A hierarchical modeling and constraint-following control method for multi-vehicle cooperative transportation system

Abstract

The application relates to a hierarchical modeling and constraint following control method of a multi-vehicle cooperative transportation system. The method comprises the following steps: acquiring the position relationship between each vehicle and target goods, the force data between each vehicle and target goods, the spatial position information of the destination, and the expected transportation trajectory of the target goods; constructing external constraint information and internal constraint information of the transportation system; generating a tracking control law expression of the target goods according to the external constraint information of the transportation system, and generating a following control law expression of each vehicle according to the internal constraint information of the transportation system; based on the control law expressions of the target goods and each vehicle, and according to the force data between each vehicle and the target goods, establishing an actual control law expression of each vehicle; and determining and outputting the control instructions corresponding to each vehicle according to the actual control law expression of each vehicle. The method can improve the efficiency of cooperative transportation of the target goods.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to a hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system. Background Technology

[0002] Multi-vehicle cooperative transportation is a development direction for heavy freight road transport. By combining multiple tractor-trailers to form a multi-vehicle transport system to jointly transport heavy goods, the carrying capacity limit of a single vehicle can be broken. Currently, multi-vehicle cooperative road transport has a few practical applications, such as using two heavy vehicles to pull and push each other to transport narrow and long heavy goods. However, this type of transportation currently relies on the coordinated work of multiple drivers and operators. The multi-vehicle system is complex, and manual operation is difficult and prone to interference, which can lead to damage to vehicles and goods.

[0003] Current collaborative transportation methods involve multiple autonomous driving tractors working together under unified control to transport goods. However, because these methods primarily focus on small robots operating indoors, their agent dynamics models are simple. In contrast, the dynamics models and constraints of heavily loaded vehicles transporting target goods are far more complex. This makes it difficult to directly transfer existing collaborative transportation methods to the collaborative control of heavily loaded vehicles transporting target goods outdoors, resulting in low accuracy in the collaborative transportation of target goods. Summary of the Invention

[0004] Therefore, it is necessary to provide a hierarchical modeling and constraint-following control method, device, computer equipment, computer-readable storage medium, and computer program product for a multi-vehicle cooperative transportation system to address the above-mentioned technical problems.

[0005] Firstly, this application provides a hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system. The method includes:

[0006] The system acquires the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo.

[0007] Based on the desired transportation trajectory, external constraint information of the transportation system is constructed, and internal constraint information of the transportation system is constructed according to the positional relationship between each vehicle and the target cargo.

[0008] Based on the external constraint information of the transportation system, the tracking control law expression of the target cargo is generated through the unconstrained three-dimensional model of the target cargo, and based on the internal constraint information of the transportation system, the following control law expression of each vehicle is generated through the unconstrained three-dimensional model of each vehicle.

[0009] Based on the tracking control law expression of the target cargo and the following control law expression of each vehicle, and according to the force data between each vehicle and the target cargo, the actual control law expression of each vehicle is established.

[0010] Based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle, the control command corresponding to each vehicle is determined and output.

[0011] Optionally, the step of constructing external constraint information for the transportation system based on the desired transportation trajectory, and constructing internal constraint information for the transportation system based on the positional relationship between each vehicle and the target cargo, includes:

[0012] Obtain the spatial location information of the centroid of the target cargo;

[0013] Based on the desired transportation trajectory, the spatial location range of the multi-dimensional change of the spatial location of the desired transportation trajectory is extracted, and based on each spatial location range, the desired transportation trajectory is divided into multiple sub-transport trajectories. Based on each sub-transport trajectory, the external constraint information of the transportation system is determined.

[0014] For each vehicle, based on the spatial location information of the vehicle and the spatial location information of the target cargo, the connection point between the vehicle and the target cargo, and the relative position information between the vehicle and the centroid of the target cargo are calculated. Based on the relative position information, the internal constraint information of the transportation system corresponding to the vehicle is determined. The relative position information includes relative distance information and relative angle information.

[0015] Optionally, the step of generating a tracking control law expression for the target cargo based on the external constraint information of the transportation system and an unconstrained three-dimensional model of the target cargo includes:

[0016] For each sub-transport trajectory, a trajectory change expression is fitted based on the spatial location information points contained in the sub-transport trajectory;

[0017] Based on the unconstrained three-dimensional model of the target cargo, the parameter information of the trajectory change expression of each sub-transport trajectory is adjusted, and the tracking control law expression of the target cargo is determined according to the spatial position information of the target cargo at the starting position of each sub-transport trajectory, the spatial position information of the target cargo at the ending position of each sub-transport trajectory, and the adjusted trajectory change expression of each sub-transport trajectory.

[0018] Optionally, the step of generating a following control law expression for each vehicle based on the internal constraint information of the transportation system and an unconstrained three-dimensional model of each vehicle includes:

[0019] For each vehicle, based on the connection point between the vehicle and the target cargo and the relative position information of the vehicle and the centroid of the target cargo, a positional constant expression for the spatial position information of the target cargo and the spatial position information of the vehicle is established.

[0020] Based on the unconstrained three-dimensional model of the vehicle, the parameter information of the position constant expression is adjusted to obtain the following control law expression of the vehicle.

[0021] Optionally, the step of establishing the actual control law expression for each vehicle based on the tracking control law expression of the target cargo and the following control law expression for each vehicle, according to the force data between each vehicle and the target cargo, includes:

[0022] Obtain the force data between each of the vehicles and the target cargo;

[0023] For each vehicle, the vehicle's operation control law expression is determined based on the vehicle's following control law expression and the target cargo's tracking control law expression.

[0024] Based on the force data between the vehicle and the target cargo, the constant parameters of the vehicle's operating control law expression are adjusted, and the adjusted operating control law expression of the vehicle is used as the actual control law expression of the vehicle.

[0025] Optionally, determining and outputting control commands corresponding to each vehicle based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle includes:

[0026] Based on the current spatial location information of each vehicle and the current spatial location information of the target cargo, calculate the relative position information between each vehicle and the target cargo;

[0027] For each vehicle, based on the current spatial location information of the target cargo, the current spatial location information of the vehicle, and the actual control law expression of the vehicle, the new spatial location information of the vehicle and the sub-control command of the vehicle from the current spatial location information of the vehicle to the new spatial location information of the vehicle are calculated, and the spatial location information of the connection point between the vehicle and the target cargo is determined based on the relative position of the vehicle and the target cargo.

[0028] Based on the spatial location information of the connection point between each vehicle and the target cargo, the new spatial location information of the target cargo is obtained;

[0029] If the new spatial location information of the target cargo does not coincide with the spatial location information of the destination, the current spatial location information of each vehicle is updated to the new spatial location information of each vehicle, and the current spatial location information of the target cargo is updated to the new spatial location information of the target cargo. Then, the process returns to the step of calculating the new spatial location information of each vehicle based on the current spatial location information of the target cargo and the current spatial location information of the vehicle, and through the actual control law expression of the vehicle, until the new spatial location information of the target cargo coincides with the spatial location information of the destination. Finally, the control command for each vehicle from the current spatial location information of the target cargo to the spatial location information of the destination is output.

