Intelligent logistics transportation stacking AGV trolley and control method and system thereof

Abstract

The invention provides an intelligent logistics transportation stacking AGV trolley and a control method and system thereof. The trolley is of an X-shaped Mecanum wheel structure. The method comprises the following steps: acquiring whether a trolley is unloaded and the real-time mass of loaded cargos; monitoring the center-of-gravity position and course angle of the trolley in a world coordinate system and the center-of-gravity position and deviation angle of the cargo in a vehicle body coordinate system in real time, and further constructing a cargo center-of-mass acceleration matrix; calculating an overall required three-dimensional driving force based on the acceleration information; constructing a slip speed matrix by monitoring the wheel speed and the roller rotating speed of each Mecanum wheel; and further calculating the real-time driving force required by each wheel, solving the optimal real-time driving force of each wheel by combining a state variable feedback method, and finally obtaining the optimal real-time rotating speed of each wheel. The method can effectively adapt to dynamic load change and a non-ideal driving state, and the dynamic stability, the path control precision and the intelligent response capability of the trolley in a complex logistics scene are improved.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent AGV vehicles, and particularly relates to an intelligent logistics transportation and palletizing AGV vehicle, and a control method and system thereof. Background Art

[0002] With the development of modern logistics industry, automated forklifts are widely used in logistics warehousing. However, due to the limitation of the wheel system structure, traditional forklifts can only move forward, backward and turn within a limited range, and it is difficult to flexibly cope with the narrow space and complex path operation environment in the warehouse.

[0003] Mecanum Wheel forklifts can achieve omnidirectional free movement, with the capabilities of moving forward, backward, laterally, obliquely and rotating in place, and are very suitable for precise and flexible transportation tasks in the logistics warehousing environment. However, at present, when a Mecanum Wheel forklift lifts goods while transporting them, due to the change in the position of the load center of mass, it is difficult to guarantee its motion control accuracy and safety stability. Therefore, how to achieve precise control of a Mecanum Wheel forklift when transporting and lifting goods simultaneously urgently requires an effective solution. Summary of the Invention

[0004] Based on the above problems, according to an exemplary embodiment of the present disclosure, an intelligent logistics transportation and palletizing AGV vehicle, and a control method and system thereof are provided. The present disclosure optimally solves for the optimal driving force by using a state variable feedback method with an improved coefficient matrix, and finally obtains the optimal real-time rotational speeds of each wheel. This method improves the attitude control stability and driving accuracy of the AGV vehicle under complex loads and dynamic scenarios, and is applicable to efficient anti-rollover palletizing operations.

[0005] In a first aspect of the present disclosure, a control method for an intelligent logistics transportation and palletizing AGV vehicle is provided. The vehicle is an AGV vehicle with X-shaped Mecanum wheels, and is characterized by including the following steps:

[0006] S1: Obtain whether the AGV vehicle is unloaded. If it is carrying goods, obtain the real-time mass of the carried goods;

[0007] S2: Real-time monitor the real-time center of gravity position and heading angle of the entire AGV vehicle carrying goods in the world coordinate system, as well as the real-time center of gravity position and offset angle of the carried goods in the vehicle body coordinate system, and construct a real-time acceleration matrix of the center of gravity of the goods carried on the AGV vehicle in the vehicle body coordinate system;

[0008] S3: Based on the real-time acceleration matrix of the center of gravity of the goods constructed in step S2, calculate the required three-dimensional driving force of the entire AGV vehicle carrying goods;

[0009] S4: Based on the rotational speed of each Mecanum wheel and the rotational speed of the roller obtained from real-time monitoring, construct the slip speed calculation matrix of each wheel of the AGV cart in the vehicle body coordinate system when the AGV cart is walking with the load in real time and lifting the load.

[0010] S5: Based on the calculation results of steps S3 - S4, further calculate the required real-time driving force of each wheel of the AGV cart carrying the load.

[0011] S6: Further, based on the state variable feedback method, solve the optimal real-time driving force of each wheel of the AGV cart carrying the load, and finally obtain the optimal real-time rotational speed of each wheel of the AGV cart carrying the load.

[0012] According to the second aspect of the present disclosure, there is provided a control system for an intelligent logistics transportation and palletizing AGV cart that executes the control method as described above. The control system includes:

[0013] An empty-load and load detection module, configured to obtain information on whether the AGV cart is empty, and if it is carrying a load, the real-time mass of the load carried by the load.

[0014] An IMU inertial measurement unit, configured to obtain the attitude and angular velocity of the whole cart carrying the load in the world coordinate system in real time.

[0015] A real-time kinematic differential positioning module, configured to provide the real-time centroid position and heading angle ψ of the whole AGV cart carrying the load in the world coordinate system in real time.

[0016] A cargo offset angle detection unit, configured to obtain the real-time centroid position and offset angle of the carried load in the vehicle body coordinate system; an encoder, configured to obtain the rotational angular velocity of each Mecanum wheel and the rotational angular velocity of the roller of each Mecanum wheel.

[0017] A cargo centroid acceleration matrix construction module, configured to construct the real-time acceleration matrix of the load carried on the AGV cart.

[0018] A three-dimensional driving force calculation module, configured to calculate the required three-dimensional driving force of the whole AGV cart carrying the load based on the data of the empty-load and load detection module, the IMU inertial measurement unit, the real-time kinematic differential positioning module, the cargo offset angle monitoring unit, and the cargo centroid acceleration matrix construction module.

[0019] A slip speed calculation module, configured to construct the slip speed calculation matrix of each wheel of the AGV cart in the vehicle body coordinate system when the AGV cart is walking with the load in real time and lifting the load.

[0020] A real-time driving force calculation module, configured to further calculate the required real-time driving force of each wheel of the AGV cart carrying goods based on the calculation results of the three-dimensional driving force calculation module and the slip speed calculation module;

[0021] A state feedback optimization solution module, configured to solve the optimal real-time driving force of each wheel of the AGV cart carrying goods based on the state variable feedback method, and finally obtain the optimal real-time rotational speed of each wheel of the AGV cart carrying goods.

[0022] According to the third aspect of the present invention, there is provided an intelligent logistics transportation and palletizing AGV cart, which includes a vehicle base, four Mecanum wheels with an X-shaped installation structure on the vehicle base. The AGV cart further includes the above-mentioned control system, a lift housing arranged above the rear end of the vehicle base, and a transport box carrying component;

[0023] A plurality of lift shafts are arranged in the lift housing for lifting the goods in the goods box fixed by the transport box carrying component;

[0024] A goods box flipping mechanism is arranged in the transport box carrying component for flipping the goods box.

[0025] It should be understood that the content described in the summary of the invention is not intended to limit the key or important features of the embodiments of the present disclosure, nor to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. Brief Description of the Drawings

[0026] The present invention will be described in more detail below based on embodiments and with reference to the drawings. Among them:

[0027] Figure 1 Shows the installation structure of the four Mecanum wheels of the AGV cart on the chassis;

[0028] Figure 2 Shows a schematic flowchart of the control method of the intelligent logistics transportation and palletizing AGV cart of the present disclosure;

[0029] Figure 3 Shows the heading angle direction of the AGV cart in the world coordinate system;

[0030] Figure 4 Shows the offset angle of the centroid of the loaded goods relative to the overall centroid of the cart in the vehicle body coordinate system;

[0031] Figure 5 Shows the offset angle α of the center point of the Mecanum wheel relative to the horizontal axis x of the vehicle body coordinate system i ;

[0032] Figure 6Shows a comparison graph of the control effect of the centroid acceleration of the goods on the path deviation constructed by the method of the present disclosure compared with not using it;

[0033] Figure 7 Shows the wheel plane of the Mecanum wheel and the rolling direction of the rollers;

