicle at the next moment and the third triangular velocity of the vehicle; An actual driving instruction is generated based on the driving direction of the vehicle at the next moment, and the actual driving instruction is sent to the wheel driver.

2. The method according to claim 1, characterized in that Calculating a vehicle state error between the target vehicle body state and the actual vehicle body state includes: The vehicle state error is calculated as: ， Wherein, A represents the first parameter matrix related to the state variables, B represents the second parameter matrix related to the state variables, the state variables include the angle between the vehicle orientation and the obstacle wall, the distance between the wheel and the obstacle wall, and the steering angle of the wheel; X is the error input variable, which is the difference between the first input and the second input; the first input is the orientation angle and the distance between the vehicle in the actual vehicle body state, and the second input is the orientation angle and the distance between the vehicle in the target vehicle body state; U is related to the linear speed of the wheel and the angle of the four steering motors during the vehicle's movement; The vehicle state error is solved with the goal of minimizing the vehicle state error, including: Setting up a state feedback controller for a state-space linear system ; Substituting the state feedback controller into the vehicle state error yields: ， The vehicle state error is optimized by using a state space linear system to minimize the vehicle state error, and the error minimum optimization equation is obtained: K is the optimized gain parameter; ， Among them, Q and R represent the weight matrices in the state space linear system; Indicates ( ) is the transpose operation; Jtarget is the subscript symbol indicating the minimum state error; The vehicle state error is solved by using the error minimum optimization equation to obtain the driving direction of the vehicle at the next moment.

3. The method according to claim 2, characterized in that The method further comprises: Based on the vehicle running within the rated speed, in the constant torque range, with Ti as the drive torque of the i-th wheel, the torque balance equation is obtained by direct sensor data detection: ， Among them, size indicates the size of the optimization window; Jtorque is the subscript symbol indicating torque balance; Solving the vehicle state error with the error minimum optimization equation to obtain the vehicle's driving direction at the next moment includes: The vehicle state error is solved by using the error minimization optimization equation and the torque balance equation to obtain the driving direction of the vehicle at the next moment.

4. The method according to claim 1, characterized in that Calculating the actual body state of the vehicle according to the second linear velocity and the second angular velocity includes: Establish the forward kinematics model of the vehicle: ， Where θ represents the second angular velocity, Indicates The second steering angle of the wheels, Indicates The second linear speed of the wheel; The vehicle linear speed is The weight of the axis, The vehicle linear speed is The components of the axis; ω represents the angular velocity of the vehicle; R is the radius of wheel rotation; The second linear velocity, the second angular velocity and the second steering angle are brought into the forward kinematics model of the vehicle to calculate the actual vehicle body state; the actual vehicle body state is based on the actual linear velocity of the vehicle. The components of the axle and the actual linear speed of the vehicle are The axis components and the actual linear speed of the vehicle are expressed.

5. The method according to claim 1, characterized in that The method further comprises: Collect the distance between the wheel and the obstacle wall and the angle between the wheel and the obstacle wall at the moment before the current moment; Convert the interval distance and the heading angle into the vehicle coordinate system to obtain the actual position of the vehicle at the previous moment; Real-time detection of the distance between the obstacle walls on both sides of the wheel, connecting multiple intermediate points to form a driving trajectory; Extending the driving trajectory to obtain a target position point of the vehicle at a next time point after the current time; Calculating the driving parameters of the vehicle from the actual position point to the target position point; Converting the driving parameters into a wheel coordinate system to obtain a first linear angle of the wheel, a first angular velocity of the wheel, and a first steering angle of the wheel; The pre-travel command is generated based on a first linear angle of the wheel, a first angular velocity of the wheel, and a first steering angle of the wheel.

6. The method according to claim 5, characterized in that Generating an actual driving instruction based on the driving direction of the vehicle at the next moment, comprising: An inverse kinematics model is established, and the driving direction of the vehicle at the next moment is sent to each wheel using the inverse kinematics model to obtain the fourth linear velocity and the fourth angular velocity of each wheel at the next moment: ， Indicates The linear speed of the wheels is The weight of the axis, Indicates The linear speed of the wheels is The weight of the axis; Indicates the radius of the wheel; The vehicle linear speed is The weight of the axis, The vehicle linear speed is The weight of the axis; According to the output of the inverse kinematics model, the fourth linear velocity is The axis components and The components of the axis are used to calculate the resultant velocity υ vector of the fourth linear velocity and the fourth angular velocity σ; ， Generating an actual driving instruction based on the driving direction of the vehicle at the next moment, comprising: An actual driving instruction is generated based on the resultant velocity υ vector of the fourth linear velocity and the fourth angular velocity σ.

7. The method according to claim 2, characterized in that: Solving the vehicle state error with the error minimum optimization equation to obtain the vehicle's driving direction at the next moment includes: The cost function for configuring the state-space linear system is: ， e is a symbol representing the cost function, and the calculation method of e is; , , represents torque; Solve the error minimum optimization equation with the cost function to obtain the optimal gain ; The first linear velocity, the first angular velocity, and the first steering angle are calculated with the optimal gain to obtain a third linear velocity of the vehicle at the next moment and a third angular velocity of the vehicle.

8. A vehicle driving control device, characterized in that: The device comprises: a first calculation module, for calculating a target vehicle state of the vehicle body when the wheels are traveling according to a pre-travel instruction issued at a first moment before the current moment; the pre-travel instruction includes a first spacing distance of the wheels, a first linear velocity, a first angular velocity of the wheels, and a first steering angle of the wheels; A detection module, used to detect a second spacing distance, a second linear velocity, a second angular velocity of the wheels, and a second steering angle of the wheels during actual operation of the vehicle; a second calculation module, configured to calculate an actual vehicle body state of the vehicle according to the second interval distance, the second linear velocity, the second angular velocity and the second steering angle; A third calculation module, used for calculating a vehicle state error between the target vehicle body state and the actual vehicle body state; a fourth calculation module, for solving the vehicle state error with the goal of minimizing the vehicle state error, and obtaining the driving direction of the vehicle at the next moment; the driving direction includes the third linear speed of the vehicle at the next moment and the third triangular speed of the vehicle; The instruction sending module is used to generate an actual driving instruction based on the driving direction of the vehicle at the next moment, and send the actual driving instruction to the wheel driver.

9. An electronic device, characterized in that: The method comprises at least one processor and at least one memory connected to the processor; the memory stores program instructions for being executed by the processor, and the processor calls the program instructions to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: A program is stored on the storage medium, and the stored program includes a method that can be loaded by a processor and process any one of claims 1 to 7.

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