[0030] Secondly, this application also provides a hierarchical modeling and constraint-following control device for a multi-vehicle cooperative transportation system.

[0031] The device includes:

[0032] The acquisition module is used to acquire the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo;

[0033] The modeling module is used to construct external constraint information of the transportation system based on the desired transportation trajectory, and to construct internal constraint information of the transportation system according to the positional relationship between each vehicle and the target cargo.

[0034] The generation module is used to generate a tracking control law expression for the target cargo based on the external constraint information of the transportation system and the unconstrained three-dimensional model of the target cargo, and to generate a following control law expression for each vehicle based on the internal constraint information of the transportation system and the unconstrained three-dimensional model of each vehicle.

[0035] A module is established to establish the actual control law expression for each vehicle based on the tracking control law expression of the target cargo, the following control law expression of each vehicle, and the force data between each vehicle and the target cargo.

[0036] The output module is used to determine and output the control commands corresponding to each vehicle based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle.

[0037] Optionally, the modeling module is specifically used for:

[0038] Obtain the spatial location information of the centroid of the target cargo;

[0039] Based on the desired transportation trajectory, the spatial location range of the multi-dimensional change of the spatial location of the desired transportation trajectory is extracted, and based on each spatial location range, the desired transportation trajectory is divided into multiple sub-transport trajectories. Based on each sub-transport trajectory, the external constraint information of the transportation system is determined.

[0040] For each vehicle, based on the spatial location information of the vehicle and the spatial location information of the target cargo, the connection point between the vehicle and the target cargo, and the relative position information between the vehicle and the centroid of the target cargo are calculated. Based on the relative position information, the internal constraint information of the transportation system corresponding to the vehicle is determined. The relative position information includes relative distance information and relative angle information.

[0041] Optionally, the generation module is specifically used for:

[0042] For each sub-transport trajectory, a trajectory change expression is fitted based on the spatial location information points contained in the sub-transport trajectory;

[0043] Based on the unconstrained three-dimensional model of the target cargo, the parameter information of the trajectory change expression of each sub-transport trajectory is adjusted, and the tracking control law expression of the target cargo is determined according to the spatial position information of the target cargo at the starting position of each sub-transport trajectory, the spatial position information of the target cargo at the ending position of each sub-transport trajectory, and the adjusted trajectory change expression of each sub-transport trajectory.

[0044] Optionally, the generation module is specifically used for:

[0045] For each vehicle, based on the connection point between the vehicle and the target cargo and the relative position information of the vehicle and the centroid of the target cargo, a positional constant expression for the spatial position information of the target cargo and the spatial position information of the vehicle is established.

[0046] Based on the unconstrained three-dimensional model of the vehicle, the parameter information of the position constant expression is adjusted to obtain the following control law expression of the vehicle.

[0047] Optionally, the establishment module is specifically used for:

[0048] Obtain the force data between each of the vehicles and the target cargo;

[0049] For each vehicle, the vehicle's operation control law expression is determined based on the vehicle's following control law expression and the target cargo's tracking control law expression.

[0050] Based on the force data between the vehicle and the target cargo, the constant parameters of the vehicle's operating control law expression are adjusted, and the adjusted operating control law expression of the vehicle is used as the actual control law expression of the vehicle.

[0051] Optionally, the output module is specifically used for:

[0052] Based on the current spatial location information of each vehicle and the current spatial location information of the target cargo, calculate the relative position information between each vehicle and the target cargo;

[0053] For each vehicle, based on the current spatial location information of the target cargo, the current spatial location information of the vehicle, and the actual control law expression of the vehicle, the new spatial location information of the vehicle and the sub-control command of the vehicle from the current spatial location information of the vehicle to the new spatial location information of the vehicle are calculated, and the spatial location information of the connection point between the vehicle and the target cargo is determined based on the relative position of the vehicle and the target cargo.

[0054] Based on the spatial location information of the connection point between each vehicle and the target cargo, the new spatial location information of the target cargo is obtained;

[0055] If the new spatial location information of the target cargo does not coincide with the spatial location information of the destination, the current spatial location information of each vehicle is updated to the new spatial location information of each vehicle, and the current spatial location information of the target cargo is updated to the new spatial location information of the target cargo. Then, the process returns to the step of calculating the new spatial location information of each vehicle based on the current spatial location information of the target cargo and the current spatial location information of the vehicle, and through the actual control law expression of the vehicle, until the new spatial location information of the target cargo coincides with the spatial location information of the destination. Finally, the control command for each vehicle from the current spatial location information of the target cargo to the spatial location information of the destination is output.

[0056] Thirdly, this application provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described in any one of the first aspects.

[0057] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0058] Fifthly, this application provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0059] A hierarchical modeling and constrained following control method for a multi-vehicle cooperative transportation system is proposed. This method acquires the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo. Based on the expected transportation trajectory, external constraint information of the transportation system is constructed. Internal constraint information of the transportation system is constructed based on the positional relationship between each vehicle and the target cargo. Based on the external constraint information, a tracking control law expression for the target cargo is generated using an unconstrained 3D model of the target cargo. Similarly, based on the internal constraint information, a following control law expression for each vehicle is generated using an unconstrained 3D model of each vehicle. Based on the tracking control law expression for the target cargo and the following control law expression for each vehicle, and according to the force data between each vehicle and the target cargo, an actual control law expression for each vehicle is established. Finally, based on the current spatial location information of each vehicle and the current spatial location information of the target cargo, control commands for all vehicles are output using the actual control law expressions for each vehicle. Firstly, establishing unconstrained 3D models of the target cargo and each vehicle enhances the practicality of the control method. Secondly, by establishing the expected transportation trajectory of the target cargo and the positional relationship between each vehicle and the target cargo, external and internal constraint information conditions of the transportation system are established to ensure the practicality of the control standards of each vehicle. Then, by using the constraint information and the three-dimensional model, the actual control law expression of each vehicle is established, realizing a multi-vehicle cooperative control method based on comprehensive constraint factors, which improves the accuracy of cooperative transportation of target cargo. Attached Figure Description

[0060] Figure 1 This is a flowchart illustrating a hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system in one embodiment.

[0061] Figure 2 This is a schematic diagram of the structure of a multi-vehicle cooperative transportation system in one embodiment;

[0062] Figure 3 This is a flowchart illustrating the constraint information construction steps in one embodiment;

[0063] Figure 4 This is a flowchart illustrating the control instruction generation steps in one embodiment;

[0064] Figure 5This is a flowchart illustrating a hierarchical modeling and constraint-following control example of a multi-vehicle cooperative transportation system in one embodiment.

[0065] Figure 6 This is a block diagram of a hierarchical modeling and constraint-following control device for a multi-vehicle cooperative transportation system in one embodiment.