[0034] Figure 8 Shows the overall center of gravity change trajectory of the trolley carrying goods within 25 minutes in an embodiment of the present disclosure, as well as the monitoring graph of the required driving force and the optimal real-time rotational speed;

[0035] Figure 9 Shows the load Q of the four wheels when the AGV trolley in the present disclosure transports and stacks goods L,i Change situation;

[0036] Figure 10 Shows a comparison graph of the improvement effect of the state variable feedback method on the coefficient matrix in the optimization model in the present disclosure;

[0037] Figure 11 Shows the change situation of the optimal driving force required for the four Mecanum wheels in an embodiment of the present disclosure;

[0038] Figure 12 Shows the change situation of the optimal real-time rotational speed of the four Mecanum wheels in an embodiment of the present disclosure;

[0039] Figure 13 Shows the control system block diagram of the intelligent logistics transportation and stacking AGV trolley in the present disclosure;

[0040] Figure 14 Shows a flipping state structure of an intelligent logistics transportation and stacking AGV trolley provided by the present disclosure;

[0041] Figure 15 Shows several lifting shaft structures arranged inside the trolley lift housing;

[0042] Figure 16 Shows the initial state structure of the trolley with a cargo box and without an empty cargo box;

[0043] Figure 17 Shows a schematic diagram of the cargo box flipping mechanism structure of the trolley;

[0044] Figure 18 Shows the position of the trolley during the process of carrying, transporting and stacking goods;

[0045] Figure 19 Shows the initial state and the lifting state of the trolley. Detailed implementation manners

[0046] The following will describe the embodiments of the present disclosure in more detail with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0047] In the description of the embodiments of the present disclosure, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment / implementation" or "the embodiment / implementation" should be understood as "at least one embodiment / implementation". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0048] The AGV car used in this disclosure is Figure 1 The installation structure layout of the four Mecanum wheels of the X-shaped Mecanum wheel AGV shown in the figure can realize compound movements such as translation, rotation, and tilting in any direction in a two-dimensional plane. It has excellent flexibility and path control capabilities and is widely used in logistics handling, palletizing, and warehouse automation tasks in narrow spaces. The structure of the X-shaped Mecanum wheel is ABAB type, that is, the left front wheel is the A wheel, and the roller faces the right rear -45°; the right front wheel is the B wheel, and the roller faces the right front +45°; the left rear wheel is the B wheel, and the roller faces the right front +45°; the right rear wheel is the A wheel, and the roller faces the left front -45°. Figure 2 The process steps of the intelligent logistics transport and palletizing AGV trolley control method provided by the present disclosure are shown. The method provided by the present disclosure includes the following steps:

[0049] S1: Get information about whether the AGV is empty. If it is loaded, get the real-time mass of the loaded cargo.

[0050] S2: Monitor the real-time center of gravity position and heading angle of the AGV with goods in the world coordinate system, as well as the real-time center of gravity position and offset angle of the goods in the vehicle coordinate system, and construct the real-time acceleration matrix of the center of gravity of the goods on the AGV in the vehicle coordinate system;

[0051] S3: Based on the real-time acceleration matrix of the cargo center constructed in step S2, the three-dimensional driving force required for the AGV with cargo is calculated;

[0052] S4: Based on the rotational speeds of each Mecanum wheel and the rotational speed of the roller obtained from real-time monitoring, construct a calculation matrix for the slip speed of each wheel of the AGV vehicle in the vehicle body coordinate system when the AGV vehicle is walking with the goods in real time and lifting the goods.

[0053] S5: Based on the calculation results of steps S3 - S4, further calculate the required real-time driving force of each wheel of the AGV vehicle carrying the goods.

[0054] S6: Further, based on the state variable feedback method, solve the optimal real-time driving force of each wheel of the AGV vehicle carrying the goods, and finally obtain the optimal real-time rotational speed of each wheel of the AGV vehicle carrying the goods.

[0055] This method can achieve multi-wheel coordinated control under complex loads and motion states, significantly improve the dynamic stability, steering accuracy, and path execution reliability of the AGV vehicle in the logistics palletizing scenario, and effectively improve the transportation safety and intelligent cooperation level of the whole vehicle under complex working conditions.

[0056] When the AGV vehicle carrying the goods is in dynamic driving or lifting, the overall center of gravity position will change, especially significantly when the goods are unevenly distributed. Only by mastering the real-time position and acceleration of the center of gravity of the goods in the vehicle body coordinate system can we ensure that the control algorithm accurately judges the dynamic stability of the whole vehicle, and adjusts the driving force and speed of each wheel in real time to ensure that the center of gravity projection falls within the support polygon to prevent tipping, and then accurately achieve state variable feedback in predictive model control (such as MPC). In some embodiments, step S2 includes:

[0057] S21: Figure 3 Illustrates the relationship between the heading angle ψ, yaw angle φ, and sideslip angle δ of the AGV vehicle walking in the world coordinate system x o Oy o Under. According to the real-time center of gravity position (x v , y v , z v ) of the AGV vehicle carrying the goods in real time monitored in the world coordinate system and the heading angle ψ, construct a rotation matrix Rotate(ψ) and obtain a rigid body transformation matrix T WB , and further obtain the inverse rigid body transformation matrix T BW through inverse transformation. According to the inverse rigid body transformation matrix and the real-time center of gravity position (x v , y v , z v ) in the world coordinate system, obtain the coordinate position (x, y, z) of the real-time center of gravity of the vehicle body of the AGV vehicle carrying the goods in the vehicle body coordinate system.

[0058]

[0059] t is the coordinate matrix of the center of gravity of the trolley with goods in the world coordinate system, t = [x v y v z v T ; It represents T WB is a 4×4 matrix in the real number field, and T WB is the transformation matrix for converting the coordinate of the center of gravity of the trolley with goods in the vehicle body coordinate system to the world coordinate system;

[0060]

[0061] T BW is the transformation matrix for converting the coordinate of the center of gravity of the trolley with goods in the world coordinate system to the vehicle body coordinate system; is the inverse transformation matrix of T WB , and Rotate T (ψ) is the transpose matrix of Rotate(ψ);

[0062] Take the x, y, and z in the real-time center of gravity coordinate matrix obtained through transformation to get the coordinate position (x, y, z) of the overall real-time center of gravity of the trolley with goods in the vehicle body coordinate system;

[0063] S22: Figure 4 It shows the offset angle θ x , θ y of the goods with mass m offset from the overall center of gravity of the trolley with goods Figure 5 It shows the offset angle α i of the projection of the connection line between the center point of the i-th Mecanum wheel and the overall center of gravity O of the trolley with goods on the xy plane of the vehicle body coordinate system relative to the x-axis of the vehicle body coordinate system i and the direction and other parameters of the required driving force F x of each Mecanum wheel, and according to the offset angle θ y of the center of mass of the goods carried by the AGV trolley relative to the center of gravity of the AGV trolley body in the xz plane of the vehicle body coordinate system C and the offset angle θ C in the yz plane of the vehicle body coordinate system C , the real-time center of gravity position (x, y, z) of the AGV trolley body with goods obtained in step S21 and the coordinates (X

[0064] C , Y C , Z C ) of the goods with mass m in the vehicle body coordinate system, calculate the distance H between the center of gravity of the goods in the vehicle body coordinate system and the overall center of gravity of the trolley with goods:

[0065] S23: Construct the real-time acceleration matrix a of the cargo centroid p :

[0066]

[0067] Among them, and are respectively the real-time accelerations of the cargo with mass m on the x-axis, y-axis, and z-axis in the vehicle body coordinate system; and are respectively the carried, are respectively the offset angular velocities of the centroid of the cargo carried by the AGV vehicle of the cargo with mass m with respect to the center of gravity of the AGV vehicle body in the xz plane of the vehicle body coordinate system and the offset angular velocities in the yz plane of the vehicle body coordinate system with respect to the center of gravity of the AGV vehicle body, are respectively the offset angular accelerations of the centroid of the cargo carried by the AGV vehicle of the cargo with mass m with respect to the center of gravity of the AGV vehicle body in the xz plane of the vehicle body coordinate system and the offset angular accelerations in the yz plane of the vehicle body coordinate system with respect to the center of gravity of the AGV vehicle body,

[0068] The formula for calculating the overall three-dimensional driving force required for the AGV vehicle carrying the cargo in step S3 is as follows:

[0069]

[0070] Among them, v x and v y are respectively the linear velocities of the overall vehicle carrying the cargo in the x-axis and y-axis directions in the vehicle body coordinate system; and are respectively the x-axis velocity and y-axis velocity of the center of gravity of the overall vehicle carrying the cargo in the world coordinate system,

[0071] M is the mass of the vehicle without carrying the cargo (i.e., the empty mass of the AGV vehicle); F x and F y and F z are respectively the driving forces required for the overall vehicle carrying the cargo with mass m in the x-axis, y-axis, and z-axis of the vehicle body coordinate system.

