A smart control and scheduling system for supply chain warehousing equipment

Abstract

This invention relates to the field of automated control technology in warehousing and logistics, and discloses an intelligent control and scheduling system for supply chain warehousing equipment, including: a path planning module, a feature mapping module, a conflict detection module, a speed allocation module, an instruction issuance module, and a low-level execution module. The system calculates the mass scalar of the warehousing and handling equipment under its current load state by extracting motor operating current data; generates conflict data based on the predicted time difference of multiple devices arriving at the same intersection area; constructs a cost function based on the mass scalar and solves for the speed compensation value; encapsulates the speed compensation value into a data frame containing spatial effective boundaries and a communication timestamp and issues it; the low-level execution module reconstructs the speed curve based on this data frame to achieve intersection staggering and triggers braking isolation upon communication timeout. This invention can dynamically allocate right-of-way based on equipment load to reduce kinetic energy loss, while avoiding collision risks caused by communication delays, thus improving scheduling safety.

Description

Technical Field

[0001] This invention relates to the field of automated control technology for warehousing and logistics, specifically to an intelligent control and scheduling system for supply chain warehousing equipment. Background Technology

[0002] With the development of supply chain warehousing automation, collaborative operation of multiple warehousing and handling equipment has become the mainstream mode. The scheduling system needs to plan routes for various types of handling equipment operating within the area and perform collision avoidance scheduling control in intersections and other convergence areas.

[0003] Existing warehouse dispatching systems typically employ first-come, first-served or fixed stopping and waiting strategies when handling conflicts between multiple vehicles. These conventional control strategies primarily allocate right-of-way based on the geographical location of the equipment and preset route priorities, failing to dynamically adjust according to the actual load status of the equipment. Because load differences are ignored when issuing dispatching instructions, heavy-load handling equipment is often assigned stop and yield instructions, resulting in frequent braking and restarting actions at intersections. This simplistic start-stop control logic increases the overall kinetic energy loss of the system, exacerbates the wear and tear on the equipment's motors and mechanical transmission components, and also limits the traffic efficiency in intersection areas.

[0004] Furthermore, existing centralized scheduling schemes heavily rely on real-time wireless communication between the central scheduling platform and the underlying material handling equipment. Control commands issued by the scheduling center typically lack joint verification mechanisms for communication delays and effective spatial boundaries. In actual warehouse environments, dense metal racking structures and dynamically changing cargo stacking can easily cause network fluctuations and signal interference. When system communication delays occur, deceleration or braking commands issued by the central system may not reach the underlying equipment on time. Lacking local timeliness assessment and active isolation logic, the underlying equipment will continue to approach the intersection zone at a predetermined speed according to historical commands. In this situation, once the underlying equipment receives a delayed braking command, its actual remaining physical distance from obstacles or intersecting vehicles is often less than the safe braking threshold, leading to braking failure and a collision.

[0005] Therefore, this invention proposes an intelligent control and scheduling system for supply chain warehousing equipment to address the shortcomings of existing technologies. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention provides an intelligent control and scheduling system for supply chain warehousing equipment. It solves the problems of existing warehousing scheduling systems failing to dynamically allocate right-of-way based on the actual load status of the equipment, resulting in large overall energy loss when multiple vehicles converge, and lacking a communication timeliness verification mechanism for issued instructions, which can easily lead to collisions under network latency conditions.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control and scheduling system for supply chain warehousing equipment, comprising:

[0008] The path planning module is used to generate node sequence paths and baseline cruising speeds for warehouse handling equipment;

[0009] The feature mapping module is used to extract operating current data during the operation of the warehousing and handling equipment and calculate the mass scalar under the current load condition.

[0010] The conflict detection module is used to calculate the predicted arrival time difference to the same intersection area based on the real-time location coordinates of multiple storage and handling equipment and the node sequence path, and generate conflict data when the predicted arrival time difference is less than a preset safety time interval threshold.

[0011] The speed allocation module is used to construct a cost function based on the conflict data and the mass scalar of each warehousing and handling equipment participating in the intersection, and solve for the speed compensation value under physical acceleration and deceleration boundary constraints.

[0012] The instruction issuing module is used to encapsulate the speed compensation value into a data frame with a valid spatial limit and a communication timestamp and then issue it.

[0013] The underlying execution module is used to parse the data frame, reconstruct the speed planning curve according to the speed compensation value to change the time phase of arrival at the intersection area, and perform timeliness verification based on the communication timestamp, and trigger braking isolation control when the timeliness verification times out.

[0014] Furthermore, the process by which the feature mapping module calculates the mass scalar under the current load condition includes:

[0015] When the warehousing and handling equipment is in steady-state cruise mode, the q-axis current component output by the servo driver that provides the operating current data is extracted, and the dynamic frictional resistance torque is calculated.

[0016] When the warehousing and handling equipment performs a start-up operation according to a preset benchmark start-up acceleration, the filtered q-axis current component of the acceleration phase is extracted.

[0017] Combining the dynamic frictional resistance torque and the reference starting acceleration, the equivalent moment of inertia referred to the motor shaft end is calculated;

[0018] The equivalent moment of inertia is mapped to the dimensionless mass scalar using a linear normalization function.

[0019] Furthermore, the process of generating conflict data by the conflict detection module includes: extracting overlapping nodes between the node sequence paths of different warehousing and handling equipment as physical intersection coordinates;

[0020] Assuming the warehousing and handling equipment approaches at the reference cruising speed, calculate the predicted absolute time for each warehousing and handling equipment participating in the intersection to reach the physical intersection coordinate, and obtain the predicted arrival time difference between different warehousing and handling equipment;

[0021] When the predicted arrival time difference is less than the preset safety time interval threshold, the equipment number of each warehousing and handling equipment participating in the intersection, the current remaining route length of each warehousing and handling equipment to the physical intersection coordinate, and the quality scalar are extracted, encapsulated as the conflict data, and output to the speed allocation module.

[0022] Furthermore, the process of constructing and solving the cost function by the speed allocation module includes:

[0023] Using the speed compensation values ​​of each warehousing and handling equipment participating in the intersection as control decision variables, and the corresponding mass scalar as cost weights, a quadratic objective function that minimizes the cost of kinetic energy adjustment is constructed.

[0024] A time-domain peak-shifting constraint is constructed based on the current remaining route length and the preset safety time interval threshold, and a physical execution boundary constraint is constructed based on the preset maximum allowable acceleration boundary and maximum allowable deceleration boundary of each warehousing and handling equipment.

[0025] Within the feasible region jointly defined by the temporal peak-shifting constraint and the physical execution boundary constraint, a minimum search is performed on the quadratic objective function to obtain a set of optimal solutions that minimize the total cost of kinetic energy adjustment, which are then used as the velocity compensation values.

[0026] The quadratic objective function uses the mass scalar as a weight to make the speed compensation value of the storage and handling equipment with a higher load capacity less than that of the storage and handling equipment with a lower load capacity, thereby reducing the overall kinetic energy loss of the system.

[0027] Furthermore, the speed allocation module is also used for:

[0028] When there is no feasible solution for the speed compensation value that satisfies the temporal peak-shifting constraint and the physical execution boundary constraint within the feasible domain, stop the minimum value search and execute the degradation isolation strategy.

[0029] The mass scalar of each participating storage and handling equipment, the remaining route length to the preset physical collision avoidance zone boundary, the real-time calculated safety braking critical distance, and the status information of whether or not the equipment has entered the physical collision avoidance zone are compared.

[0030] Warehouse handling equipment with a relatively small mass scalar that has not yet entered the physical collision avoidance zone, and whose remaining route length to the boundary of the physical collision avoidance zone is greater than or equal to the sum of the safety braking critical distance and the preset collision avoidance margin, is identified as a candidate avoidance equipment, and a physical stop command is issued to it.

[0031] Furthermore, the process by which the instruction issuing module encapsulates the speed compensation value into a data frame with valid spatial limits and a communication timestamp includes:

[0032] The speed compensation value is superimposed on the reference cruise speed to generate the target cruise speed; a two-dimensional circular domain set is constructed with the physical intersection coordinates of the intersection area as the center and combined with the safety boundary radius, which is written into the effective spatial limit as the geometric boundary of the intersection physical collision avoidance zone;

[0033] The system's absolute physical time at the time the data frame was generated is used as the communication timestamp, and a valid lifetime parameter is configured.

[0034] The data frame is generated by combining the target cruise speed, the effective space limit, the communication timestamp, the effective lifetime parameter, and the instruction type field.

[0035] Furthermore, the process by which the underlying execution module reconstructs the speed planning curve based on the speed compensation value includes:

[0036] Once the data frame passes the integrity check, the target cruising speed is parsed and extracted.

[0037] Based on the current actual operating speed of the warehousing and handling equipment, the preset maximum allowable acceleration boundary, and the acceleration limit, an S-shaped acceleration / deceleration algorithm is used to generate a continuous speed command, so that the current actual operating speed of the warehousing and handling equipment can smoothly transition to the target cruising speed.