[0066] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0068] This application provides a hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system. This embodiment illustrates the method using a terminal as an example. It is understood that this method can also be applied to a server, or to a system including both a terminal and a server, and implemented through interaction between the terminal and the server. The terminal can be, but is not limited to, various personal computers, laptops, smartphones, tablets, etc. The server can be a standalone server or a server cluster composed of multiple servers. First, the terminal establishes an unconstrained 3D model of the target cargo and each vehicle to enhance the practicality of the control method. Second, by using the expected transportation trajectory of the target cargo and the positional relationship between each vehicle and the target cargo, external and internal constraint information conditions of the transportation system are established to ensure the practicality of the control standards for each vehicle. Then, the actual control law expression for each vehicle is established using the constraint information and the 3D model. This considers comprehensive constraint factors, avoids ideal-state control calculations, and improves the efficiency of cooperative transportation of the target cargo.

[0069] In one embodiment, such as Figure 1 As shown, a hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system is provided. Taking the application of this method to a terminal as an example, the method includes the following steps:

[0070] Step S101: Obtain the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo.

[0071] In this embodiment, the terminal obtains the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo through data information pre-transmitted by multiple sub-terminals. Each sub-terminal is installed in each vehicle, which is an autonomous driving vehicle. Each vehicle obtains the force data between itself and the target cargo based on the weight of the target cargo it carries, and obtains the spatial location information of each vehicle using a geodetic coordinate system. The positional relationship between each vehicle and the target cargo is the positional relationship between the connection point of the vehicle and the target cargo and the spatial location of the target cargo's center of mass. The positional relationship between each vehicle and the large target cargo includes the current spatial location information of each vehicle and the current spatial location information of the target cargo. The expected transportation trajectory of the target cargo can be stored in any one of the sub-terminals. This expected trajectory includes the expected horizontal and vertical positions and orientation angles of each location point on the transportation trajectory, denoted as x, y ... od (t), y id (t), θ od (t). For example... Figure 2 As shown, the location circled by the irregular polygon is the target cargo, and the connection point between each vehicle and the target cargo is the hinge point. The positional relationship between the hinge point and the center of mass of the target cargo is the positional relationship between each vehicle and the target cargo.

[0072] Step S102: Based on the desired transportation trajectory, construct the external constraint information of the transportation system, and construct the internal constraint information of the transportation system according to the positional relationship between each vehicle and the target cargo.

[0073] In this embodiment, the terminal constructs external constraint information for the entire transportation system based on the desired transportation trajectory. The transportation system is the overall system of all vehicles and target cargo. The terminal constructs internal constraint information for each vehicle based on the positional relationship between each vehicle and the target cargo. Specifically, the external constraint information constrains the desired trajectory of the cargo, represented as functions x = x(t), y = y(t), θ = θ(t) that express the desired coordinates of the cargo. The internal constraint information specifically concerns the positional relationship between the transport vehicle and the cargo. To coordinate the transportation of rigid cargo, this positional relationship should remain constant, specifically represented as a geometric relationship. The detailed construction process will be explained in detail later.

[0074] Step S103: Based on the external constraint information of the transportation system, generate the tracking control law expression for the target cargo using the unconstrained three-dimensional model of the target cargo, and based on the internal constraint information of the transportation system, generate the following control law expression for each vehicle using the unconstrained three-dimensional model of each vehicle.

[0075] In this embodiment, the terminal establishes an unconstrained 3D model of each vehicle and an unconstrained 3D model of the target vehicle based on an aerodynamic model construction method. The aerodynamic model construction method can be, but is not limited to, Newton's laws of motion or the Lagrange method. Based on the external constraint information of the transportation system, the terminal generates a tracking control law expression for the target cargo using the unconstrained 3D model of the target cargo. Based on the internal constraint information of the transportation system, the terminal generates a following control law expression for each vehicle based on its unconstrained 3D model. The control law expression is a formula for controlling the vehicle to perform transportation. The specific generation process will be explained in detail later.

[0076] Step S104: Based on the tracking control law expression of the target cargo and the following control law expression of each vehicle, and according to the force data between each vehicle and the target cargo, establish the actual control law expression of each vehicle.

[0077] In this embodiment, the terminal, for each vehicle, establishes an actual control law expression for each vehicle based on the tracking control law expression of the target cargo and the following control law expression of the vehicle, according to the force data between the vehicle and the target cargo. The input to the actual control law expression includes two parts: one is the vehicle's control input, such as wheel angle and driving force for a typical car. For wheel angle and driving force, this could be the steering angle of the front and rear wheels and the driving force of the rear wheels. The other part is the vehicle's state input, including position, speed, etc. Similarly, through the above steps and methods, the terminal establishes the actual control law expression for each vehicle.

[0078] Step S105: Based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle, determine and output the control command corresponding to each vehicle.

[0079] In this embodiment, for each vehicle, the terminal, based on the vehicle's current spatial location information and the target cargo's current spatial location information, obtains the control command for the current stage of the vehicle through the actual control law expression of each vehicle, and outputs the vehicle's new spatial location information. Repeating the above steps, the terminal obtains control commands for all stages from the target cargo's current spatial location information to the destination's spatial location information, and integrates the control commands for each stage to obtain the overall control command for the vehicle. Similarly, through the above steps, the terminal obtains the control commands for all vehicles.

[0080] Based on the above scheme, firstly, the practicality of the control method is improved by establishing an unconstrained 3D model of the target cargo and each vehicle. Secondly, by establishing the expected transportation trajectory of the target cargo and the positional relationship between each vehicle and the target cargo, external and internal constraint information conditions of the transportation system are established to ensure the practicality of the control standards for each vehicle. Then, the actual control law expression for each vehicle is established using the constraint information and the 3D model, realizing a multi-vehicle cooperative control method based on comprehensive constraint factors. This avoids the control calculation method of ideal state and improves the accuracy of cooperative transportation of the target cargo.

[0081] Optional, such as Figure 3 As shown, based on the desired transportation trajectory, external constraint information of the transportation system is constructed, and internal constraint information of the transportation system is constructed according to the positional relationship between each vehicle and the target cargo, including:

[0082] Step S301: Obtain the spatial location information of the centroid of the target cargo.

[0083] In this embodiment, the terminal determines the spatial location information of the centroid of the target cargo based on the target cargo's spatial location information by using the target cargo's preset centroid location.

[0084] Step S302: Based on the desired transportation trajectory, extract the spatial location intervals of the multi-dimensional changes in the spatial location of the desired transportation trajectory, and divide the desired transportation trajectory into multiple sub-transportation trajectories based on each spatial location interval. Based on each sub-transportation trajectory, determine the external constraint information of the transportation system.