[0072] F z The first term (M + m)g in is the total gravity of the vehicle carrying the cargo with mass m; the sum of the second term and the third term: The vertical load on the cart caused by the acceleration component of the loaded goods in the vertical direction (the z-axis direction of the vehicle body coordinate system); the fourth term is the vertical load component caused by the inertial acceleration during the rotation of the cart. When rotating around the z-axis of the vehicle body coordinate system, the total mass (m + M) of the cart carrying the goods rotates horizontally, bringing an additional upward inertial force. The negative sign before indicates that the direction of this inertial force is upward, offsetting a part of the downward load forces of the first to third terms, reducing the load force provided by the ground for the cart with a mass of m); F x 、F y and F z are used for subsequent tire load distribution calculations.

[0073] Figure 6 shows the acceleration of the goods carried on the AGV cart constructed in steps S21 - S23 in the real-time acceleration matrix of the center of gravity of the goods in the vehicle body coordinate system and are applied to the calculation of the three-dimensional driving force required for the entire AGV cart carrying goods in step S3, and then the driving force F required for each Mecanum wheel is calculated i is introduced as a feedback variable into the state variable feedback method for the comparison effect of path deviation control. The black dotted line in the figure is the target reference circular turning path. Figure 6 (a) is the trajectory comparison. Figure 6 (b) is the a constructed according to the method S21 - S23 of the present disclosure p matrix and the control error comparison diagram of F calculated without using the real-time acceleration of the center of mass of the goods in steps S21 - S23 of the present disclosure x 、F y 、F z The calculated F i The red trajectory is the method that does not use the driving force Fi constructed by the matrix a p as the four elements of the control input U. From Figure 6As can be seen from (b), after the 6th minute, the path starts to deviate significantly from the target reference path due to the disturbance caused by the change in the centroid of the goods. The error oscillates significantly, with a maximum error exceeding 10 cm. The blue trajectory is the result of using the method disclosed in the present disclosure. The trajectory tracking result of the method disclosed in the present disclosure shows that its controlled trajectory is closer to the target trajectory, and it responds faster and more stably to the disturbance caused by the change in the centroid of the goods itself. The error amplitude of the blue trajectory relative to the target trajectory of the black dashed line is always small, with a maximum not exceeding 5 cm. The root mean square error of the path deviation of the red trajectory is 0.051 m, and the root mean square error of the path deviation of the blue trajectory is 0.026 m, indicating that introducing the consideration factor of the real-time acceleration calculation of the centroid of the goods itself into the control input in steps S21 - S23 enables the system to more quickly suppress the trajectory disturbance caused by the deviation of the goods, and the path remains more accurate.

[0074] As another embodiment of the present invention, step S4 includes:

[0075] S41: Construct the conversion coefficient matrix T of the i-th wheel roller i :

[0076] When i = 1, the i-th Mecanum wheel is the left front wheel; when i = 2, the i-th Mecanum wheel is the right front wheel; when i = 3, the i-th Mecanum wheel is the left rear wheel; when i = 4, the i-th Mecanum wheel is the right rear wheel. α i is the offset angle of the projection of the line connecting the center point of the i-th Mecanum wheel and the overall center of gravity of the cart carrying the goods in the xy plane of the vehicle body coordinate system relative to the x-axis of the vehicle body coordinate system

[0077] Among them, represents the matrix T i is a real number matrix with a dimension of 2 rows × 3 columns; T i 's first row indicates converting the overall x-axis velocity v x and y-axis velocity v x of the cart carrying the goods in the vehicle body coordinate system, as well as the rotational velocity to the velocity component along the rolling direction of the i-th wheel roller (i.e., the direction where the tilt angle γ i is located. Since the roller rotates freely, there is no constraint; T i 's second row indicates converting the vehicle y-axis velocity v y and x-axis velocity v x to the direction perpendicular to the direction of the i-th wheel roller ; T i 's first column indicates the three-dimensional velocity v x and v y of the vehicle and along the rolling direction of the roller The velocity component; in the vehicle body coordinate system, the x-axis is the forward direction and the y-axis is the lateral displacement direction; Figure 7 shows the wheel plane formed by the a-axis and the b-axis, the b-axis is the roller tilt axis, and the a-axis is the direction orthogonal to the roller tilt axis, that is, the direction perpendicular to the i-th roller direction, Figure 7 The green arrow direction in is the rolling direction of the i-th wheel roller direction.

[0078] That is, T i is the parameter of the trolley in the vehicle body coordinate system The linear transformation matrix that maps to the local coordinate system of the wheel;

[0079] S42: According to the conversion coefficient matrix T of the i-th wheel roller i Obtain the slip direction velocity component coefficient matrix block B of the i-th wheel i , and the drive mapping matrix block C of the i-th wheel i :

[0080] B i = [-sin(γ i ) cos(γ i ) d i cos(γ i -α i )]; d i is the distance from the center point of the i-th Mecanum wheel to the center of gravity of the vehicle body; L i 、W i are respectively the longitudinal distance of the center point of the i-th Mecanum wheel in the vehicle body coordinate system from the overall real-time y-axis of the trolley carrying goods and the transverse distance from the x-axis, L1 + L3 = L2 + L4 = 2L, W1 + W2 = W3 + W4 = 2W;

[0081] C i = [R i cos(γ i ) r i ; where, R i is the wheel radius of the i-th Mecanum wheel, r i is the roller radius of the i-th Mecanum wheel;

[0082] C i is used to convert the wheel rotation speed and the roller rotation speed into the velocity component of the wheel-ground contact point in the slip direction (i.e., perpendicular to the roller rolling direction) That is, C iThe first component in the matrix represents the component of the rotation of the wheel spindle in the slip direction; C i The second component in the matrix represents the direct projection of the rotation of the roller about its own axis in the slip direction;

[0083] Then obtain the second row elements of the i-th wheel roller conversion coefficient matrix T constructed in step S41 i to form the matrix block B i , and at the same time, according to T i further calculate the drive mapping matrix block C of each wheel i ;

[0084] S43: Construct the slip velocity calculation matrix v of each wheel in the vehicle body coordinate system slip :

[0085]

[0086] Among them, is the state component of the trolley carrying goods, is the rotational angular velocity of the i-th Mecanum wheel roller, is the rotational angular velocity of the i-th Mecanum wheel obtained by real-time monitoring;

[0087]

[0088] R i is the wheel radius of the i-th Mecanum wheel, r i is the radius of the i-th Mecanum wheel roller;

[0089] Coefficient matrix is the mapping relationship between the slip velocity of each wheel and the system state (position velocity, angular velocity of each wheel), which is 4 rows and 11 columns, is a matrix of 1 row and 11 columns. Therefore, the result obtained by multiplying the two is the slip velocity v of each wheel in the vehicle body coordinate system, which is 4 rows and 1 column slip,i composed of v slip , that is, obtained through the above calculation