[0038] Furthermore, before performing the timeliness check, the underlying execution module is also used to:

[0039] Based on the current actual operating speed and the bus response delay time from the triggering of the braking signal to the establishment of the braking torque by the servo driver of the motor in the underlying system, calculate the safe braking critical distance at the current moment.

[0040] Based on local real-time positioning, calculate the real-time remaining distance from the geometric center of the warehousing and handling equipment to the geometric boundary of the physical collision avoidance zone at the intersection;

[0041] The calculation of the critical safe braking distance includes the response delay of the servo driver in establishing braking torque.

[0042] Furthermore, the underlying execution module performs the timeliness check based on the communication timestamp, and the process of triggering braking isolation control when the timeliness check times out includes:

[0043] Obtain the vehicle's local physical time and determine whether the difference between the vehicle's local physical time and the communication timestamp is greater than the effective lifetime parameter;

[0044] If the difference is greater than the effective survival period parameter, and the real-time remaining distance is less than or equal to the sum of the safe braking critical distance and the preset anti-collision margin, and the warehousing and handling equipment has not yet entered the geometric boundary of the intersection physical collision avoidance zone, then the braking trigger condition is determined to be met.

[0045] A zero-speed command is issued to the servo driver, causing the storage and handling equipment to stop outside the geometric boundary of the physical collision avoidance zone at the intersection.

[0046] Furthermore, the underlying execution module is also used for:

[0047] If the difference between the vehicle's local physical time and the communication timestamp is greater than the effective lifetime parameter, but the warehousing and handling equipment has already entered the geometric boundary of the intersection's physical collision avoidance zone, the warehousing and handling equipment is controlled to leave based on the direction of travel in the most recent valid data frame received.

[0048] If the warehousing and handling equipment fails to leave the geometric boundary of the physical collision avoidance zone of the intersection within the preset clearing time, or detects an obstacle ahead or a positioning abnormality, an emergency braking command is triggered.

[0049] This invention provides an intelligent control and scheduling system for supply chain warehousing equipment. It has the following beneficial effects:

[0050] 1. This invention extracts the q-axis current component during motor operation to infer the mass scalar of the storage and handling equipment, and uses it as a penalty weight when constructing the speed allocation cost function, thus limiting the speed change range of heavy-duty equipment during intersection adjustments. This design utilizes underlying electrical data to achieve seamless acquisition of load status, allocating more acceleration and deceleration tasks to unloaded or lightly loaded equipment, avoiding kinetic energy loss caused by frequent stops and starts of heavy-duty equipment at intersections, and reducing overall energy consumption and mechanical wear during multi-vehicle intersections.

[0051] 2. This invention constructs a feasible domain solution for speed compensation values ​​that includes temporal peak-shifting constraints and physical execution boundary constraints, guiding intersecting devices to stagger their passage through intersections on the time axis through dynamic and smooth speed adjustment. When the speed adjustment range cannot meet the safe intersection conditions, the system triggers degraded isolation control based on the status information of each device, such as its mass scalar and remaining route length from the physical collision avoidance zone. It prioritizes instructing devices with lighter loads and greater distances to stop and yield, thereby improving the continuity of intersection traffic under normal operating conditions while ensuring scheduling safety under extreme spatial constraints.

[0052] 3. This invention encapsulates communication timestamps and spatial validity limits in the scheduling instructions, and directly incorporates the bus response delay time into the calculation benchmark for the safe braking critical distance during low-level control execution. The warehousing and handling equipment performs timeliness verification locally by comparing absolute time differences, and determines whether to trigger a stop command based on the braking distance, which includes physical hard delay. This avoids collision risks caused by network communication congestion, delayed control command issuance, and deviations in conventional pure kinematic calculations, thus improving the system's control reliability under low-level network fluctuation environments. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the system framework of the present invention;

[0054] Figure 2 This is a schematic diagram of the method flow of the present invention;

[0055] Figure 3 This is a schematic diagram of the global path planning and initialization parameter distribution process of the present invention;

[0056] Figure 4 This is a schematic diagram of the two-stage physical feature observation and inertia mapping process of the present invention;

[0057] Figure 5 This is a schematic diagram of the encounter topology matrix construction and conflict pre-detection process of the present invention;

[0058] Figure 6 This is a schematic diagram of the asymmetric velocity distribution process controlled by boundary conditions according to the present invention;

[0059] Figure 7 This is a schematic diagram of the data frame construction and distribution process containing spatiotemporal security envelopes according to the present invention;

[0060] Figure 8 This is a schematic diagram of the underlying closed-loop execution and communication anti-collision fallback process of the present invention;

[0061] Figure 9 Figure (a) is a schematic diagram of the phase trajectory and velocity curve of the dual-device convergence velocity distribution according to the present invention; wherein, Figure (b) is a schematic diagram of the phase trajectory of convergence approaching in space and time; and Figure (c) is a schematic diagram of the velocity reconstruction compensation curve.

[0062] Among them, 10 is the path planning module; 20 is the feature mapping module; 30 is the conflict detection module; 40 is the speed allocation module; 50 is the command issuance module; 60 is the low-level execution module; 100 is the central scheduling server; 200 is the edge controller; 300 is the vehicle-mounted programmable logic controller; 400 is the servo driver; and 500 is the warehousing and handling equipment. Detailed Implementation

[0063] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0064] See attached document Figure 1 This invention provides an intelligent control and scheduling system for supply chain warehousing equipment. The system includes a path planning module 10, a feature mapping module 20, a conflict detection module 30, a speed allocation module 40, an instruction issuance module 50, and an underlying execution module 60.

[0065] The path planning module 10 is deployed on the central scheduling server 100. It is used to receive warehousing and handling tasks and generate a node sequence path from the starting coordinates to the target coordinates for the warehousing and handling equipment 500 based on the node information of the warehousing grid road network. At the same time, the path planning module 10 sends the reference cruise speed and basic kinematic parameters to the warehousing and handling equipment 500.

[0066] The feature mapping module 20 runs on the vehicle-mounted programmable logic controller 300. During the process of the storage and handling equipment 500 traveling along the node sequence path, it extracts the operating current data from the servo driver 400 and calculates the mass scalar of the storage and handling equipment 500 under the current load state by combining the operating current data and the equipment motion state. After the calculation is completed, the feature mapping module 20 sends the mass scalar to the central scheduling server 100.

[0067] The conflict detection module 30 is located in the central scheduling server 100. It is used to acquire the real-time location coordinates and node sequence paths of multiple storage and handling equipment 500, and to calculate the predicted arrival time difference of different storage and handling equipment 500 to the same geometric intersection coordinate. When there are collinear overlapping sections on the paths of different storage and handling equipment 500, the conflict detection module 30 further calculates the predicted time interval occupied by each storage and handling equipment 500 for that collinear overlapping section. If the predicted arrival time difference is less than a preset safety time interval threshold, or if there is a conflict in the predicted time interval, the conflict detection module 30 triggers the speed allocation module 40.

[0068] The speed allocation module 40 is used to construct a cost function based on the collision data output by the collision detection module 30 and the mass scalar of each storage and handling equipment 500 participating in the intersection. Under the physical acceleration and deceleration boundary constraints of the storage and handling equipment 500, the cost function is optimized to obtain the speed compensation value used to adjust the reference cruise speed. When there is no feasible solution under the physical acceleration and deceleration boundary constraints, the speed allocation module 40 outputs a physical stop command or an emergency braking command.

[0069] The instruction issuing module 50 is used to combine the speed compensation value output by the speed distribution module 40 with the basic motion instruction to generate a data frame with a valid spatial limit and a communication timestamp, and then issue the data frame to the corresponding vehicle programmable logic controller 300 via the edge controller 200.

[0070] The underlying execution module 60 is deployed in the underlying control program of the vehicle-mounted programmable logic controller 300. It is used to parse data frames and reconstruct the speed planning curve of the storage and handling equipment 500 during its travel based on the speed compensation value, so as to change the time phase of the storage and handling equipment 500 reaching the geometric intersection coordinates. The underlying execution module 60 also performs communication heartbeat verification based on timestamp data. When the timestamp verification times out, it performs braking isolation outside the collision avoidance zone or restricted departure control inside the collision avoidance zone, depending on whether the storage and handling equipment 500 has entered the physical collision avoidance zone of the intersection. In abnormal conditions, the underlying execution module 60 controls the servo driver 400 to perform braking operations.

[0071] See attached document Figure 2 The present invention also provides a continuous flow collaborative scheduling method for storage equipment with dynamic boundary fault tolerance and torque feedback, the method comprising the following steps.

[0072] S10 receives the warehousing and handling task through the path planning module 10, generates a node sequence path from the starting coordinate to the target coordinate for the warehousing and handling equipment 500 based on the node information of the warehousing grid road network, and sends the reference cruise speed and basic kinematic parameters.

[0073] S20: The operating current data is extracted from the servo driver 400 through the feature mapping module 20, and the mass scalar of the warehouse handling equipment 500 under the current load state is calculated by combining the operating current data and the equipment motion state; then, the mass scalar is sent to the central scheduling server 100.