[0085] In this embodiment, the terminal divides the desired transportation trajectory into multiple spatial location intervals and extracts the multi-dimensional changing spatial location intervals within each trajectory interval. A spatial location interval is a combination of multiple spatial location points, representing a segment of the transportation trajectory. A multi-dimensional changing spatial location interval is a transportation trajectory where information changes occur in more than one dimension; these multi-dimensional changes can be, but are not limited to, combinations of one or more of the following: climbing, turning, and descending. The terminal treats each spatial location interval as a sub-transportation trajectory and determines the external constraint information of the transportation system based on the expressions for each sub-transportation trajectory (i.e., expressions showing coordinate changes over time).

[0086] Specifically, the process of constructing the external constraint information of the transportation system is as follows:

[0087] The purpose of multi-vehicle cooperative transportation is to enable goods to move from the starting point to the destination along a desired trajectory. Given the desired trajectory, the formula for determining the external constraints based on all sub-traffic trajectories is as follows:

[0088]

[0089] Where e o This indicates the error in cargo tracking. That is:

[0090]

[0091] In equation (2), x o y o and θ o Let x represent the actual coordinates and orientation angle of the cargo, respectively. od y od and θ od Let represent the expected coordinates and expected orientation angle of the cargo at the same moment, respectively, while γ o It is a constant greater than 0. Differential equation (1) guarantees the error vector e. o It converges smoothly to the zero vector, which meets the requirements of the external constraint information.

[0092] Step S303: For each vehicle, based on the vehicle's spatial location information and the target cargo's spatial location information, calculate the connection point between the vehicle and the target cargo, and the relative position information between the vehicle and the target cargo's centroid. Based on the relative position information, determine the internal constraint information of the transportation system corresponding to the vehicle.

[0093] The relative position information includes relative distance information and relative angle information.

[0094] In this embodiment, for each vehicle, the terminal calculates the connection point between the vehicle and the target cargo, and the relative position information between the vehicle and the target cargo's centroid, based on the vehicle's spatial location information and the target cargo's spatial location information. The relative position information includes the spatial distance and azimuth angle between the connection point between the vehicle and the target cargo, and between the vehicle and the target cargo's centroid (i.e., relative distance information and relative angle information). This relative position information is then used as internal constraint information for the transportation system corresponding to the vehicle.

[0095] Specifically, the process of constructing the internal constraint information of the transportation system is as follows:

[0096] When multiple vehicles collaboratively transport rigid goods, a significant characteristic is that the relative positional relationship between the connection point between the vehicle and the goods and any point on the goods remains unchanged (i.e., the relative positional information remains constant). For convenience, this point is chosen as the center of mass of the goods. In a fixed coordinate system B of the goods with the center of mass of the goods as the origin and the orientation of the goods as the positive direction, we have:

[0097]

[0098] In formula (3) and Let r represent the coordinates of the end effector of the i-th vehicle in the cargo coordinate system B. iLet φ be the distance from the end unit of the i-th vehicle to the center of the cargo. i Let be the angle between the line connecting the end device of vehicle i and the center of gravity of the cargo and the cargo orientation. Transform to a geodetic coordinate system. Below, there is

[0099]

[0100] Substituting into equation (3), we get:

[0101]

[0102] This refers to the internal constraint information that the system should satisfy under rigid cargo constraints. Although this constraint should theoretically always be satisfied in collaborative transportation, in order to ensure stable and reliable requirements, the constraint is still rewritten in a form similar to equation (1) to ensure rapid convergence when errors occur.

[0103]

[0104] in:

[0105]

[0106] γ represents the deviation between the actual and desired positions of the end effector of the i-th vehicle (in fact, this error is always zero when there is a rigid constraint between the cargo and the vehicle). i It is a positive constant.

[0107] Based on the above scheme, by determining the internal and external constraint information of the transportation system, a reference basis is provided for subsequently determining the tracking control law expression for the target cargo and the following control law expression for each vehicle.

[0108] Optionally, based on the external constraint information of the transportation system, a tracking control law expression for the target cargo is generated using an unconstrained 3D model of the target cargo. This includes: for each sub-transport trajectory, fitting a trajectory change expression for the sub-transport trajectory based on the spatial location information points contained in the sub-transport trajectory; adjusting the parameter information of the trajectory change expression for each sub-transport trajectory based on the unconstrained 3D model of the target cargo; and determining the tracking control law expression for the target cargo based on the spatial location information of the target cargo at the starting position of each sub-transport trajectory, the spatial location information of the target cargo at the ending position of each sub-transport trajectory, and the adjusted trajectory change expression for each sub-transport trajectory.

[0109] In this embodiment, for each sub-transport trajectory, the terminal fits a trajectory change expression for that sub-transport trajectory based on the spatial location information points contained within it. This trajectory change expression is a three-dimensional expression. Based on an unconstrained three-dimensional model of the target cargo, the terminal adjusts the parameter information of the trajectory change expression for each sub-transport trajectory. Specifically, the terminal adjusts the constant parameter information in the trajectory change expression to ensure successful transportation of the target cargo across multi-dimensional spatial location ranges such as turns, uphill sections, and downhill sections. The terminal uses the spatial location information of the target cargo at the starting and ending positions of each sub-transport trajectory, along with the adjusted set of trajectory change expressions for each sub-transport trajectory, as the tracking control law expression for the target cargo.

[0110] Specifically, the process of constructing an unconstrained 3D model of the target cargo is as follows:

[0111] Select the lateral position, longitudinal position, and orientation angle q of the cargo. o =(x o (t),y o (t),θ o Using the generalized coordinates (t), an unconstrained dynamic model of the cargo (an unconstrained three-dimensional model of the target cargo) can be constructed based on the Newton-Euler method or the Lagrange method. This dynamic model can be expressed as:

[0112]

[0113] Where M o The cargo inertia matrix can be represented as:

[0114]

[0115] Where m o For the quality of goods, I o Let be the moment of inertia of the cargo about the z-axis. This represents the total damping force acting on the cargo, such as air resistance. Due to the large mass of the cargo and the low speed of the cooperative transport system, the damping coefficient C... o Generally small. This dynamic model holds true when no external active force is applied to the cargo.

[0116] The expression for the tracking control law of the target cargo is as follows:

[0117] Taking the zeroth and first-order differentials of equation (8) respectively, we can obtain the following expression:

[0118]

[0119]

[0120] Among them, A o It is the identity matrix.

[0121]

[0122]

[0123] In the above formula, c o b is the result of the zeroth-order differential. o γ is the result of the first derivative. o It is a positive constant (see equation (2) for further explanation). Based on the Udwadia-Kalaba equations in analytical mechanics and the Lyapunov stability analysis method in modern control theory, the expression for the tracking control law applied to the cargo is:

[0124]

[0125] in κ represents the inherent property force acting on the goods. o >0 is a constant, an adjustable controller parameter that determines the error convergence rate. (·) + This represents the pseudo-inverse of the matrix. The constrained dynamic model of the cargo itself is as follows:

[0126]

[0127] Substituting into equation (14) and solving the differential equation (i.e., adjusting the parameter information of the trajectory change expression of each sub-transport trajectory based on the unconstrained three-dimensional model of the target cargo), we get the movement trajectory of the cargo under the control law (i.e., the trajectory change expression of the sub-transport trajectory).