[0090] Figure 8 shows the change trajectory of the overall center of gravity of the trolley carrying a mass m within the monitoring time of 25 min( Figure 8 (a)) and the force F on the four wheels i and the magnification value 100v of the slip velocity v slip,i ( slip,i (b)), Figure 8 (b)), Figure 8(a) The black frame line is the overall chassis frame of the AGV cart carrying goods. The red trajectory in the middle is the projection trajectory of the overall cart changing with time in the vehicle coordinate system. The four blue "×" points represent the four Mecanum wheels. Figure 8 (a) shows that the dynamic trajectory of the center of gravity of the cart carrying goods converges significantly and is stably distributed in the central area of the support polygon. That is, by constructing the centroid acceleration a of the goods in real time p and feeding it back to the multi-wheel driving force optimization module (F i optimal solution), multi-wheel coordinated control and anti-disturbance dynamic balance are effectively achieved, avoiding the risk of the overall center of gravity exceeding the frame of the cart chassis, and preventing the AGV cart from tipping over or skidding due to unstable center of gravity;

[0091] Figure 8 (b) shows the slip speed v slip,i multiples of 100v slip,i and the corresponding required driving force F i show a non-linear but correlated trend. The driving force model constructed in the present invention fully considers the functional relationship between the slip speed and the ground friction and adopts correction of the ratio of the degree of wheel slip relative to the overall longitudinal driving speed v x v slip,i is the local slip disturbance received by the i-th Mecanum wheel in its local coordinate system. The ratio of the two is used to measure the degree of wheel slip along the constraint direction, and it is not necessary for both to be unified in one coordinate system. The ratio of the two is a manifestation of normalization. Figure 8 (b) shows that the optimal driving force F provided by the method disclosed in the present disclosure i,best and the optimal real-time rotational speed make the forces of the four Mecanum wheels change basically synchronously with the slip speed, showing a good dynamic coordination relationship, and the tire operating point is stable in the controllable range, avoiding slipping and / or stalling phenomena.

[0092] The present disclosure significantly improves the multi-wheel coordinated control ability of the AGV cart in load disturbance and path diversion by integrating the dynamic modeling of the centroid acceleration of the goods, the feedback of the wheel slip speed, and the correction of the friction model. Figure 8 The center of gravity trajectory of the overall cart shown in does not cross the boundary, and the driving force and the slip speed are coordinated and synchronized, fully verifying its significant advantages in improving dynamic stability, path control accuracy, and tire force utilization rate.

[0093] As another example of the present invention, step S5 includes the following steps:

[0094] S51: Calculate the real-time lateral load transfer amount of the i-th Mecanum wheel and the real-time vertical load transfer amount

[0095]

[0096] 2W is the total length from the center point of the left wheel to the center point of the right wheel of the cart in the lateral y-axis direction within the vehicle body coordinate system; 2L is the total length from the center point of the rear wheel to the center point of the front wheel of the cart in the longitudinal x-axis direction within the vehicle body coordinate system.

[0097] S52: Calculate the real-time vertical total load Q of the i-th Mecanum wheel L,i :

[0098] That is:

[0099]

[0100] Among them, α i is the angle between the line connecting the center point of the i-th Mecanum wheel and the overall center of gravity of the cart carrying goods and the transverse y-axis of the vehicle body coordinate system; s x,i , s y,i are the sign coefficients of the real-time lateral load transfer and the real-time vertical load transfer respectively; s x,1 =-1, s y,1 =-1; s x,2 =-1, s y,2 =1; s x,3 =1, s y,3 =-1; s x,4 =1, s y,4 =1;

[0101] S53: Calculate the real-time driving force F required for the i-th Mecanum wheel i :

[0102]

[0103] Among them, μ i is the friction coefficient between the i-th Mecanum wheel and the ground, μ i =0.3 - 0.5, and the value of μ i is determined according to the material of the Mecanum wheel and the ground conditions. For example, if the Mecanum wheel is wrapped with soft rubber and the ground is a flat and dry floor (such as epoxy floor, wooden floor or cement floor), then μ i =0.4 - 0.5. If the wheel is harder and there is dust on the ground, then μ i =0.3 - 0.4.

[0104] Figure 9 Shows the dynamic vertical loads of the four Mecanum wheels calculated by the above calculation method applied to the intelligent logistics transportation and palletizing AGV cart in this disclosure when transporting and palletizing goods QL,i The variation of the vertical load Q of the four wheels L,i shows periodic fluctuations throughout the 250 - second interval, reflecting the uneven wheel load phenomenon caused by factors such as the center - of - mass offset, acceleration and deceleration, and yaw - rate perturbation during the dynamic operation of the trolley;

[0105] During certain periods, such as [60s, 120s] and [190s, 230s], Q L,3 and Q L,4 fluctuates significantly, possibly because the load on the rear wheels is more intense during the steering process; compared with the traditional static average distribution, the dynamic load can more realistically reflect the force on each wheel, and thus can be more reasonably used for tire friction force modeling and slip control.

[0106] As another example of the present invention, the state - variable feedback method in step S6 includes the following steps:

[0107] S61: Construct a state - space model including the vehicle body motion state and the cargo attitude:

[0108] where X is the state - vector matrix, is the state - derivative vector matrix, that is, each element in is the first - order derivative of the corresponding element in X with respect to time, and are respectively the heading angular velocity and heading angular acceleration of the AGV trolley with the cargo in the world coordinate system; U is the control - input vector matrix, U = [F1, F2, F3, F4] T ; A is the state - vector coefficient matrix, E is the control - input vector coefficient matrix,

[0109]

[0110] In the matrix A, the first row, the third row, the fifth row, the seventh row, and the ninth row are respectively the limitations on the vectors each with a coefficient of 1; the coefficients in the second row act on the matrix to obtain the lateral dynamic equation of the trolley. It reflects three key couplings: is the product term of the yaw angular velocity and the longitudinal velocity of the vehicle body, belonging to the Coriolis acceleration term in the non - inertial coordinate system, which affects the lateral acceleration; - gθ x and - gθ yis the projection term of gravity along the swing rod deflection angle direction, which reflects the restoring force of the center of gravity movement in the vehicle body coordinate system during the overall movement of the trolley carrying goods caused by the disturbance of the center of mass of the goods. The fourth line is for the matrix After the action, This is a simplified longitudinal direction dynamic model, indicating that due to the offset of the goods in the θ y direction, the movement of the vehicle body in the front-back direction changes, indicating that the acceleration of the trolley in the x direction is mainly affected by the disturbance of θ y . For example, if the goods deviate forward, the vehicle body will accelerate forward. All the coefficients in the sixth row of matrix A are 0 because the sixth element in the matrix is which is mainly affected by the control vector of the input by matrix E, that is, the driving force of each Mecanum wheel rotation on the entire trolley. After the action of the eighth row of matrix A on the matrix , we get This is the linearized expression of the offset model of the center of mass of a single piece of goods with mass m relative to the overall center of gravity of the trolley carrying it in the xz plane, indicating that the entire control system will generate a restoring moment with the offset angle θ x of the center of gravity. The tenth row of the matrix is similar, which is the linearized expression of the center of gravity offset model in the yz plane.

[0111]

[0112] Among them, is the simplification result of considering a single vehicle body (without carrying goods) with mass M as a rectangular structure (length 2L, width 2W), and the moment of inertia about the vertical axis of the center of mass is , which considers the moment of inertia of the single trolley, is the moment of inertia considering the goods with mass m rotating around its own center of gravity. The sum of the two is the total moment of inertia of the trolley carrying goods with mass m;

[0113] β x and β y are the coupling coefficients of the center of mass offset of the carried goods respectively. β x =cosβ, β y =sinβ; if the center of mass of the carried goods is biased towards pure front-back movement, then at this time, β = 0°, β x =1, β y =0; if the center of mass of the carried goods is biased towards pure left-right movement, then at this time, β = 90°, β x =0, β y =1.