[0074] S30: The real-time location coordinates and node sequence paths of multiple storage and handling equipment 500 are obtained through the conflict detection module 30. The predicted arrival time difference of different storage and handling equipment 500 to the same geometric intersection coordinate is calculated. When there are collinear overlapping road segments on the paths of different storage and handling equipment 500, the predicted time interval for each storage and handling equipment 500 to enter and leave the collinear overlapping road segment is further calculated. If the predicted arrival time difference is less than the preset safety time interval threshold, or if there is a conflict in the road segment occupancy time interval, then step S40 is executed.

[0075] S40, through the speed distribution module 40, constructs a cost function by combining the mass scalars of each warehousing and handling equipment 500 participating in the intersection, and optimizes the cost function under the physical acceleration and deceleration boundary constraints to obtain the speed compensation value used to adjust the reference cruise speed; when there is no feasible solution that meets the safety time interval requirements under the physical acceleration and deceleration boundary constraints, the speed distribution module 40 combines the mass scalars, the safety braking critical distance, and the state of whether it has entered the physical collision avoidance zone to output a physical stop command or an emergency braking command.

[0076] S50 combines the speed compensation value with the basic motion command through the command sending module 50 to generate a data frame with a valid spatial limit and a communication timestamp, and sends the data frame to the corresponding on-board programmable logic controller 300.

[0077] S60, the underlying execution module 60 performs validity verification on the data frame. After successful verification, the underlying execution module 60 reconstructs the speed planning curve based on the speed compensation value to change the time phase of the warehousing and handling equipment 500 reaching the geometric intersection coordinates. The underlying execution module 60 performs communication heartbeat verification based on timestamp data. When the timestamp verification times out, the underlying execution module 60 performs braking isolation outside the collision avoidance zone or restricted departure control within the collision avoidance zone, depending on whether the warehousing and handling equipment 500 has entered the intersection's physical collision avoidance zone. After the warehousing and handling equipment 500 leaves the corresponding geometric boundary of the intersection's physical collision avoidance zone, the underlying execution module 60 restores the target speed to the base cruise speed based on the failed endpoint coordinates or the cruise recovery command in the data frame. After the warehousing and handling equipment 500 enters the braking lock state, the underlying execution module 60 unlocks the system upon receiving a valid data frame that meets the timestamp, sequence number, and integrity verification conditions, and waits for the central scheduling server 100 to reissue the task recovery command.

[0078] To further clarify the implementation of each technical aspect of the present invention, the following will provide a detailed description of the implementation of each functional module involved above and its internal processing flow.

[0079] See attached document Figure 3In step S10, the path planning module 10 is deployed on the central scheduling server 100 to receive warehousing and handling tasks and determine the running path and initial motion parameters for the warehousing and handling equipment 500. This process may include the following steps.

[0080] S11, Establish the road network topology model.

[0081] The central dispatch server 100 abstracts the physical warehouse operation space into a two-dimensional grid road network and constructs a topology graph structure. Among them, the vertex set This includes physical intersection coordinates in the road network, cargo parking locations, and other nodes that allow 500 units of warehousing and handling equipment to pass through or park; edge sets. This includes straight-line travel tracks connecting adjacent vertices.

[0082] In actual modeling, the warehouse map can be divided according to a preset grid size, and the intersections, turns, and entrances / exits of driving lanes can be set as topological nodes. For the specific method of building an environmental model using the topological graph structure, those skilled in the art can use conventional rasterization mapping processing, which is a well-known technique in the field and will not be elaborated upon here.

[0083] S12, Generate node sequence path.

[0084] The path planning module 10 parses the starting and target coordinates in the warehousing and handling task, and maps the starting and target coordinates to the corresponding vertices in the topological graph structure G. Subsequently, the path planning module 10 performs path search in the topological graph structure G, and determines the set of edges connecting the starting vertex and the target vertex based on path distance, path accessibility, or preset path cost.

[0085] The path planning module 10 extracts each vertex traversed on the edge set according to the travel sequence of the warehousing and handling equipment 500, forming a node sequence path pointing from the starting coordinates to the target coordinates. For the specific pathfinding iteration process of the graph search algorithm, those skilled in the art can use algorithms such as A* or Dijkstra's algorithm for node expansion and cost calculation, which are well-known techniques in the field and will not be elaborated upon here.

[0086] S13, configures basic kinematic parameters.

[0087] The path planning module 10 configures the basic kinematic parameters required for the storage and handling equipment 500 to perform the current task, based on the mechanical structure, driving performance, and current task requirements of the equipment. These basic kinematic parameters include: a reference cruising speed for specifying the equipment's constant-speed travel on a straight segment. Used to specify the reference starting acceleration of the motor command during the starting phase of the equipment. Maximum permissible acceleration boundary used to limit the upper limit of device drive performance. The maximum permissible deceleration boundary used to limit the safe braking performance of equipment. And jerk limits used to limit the rate of change of acceleration of the device. .

[0088] In actual calculations, the deceleration direction is opposite to the forward direction of the equipment. Therefore, when participating in boundary calculations, the maximum permissible deceleration boundary can be taken. absolute value As a constraint on braking capacity.

[0089] In some embodiments of the present invention, the reference cruise speed and benchmark starting acceleration The maximum permissible acceleration boundary can be preset based on the efficiency requirements of warehousing and handling tasks, path length, and road traffic conditions. The maximum permissible deceleration boundary can be determined based on the peak output current capability of the servo driver 400. The acceleration limit can be determined based on the static friction coefficient between the 500 drive wheels of the warehousing and handling equipment and the road surface, the load condition, and braking safety requirements; The parameters can be set based on cargo stability, equipment structural rigidity, and the interpolation capability of the underlying motion controller. These parameters can be calibrated during the equipment factory commissioning phase or the system initialization phase and then written into the configuration table.

[0090] S14, Packaging and distributing task parameters.

[0091] The path planning module 10 will generate the node sequence path and the baseline cruise speed. Reference starting acceleration Maximum permissible acceleration boundary Maximum permissible deceleration boundary and jerk limits The initialization task data packet is encapsulated and sent from the central dispatch server 100 to the on-board programmable logic controller 300 of the target warehousing and handling equipment 500 via the edge controller 200.

[0092] After receiving and parsing the initialization task data packet, the on-board programmable logic controller 300 generates a start-up control command based on the node sequence path and basic kinematic parameters, and controls the servo driver 400 to drive the motor, so that the warehousing and handling equipment 500 starts with a reference acceleration. Move away from the current location and gradually accelerate to the base cruise speed. Therefore, the storage and handling equipment 500 enters the task execution state of traveling along the node sequence path, providing the basic operating conditions for subsequent operation current extraction, physical feature observation and conflict scheduling.

[0093] See attached document Figure 4 In step S20, the feature mapping module 20 operates on the on-board programmable logic controller 300, and is used to acquire operating current data from the servo driver 400 and calculate the mass scalar under the current load state in combination with the motion state of the storage and handling equipment 500. This mass scalar is used for weight calculation in the subsequent speed allocation process. The specific process may include the following steps.

[0094] S21, extract the dynamic frictional resistance torque during the steady-state cruise segment.

[0095] When the storage and handling equipment 500 enters a steady-state cruise state on a straight segment, its actual acceleration approaches zero. The feature mapping module 20 continuously monitors the real-time acceleration of the storage and handling equipment 500; when the real-time acceleration is maintained within a preset zero-point dead zone threshold range for more than a predetermined time window, it is determined that the storage and handling equipment 500 is in a steady-state dynamic equilibrium state.

[0096] For a storage and handling equipment 500 performing a task for the first time, not yet entering a steady-state cruise phase, or whose current task has not yet formed an effective dynamic frictional resistance torque cache, the feature mapping module 20 first calls the historical dynamic frictional resistance torque most recently obtained by the equipment on the same or adjacent road segment as the initial compensation value; if no historical cache exists, it calls the default frictional resistance torque pre-calibrated during the system initialization phase as the initial compensation value. After the storage and handling equipment 500 enters the steady-state cruise phase and completes real-time calculation, the feature mapping module 20 updates the cache value in the local register with the dynamic frictional resistance torque obtained in real-time calculation.

[0097] When the feature mapping module 20 determines that the storage and handling equipment 500 has entered a steady-state dynamic equilibrium state, it reads the q-axis current component output by the field orientation control loop of the servo driver 400 through the internal communication bus. At this time, the electromagnetic torque output by the motor is mainly used to overcome the dynamic frictional resistance torque of the current road surface. The feature mapping module 20 calculates the dynamic frictional resistance torque based on the electromagnetic torque equation:

[0098] ;

[0099] In the formula, The inherent torque constant of the motor is determined by the motor winding structure and magnetic circuit parameters. The feature mapping module 20 will calculate the... The data is written to a local register as environmental calibration parameters in subsequent inertia extrapolation. By extracting actual current feedback during equipment operation, the impact of variations in warehouse floor flatness, local adhesion differences, and track resistance on load estimation results can be reduced.

[0100] S22, deduce the equivalent moment of inertia during the transient acceleration phase.

[0101] When the warehouse handling equipment 500 receives the task and starts with the reference acceleration set in step S10, During the start-up operation, the feature mapping module 20 reads the q-axis current component output by the servo driver 400 during the acceleration phase. .