[0128] Based on the above scheme, the terminal adjusts the trajectory change expression of the target cargo using an unconstrained three-dimensional model of the target cargo, thereby obtaining the tracking control law expression of the target cargo and improving the actual operability of the tracking control law expression of the target cargo.

[0129] Optionally, based on the internal constraint information of the transportation system, a following control law expression for each vehicle is generated using an unconstrained 3D model of each vehicle. This includes: for each vehicle, establishing a position-constant expression for the spatial position information of the target cargo and the vehicle based on the relative position information of the connection point between the vehicle and the target cargo and the centroid of the target cargo; and adjusting the parameter information of the position-constant expression based on the unconstrained 3D model of the vehicle to obtain the following control law expression for the vehicle.

[0130] In this embodiment, for each vehicle, the terminal establishes a position-constant expression for the spatial position information of the target cargo and the vehicle, based on the connection point between the vehicle and the target cargo and the relative position information of the vehicle and the target cargo's center of mass. This position-constant expression ensures that the connection point between the vehicle and the target cargo and the relative position information of the target cargo's center of mass remain unchanged, thereby enabling the vehicle to transport the target cargo smoothly. Based on the unconstrained 3D model of the vehicle, the terminal adjusts the parameters of the position-constant expression to obtain the vehicle's following control law expression. This following control law expression enables lateral and longitudinal coupled control of the vehicle, including generalized control inputs in the lateral, longitudinal, and yaw directions.

[0131] Specifically, the process of constructing an unconstrained 3D model for each vehicle is as follows:

[0132] Select the vehicle's lateral position, longitudinal position, and heading angle q. i =(x i (t),y i (t),θ i (t) represents the generalized coordinates, and an unconstrained dynamic model of the vehicle can be constructed using the Newton-Euler method or the Lagrange method. Different vehicle drive and steering configurations result in different dynamic models. This invention does not require a specific vehicle drive and steering configuration. Assuming the vehicle has four-wheel steering and rear-wheel drive capabilities, the vehicle dynamic model (unconstrained three-dimensional model) can be expressed as:

[0133]

[0134] in:

[0135]

[0136] Let m be the vehicle inertia matrix. i For single vehicle mass, I i Let C be the moment of inertia of the vehicle about the z-axis (i.e., the coordinate axis perpendicular to the ground). i Given the damping matrix, we have:

[0137]

[0138] and:

[0139]

[0140] In equations (18) and (19), u i Let C be the velocity component of the i-th vehicle along its orientation. fi C ri These are the lateral stiffness of the front and rear tires, respectively. i b is the distance from the center of mass to the front axle. iF is the distance from the center of mass to the rear axle. Ffi For front axle running resistance, F Fri These are the rear axle running resistances, which can be calculated based on the vertical load and the rolling resistance coefficient between the ground and the tire.

[0141] like Figure 2 As shown, the vehicle and cargo are connected by an articulation device. For the i-th vehicle, the articulation point is located on the vehicle's central axis at a distance d from the center of mass. i Therefore, the forward dynamics expression (i.e., the position-constant expression) from the vehicle's generalized coordinates to the connection point can be expressed as:

[0142]

[0143] This forward dynamic is denoted as:

[0144] q ei =Π(q) i )

[0145] This forward dynamics also applies to vehicles with other forward dynamics expressions; Equation (20) is only one example.

[0146] The process of constructing the vehicle's following control law expression is as follows:

[0147] The purpose of determining the following control law expression for the vehicle based on the internal constraint information is to obtain the constraint force required to maintain the internal constraint information, and then determine the control law applied to each vehicle. Substituting equation (20) into equation (7), and then substituting equation (7) into equation (6), and taking the zeroth and first order differentials of equation (6) respectively, we can obtain the following form:

[0148]

[0149]

[0150] in:

[0151]

[0152]

[0153] b i =[b i,1 b i,2 ] T #(25)

[0154] In equation (25):

[0155]

[0156]

[0157] Similarly, based on the Udwadia-Kalaba equations and the Lyapunov stability analysis method, the expression for the total constraint force of the i-th vehicle is:

[0158]

[0159] In other words, since each vehicle maintains the aforementioned relative positional relationship with the cargo, the total constraint force (i.e., net external force) on each vehicle during transportation is Q. ci It can be represented by equation (26).

[0160] Based on the above scheme, the terminal adjusts the position constant expression of the spatial position information of the target cargo and the spatial position information of the vehicle through the unconstrained three-dimensional model of the vehicle, thereby obtaining the following control law expression of the vehicle and improving the actual operability of the following control law expression of the vehicle.

[0161] Optionally, based on the tracking control law expression of the target cargo and the following control law expression of each vehicle, and according to the force data between each vehicle and the target cargo, an actual control law expression for each vehicle is established, including: acquiring the force data between each vehicle and the target cargo; for each vehicle, determining the vehicle's operating control law expression based on the vehicle's following control law expression and the target cargo's tracking control law expression; adjusting the constant parameters of the vehicle's operating control law expression based on the force data between the vehicle and the target cargo, and using the adjusted vehicle operating control law expression as the vehicle's actual control law expression.

[0162] In this embodiment, the terminal determines the vehicle's operating control law expression for each vehicle based on the vehicle's following control law expression and the target cargo's tracking control law expression. The terminal adjusts the constant parameters of the vehicle's operating control law expression based on the force data between the vehicle and the target cargo, and uses the adjusted operating control law expression as the vehicle's actual control law expression. Similarly, through the above scheme, the terminal obtains the actual control law expressions for all vehicles.

[0163] Specifically, the vehicle following control law expression given in the above steps includes the actual control exerted on the vehicle by the vehicle's actuator system and the reaction force of the cargo on the vehicle. For any transport vehicle, solving its following control law expression does not depend on the current state of other transport vehicles. Therefore, to solve for the actual control exerted on the vehicle by the actuator, it is only necessary to pre-allocate the force exerted by the vehicle on the cargo, and then calculate the difference between the generalized control law and the cargo reaction force vector to obtain the actual control law expression for that vehicle.

[0164] Specifically, the process of constructing the actual control law expression is as follows:

[0165] Force analysis of the cargo reveals that its actual control law Q co The force is applied by the end-connection devices of each vehicle. According to the embodiment, it is assumed that the force exerted by the end-connector of the i-th vehicle on the target cargo in the plane can be decomposed into two orthogonal components [F]. ex,i F ey,i ] T Let F e =[F ex,1 F ey,1 F ex,2 F ey,2 … F ex,N F ey,N ] T Then we have:

[0166] J f F e =Q co #(27)

[0167] The relationship between the force exerted by each vehicle on the cargo and the resultant force on the cargo (i.e., the tracking control law of equation (14)) is given by J. f The "grabbing matrix" can be represented as follows in this embodiment:

[0168]

[0169] in:

[0170]

[0171] Where δ i Let be the angle between the line connecting the connecting mechanism and the center of mass of the cargo along the positive x-axis. Solving equation (27) yields:

[0172]

[0173] Where z is a matrix with dimension equal to 1. Any vector with a row number of , i.e. In J f Within the null space, the design of z allows for the distribution of forces exerted by each vehicle on the cargo (i.e., the force data between the vehicle and the target cargo). If z = 0 is chosen, then F can be obtained. e The minimum Euclidean norm solution helps to reduce the force F exerted by the vehicle on the target cargo without affecting trajectory tracking performance. ei The amplitude.