[0114] It is the key "input action channel mapping matrix" in the state space variable framework constructed by the state variable feedback method for the coupled control system of the center of gravity offset during the movement and / or the lifting process when the goods are carried by the Mecanum wheel four-wheel drive AGV. Each column corresponds to the input force F of a wheel i , and each row represents the influence of this input force on the derivative of a certain state variable (i.e., acceleration). Through the matrix E, the four control inputs U = [F1, F2, F3, F4] T are transformed into the "acceleration" or dynamic driving effect generated on each dynamic quantity (speed, angular velocity, pendulum angle, etc.) in the state vector; the second row of the matrix E is the influence of the lateral resultant force related to the lateral actions of the four wheels on the lateral velocity , and its coefficient makes the control force act obliquely at 45°, bringing lateral (i.e., transverse) acceleration. The fourth row is similar, which is the influence of the longitudinal resultant force related to the longitudinal actions of the four wheels on the longitudinal velocity . In the sixth row, di is also the yaw moment arm of each Mecanum wheel relative to the current center of gravity position of the whole system around the z-axis of the vehicle body. Each coefficient group in the sixth row is used for the heading angular velocity, indicating the influence of the wheel driving force on the heading moment around the vertical axis of the vehicle body; the farther away from the overall center of gravity, the greater the influence; the coefficient in the eighth row shows the influence of the torque generated by the four-wheel driving force in the xz plane on its tilt angular velocity (the negative sign indicates the reverse), and the tenth row shows the coupling effect of the tilt angular velocity of the four-wheel driving force in the yz plane on the tilt angle.

[0115] S62: Construct the optimization objective function:

[0116]

[0117] where, [1, N p is the prediction time domain length, [0, N c - 1] is the control time domain length, X ref is the reference state trajectory, n is the nth step predicted forward from the current moment k, Q is the state value weight matrix, G is the input control value weight matrix; X k+n|k is the state prediction value at the k + nth moment based on the state value X k|k at the kth moment; U k+n|k is the control input adjustment value at the k + nth moment based on the control input value U k|k at the kth moment; is the transpose matrix of U k+n|k ;

[0118] S63: Repeat the optimization iteration of step S62 in a rolling manner. If Stop the iteration and output each element in the control state variable matrix U at this time as the optimal real-time driving force F of each wheel of the AGV cart carrying goods i,best , and further solve the optimal real-time rotational speed of each wheel of the AGV cart carrying goods based on this

[0119] The improvement methods for the state value weight matrix Q and the input control value weight matrix G in step S62 include:

[0120] S621: Construct the state vector data sample matrix X data and the driving force observation value sample matrix U of four Mecanum wheels data :

[0121] X (p) is the data sample sub-matrix at the pth sampling point, including ten state variables

[0122] U data = [U (1) , U (2) ,..., U (N) ; where is the driving force observation value of four Mecanum wheels at the pth sampling point and are the driving force observation values of the left front wheel, right front wheel, left rear wheel, and right rear wheel at the pth sampling point respectively

[0123] S622: Construct the first spatial weight matrix W1 and the second spatial weight matrix W2:

[0124] For the element w pq,1 in the pth row and qth column of the first spatial weight matrix W1 and p ≠ q, that is, X (q) is the data sample sub-matrix at the qth sampling point For the element defined in the ath row and bth column of the second spatial weight matrix W2 as w ab ; for w ab , if the interaction intensity between adjacent wheels is 1 and non-adjacent is 0, then the left front wheel is adjacent to the right front wheel and adjacent to the left rear wheel, but not adjacent to the right rear wheel, then w 12 = 1, w 13 = 1, w 14 = 0, and its own interaction has no effect, so w 11 = 0;

[0125] S623: Construct the spatial change metric consistency coefficient Input the distribution coupling degree coefficient h ab:

[0126]

[0127] Among them, x e,p and x e,q are the values of the e-th state variable in the p-th sample and the e-th state variable in the q-th sample, respectively; is the average value of the e-th state variable x e in the p-th sample; where x is y, x, ψ, θ x , θ y or

[0128]

[0129] Among them, is the n-th observation value of the a-th Mecanum wheel, is the n-th observation value of the b-th Mecanum wheel, where a = 1, 2, 3, 4; b = 1, 2, 3, 4; are the average values of the N observation values of the a-th Mecanum wheel and the average values of the N observation values of the b-th Mecanum wheel, respectively;

[0130] S624: Construct a state weight matrix Q in diagonal form according to the spatial variation metric consistency coefficient and construct an input control value weight matrix G according to the input distribution coupling coefficient h ab :

[0131]

[0132] The spatial variation metric consistency coefficient The smaller the value, the more drastic the state change → the more important the state → the greater the weight. The spatial variation metric consistency coefficient reflects the spatial autocorrelation or spatial continuity of the state variable:

[0133] The spatial variation metric consistency coefficient The smaller it is (i.e., ), the stronger the spatial continuity, indicating that the variable has strong similarity or aggregation in space;

[0134] The larger it is (i.e., ), the weaker the spatial continuity, and the variable has large differences or discontinuities in space.

[0135] When is smaller, The larger the value, the higher the weight for matrix X;

[0136] When is larger, the smaller the value, the lower the weight for matrix X;

[0137] Therefore, when its correlation with other variables is stronger, its weight for matrix X is larger in the optimization process of the state variable feedback method. Thus, this state variable error is more important in the optimal control, has a greater impact on the optimal control effect, and the controller is more sensitive to the error of this variable in matrix X.

[0138] In the input control value weight matrix G matrix, the diagonal element h aa , represents the spatial autocorrelation (autocorrelation intensity) of the a-th Mecanum wheel itself. That is, it clearly reflects the spatial or temporal continuity and stability of the control input data of the a-th Mecanum wheel itself in all sample observations:

[0139] h aa The larger it is, the more stable and autocorrelated the control input of the a-th wheel itself is, and thus it is more important in the control strategy;

[0140] h aa Being smaller indicates that the control input of this wheel has poor stability or autocorrelation in the spatial or time series, is less stable, and has lower importance.

[0141] In the H matrix, the meaning of the off-diagonal element h ab :

[0142] The off-diagonal element h ab represents the spatial synergy between different wheels, that is, it reflects the interaction strength or synergy degree between the inputs of two wheels. The larger the value of h ab , the stronger the synergy between the two wheels, and the smaller or negative the value of h ab , the weaker the synergy between the two wheels or the anti-correlation.

[0143] In the optimization objective function constructed in step S62, matrix Q determines the importance degree of the system for the state error (such as the deviation of yaw angle, position, and center of gravity offset) in the optimization. By optimizing the weight of Q, the tracking ability for the target trajectory can be strengthened. Using the spatial variation metric consistency coefficient After constructing the matrix Q, the correlation coefficients of the matrix Q weight the corresponding vectors of the state vector matrix X, adjust the sensitivity to the system state accuracy, dynamically reflect the spatial co - correlation between different state dimensions, and improve the path tracking accuracy, yaw angle stability, as well as the pertinence of control and the overall system responsiveness. The matrix G determines the penalty for the amplitude of the control input (i.e., wheel driving force); setting an appropriate G can avoid excessive input of the wheel driving force, resulting in slippage, instability, or energy waste; introducing the input distribution coupling coefficient h ab After that, the matrix G can consider the input synergy between the four wheels, balance the amplitude of the wheel driving force, prevent excessive input from causing slippage or a sharp increase in energy consumption, optimize the distribution structure of the control force, and improve stability and energy efficiency.