[0102] In this embodiment, the first Taiwan warehouse handling equipment 500's benchmark starting acceleration It can be the equivalent angular acceleration converted to the motor shaft end. When the vehicle programmable logic controller 300 collects the vehicle linear acceleration, the feature mapping module 20 converts the vehicle linear acceleration into the equivalent angular acceleration at the motor shaft end based on the drive wheel radius, reducer transmission ratio, and transmission efficiency, and then uses it in the calculation.

[0103] Considering the potential for current spikes and mechanical transients during the initial acceleration phase, the feature mapping module 20 collects multiple q-axis current samples within the stable acceleration time window and performs mean filtering on the q-axis current samples, using the filtered current values ​​as... Subsequently, the feature mapping module 20 calls the dynamic frictional resistance torque cached in the local register. Based on the dynamic equilibrium relationship of the rotating system, the equivalent moment of inertia of the warehousing and handling equipment 500 under the current load condition, converted to the motor shaft end, is calculated. :

[0104] ;

[0105] In the formula, For the first The equivalent moment of inertia of the storage and handling equipment under the current load condition; This is the inherent torque constant of the motor; For the first The filtered q-axis current component of a warehouse handling equipment during the acceleration phase; For the pre-cached first Dynamic frictional resistance torque of storage and handling equipment; For the first The baseline starting acceleration for warehouse handling equipment; subscript 500 is used to distinguish different storage and handling equipment performing tasks in the road network.

[0106] In the above calculation process, after deducting the dynamic frictional resistance torque from the total electromagnetic torque output by the motor, the remaining torque is used to characterize the torque component required to overcome the inertia of the equipment and load. Therefore, the feature mapping module 20 can reuse the existing current feedback signal of the servo driver 400 to obtain physical characteristic quantities related to the current load state of the equipment without additional weighing sensors.

[0107] S23, generate and report quality scalars.

[0108] Due to equivalent rotational inertia It has physical dimensions, and its value is affected by mechanical structural parameters such as the speed ratio of the reducer, the radius of the drive wheel, and the transmission efficiency. The feature mapping module 20 maps it to a dimensionless mass scalar. This is so that the central scheduling server 100 can use it uniformly in multi-device collaborative scheduling. The mapping process uses a linear normalization function:

[0109] ;

[0110] In the formula, and This document outlines calibration coefficients for the mechanical structure of the storage and handling equipment 500. During system initialization, the equivalent moment of inertia reference values ​​for the equipment under absolute no-load and rated full-load conditions can be extracted. The absolute no-load condition is mapped to a lower limit of the mass scalar, and the rated full-load condition is mapped to an upper limit of the mass scalar. For example, the dimensionless mass scalar... Limited to the range of 1 to 10, and determined accordingly. and .

[0111] quality scalar After the calculation is completed, the feature mapping module 20 will convert the mass scalar The device number, task number, sampling timestamp, and current path segment number are encapsulated into a quality status reporting data packet and uploaded to the central dispatch server 100 via a wireless communication network. The central dispatch server 100 only uses the quality scalar within the valid time window for speed allocation calculation. If the central dispatch server 100 does not receive an updated quality scalar from a certain storage and handling equipment 500 within a preset time, it will use the most recent valid quality scalar for that equipment; if no most recent valid quality scalar exists, it will use the default quality scalar for that equipment for scheduling.

[0112] When the warehousing and handling equipment 500 completes picking, placing, vehicle switching, or goods handover, or when the central dispatch server 100 detects a change in the task load status, the central dispatch server 100 sends a mass scalar update trigger command to the corresponding on-board programmable logic controller 300. Upon receiving this command, the on-board programmable logic controller 300 causes the feature mapping module 20 to re-execute the dynamic frictional resistance torque extraction, equivalent moment of inertia derivation, and mass scalar generation processes, thereby ensuring that the mass scalar involved in the speed allocation calculation remains consistent with the current actual load status of the warehousing and handling equipment 500.

[0113] See attached document Figure 5 In step S30, the conflict detection module 30 runs on the central scheduling server 100 and is used to predict potential spatiotemporal conflicts within the warehouse operating space based on the real-time location coordinates of each warehouse handling device 500 and the assigned node sequence paths. This process may include the following steps.

[0114] S31, extract the path intersections and construct the meeting topology matrix.

[0115] The conflict detection module 30 acquires the real-time location coordinates of each warehousing and handling equipment 500 in operation within the road network, and combines this with the node sequence paths generated in step S10 to identify overlapping nodes between different node sequence paths. For nodes that are passed through by different paths, the conflict detection module 30 extracts them as physical intersection coordinates.

[0116] In actual warehouse grid road networks, path conflicts are not limited to cross intersections. If the paths of two warehouse handling equipment 500 have collinear overlapping sections, the conflict detection module 30 extracts the first entry node of the overlapping section according to their respective travel directions and uses it as the entry position of the section-level conflict.

[0117] For overlapping road sections, the conflict detection module 30 also calculates the predicted entry and exit times of each storage and handling equipment 500 into the overlapping road section, thus forming the corresponding road section occupancy time intervals. If the road section occupancy time intervals of two storage and handling equipment 500s overlap, a road section-level conflict risk is determined. For vehicles traveling in the same direction, the conflict detection module 30 further combines the predicted speed difference between the vehicles in front and behind and the real-time distance to determine whether there is a rear-end collision risk; for vehicles traveling in opposite directions, it determines whether there is a meeting conflict risk based on whether the predicted occupancy time intervals of the two devices for the same overlapping road section overlap.

[0118] To facilitate unified management of the convergence relationships among multiple devices by the central dispatch server 100, the conflict detection module 30 dynamically constructs an encounter topology matrix. This matrix is ​​used for any two warehouse handling devices whose planned paths intersect. With warehouse handling equipment Define matrix elements in the meeting topology matrix. This matrix element stores one or more conflict units between two devices. Each conflict unit includes at least the conflict type, conflict location, predicted arrival time difference, or road segment occupancy time interval. Its data structure can be represented as follows:

[0119] ;

[0120] In the formula, For warehouse handling equipment With warehouse handling equipment The elements of the encounter topology matrix; Indicates warehouse handling equipment With warehouse handling equipment Between One conflicting unit; The total number of conflicting units between the planned paths of two warehouse handling equipment; An incremental index number for conflicting units.

[0121] When the conflict type is point intersection conflict This includes physical intersection coordinates and predicted time difference of arrival; when the conflict type is a collinear overlapping section conflict, This includes the start and end points of the overlapping road segment, as well as the predicted time interval for the overlapping road segment by the two devices.

[0122] As for how to identify and extract the coordinates of intersection points from multiple line segments, those skilled in the art can use conventional geometric intersection algorithms, which are well-known techniques in the field and will not be elaborated here.

[0123] S32, calculate the predicted time difference of arrival.

[0124] The collision detection module 30 uses the real-time location coordinates and physical intersection coordinates of each storage and handling device 500. Calculate the remaining route length from the current location of the device to the physical intersection coordinate along the corresponding node sequence path.

[0125] To reduce the computational burden on the central dispatch server 100 during the conflict pre-detection phase, this embodiment employs a steady-state equivalent kinematic model in the prediction phase. This means that local acceleration / deceleration fluctuations are temporarily disregarded in the macroscopic prediction, and it is assumed that the storage and handling equipment 500 approaches the physical intersection coordinates at a baseline cruising speed. Based on this, the conflict detection module 30 calculates the kinematics of the storage and handling equipment... With warehouse handling equipment Calculate the predicted absolute time of arrival at the same physical intersection coordinate, and then calculate the difference between their predicted arrival times:

[0126] ;

[0127] ;

[0128] In the formula, and These are warehouse handling equipment With warehouse handling equipment Reaching physical cross coordinates The absolute time of prediction; The absolute timestamp of the current system; For warehouse handling equipment The remaining route length from the current location to the physical intersection coordinates; For warehouse handling equipment The baseline cruise speed; This indicates the absolute value operation.

[0129] The encounter topology matrix is ​​updated periodically based on the position changes of the storage and handling equipment 500 and the current system time. In this embodiment, the conflict detection module 30 refreshes the encounter topology matrix according to a preset scheduling cycle. This preset scheduling cycle can be determined based on the maximum operating speed of the storage and handling equipment 500, the location data refresh cycle, and the communication delay cycle. When the central scheduling server 100 detects a new task being added, a path replanning, a sudden change in equipment position, equipment going offline, equipment returning to online, or a change in equipment load status, the conflict detection module 30 triggers an incremental refresh to update the intersection risk status in the current road network.

[0130] S33 triggers conflict warning and speed intervention logic.

[0131] The collision detection module 30 dynamically updates the predicted time difference of arrival in the encounter topology matrix. With respect to the preset safety time interval threshold Compare. Safety time interval threshold. The safe time interval threshold can be determined based on the physical vehicle length, maximum cargo extension margin, and system communication delay period of the warehousing and handling equipment 500. Specifically, the sum of the physical vehicle length and the maximum cargo extension margin can be divided by the preset lower safety speed limit in the road network, and then the system communication delay period can be added to obtain the safe time interval threshold. In some embodiments, It can be taken as 2 to 5 seconds, which is used to characterize the shortest time interval required to avoid physical collision when two devices pass through the same coordinate point one after the other.