[0174] According to Newton's third law, the reaction force exerted on the vehicle's end-connector by the cargo is -F. eiAccording to the inverse kinematics of the forward kinematics of equation (7), the equivalent force F of the reaction force on the vehicle's center of mass can be obtained. i for:

[0175]

[0176] Where the matrix is:

[0177]

[0178] Π represents the forward dynamics expression from the vehicle's center of gravity to the end effector. From the preceding steps, it can be seen that the operating control law (i.e., the operating control law expression) applied to the i-th vehicle is:

[0179]

[0180] In equation (30) z i For a matrix with dimension equal to 1 An arbitrary vector with a row number. In the operational control law, Q... ci and Q co The acquisition only requires the current status of the goods and vehicles, while z i The assignment can be made by vehicle number 1. According to vehicle dynamics, the dynamic model, including driving force and steering angle input (i.e., the actual control law), can be expressed as:

[0181]

[0182] Where M i q i C i G i The meaning is the same as in the previous expression, but:

[0183]

[0184]

[0185]

[0186] τ i,3 =-C fi a i δ fi +C ri b i δ ri -(F di -F Ffi )b i δ ri -F Ffi a i δ fi

[0187] Where FFfi and F Fri τ represents the resistance force experienced by the front and rear wheels, respectively. i =[τ i,1 τ i,2 τ i,3 ] T Therefore, by τ i The expression can be used to calculate the turning angle δ of the i-th vehicle. fi δ ri and driving force F di .

[0188] Based on the above scheme, by using the tracking control law expression for the target cargo and the following control law expression for each vehicle, and based on the force data between each vehicle and the target cargo, an actual control law expression for each vehicle is established. This ensures the practicality of the actual control law expression for each vehicle.

[0189] Optional, such as Figure 4 As shown, based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle, the control commands corresponding to each vehicle are determined and output, including:

[0190] Step S401: Calculate the relative position information between each vehicle and the target cargo based on the current spatial position information of each vehicle and the current spatial position information of the target cargo.

[0191] In this embodiment, the terminal calculates the relative position information between each vehicle and the target cargo based on the current spatial position information of each vehicle and the current spatial position information of the target cargo. The relative position information between the vehicle and the target cargo includes the spatial distance and spatial angle between the connection point between the vehicle and the target cargo and the centroid of the target cargo.

[0192] Step S402: For each vehicle, based on the current spatial location information of the target cargo, the current spatial location information of the vehicle, and the actual control law expression of the vehicle, calculate the new spatial location information of the vehicle and the sub-control instructions of the vehicle from the current spatial location information of the vehicle to the new spatial location information of the vehicle, and determine the spatial location information of the connection point between the vehicle and the target cargo based on the relative position of the vehicle and the target cargo.

[0193] In this embodiment, for each vehicle, the terminal inputs the current spatial location information of the target cargo and the current spatial location information of the vehicle into the vehicle's actual control law expression, calculates the new spatial location information of the vehicle, and generates sub-control instructions for the vehicle from its current spatial location to its new spatial location based on the current spatial location information and the new spatial location information. The terminal also calculates the spatial location information of the connection point between the vehicle and the target cargo based on the relative position of the vehicle and the target cargo.

[0194] Step S403: Based on the spatial location information of the connection point between each vehicle and the target cargo, obtain the new spatial location information of the target cargo.

[0195] In this embodiment, the terminal performs spatial arrangement processing based on the spatial location information of each vehicle's connection point with the target cargo to obtain a new spatial location range for the target cargo. Based on this new spatial location range, and according to the proportion of the target cargo's centroid in the target cargo's spatial location, the terminal calculates the new spatial location information of the target cargo's centroid and uses this new spatial location information as the new spatial location information of the target cargo.

[0196] Step S404: If the new spatial location information of the target cargo does not coincide with the spatial location information of the destination, update the current spatial location information of each vehicle to the new spatial location information of each vehicle, and update the current spatial location information of the target cargo to the new spatial location information of the target cargo. Return to the execution of the step of calculating the new spatial location information of each vehicle based on the current spatial location information of the target cargo and the current spatial location information of the vehicle, through the actual control law expression of the vehicle, until the new spatial location information of the target cargo coincides with the spatial location information of the destination. Output the control command for each vehicle from the current spatial location information of the target cargo to the spatial location information of the destination.

[0197] In this embodiment, the terminal determines whether the new spatial location information of the target cargo overlaps with the spatial location information of the destination. If the new spatial location information of the target cargo does not overlap with the spatial location information of the destination, the terminal updates the current spatial location information of each vehicle with the new spatial location information of each vehicle, and updates the current spatial location information of the target cargo with the new spatial location information of the target cargo, then returns to step S402 until the new spatial location information of the target cargo overlaps with the spatial location information of the destination. The terminal obtains multiple sub-control commands for the vehicle. The terminal arranges and combines the sub-control commands corresponding to each new spatial location information of the vehicle according to the order of spatial location to obtain the control commands for the vehicle.

[0198] Based on the above scheme, the control instructions for the vehicle are generated through the actual control law expression of the vehicle, ensuring that each vehicle can perform the transportation task according to the expected goal, thereby improving the control capability of each vehicle.

[0199] This application also provides an example of hierarchical modeling and constraint-following control for a multi-vehicle cooperative transportation system, as shown in Figure 5. The specific processing steps include:

[0200] Step S501: Obtain the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo.

[0201] Step S502: Obtain the spatial location information of the centroid of the target cargo.

[0202] Step S503: Based on the desired transportation trajectory, extract the spatial location intervals of the multi-dimensional changes in the spatial location of the desired transportation trajectory, and divide the desired transportation trajectory into multiple sub-transportation trajectories based on each spatial location interval. Based on each sub-transportation trajectory, determine the external constraint information of the transportation system.

[0203] Step S504: For each vehicle, based on the vehicle's spatial location information and the target cargo's spatial location information, calculate the connection point between the vehicle and the target cargo, and the relative position information between the vehicle and the target cargo's centroid. Based on the relative position information, determine the internal constraint information of the transportation system corresponding to the vehicle. The relative position information includes relative distance information and relative angle information.

[0204] Step S505: For each sub-transport trajectory, fit the trajectory change expression of the sub-transport trajectory based on the spatial location information points contained in the sub-transport trajectory.