[0144] Figure 10 Shows the consistency coefficient measured by spatial variation The improved Q matrix and the input distribution coupling coefficient h ab The improved G matrix as variables, respectively using the method of the present disclosure( Figure 10 (a)) and the traditional method( Figure 10 (b)) to solve for the driving force F of the Mecanum wheel i The three - dimensional distribution situation. Figure 10 In (a), the entire surface is relatively smooth, showing obvious regular changes, and the change of F i is relatively gentle as a whole, indicating that the control effect is stable, which can reduce the drastic change of the driving force received by the Mecanum wheel and is beneficial to the smooth implementation of the control strategy; in addition, the peak positions of the surface are evenly distributed, which is beneficial to the overall performance optimization of the system.

[0145] Figure 10 In (b), the entire surface changes violently, with obvious fluctuations, many and scattered local peaks, and these fluctuations may lead to frequent adjustments and system instability in the actual control process; it shows the phenomenon of local optimization and fails to achieve global smooth optimization.

[0146] By comparison, using the spatial variation measurement consistency coefficient of the present invention and the input distribution coupling coefficient h ab as the improvement methods of the matrices Q and G in the state - feedback optimization model can significantly improve the smoothness and consistency of the overall control, avoid excessive and frequent control fluctuations, which is beneficial to extending the service life of the Mecanum wheel, reducing the wear and impact of mechanical components. At the same time, the control strategy is clearer, facilitating real - time application and further improved design of the state - feedback optimization control method.

[0147] Figure 11 Shows the optimal driving force F of the four wheels obtained by using the method of the present disclosure i,bestThe curve changing with time. In the first turning stage from 10 min to 45 min, the orange solid line represents F 1,best rapidly rises to about 245 N and then levels off, indicating that the initial force on the front left wheel rises but is adjusted quickly; the brown dashed line represents F 2,best is generally slightly higher than F 1,best , reaching about 250 N, indicating that the front right wheel bears a greater lateral force; the reddish-brown dotted line represents F 3,best rises from about 260 N to 275 N, showing a slow increase, and the rear left wheel bears the maximum pressure in this stage; the magenta dotted line represents F 4,best almost changes synchronously with F 3,best but is slightly higher at the peak (about 278 N), and the rear right wheel also bears a relatively large load. Thus, it can be seen that the load borne by the rear wheels is significantly higher than that of the front wheels, especially F 4,best >F 3,best >F 2,best >F 1,best , indicating that in the initial turning, the car has the dynamic characteristics of rear-wheel master steering.

[0148] In the second turning stage from 65 min to 90 min, the driving forces of all four wheels generally enter a downward trend, but F 1,best , F 2,best decrease relatively slowly, dropping to about 225 N; within this stage, F 3,best , F 4,best decrease faster than F 1,best and F 2,best , and the lowest value is close to 215 N, with good change synchrony and no sudden change in the waveform trend, showing an overall smooth turning. In this stage, each wheel tends to be balanced, indicating that the path bend is relatively gentle, the load distribution is more uniform, and the system regulation enters the stable response range.

[0149] In the third turning stage from 110 min to 160 min, the driving forces required by each wheel re-enter the rising stage and have a large fluctuation range. F 1,best rises to a peak of 245 N; F 2,best rises to slightly higher than F 1,best to reach 250 N; F 3,best sharply rises to 275 N; F 4,best rises again to be slightly higher than F 3,best to reach 285 N; similar to the first turning stage, the rear-wheel dominant feature still exists. This section is the load regulation strengthening area, indicating that in large-radius or high-speed turning, the control system relies on the dynamic adjustment ability of the rear wheels.

[0150] In the stage from 200 min to 250 min, the driving forces required by each wheel quickly decrease again, forming a convergent state. F 1,best , F 2,bestDrop to a minimum of approximately 145 N to 160 N; F 3,best 、F 4,best Drop to a minimum of approximately 160 N to 175 N; the driving force required for each wheel in this stage shows an overall "anti-symmetric" drop, indicating that this section is for the end of transportation or turning around. The system evenly distributes the load to all wheel groups to prevent bias and slipping, and achieves a stable transition at the end of turning.

[0151] According to the optimal real-time driving force F of each wheel of the AGV cart carrying goods i,best , solve for the optimal real-time rotational speed of the i-th Mecanum wheel according to the law of conservation of energy The formula is as follows:

[0152]

[0153] Among them, P i is the rated power of the drive motor of each Mecanum wheel, and Pi = 800 W to 1200 W.

[0154] Figure 12 Shows the change curves of the corresponding rotational speeds of the four wheels calculated according to this formula of. Figure 11 Each F in i,best The peak of the curve corresponds to Figure 12 in the corresponding of the trough, and vice versa. For example, near 100 min, Figure 11 of F 1,best reaches the trough, corresponding to Figure 12 in then reaches the peak, and the consistent response of the four wheels: the four The change trends of the change curves in each turning stage are different in amplitude, but the response modes are highly consistent, indicating that this state feedback control method realizes multi-wheel collaborative optimization response.

[0155] The present disclosure constructs a 10-dimensional state space model including cargo acceleration, offset angle, heading angle, etc., and combines the prediction control model accuracy to dynamically optimize the feedback, so that each wheel obtains the optimal driving force that conforms to its position and slip state; compared with traditional constant or simplified proportional control, it can adapt to the center of gravity offset and acceleration change under complex working conditions in real time, and effectively enhance the motion stability and response accuracy. Figure 11 and Figure 12 The force and rotational speed of the four wheels in show the characteristics of "coordinated change, non-abrupt change" in multiple turning intervals, verifying that this method can effectively suppress the risk of tire slipping and instability under high-speed turning and load change conditions; the present disclosure considers the overall center of gravity change of the vehicle and the individual slip characteristics for the driving strategy of each wheel, avoiding problems such as overturning or cargo tipping caused by control mismatch in traditional methods.

[0156] On the other hand, the present disclosure provides a control system for an intelligent logistics transportation and palletizing AGV cart that executes the control method as described above. Figure 13 The control system is shown to include:

[0157] An empty-load and load detection module for obtaining information on whether the AGV cart is empty. If there is a load, the real-time mass m of the load carried by the goods; this module can use a capacitance sensor array or a pressure sensor array, which is arranged on the vehicle body lifting platform to detect whether there is a load placed.

[0158] An IMU inertial measurement unit for obtaining the attitude and angular velocity of the entire cart carrying goods in the world coordinate system in real time.

[0159] A real-time kinematic differential positioning module, which can use an RTK-GPS module or a visual SLAM positioning unit, combined with the IMU inertial measurement unit to provide the real-time centroid position (x v , y v , z v ) and the heading angle ψ of the entire AGV cart carrying goods in the world coordinate system in real time.

[0160] A cargo offset angle detection unit for obtaining the real-time centroid position and offset angle of the carried cargo in the vehicle body coordinate system; that is, this unit is used to obtain the offset angles θ x 、θ y of the cargo in the xz plane and yz plane of the vehicle body coordinate system. This unit can use a biaxial gyroscope or a laser ranging device.

[0161] An encoder for obtaining the rotational angular velocity of each Mecanum wheel and the rotational angular velocity of each roller of each Mecanum wheel installed on each Mecanum wheel axle and roller axle.

[0162] A cargo centroid acceleration matrix construction module for constructing a real-time acceleration matrix of the cargo carried on the AGV cart.

[0163] A three-dimensional driving force calculation module for calculating the required three-dimensional driving force of the entire AGV cart carrying goods based on the data of the empty-load and load detection module, the IMU inertial measurement unit, the real-time kinematic differential positioning module, the cargo offset angle monitoring unit, and the cargo centroid acceleration matrix construction module.