[0132] When the predicted time difference of arrival meets the following conditions, the collision detection module 30 determines that there is a risk of intersection and collision:

[0133] ;

[0134] For overlapping road sections, when the predicted occupancy time intervals of two warehousing and handling equipment 500 for the same overlapping road section overlap, or when the predicted safe distance between the following vehicle and the preceding vehicle is less than the preset safe distance threshold in the same direction driving scenario, the conflict detection module 30 also determines that there is a conflict risk.

[0135] When the trigger point cross-collision determination condition or the road segment-level collision determination condition is met, the collision detection module 30 extracts the warehousing and handling equipment involved in the intersection. With warehouse handling equipment The device number, the current remaining route length, and the quality scalar obtained in step S20 are used to encapsulate the above information into conflict data and output it to the speed allocation module 40 to initiate subsequent speed coordination intervention.

[0136] When three or more storage and handling equipment 500 are associated with the same physical intersection coordinate or the same collinear overlapping road segment, the conflict detection module 30 will construct a conflict set of the storage and handling equipment 500 participating in the intersection area. Conflict set This includes the device number, predicted arrival time, remaining route length, baseline cruise speed, mass scalar, and physical acceleration / deceleration boundaries for each device.

[0137] For conflict sets The speed allocation module 40 can establish a multivariate constrained optimization model for joint solution; it can also determine the candidate passage order based on the predicted arrival time, mass scalar, and safe braking critical distance, and apply safe time interval constraints between adjacent passing equipment. If the same storage and handling equipment 500 belongs to multiple conflict sets simultaneously in the same scheduling cycle, the central scheduling server 100 selects the speed compensation value with the strictest constraint as the final speed compensation value of the equipment, or triggers a global joint optimization process.

[0138] See attached document Figure 6 In step S40, the speed allocation module 40 receives the collision data output by the collision detection module 30 and calculates the speed compensation result within the physical acceleration / deceleration boundary of the equipment. This speed compensation result is used to change the time sequence of arrival of the warehousing and handling equipment 500 participating in the intersection to the collision area.

[0139] The following uses two warehouse handling equipment and warehousing and handling equipment Taking the same intersection area as an example, the speed allocation process is explained. When the number of warehousing and handling equipment 500 participating in the same intersection area is greater than two, the speed allocation module 40 can use the speed compensation value of each equipment in the conflict set C as the control decision variable, use the mass scalar of each equipment as the cost weight, establish a multivariate kinetic energy adjustment cost function, and set safety time interval constraints between adjacent passing sequence equipment. This process may include the following steps.

[0140] S41, Construct the constrained optimization objective function.

[0141] Speed ​​allocation module 40 extracts the warehousing and handling equipment involved in the intersection. and warehousing and handling equipment quality scalar , This value is used as the cost weight during speed intervention. In this embodiment, the speed compensation values ​​of the two devices are used as control decision variables to construct an objective function that minimizes the cost of kinetic energy adjustment:

[0142] ;

[0143] In the formula, The total cost of adjusting the system's kinetic energy; and These are warehouse handling equipment With warehouse handling equipment Dimensionless mass scalar; and These are the speed compensation values ​​that the system prepares to allocate to the two devices.

[0144] The objective function described above adopts a quadratic form, causing the cost to increase non-linearly as the speed compensation amplitude increases. Since equipment with a larger mass scalar experiences a more significant impact from inertia during acceleration and deceleration, using the mass scalar as a cost weight tends to reduce the speed change of heavily loaded equipment, allowing lightly loaded equipment to bear a relatively larger speed adjustment. This reduces energy loss and operational shock caused by frequent acceleration and deceleration of heavily loaded equipment while satisfying collision avoidance constraints.

[0145] S42, establish temporal peak-shifting constraints and physical execution boundary constraints.

[0146] Before calculating the speed compensation value, the speed allocation module 40 first determines the candidate passage order. The candidate passage order can be determined based on the warehouse handling equipment. , The original predicted arrival time, mass scalar, and remaining route length to the physical collision avoidance zone boundary. , And the determination of the critical distance for safe braking. Among them, and These represent the remaining route lengths of storage and handling equipment i and j from the boundary of their respective physical collision avoidance zones.

[0147] In one implementation, the speed allocation module 40 constructs the warehouse handling equipment respectively. Pre-shipment and warehouse handling equipment Two candidate constraint models are first tested, and the corresponding velocity compensation values ​​are solved for each. When both candidate constraint models have feasible solutions, the solution with the smaller total cost of kinetic energy adjustment is selected as the final velocity compensation result.

[0148] Time-domain peak-shifting constraints are used to ensure that the time interval between two devices passing through the conflict zone after applying speed compensation is not less than a preset safe time interval threshold. The following constraint model is used to represent the time-domain peak-shifting relationship under one of the candidate passage sequences; when the candidate passage sequence changes, the speed allocation module 40 adjusts the positions of the two predicted arrival time items accordingly, so that the difference between the predicted arrival time of the later passing device and the predicted arrival time of the earlier passing device is not less than [a certain value]. Its constraint model can be expressed as:

[0149] ;

[0150] In the formula, and These represent the current remaining route lengths between the two devices and their physical intersection coordinates; and The reference cruise speed for both devices.

[0151] In addition to temporal peak-shifting constraints, the speed allocation module 40 also sets physical execution boundary constraints. These constraints limit the speed compensation value, ensuring that the adjusted target speed does not exceed the acceleration or deceleration capabilities achievable by the device within the current remaining distance. The physical execution boundary constraints can be expressed as:

[0152] ;

[0153] ;

[0154] In the formula, Preparing the system for warehouse handling equipment The allocated speed compensation value; For warehouse handling equipment Current remaining distance and maximum allowable acceleration boundary The calculated upper limit of the currently available speed compensation; For warehouse handling equipment Current remaining distance and maximum allowable deceleration boundary The calculated lower limit of the currently available speed compensation; Preparing the system for warehouse handling equipment The allocated speed compensation value; For warehouse handling equipment Current remaining distance and maximum allowable acceleration boundary The calculated upper limit of the currently available speed compensation; For warehouse handling equipment Current remaining distance and maximum allowable deceleration boundary The calculated lower limit of the currently available speed compensation.

[0155] For example, based on the relationship of uniformly accelerated linear motion, the speed allocation module 40 can calculate the upper limit of the currently available speed compensation based on the remaining route length, the reference cruising speed, and the maximum allowable acceleration boundary; and calculate the lower limit of the currently available speed compensation based on the maximum allowable deceleration boundary. Meanwhile, to avoid the optimization results causing the equipment to reverse or an abnormal situation where the speed denominator is zero, the speed allocation module 40 applies a non-negative speed constraint to the adjusted target speed, i.e., satisfies... and .

[0156] S43, solve for the velocity compensation value.

[0157] The speed allocation module 40, within the feasible region jointly defined by the temporal peak-shifting constraint and the physical execution boundary constraint, performs a speed allocation function... A minimum search is performed to obtain a set of velocity compensation values ​​that minimize the total cost of kinetic energy adjustment. This optimal solution can be expressed as:

[0158] ( );

[0159] in, and As storage and handling equipment respectively and warehousing and handling equipment The final speed compensation value is used to correct the reference cruise speed of the corresponding device. For the optimization problem involving the quadratic objective function and nonlinear inequality constraints, those skilled in the art can solve it using the interior point method, sequential quadratic programming algorithm, or other conventional numerical optimization methods. These are well-known techniques in the field and will not be elaborated upon here.

[0160] S44, execute the downgrade isolation strategy.

[0161] When two devices are too close to the intersection coordinates, the reference speed is too high, or the physical execution boundary is too narrow, the speed allocation module 40 may not be able to obtain a speed compensation solution that meets the safety time interval requirement within the constrained feasible region. In this case, the speed allocation module 40 determines that the current working condition has entered a state of no feasible solution and stops the conventional speed optimization solution.

[0162] In the case of no feasible solution, the speed allocation module 40 executes a degradation isolation strategy. This strategy no longer determines the avoidance equipment solely based on mass scalars, but rather comprehensively compares warehouse handling equipment. and warehousing and handling equipment The mass scalar, the remaining path length to the physical collision avoidance zone boundary , Information such as the critical braking distance and whether the vehicle has entered the physical collision avoidance zone.

[0163] When the storage and handling equipment 500 with a smaller mass scalar has not yet entered the physical collision avoidance zone, and the remaining route length to the boundary of the physical collision avoidance zone is... When the distance is greater than or equal to the sum of the critical safe braking distance and the preset collision avoidance margin, the speed distribution module 40 identifies the device with the smaller mass as a candidate avoidance device and issues a physical stop command to it, reducing its target speed to zero; after the device comes to a complete stop, the device with the larger mass is allowed to cross the intersection area as originally planned. This indicates the remaining route length from warehouse handling equipment 500, which has been identified as a candidate collision avoidance device, to the boundary of the physical collision avoidance zone.