[0205] Step S506: Based on the unconstrained 3D model of the target cargo, adjust the parameter information of the trajectory change expression of each sub-transport trajectory, and determine the tracking control law expression of the target cargo according to the spatial position information of the target cargo at the starting position of each sub-transport trajectory, the spatial position information of the target cargo at the ending position of each sub-transport trajectory, and the adjusted trajectory change expression of each sub-transport trajectory.

[0206] Step S507: For each vehicle, based on the connection point between the vehicle and the target cargo and the relative position information of the vehicle and the centroid of the target cargo, establish a position constant expression for the spatial position information of the target cargo and the spatial position information of the vehicle.

[0207] Step S508: Based on the unconstrained three-dimensional model of the vehicle, adjust the parameter information of the position constant expression to obtain the following control law expression of the vehicle.

[0208] Step S509: Obtain the force data between each vehicle and the target cargo.

[0209] Step S510: For each vehicle, determine the vehicle's operation control law expression based on the vehicle's following control law expression and the target cargo's tracking control law expression.

[0210] Step S511: Based on the force data between the vehicle and the target cargo, adjust the constant parameters of the vehicle's operating control law expression, and use the adjusted vehicle operating control law expression as the vehicle's actual control law expression.

[0211] Step S512: Calculate the relative position information between each vehicle and the target cargo based on the current spatial position information of each vehicle and the current spatial position information of the target cargo.

[0212] Step S513: For each vehicle, based on the current spatial location information of the target cargo, the current spatial location information of the vehicle, and the actual control law expression of the vehicle, calculate the new spatial location information of the vehicle and the sub-control instructions of the vehicle from the current spatial location information of the vehicle to the new spatial location information of the vehicle, and determine the spatial location information of the connection point between the vehicle and the target cargo based on the relative position of the vehicle and the target cargo.

[0213] Step S514: Based on the spatial location information of the connection point between each vehicle and the target cargo, obtain the new spatial location information of the target cargo.

[0214] Step S515: If the new spatial location information of the target cargo does not coincide with the spatial location information of the destination, update the current spatial location information of each vehicle to the new spatial location information of each vehicle, and update the current spatial location information of the target cargo to the new spatial location information of the target cargo. Return to the execution of the step of calculating the new spatial location information of each vehicle based on the current spatial location information of the target cargo and the current spatial location information of the vehicle, through the actual control law expression of the vehicle, until the new spatial location information of the target cargo coincides with the spatial location information of the destination. Output the control command for each vehicle from the current spatial location information of the target cargo to the spatial location information of the destination.

[0215] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0216] Based on the same inventive concept, this application also provides a hierarchical modeling and constraint-following control device for a multi-vehicle cooperative transportation system, used to implement the hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system described above. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of the one or more embodiments of the hierarchical modeling and constraint-following control device for a multi-vehicle cooperative transportation system provided below can be found in the limitations of the hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system described above, and will not be repeated here.

[0217] In one embodiment, such as Figure 6 As shown, a hierarchical modeling and constraint-following control device for a multi-vehicle cooperative transportation system is provided, comprising: an acquisition module 610, a modeling module 620, a generation module 630, a creation module 640, and an output module 650, wherein:

[0218] The acquisition module 610 is used to acquire the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo;

[0219] The modeling module 620 is used to construct external constraint information of the transportation system based on the desired transportation trajectory, and to construct internal constraint information of the transportation system according to the positional relationship between each vehicle and the target cargo.

[0220] The generation module 630 is used to generate a tracking control law expression for the target cargo based on the external constraint information of the transportation system and the unconstrained three-dimensional model of the target cargo, and to generate a following control law expression for each vehicle based on the internal constraint information of the transportation system and the unconstrained three-dimensional model of each vehicle.

[0221] The module 640 is used to establish the actual control law expression for each vehicle based on the tracking control law expression of the target cargo, the following control law expression of each vehicle, and the force data between each vehicle and the target cargo.

[0222] The output module 650 is used to determine and output the control commands corresponding to each vehicle based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle.

[0223] Optionally, the modeling module 620 is specifically used for:

[0224] Obtain the spatial location information of the centroid of the target cargo;

[0225] Based on the desired transportation trajectory, the spatial location range of the multi-dimensional change of the spatial location of the desired transportation trajectory is extracted, and based on each spatial location range, the desired transportation trajectory is divided into multiple sub-transport trajectories, and each sub-transport trajectory is used as the external constraint information of the transportation system.

[0226] For each vehicle, based on the spatial location information of the vehicle and the spatial location information of the target cargo, the connection point between the vehicle and the target cargo, and the relative position information between the vehicle and the centroid of the target cargo are calculated. Based on the relative position information, the internal constraint information of the transportation system corresponding to the vehicle is determined. The relative position information includes relative distance information and relative angle information.

[0227] Optionally, the generation module 630 is specifically used for:

[0228] For each sub-transport trajectory, a trajectory change expression is fitted based on the spatial location information points contained in the sub-transport trajectory;

[0229] Based on the unconstrained three-dimensional model of the target cargo, the parameter information of the trajectory change expression of each sub-transport trajectory is adjusted, and the tracking control law expression of the target cargo is determined according to the spatial position information of the target cargo at the starting position of each sub-transport trajectory, the spatial position information of the target cargo at the ending position of each sub-transport trajectory, and the adjusted trajectory change expression of each sub-transport trajectory.

[0230] Optionally, the generation module 630 is specifically used for:

[0231] For each vehicle, based on the connection point between the vehicle and the target cargo and the relative position information of the vehicle and the centroid of the target cargo, a positional constant expression for the spatial position information of the target cargo and the spatial position information of the vehicle is established.

[0232] Based on the unconstrained three-dimensional model of the vehicle, the parameter information of the position constant expression is adjusted to obtain the following control law expression of the vehicle.

[0233] Optionally, the establishment module 640 is specifically used for:

[0234] Obtain the force data between each of the vehicles and the target cargo;

[0235] For each vehicle, the vehicle's operation control law expression is determined based on the vehicle's following control law expression and the target cargo's tracking control law expression.

[0236] Based on the force data between the vehicle and the target cargo, the constant parameters of the vehicle's operating control law expression are adjusted, and the adjusted operating control law expression of the vehicle is used as the actual control law expression of the vehicle.

[0237] Optionally, the output module 650 is specifically used for:

[0238] Based on the current spatial location information of each vehicle and the current spatial location information of the target cargo, calculate the relative position information between each vehicle and the target cargo;

[0239] For each vehicle, based on the current spatial location information of the target cargo, the current spatial location information of the vehicle, and the actual control law expression of the vehicle, the new spatial location information of the vehicle and the sub-control command of the vehicle from the current spatial location information of the vehicle to the new spatial location information of the vehicle are calculated, and the spatial location information of the connection point between the vehicle and the target cargo is determined based on the relative position of the vehicle and the target cargo.