[0164] A slip velocity calculation module for constructing a slip velocity calculation matrix v of each wheel of the AGV cart in the vehicle body coordinate system when the cart is walking with the load in real time and lifting the cargo. slip ;

[0165] A real-time driving force calculation module, used to further calculate the real-time driving force required for each wheel of the AGV vehicle carrying goods based on the calculation results of the three-dimensional driving force calculation module and the slip speed calculation module;

[0166] The state feedback optimization solution module is used to solve the optimal real-time driving force F of each wheel of the AGV with goods based on the state variable feedback method. i,best , and finally get the optimal real-time speed of each wheel of the AGV with goods

[0167] The third aspect of the present disclosure is Figure 14 The present invention provides an intelligent logistics transport and palletizing AGV trolley, which includes a vehicle base 1 and four Mecanum wheels 2. The four Mecanum wheels are installed in an X-shaped structure at the position of the vehicle base 1, that is, Figure 1 The Mecanum wheels at the left front and right rear are shown in the A type of rotation structure, and the Mecanum wheels at the right front and left rear are in the B type of rotation structure; the AGV trolley of the present disclosure also includes the above-mentioned Figure 13 The control system shown is provided with a lift housing 3 and a transport box bearing member 4 above the rear end of the vehicle base;

[0168] A plurality of lifting shafts are arranged in the elevator housing 3 for lifting and lowering the cargo in the cargo box 5 fixed by the transport box bearing member 4;

[0169] Specifically Figure 15 As shown, the first lifting shaft 31, the second lifting shaft 32, the third lifting shaft 33, the fourth lifting shaft 34, the fifth lifting shaft 35 and the sixth lifting shaft 36 are arranged in the elevator shell 3 from the outside to the inside, and the transport image bearing component 4 is fixedly connected to the top of the innermost lifting shaft, that is, it is fixedly connected to the top of the sixth lifting shaft 36.

[0170] A cargo box flipping mechanism is provided in the transport box bearing component 4, which is used to flip the cargo box 5, lift or lower the cargo to a required height before unloading, or flip it to an upright state after loading and lift it to the target stacking position again.

[0171] As an embodiment of the present disclosure, Figure 14 , Figure 16 The transport box receiving component 4 includes two left and right sub-receiving components 41, both of which are L-shaped. The upper parts of the left and right sub-receiving components 41 are laterally integrated. Figure 14It is shown that each sub-bearing component 41 includes a lower bearing component 411 and an upper bearing component 412, both of which are in an L shape. The lower bearing component 411 and the upper bearing component 412 are fixedly connected by a connecting shaft 410 provided at the front end of the lower bearing component 411. An inner snap hook 44 is provided on the upper part of the vertical section of the lower bearing component 411. Figure 14 , Figure 17 It is shown that the cargo box flipping mechanism includes a first electric telescopic rod 42 provided on the vertical section of each lower bearing component 411, a second electric telescopic rod 43 provided on the horizontal section of each lower bearing component 411, and a third electric telescopic rod 46 provided on the horizontal section of each upper bearing component 412. The telescopic end of the first electric telescopic rod 42 is fixedly connected to the hook 44, and the hook can rise or fall along the sliding groove in the vertical section of the lower bearing component 411 to the initial position under the drive of the first electric telescopic rod 42.

[0172] As an embodiment of the present disclosure, Figure 17 It is shown that the front end of each second electric telescopic rod 43 is fixedly provided at the lower part of the corresponding upper bearing component 412 through a rod head ring 431 and a fixing rod 432.

[0173] The telescopic end of the third electric telescopic rod 46 faces forward (i.e., the moving direction of the AGV cart), and chevron-shaped fixing blocks 45 are provided at both the motor end and the telescopic end of the third electric telescopic rod. The converging end of the chevron-shaped fixing blocks 45 is fixedly connected to the circumferential outer wall of the same fixed rod 451. A clamping hole is provided in the upper part of the telescopic end of the second electric telescopic rod 43. When in the initial state, that is, when the upper bearing component 412 and the lower bearing component 411 are in a state where their vertical sections are in contact with each other and their horizontal sections are in contact with each other, the fixed rod 451 at the telescopic end of the third electric telescopic rod is clamped into the clamping hole at the telescopic end of the second electric telescopic rod 43 from top to bottom.

[0174] The motor end of the second electric telescopic rod 43 is fixed at the starting end (near the rear of the vehicle body) of the hollow groove 49 of the corresponding lower bearing component 411, and when the second electric telescopic rod 43 is in the initial state (contracted state), the entire telescopic end and the motor end of the second electric telescopic rod 43 are located within the corresponding hollow groove 49.

[0175] When it is necessary to dump the goods in the cargo box 5 or when it is necessary to load the goods to be transported and / or lifted into the cargo box 5, such as Figure 18 shown, after being transported to other positions by the AGV cart and then lifted and stacked, it is necessary to control the cargo box flipping mechanism to flip the cargo box 5 from Figure 16 the shown initial state, that is, the upright state of the cargo box 5, to Figure 14In the dumping state shown, when the control is reversed, the first electric telescopic rod 42 is first controlled to start, driving the hook 44 to rise from the initial position along the sliding groove, and then the hook 44 moves upward and separates from the rear upper edge of the cargo box 5. Then, the movement of the first electric telescopic rod 42 is stopped, and the third electric telescopic rod 46 and the second electric telescopic rod 43 are turned on. The telescopic end of the third electric telescopic rod 46 drives the fixed rod 451 at its front to move toward the front end of the trolley. Since the fixed rod 451 is clamped in the telescopic end of the second electric telescopic rod 43, the second electric telescopic rod 43 is also in the open state at this time. Therefore, the second electric telescopic rod 43 moves forward at the same speed as the second electric telescopic rod 46. Since the second electric telescopic rod 43 is fixed to the front end of the upper supporting component 412 by the rod head ring 431 and the fixing rod 432, the upper supporting component 412 drives the cargo box 5 supported on its upper part to move forward under the parallel forward push of the second electric telescopic rod 43 and the third electric telescopic rod 46 in the horizontal plane. The entire upper assembly has not yet rotated at a large angle, but has shown a slight forward tilting tendency.

[0176] In the third stage of flipping the cargo box 5, the third electric telescopic rod 46 is stopped from continuing to move forward, and the telescopic movement of the second electric telescopic rod 43 is continued. At this time, due to the limitation of the hollow groove 49, the rod head ring 431 at the front end of the second electric telescopic rod 43 and the fixed point of the fixed rod 432 and the upper supporting component 412 are used as the fulcrum, and the upper supporting component 412 and the lower supporting component 411 are used as the rotation fixed point through the connecting shaft 410. The telescopic movement of the second electric telescopic rod 43 gives the fulcrum a forward and upward lifting force to form a force couple, thereby driving the upper supporting component 412 and the cargo box 5 thereon to rotate along the direction of the rotation fixed point exceeding the lower supporting component 411, so that the vertical section and the horizontal section of the upper supporting component 412 are separated from the vertical section and the horizontal section of the lower supporting component 411 respectively, forming a Figure 14 The flipped state shown completes the 90° tilting.

[0177] When the cargo box 5 needs to be lifted, the lifting shafts arranged in the lifting machine housing 3 are controlled to drive the transport box receiving component 4 to gradually lift the cargo box 5 to the upper position. Figure 19 Status shown.

[0178] It should be clear that the mass m of the cargo in the method provided by the present disclosure includes the net weight of the cargo and the mass of the cargo box 5, and the mass M of the trolley itself is only Figure 16 The mass of the trolley without the cargo box 5 is shown on the left side.

[0179] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of an instruction, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or by a combination of dedicated hardware and computer instructions.

[0180] The embodiments of the present disclosure have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations are obvious to those of ordinary skill in the art in the technical field without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles of the embodiments, the practical application, or the technical improvement of the technology in the market, or to enable other ordinary skill in the art in the technical field to understand the embodiments disclosed herein.