[0164] When a small-scale storage and handling equipment 500 has entered the physical collision avoidance zone, or its remaining route length to the boundary of the physical collision avoidance zone... When the speed is insufficient to complete safe braking, the speed distribution module 40 will no longer treat the device as a collision avoidance target. Instead, it will identify the device that has already entered the physical collision avoidance zone, or the device that is closer to the intersection coordinate and is difficult to stop outside the collision avoidance zone, as the priority passing device. The remaining warehouse handling equipment 500 involved in the conflict will receive physical stop command or emergency braking command.

[0165] If none of the devices involved in the conflict meet the single-vehicle avoidance conditions, the speed distribution module 40 issues an emergency braking command to all devices in the conflict set to prioritize reducing the collision risk and keep each device outside the physical collision avoidance zone or in the position with the least risk as much as possible.

[0166] In some embodiments, when the mass scalars of two devices are equal, the speed allocation module 40 further compares the unique factory hardware communication numbers of the two devices and arbitrates based on the safe braking critical distance, remaining route length, and whether the device has entered the physical collision avoidance zone. If both devices meet the safe stopping conditions, the device with the smaller hardware communication number is identified as the avoidance device; if the device with the smaller hardware communication number does not meet the safe stopping conditions, the other device that meets the safe stopping conditions is identified as the avoidance device. Through the above processing, even in boundary conditions where the optimization algorithm has no feasible solution, the system can still form a definite avoidance result, avoiding control deadlock between multiple devices due to uncertainty in right-of-way arbitration.

[0167] See attached document Figure 7 In step S50, the instruction issuing module 50 is deployed on the central scheduling server 100 and is used to convert the scheduling result obtained by the speed allocation module 40 into a control data frame that can be recognized and executed by the on-board programmable logic controller 300. This process may include the following steps.

[0168] S51, composite target cruise speed.

[0169] The instruction issuing module 50 extracts the information from step S40 concerning the warehouse handling equipment. The obtained velocity compensation value and the speed compensation value Compared with the reference cruise speed configured in step S10 By superimposing the values, we can obtain the target cruising speed that warehouse handling equipment i needs to achieve within the current scheduling cycle. :

[0170] ;

[0171] In the formula, For warehouse handling equipment The target cruise speed after system-wide adjustment; For warehouse handling equipment The initial assigned baseline cruise speed; For the system targeting warehouse handling equipment The calculated speed compensation value is the optimal solution.

[0172] Through the above processing, the relative speed adjustment obtained by the speed allocation module 40 in the optimization space is converted into an absolute speed setpoint that can be directly used by the underlying servo control system. This applies to warehouse handling equipment participating in the intersection simultaneously. The method of synthesizing its target cruising speed is similar to that of warehousing and handling equipment. same.

[0173] At target cruising speed After generation, the instruction issuing module 50 performs amplitude limiting verification on it. The verified target cruising speed The operating speed shall not exceed the maximum permissible speed of the warehousing and handling equipment (500), shall not be lower than the minimum permissible speed of the system, and shall comply with the speed limit requirements of the current route segment. If the speed allocation module 40 outputs a physical stop command, the command issuing module 50 shall set the target cruising speed. Set it to zero, and write the corresponding parking instruction type identifier in subsequent data frames.

[0174] S52 encapsulates composite data frames.

[0175] The instruction issuing module 50 constructs a composite data frame with a spatiotemporal safety envelope based on the target cruising speed, speed compensation value, and corresponding task information. This composite data frame is used to limit the execution target, execution time, and spatial effective range of the speed compensation instruction, preventing the on-board control terminal from executing invalid scheduling instructions in the event of communication delays, out-of-order transmission, or instruction expiration.

[0176] In the spatial dimension, the composite data frame is configured with effective start coordinates and failure end coordinates. When the warehousing and handling equipment 500 has not yet entered the effective spatial range, the on-board programmable logic controller 300 does not execute the corresponding speed compensation; the warehousing and handling equipment 500 departs from the failure end coordinates, or departs from the geometric boundary of the intersection's physical collision avoidance zone. Afterwards, the on-board programmable logic controller 300 stops executing the speed compensation command and waits for the central dispatch server 100 to issue a new speed compensation command or a cruise resumption command.

[0177] In terms of data structure, a composite data frame must include at least the target cruise speed. The fields include: speed compensation value, target device number, task number, path segment number, data frame sequence number, instruction type, effective start coordinates, failure end coordinates, and geometric boundaries of the intersection's physical collision avoidance zone. Valid timestamp Effective survival parameters And an integrity verification field.

[0178] The target device number is used by the on-board programmable logic controller 300 to confirm whether the data frame belongs to the vehicle's equipment; the task number and path segment number are used to confirm whether the data frame corresponds to the currently executing warehousing and handling task and the current path segment; the instruction type field is used to distinguish between speed adjustment instructions, physical stop instructions, cruise control resumption instructions, and emergency braking instructions; the data frame sequence number is used to identify old frames, out-of-order frames, or duplicate frames; the integrity check field is used to verify whether the data frame payload has experienced a transmission abnormality; and the valid timestamp is also included. and effective survival parameters Together they are used to determine whether a data frame is still within the executable time window.

[0179] Geometric boundaries of physical collision avoidance zones at intersections With the extracted physical cross coordinates Constructed around a central point. To facilitate rapid decision-making by the vehicle control unit, this geometric boundary can be defined as a set of circular domains in a two-dimensional coordinate system:

[0180] ;

[0181] In the formula, These are the physical intersection coordinates or the center coordinates of the physical collision avoidance zone. Let be any coordinate point to be determined in the two-dimensional road network; For the safety boundary radius. In some embodiments, The sum of half the physical diagonal length of the 500-ton vehicle body and the preset safety redundancy distance can be taken. The preset safety redundancy distance can be set according to the on-site positioning accuracy, vehicle body outline error and cargo extension amount, for example, 0.5 meters to 1 meter.

[0182] Valid timestamp Record the absolute physical time of the system when the central scheduling server 100 generates this data frame. Effective lifetime parameter. It can be written into the data frame header, or it can be uniformly distributed by the system configuration table. In an industrial wireless network environment, The calibration can be performed based on typical communication delays, scheduling cycles, and on-board controller response cycles, for example, between 200 and 500 milliseconds. The on-board programmable logic controller 300 then determines whether the data frame has expired and decides whether to execute the corresponding control command.

[0183] S53, execute node data distribution.

[0184] After the composite data frame is encapsulated, the instruction issuing module 50 executes the instruction issuance according to the preset communication route. Specifically, the central dispatch server 100 sends the composite data frame to the edge controller 200 responsible for the corresponding warehouse area via a wired industrial Ethernet.

[0185] After receiving the composite data frame, the edge controller 200 does not change the core control payload and transmits the composite data frame to the target warehousing and handling equipment 500 via a wireless LAN or 5G private network link. After receiving the composite data frame, the on-board programmable logic controller 300 in the target warehousing and handling equipment 500 unpacks, verifies, and extracts fields, and then passes the extracted data such as target cruising speed, effective spatial range, timestamp, and instruction type to the underlying execution module 60 for processing.

[0186] For the routing, link establishment, and underlying handshake of network communication data packets between hardware nodes, those skilled in the art can use conventional TCP / IP network communication technology for configuration and implementation, which is well-known in the field and will not be elaborated here.

[0187] See attached document Figure 8 In step S60, the on-board programmable logic controller 300 receives a composite data frame containing a spatiotemporal safety envelope and converts the scheduling instructions generated by the central scheduling server 100 into low-level motion control actions for the warehousing and handling equipment 500. Simultaneously, the on-board programmable logic controller 300 locally runs communication timeliness verification and autonomous collision avoidance control logic to constrain the equipment's operating state in case of communication anomalies or instruction failures. This process may include the following steps.

[0188] S61, velocity curve reconstruction and phase modulation.

[0189] After receiving the composite data frame, the vehicle-mounted programmable logic controller 300 first performs a data frame validity check. Specifically, the vehicle-mounted programmable logic controller 300 determines whether the data frame corresponds to the vehicle's equipment based on the target device number, and determines whether the data frame matches the current task, current path segment, and current control cycle based on the task number, path segment number, data frame sequence number, valid timestamp, and integrity check field.

[0190] When a data frame fails integrity verification, or is identified as an old frame, out-of-order frame, or duplicate frame, the on-board programmable logic controller 300 refuses to execute the data frame. Once the data frame passes verification, the on-board programmable logic controller 300 parses the composite data frame and extracts the target cruising speed. Fields such as speed compensation value, valid spatial range, valid timestamp, and instruction type.

[0191] To avoid the target cruising speed Electromagnetic shock or mechanical vibration caused by a step-like direct application to the servo driver 400 is reacted by the on-board programmable logic controller 300 according to the current actual operating speed. Maximum permissible acceleration boundary and jerk limits The speed planning curve is reconstructed to be smooth. In some embodiments, the speed planning curve may be an S-shaped acceleration / deceleration curve.

[0192] Jerk is used to characterize the rate of change of equipment acceleration. By limiting the jerk, the inertial sway of flexible loads during acceleration and deceleration can be reduced, and the transient impact on the chassis structure can be decreased. The onboard programmable logic controller 300 generates the connection to the current speed based on the S-shaped speed planning algorithm. cruise speed of the target The system continuously provides speed commands and periodically outputs these speed commands to the servo driver 400.