[0240] Based on the spatial location information of the connection point between each vehicle and the target cargo, the new spatial location information of the target cargo is obtained;

[0241] If the new spatial location information of the target cargo does not coincide with the spatial location information of the destination, the current spatial location information of each vehicle is updated to the new spatial location information of each vehicle, and the current spatial location information of the target cargo is updated to the new spatial location information of the target cargo. Then, the process returns to the step of calculating the new spatial location information of each vehicle based on the current spatial location information of the target cargo and the current spatial location information of the vehicle, and through the actual control law expression of the vehicle, until the new spatial location information of the target cargo coincides with the spatial location information of the destination. Finally, the control command for each vehicle from the current spatial location information of the target cargo to the spatial location information of the destination is output.

[0242] The various modules in the hierarchical modeling and constraint-following control device of the aforementioned multi-vehicle cooperative transportation system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0243] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0244] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0245] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of the method described in the first aspect.

[0246] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect.

[0247] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described in the first aspect.

[0248] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0249] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0250] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0251] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A hierarchical modeling and constraint-following control method for a multi-vehicle cooperative transportation system, characterized in that, The method includes: The system acquires the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo. Based on the desired transportation trajectory, external constraint information of the transportation system is constructed, and internal constraint information of the transportation system is constructed according to the positional relationship between each vehicle and the target cargo. Based on the external constraint information of the transportation system, a tracking control law expression for the target cargo is generated using an unconstrained 3D model of the target cargo. Based on the internal constraint information of the transportation system, a following control law expression for each vehicle is generated using an unconstrained 3D model of each vehicle. For any vehicle, the solution to the following control law expression of the vehicle does not depend on the current state of other vehicles. Based on the tracking control law expression of the target cargo and the following control law expression of each vehicle, and according to the force data between each vehicle and the target cargo, the actual control law expression of each vehicle is established. Based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle, the control command corresponding to each vehicle is determined and output.

2. The method according to claim 1, characterized in that, The process of constructing external constraint information for the transportation system based on the desired transportation trajectory, and constructing internal constraint information for the transportation system based on the positional relationship between each vehicle and the target cargo, includes: Obtain the spatial location information of the centroid of the target cargo; Based on the desired transportation trajectory, the spatial location range of the multi-dimensional change of the spatial location of the desired transportation trajectory is extracted, and based on each spatial location range, the desired transportation trajectory is divided into multiple sub-transport trajectories. Based on each sub-transport trajectory, the external constraint information of the transportation system is determined. For each vehicle, based on the spatial location information of the vehicle and the spatial location information of the target cargo, the connection point between the vehicle and the target cargo, and the relative position information between the vehicle and the centroid of the target cargo are calculated. Based on the relative position information, the internal constraint information of the transportation system corresponding to the vehicle is determined. The relative position information includes relative distance information and relative angle information.

3. The method according to claim 2, characterized in that, The step of generating a tracking control law expression for the target cargo based on the external constraint information of the transportation system and an unconstrained three-dimensional model of the target cargo includes: For each sub-transport trajectory, a trajectory change expression is fitted based on the spatial location information points contained in the sub-transport trajectory; Based on the unconstrained three-dimensional model of the target cargo, the parameter information of the trajectory change expression of each sub-transport trajectory is adjusted, and the tracking control law expression of the target cargo is determined according to the spatial position information of the target cargo at the starting position of each sub-transport trajectory, the spatial position information of the target cargo at the ending position of each sub-transport trajectory, and the adjusted trajectory change expression of each sub-transport trajectory.

4. The method according to claim 1, characterized in that, The step of generating a following control law expression for each vehicle based on the internal constraint information of the transportation system and an unconstrained 3D model of each vehicle includes: For each vehicle, based on the connection point between the vehicle and the target cargo and the relative position information of the vehicle and the centroid of the target cargo, a positional constant expression for the spatial position information of the target cargo and the spatial position information of the vehicle is established. Based on the unconstrained three-dimensional model of the vehicle, the parameter information of the position constant expression is adjusted to obtain the following control law expression of the vehicle.

5. The method according to claim 1, characterized in that, The tracking control law expression based on the target cargo and the following control law expression for each vehicle, and the establishment of the actual control law expression for each vehicle based on the force data between each vehicle and the target cargo, include: Obtain the force data between each of the vehicles and the target cargo; For each vehicle, the vehicle's operation control law expression is determined based on the vehicle's following control law expression and the target cargo's tracking control law expression. Based on the force data between the vehicle and the target cargo, the constant parameters of the vehicle's operating control law expression are adjusted, and the adjusted operating control law expression of the vehicle is used as the actual control law expression of the vehicle.

6. The method according to claim 1, characterized in that, The step of determining and outputting control commands corresponding to each vehicle based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle includes: Based on the current spatial location information of each vehicle and the current spatial location information of the target cargo, calculate the relative position information between each vehicle and the target cargo; For each vehicle, based on the current spatial location information of the target cargo, the current spatial location information of the vehicle, and the actual control law expression of the vehicle, the new spatial location information of the vehicle and the sub-control command of the vehicle from the current spatial location information of the vehicle to the new spatial location information of the vehicle are calculated, and the spatial location information of the connection point between the vehicle and the target cargo is determined based on the relative position of the vehicle and the target cargo. Based on the spatial location information of the connection point between each vehicle and the target cargo, the new spatial location information of the target cargo is obtained; If the new spatial location information of the target cargo does not coincide with the spatial location information of the destination, the current spatial location information of each vehicle is updated to the new spatial location information of each vehicle, and the current spatial location information of the target cargo is updated to the new spatial location information of the target cargo. Then, the process returns to the step of calculating the new spatial location information of each vehicle based on the current spatial location information of the target cargo and the current spatial location information of the vehicle, and through the actual control law expression of the vehicle, until the new spatial location information of the target cargo coincides with the spatial location information of the destination. Finally, the control command for each vehicle from the current spatial location information of the target cargo to the spatial location information of the destination is output.

7. A hierarchical modeling and constraint-following control device for a multi-vehicle cooperative transportation system, characterized in that, The device includes: The acquisition module is used to acquire the positional relationship between each vehicle and the target cargo, the force data between each vehicle and the target cargo, the spatial location information of the destination, and the expected transportation trajectory of the target cargo; The modeling module is used to construct external constraint information of the transportation system based on the desired transportation trajectory, and to construct internal constraint information of the transportation system according to the positional relationship between each vehicle and the target cargo. The generation module is used to generate a tracking control law expression for the target cargo based on the external constraint information of the transportation system and an unconstrained 3D model of the target cargo, and to generate a following control law expression for each vehicle based on the internal constraint information of the transportation system and an unconstrained 3D model of each vehicle; wherein, for any vehicle, the solution of the following control law expression of the vehicle does not depend on the current state of other vehicles. A module is established to establish the actual control law expression for each vehicle based on the tracking control law expression of the target cargo, the following control law expression of each vehicle, and the force data between each vehicle and the target cargo. The output module is used to determine and output the control commands corresponding to each vehicle based on the current spatial location information of each vehicle, the current spatial location information of the target cargo, and the actual control law expression of each vehicle.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 6.

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