Claims

1. Control method for intelligent logistics transportation and palletizing AGV vehicle, the vehicle being an AGV vehicle with X-shaped Mecanum wheels, characterized in that, It includes the following steps: S1: Obtain whether the AGV vehicle is unloaded. If it is carrying goods, obtain the real-time mass of the carried goods; S2: Real-time monitor the real-time center-of-gravity position and heading angle of the AGV vehicle carrying goods in the world coordinate system, as well as the real-time center-of-gravity position and offset angle of the carried goods in the vehicle body coordinate system, and construct the real-time acceleration matrix of the center of gravity of the goods carried on the AGV vehicle in the vehicle body coordinate system; S3: Based on the real-time acceleration matrix of the center of gravity of the goods constructed in step S2, calculate the three-dimensional driving force required for the AGV vehicle carrying goods as a whole; S4: Based on the rotational speed of each Mecanum wheel and the rotational speed of the roller obtained by real-time monitoring, construct the slip speed calculation matrix of each wheel of the AGV vehicle when carrying goods and lifting the goods in the vehicle body coordinate system; S5: Based on the calculation results of steps S3 - S4, further calculate the real-time driving force required for each wheel of the AGV vehicle carrying goods; S6: Further, based on the state variable feedback method, solve the optimal real-time driving force for each wheel of the AGV vehicle carrying goods, and finally obtain the optimal real-time rotational speed of each wheel of the AGV vehicle carrying goods.

2. The method according to claim 1, wherein Step S2 includes: Based on the real-time center-of-gravity position and attitude angle of the AGV vehicle carrying goods in the world coordinate system, construct a rotation transformation matrix and obtain the rigid body transformation relationship, so as to calculate the center-of-gravity position of the AGV vehicle as a whole in the vehicle body coordinate system; further, in combination with the center-of-gravity position offset angle and relative distance of the goods, construct the real-time acceleration matrix of the center of gravity of the goods carried on the AGV vehicle.

3. The method according to claim 2, wherein The calculation of the three-dimensional driving force required for the AGV vehicle carrying goods in step S3 includes: Considering the mass and motion state of the AGV vehicle and the goods as a whole, combining the vertical acceleration component of the goods themselves in the vehicle body coordinate system, the offset angular velocity and angular acceleration of the goods, and the additional upward inertia term generated in the overall rotational motion of the AGV vehicle carrying goods, respectively calculate the three-dimensional driving force required for the AGV vehicle carrying goods as a whole in the vehicle body coordinate system for subsequent tire load distribution and dynamic control.

4. The method according to claim 3, characterized in that Step S4 includes: According to the position relationship of each Mecanum wheel relative to the vehicle body coordinate system, construct a wheel-roller conversion coefficient matrix to describe the mapping between the linear velocity of the AGV vehicle and the local velocity of the wheel; Obtain the slip direction velocity component coefficient matrix block and construct the drive mapping matrix block; According to the rotational speed of the wheel, the rotational speed of the roller, and the linear velocity of the center of gravity of the vehicle carrying goods as a whole in the world coordinate system, construct the slip speed calculation matrix of each Mecanum wheel in the vehicle body coordinate system to describe the linear mapping relationship between the slip speed of each Mecanum wheel and the system state.

5. The method according to claim 4, wherein Step S5 includes the following steps: Based on the motion acceleration of the center of gravity of the goods carried by the AGV vehicle in the vehicle body coordinate system and the offset angle of the goods, calculate the lateral and vertical load transfer amounts of each Mecanum wheel; Based on the lateral and vertical load transfer amounts, fuse the vertical driving force required for the AGV vehicle carrying goods as a whole, and calculate the total vertical load of each wheel; Integrate the longitudinal and lateral driving forces required by the overall AGV vehicle and the slip speed of the Mecanum wheels, and calculate the real-time driving forces of the four wheels in combination with the friction coefficients of each wheel.

6. The method according to claim 5, wherein The state variable feedback method in step S6 includes the following steps: Construct a state space model including the vehicle body motion state and the cargo attitude; Design and construct a state feedback optimization objective function, jointly considering the state error and the control input; Introduce a spatial variation metric consistency coefficient to improve the state value weight matrix in the state feedback optimization objective function, and introduce an input distribution coupling coefficient to improve the input control value weight matrix in the state feedback optimization objective function; Set the termination threshold condition and iteratively solve for the optimal control input; Further solve to obtain the optimal real-time rotational speed of each wheel of the AGV vehicle carrying the cargo.

7. The control system of an intelligent logistics transportation and palletizing AGV cart that executes the control method according to any one of claims 1-6, characterized in that, The control system includes: An empty-load and load detection module, used to obtain information on whether the AGV vehicle is empty. If it is carrying cargo, obtain the real-time mass of the cargo carried; An IMU inertial measurement unit, used to obtain the attitude and angular velocity of the overall vehicle carrying the cargo in the world coordinate system in real time; A real-time kinematic differential positioning module, used to provide the real-time centroid position and heading angle ψ of the overall AGV vehicle carrying the cargo in the world coordinate system in real time; A cargo offset angle detection unit, used to obtain the real-time centroid position and offset angle of the carried cargo in the vehicle body coordinate system; an encoder, used to obtain the rotational angular velocity of each Mecanum wheel and the rotational angular velocity of each roller of each Mecanum wheel; A cargo centroid acceleration matrix construction module, used to construct the real-time acceleration matrix of the cargo carried on the AGV vehicle; A three-dimensional driving force calculation module, used to calculate the three-dimensional driving forces required by the overall AGV vehicle carrying the cargo based on the data of the empty-load and load detection module, the IMU inertial measurement unit, the real-time kinematic differential positioning module, the cargo offset angle monitoring unit, and the cargo centroid acceleration matrix construction module; A slip speed calculation module, used to construct a slip speed calculation matrix of each wheel of the AGV vehicle in the vehicle body coordinate system during real-time walking while carrying the cargo and lifting the cargo; A real-time driving force calculation module, used to further calculate the required real-time driving forces of each wheel of the AGV vehicle carrying the cargo based on the calculation results of the three-dimensional driving force calculation module and the slip speed calculation module; A state feedback optimization solution module, used to solve for the optimal real-time driving forces of each wheel of the AGV vehicle carrying the cargo based on the state variable feedback method, and finally obtain the optimal real-time rotational speed of each wheel of the AGV vehicle carrying the cargo.

8. Intelligent logistics transportation and palletizing AGV cart, the AGV cart includes a vehicle base (1) and four Mecanum wheels (2) with an X-shaped installation structure on the vehicle base (1), characterized in that, The AGV vehicle further includes the control system as claimed in claim 7, a lift housing (3) provided above the rear end of the vehicle base, and a transport box carrying component (4); A plurality of lift shafts are provided in the lift housing (3) for lifting the cargo in the cargo box (5) fixed by the transport box carrying component (4); A cargo box flipping mechanism is provided in the transport box carrying component (4) for flipping the cargo box (5).

9. The intelligent logistics transportation and palletizing AGV trolley according to claim 8, wherein The transport box receiving component (4) includes two sub-receiving components (41) both in an L shape. Each sub-receiving component (41) includes a lower receiving component (411) and an upper receiving component (412) both in an L shape. The lower receiving component (411) and the upper receiving component (412) are fixedly connected by a connecting shaft (410) provided at the front end of the lower receiving component (411). An internal hook (44) is provided on the upper part of the upper receiving component (411). The cargo box turning mechanism includes a first electric telescopic rod (42) provided on the vertical section of each upper receiving component (412), a second electric telescopic rod (43) provided on the horizontal section of each lower receiving component (411), and a third electric telescopic rod (46) provided on the horizontal section of each upper receiving component (412).

10. The intelligent logistics transportation and palletizing AGV cart according to claim 9, characterized in that, The front end of each second electric telescopic rod (43) is fixedly provided at the lower part of the corresponding upper receiving component (412) through a rod head ring (431) and a fixing rod (432).

Images