[0193] The aforementioned speed adjustment does not alter the node sequence path of the storage and handling equipment 500. Instead, it shifts the time phase of the equipment's arrival at the physical intersection coordinates by changing the time integral progress of the equipment's travel along the predetermined path, thereby achieving time-domain peak shifting in scenarios where multiple equipment intersect. For the discretization interpolation and smoothing planning calculations of the S-shaped acceleration / deceleration curves, those skilled in the art can implement them using conventional motion control algorithm libraries, which are well-known techniques in the field and will not be elaborated upon here.

[0194] S62, calculates the critical distance for safe braking.

[0195] As the warehousing and handling equipment 500 travels towards the intersection area, the on-board programmable logic controller 300 periodically calculates the safe braking distance required to complete braking under the current operating condition based on the real-time vehicle speed feedback from the on-board encoder. The on-board programmable logic controller 300, combined with the underlying firmware response delay parameters, establishes the following calculation relationship:

[0196] ;

[0197] In the formula, For warehouse handling equipment The critical safe braking distance at the current moment; For warehouse handling equipment Real-time actual running speed; The bus response delay time from the trigger braking signal to the actual establishment of braking torque by the servo driver 400 in the underlying system is usually measured and written during the system factory commissioning phase. It is the absolute value of the maximum permissible deceleration boundary in the basic kinematic parameters.

[0198] The above bus response delay time The parameters can be measured and written into the vehicle control parameter table during the equipment's factory commissioning phase. In some embodiments, to avoid braking slippage caused by changes in ground adhesion conditions, the vehicle programmable logic controller 300 can also derate the maximum permissible deceleration boundary based on the current dynamic friction coefficient of the ground. Thus, the vehicle programmable logic controller 300 can obtain the minimum safe braking depth at the current speed.

[0199] S63, communication timeliness verification and autonomous defense isolation.

[0200] To ensure that all control nodes are in a unified clock domain, a precise time synchronization mechanism based on the IEEE 1588 protocol can be configured between the vehicle-mounted programmable logic controller 300 and the central dispatch server 100. The vehicle-mounted programmable logic controller 300 executes the speed command in parallel with the timestamp verification logic.

[0201] Specifically, the on-board programmable logic controller 300 reads the current absolute time from the local hardware clock. and compare it with the valid timestamp in the composite data frame. Effective survival parameters The comparison is then performed. Simultaneously, the onboard programmable logic controller 300 calculates the real-time remaining distance from the geometric center of the storage and handling equipment 500 to the geometric boundary of the physical collision avoidance zone at the intersection, based on its own positioning results. .

[0202] When determining whether to trigger brake isolation, the on-board programmable logic controller 300 uses the following composite triggering conditions:

[0203] ;

[0204] and;

[0205] ;

[0206] When the above conditions are met simultaneously, it is determined that the storage and handling equipment 500 is in a state of communication command timeout and approaching the braking envelope limit.

[0207] In the formula, For vehicle local physical time; A valid timestamp generated for the instruction; This refers to the effective lifetime parameter of the instruction; This represents the remaining distance from the physical collision avoidance zone boundary. The critical distance for safe braking; This is a preset mechanical positioning collision avoidance margin. This collision avoidance margin... It is mainly used to compensate for measurement errors caused by sensor positioning drift and control dead zone. Its specific value is usually set to 0.1 meters to 0.3 meters in combination with the sensor accuracy level.

[0208] The above-mentioned composite triggering conditions apply to the approaching state of the warehouse handling equipment 500 before it has entered the physical collision avoidance zone.

[0209] When the on-board programmable logic controller 300 detects ,but If the data frame times out, it indicates that the storage and handling equipment 500 has not yet entered the distance range where immediate braking is required. At this time, the onboard programmable logic controller 300 refuses to execute new expired business instructions and maintains restricted operation or performs pre-deceleration control according to the most recent valid data frame, while continuously updating... and This continues until communication is restored or the aforementioned braking triggering conditions are met.

[0210] When the warehousing and handling equipment 500 has entered the geometric boundary of the intersection's physical collision avoidance zone. If an internal timestamp verification timeout occurs, the on-board programmable logic controller 300 will not execute a new speed compensation command. Instead, based on the travel direction in the most recent valid data frame, it will control the storage and handling equipment 500 to leave the physical collision avoidance zone, provided that the preset clearing speed limit is not exceeded. If the storage and handling equipment 500 fails to leave the physical collision avoidance zone within the preset clearing time, or if the on-board programmable logic controller 300 detects an obstacle ahead, a positioning anomaly, or a speed tracking anomaly, it will immediately trigger an emergency braking command. After leaving the physical collision avoidance zone, the storage and handling equipment 500 will enter a brake lock state and wait for the central dispatch server 100 to reissue the task recovery command.

[0211] When the warehousing and handling equipment 500 has not yet entered the physical collision avoidance zone, and simultaneously meets the following conditions... and At this time, the on-board programmable logic controller 300 triggers a hardware-level braking program, refusing to execute or blocking subsequent business instructions issued by the central dispatch server 100, and issues a zero-speed command to the servo driver 400. The servo driver 400 then operates according to the maximum deceleration boundary based on this zero-speed command. Output reverse braking torque to stop the storage and handling equipment 500 outside the physical collision avoidance zone boundary.

[0212] After the storage and handling equipment 500 enters the communication timeout braking state, the on-board programmable logic controller 300 remains in a local locked state and continuously listens for data frames resent by the central dispatch server 100 or the edge controller 200. When the on-board programmable logic controller 300 receives a preset number of data frames consecutively, and all data frames meet the conditions of valid timestamp, incrementing sequence number, passed integrity verification, and matching target device number, the communication timeout lock state is released. After the lock is released, the storage and handling equipment 500 does not directly resume its original operating speed, but waits for the central dispatch server 100 to resend the path recovery command, cruise recovery command, or manual reset command before continuing to execute the task.

[0213] S64, Space Failure Detection and Cruise Recovery.

[0214] During the execution of speed compensation instructions, the on-board programmable logic controller 300 continuously determines whether the current geometric center of the storage and handling equipment 500 is still within the valid spatial range defined by the data frame.

[0215] When the warehousing and handling equipment 500 departs from the failure endpoint coordinates in the data frame, or departs from the geometric boundary of the intersection's physical collision avoidance zone... Subsequently, the underlying execution module 60 determines that the current speed compensation command has failed. If the central dispatch server 100 does not issue a new speed compensation command, physical stop command, or emergency braking command, and there are no other conflicting data frames still valid on the current path segment, then the underlying execution module 60 executes the command according to the preset acceleration boundary or jerk limit. Generate a recovery cruise speed curve to smoothly restore the target speed of the warehouse handling equipment 500 to the baseline cruise speed. .

[0216] Through the above processing, the vehicle-mounted programmable logic controller 300 can perform speed compensation when the data frame is valid, and perform local braking, restricted departure, or resume cruise control when the data frame fails or communication is abnormal. In this way, the basic collision avoidance capability of the warehouse handling equipment 500 can be maintained in the event of delay, interruption, or out-of-order transmission in the industrial wireless network.

[0217] To further illustrate the effectiveness of the intelligent control and scheduling system in this invention, the following explanation combines specific intersection numerical calculation scenarios and comparative experimental data on continuous multi-vehicle operation.

[0218] See attached document Figure 9 , Figure 9 This is a schematic diagram of the phase trajectory and velocity curve of the intersection speed of two devices according to an embodiment of the present invention. In this application embodiment, two warehouse handling devices 500 (denoted as device A and device B, respectively) are arranged to travel along their respective node sequence paths, and it is expected that they will meet at the physical intersection coordinates ahead. A path intersection occurs at this point. During the current scheduling cycle, device A is at full load, while device B is at idle.

[0219] During the parameter initialization and observation phase, the configuration parameters issued by the central dispatch server 100 set the baseline cruising speed of device A. The reference cruising speed of device B is 1.5 m / s. The speed is 1.2 m / s; this is the system-set safety time interval threshold for intersections. The time is 3.0s. At this point, the remaining path length of device A from the physical intersection coordinates is... The remaining route length from device B to this physical intersection coordinate is 15.0m. It is 10.0m.

[0220] During the feature mapping and collision detection process, the feature mapping module 20 at the bottom layer of the on-board programmable logic controller 300 extracts the operating current data of each servo driver 400 and performs calculations to deduce the mass scalar of device A. The mass scale of device B is 8.0. Version 2.0. The collision detection module 30 within the central dispatch server 100 calculates the predicted arrival time of device A based on a uniform speed travel model. The predicted arrival time of device B is 10.0s. The difference in predicted arrival times is approximately 8.33 seconds. The time interval is approximately 1.67 seconds. Since 1.67 seconds is less than the preset safe time interval threshold of 3.0 seconds, the system determines that there is a risk of physical collision between the two devices at the intersection and triggers the speed allocation module 40 to intervene.

[0221] Speed ​​distribution module 40 establishes a system kinetic energy adjustment cost based on the mass scalar of each device. Minimize the optimization function:

[0222] ;

[0223] In the formula, and The system prepares speed compensation values ​​for equipment A and equipment B respectively. During the solution process, a time-domain peak-shifting constraint must be met to ensure that the actual peak-shifting time difference between the two devices is no less than 3.0 seconds. If the traditional first-come-first-served rule is used, the device that is farther away or predicted to arrive later is usually forced to decelerate to avoid the obstacle. In this operating condition, if the heavily loaded equipment A is forced to decelerate, delaying its arrival time to after 11.33 seconds, the required speed compensation value for equipment A is calculated. At least -0.18 m / s; if device B maintains its original speed... The kinetic energy adjustment cost is 0 at this point. .

[0224] When using the optimization solution of this invention, the speed allocation module 40 searches for the combination with the minimum overall cost within the feasible region. Through internal iteration, it was found that assigning unloaded device B to accelerate and pass through the intersection as quickly as possible, while maintaining the base speed of heavily loaded device A, results in a lower overall cost. Specifically, the system allocates a speed compensation value to device B. The target cruise speed is set at 0.3 m / s, bringing it to 1.5 m / s. At this target speed, device B's time to cross the physical intersection coordinate is advanced to 6.67 s. Meanwhile, heavily loaded device A travels at its original baseline cruise speed, with its predicted arrival time remaining unchanged at 10.0 s. The actual time difference between the two devices reaching the physical intersection coordinate expands to 3.33 s, meeting the requirement of exceeding the safe time interval threshold of 3.0 s. At this point, the corresponding speed compensation value for device A... The cost of adjusting the system's kinetic energy is 0. .

[0225] After the optimal solution is output, the instruction issuing module 50 encapsulates and issues the speed compensation result. Compared with the traditional distance-based strategy that forces heavy-load equipment to brake and decelerate, the strategy of this invention guides light-load equipment to accelerate slightly, thus preventing heavy-load equipment from decelerating. This not only successfully resolves the spatial conflict but also avoids the peak power loss and mechanical shock to the transmission mechanism caused by the high-current braking of heavy-load equipment and subsequent secondary acceleration.

[0226] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent control and scheduling system for supply chain warehousing equipment, characterized in that, include: The path planning module is used to generate node sequence paths and baseline cruising speeds for warehouse handling equipment; The feature mapping module is used to extract operating current data during the operation of the warehousing and handling equipment and calculate the mass scalar under the current load condition. The conflict detection module is used to calculate the predicted arrival time difference to the same intersection area based on the real-time location coordinates of multiple storage and handling equipment and the node sequence path, and generate conflict data when the predicted arrival time difference is less than a preset safety time interval threshold. The speed allocation module is used to construct a cost function based on the conflict data and the mass scalar of each warehousing and handling equipment participating in the intersection, and solve for the speed compensation value under physical acceleration and deceleration boundary constraints. The instruction issuing module is used to encapsulate the speed compensation value into a data frame with a valid spatial limit and a communication timestamp and then issue it. The underlying execution module is used to parse the data frame, reconstruct the speed planning curve according to the speed compensation value to change the time phase of arrival at the intersection area, and perform timeliness verification based on the communication timestamp, and trigger braking isolation control when the timeliness verification times out.

2. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 1, characterized in that, The process by which the feature mapping module calculates the mass scalar under the current load condition includes: When the warehousing and handling equipment is in steady-state cruise mode, the q-axis current component output by the servo driver that provides the operating current data is extracted, and the dynamic frictional resistance torque is calculated. When the warehousing and handling equipment performs a start-up operation according to a preset benchmark start-up acceleration, the filtered q-axis current component of the acceleration phase is extracted. Combining the dynamic frictional resistance torque and the reference starting acceleration, the equivalent moment of inertia referred to the motor shaft end is calculated; The equivalent moment of inertia is mapped to the dimensionless mass scalar using a linear normalization function.

3. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 1, characterized in that, The process by which the conflict detection module generates conflict data includes: Extract the overlapping nodes between the node sequence paths of different warehousing and handling equipment as physical intersection coordinates; Assuming the warehousing and handling equipment approaches at the reference cruising speed, calculate the predicted absolute time for each warehousing and handling equipment participating in the intersection to reach the physical intersection coordinate, and obtain the predicted arrival time difference between different warehousing and handling equipment; When the predicted arrival time difference is less than the preset safety time interval threshold, the equipment number of each warehousing and handling equipment participating in the intersection, the current remaining route length of each warehousing and handling equipment to the physical intersection coordinate, and the quality scalar are extracted, encapsulated as the conflict data, and output to the speed allocation module.

4. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 3, characterized in that, The process of constructing and solving the cost function by the velocity allocation module includes: Using the speed compensation values ​​of each warehousing and handling equipment participating in the intersection as control decision variables, and the corresponding mass scalar as cost weights, a quadratic objective function that minimizes the cost of kinetic energy adjustment is constructed. A time-domain peak-shifting constraint is constructed based on the current remaining route length and the preset safety time interval threshold, and a physical execution boundary constraint is constructed based on the preset maximum allowable acceleration boundary and maximum allowable deceleration boundary of each warehousing and handling equipment. Within the feasible region jointly defined by the temporal peak-shifting constraint and the physical execution boundary constraint, a minimum search is performed on the quadratic objective function to obtain a set of optimal solutions that minimize the total cost of kinetic energy adjustment, which are then used as the velocity compensation values.

5. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 4, characterized in that, The speed allocation module is also used for: When there is no feasible solution for the speed compensation value that satisfies the temporal peak-shifting constraint and the physical execution boundary constraint within the feasible domain, stop the minimum value search and execute the degradation isolation strategy. The mass scalar of each participating storage and handling equipment, the remaining route length to the preset physical collision avoidance zone boundary, the real-time calculated safety braking critical distance, and the status information of whether or not the equipment has entered the physical collision avoidance zone are compared. Warehouse handling equipment with a relatively small mass scalar that has not yet entered the physical collision avoidance zone, and whose remaining route length to the boundary of the physical collision avoidance zone is greater than or equal to the sum of the safety braking critical distance and the preset collision avoidance margin, is identified as a candidate avoidance equipment, and a physical stop command is issued to it.

6. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 1, characterized in that, The process by which the instruction issuing module encapsulates the speed compensation value into a data frame with valid spatial limits and a communication timestamp includes: The speed compensation value is superimposed on the reference cruise speed to generate the target cruise speed; Using the physical intersection coordinates of the intersection area as the center, and combining the safety boundary radius, a set of two-dimensional circular domains is constructed, which is written into the effective spatial limit as the geometric boundary of the physical collision avoidance zone of the intersection. The system's absolute physical time at the time the data frame was generated is used as the communication timestamp, and a valid lifetime parameter is configured. The data frame is generated by combining the target cruise speed, the effective space limit, the communication timestamp, the effective lifetime parameter, and the instruction type field.

7. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 6, characterized in that, The process by which the underlying execution module reconstructs the speed planning curve based on the speed compensation value includes: Once the data frame passes the integrity check, the target cruising speed is parsed and extracted. Based on the current actual operating speed of the warehousing and handling equipment, the preset maximum allowable acceleration boundary, and the acceleration limit, an S-shaped acceleration / deceleration algorithm is used to generate a continuous speed command, so that the current actual operating speed of the warehousing and handling equipment can smoothly transition to the target cruising speed.

8. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 7, characterized in that, Before performing the timeliness check, the underlying execution module is also used for: Based on the current actual operating speed and the bus response delay time from the triggering of the braking signal to the establishment of the braking torque by the servo driver of the motor in the underlying system, calculate the safe braking critical distance at the current moment. Based on local real-time positioning, calculate the real-time remaining distance from the geometric center of the warehousing and handling equipment to the geometric boundary of the physical collision avoidance zone at the intersection.

9. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 8, characterized in that, The underlying execution module performs the timeliness check based on the communication timestamp, and the process of triggering braking isolation control when the timeliness check times out includes: Obtain the vehicle's local physical time and determine whether the difference between the vehicle's local physical time and the communication timestamp is greater than the effective lifetime parameter; If the difference is greater than the effective survival period parameter, and the real-time remaining distance is less than or equal to the sum of the safe braking critical distance and the preset anti-collision margin, and the warehousing and handling equipment has not yet entered the geometric boundary of the intersection physical collision avoidance zone, then the braking trigger condition is determined to be met. A zero-speed command is issued to the servo driver, causing the storage and handling equipment to stop outside the geometric boundary of the physical collision avoidance zone at the intersection.

10. The intelligent control and scheduling system for supply chain warehousing equipment according to claim 9, characterized in that, The underlying execution module is also used for: If the difference between the vehicle's local physical time and the communication timestamp is greater than the effective lifetime parameter, but the warehousing and handling equipment has already entered the geometric boundary of the intersection's physical collision avoidance zone, the warehousing and handling equipment is controlled to leave based on the direction of travel in the most recent valid data frame received. If the warehousing and handling equipment fails to leave the geometric boundary of the physical collision avoidance zone of the intersection within the preset clearing time, or detects an obstacle ahead or a positioning abnormality, an emergency braking command is triggered.

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