Control method and control device of cross-belt sorting equipment and cross-belt sorting equipment

Abstract

The application provides a control method and device of a cross-belt sorting equipment and the cross-belt sorting equipment, relates to the technical field of logistics equipment, and the control method of the cross-belt sorting equipment comprises the following steps: obtaining identification information, weight information and shape information of a package to be sorted; determining a target sorting position corresponding to the identification information, and calculating an optimal dropping time and a running speed of the package on the cross-belt according to the weight information and the shape information; controlling a sorting and transporting device to transport the package at the running speed, and controlling a dropping device to drop the package at the optimal dropping time at the target sorting position. The application dynamically obtains the weight and shape information of the package, combines the calculation of the inertia coefficient and the sorting priority, optimizes the decision process of the running speed and the dropping time, effectively solves the problems of collision deviation, dropping deviation and insufficient system cooperation caused by neglecting the physical characteristics of the package in the prior art, and can improve the sorting accuracy, reduce the risk of damage of goods and improve the system running efficiency.

Description

Technical Field

[0001] This application relates to the field of logistics equipment technology, and in particular to a control method, control device and cross-belt sorting equipment. Background Technology

[0002] Cross-belt sorting equipment, as a core piece of equipment in modern logistics warehousing systems, achieves efficient and automated sorting of items such as parcels and mail through sorting trolleys that run continuously on a circular track.

[0003] However, existing control methods have revealed deep-seated technical flaws in practical applications. Traditional strategies generally employ preset fixed operating speeds or simplified path planning logic, completely ignoring the complex impact of the package's physical characteristics on the dynamic sorting process. Summary of the Invention

[0004] The main objective of this invention is to provide a control method for a cross-belt sorting device, which aims to improve sorting accuracy and reduce the risk of cargo damage.

[0005] To achieve the above objectives, the present invention provides a control method for a cross-belt sorting device, the cross-belt sorting device including a sorting and transport device and a delivery device, and the control method for the cross-belt sorting device includes: Obtain the identification information, weight information, and shape information of the packages to be sorted; Determine the target sorting location corresponding to the identification information, and calculate the optimal delivery time and running speed of the package on the cross belt based on the weight and shape information; The sorting and transporting device is controlled to transport the package at the operating speed, and the delivery device is controlled to deliver the package at the optimal delivery time at the target sorting location.

[0006] Optionally, determining the target sorting location corresponding to the identification information, and calculating the optimal delivery time and running speed of the package on the cross belt based on the weight and shape information, includes: Based on the weight and shape information, calculate the inertia coefficient and sorting priority of the package; The operating speed is calculated based on the inertia coefficient and sorting priority using a dynamic speed balancing algorithm. Query the target sorting location in the preset sorting database that corresponds to the identification information; Calculate the optimal delivery time corresponding to the running speed and the target sorting location.

[0007] Optionally, calculating the inertia coefficient and sorting priority of the package based on the weight and shape information includes: Determine the mass factor of the package corresponding to the weight information; Based on the shape information, the volume factor and stability index of the package are calculated. The inertia coefficient is determined by the mass factor, the volume factor, and the stability index according to a preset calculation formula; Obtain the sorting urgency corresponding to the identification information; The sorting priority is determined by combining the inertia coefficient and the sorting urgency according to a weighted ratio.

[0008] Optionally, the step of calculating the operating speed based on the inertia coefficient and sorting priority using a dynamic speed balancing algorithm includes: Obtain the operational status data of multiple packages in the current sorting system; Based on the operational status data and the sorting priority, a weighted average method is used to allocate a temporary operating speed for each package; The temporary operating speed is adjusted by the inertia coefficient to determine the operating speed with the least overall sorting impact; The operating speed is defined as the operating speed that minimizes the overall sorting impact.

[0009] Optionally, adjusting the temporary operating speed using the inertia coefficient to determine the operating speed with the least overall sorting impact includes: Obtain the current operating data of each package on the sorting and transport device, including the current speed, position deviation, and sorting impact force index; The optimal speed correction value corresponding to the current running data for each package is calculated using the minimum impact optimization algorithm. The optimal speed correction value and the inertia coefficient are then substituted into the current running data to calculate and determine the corresponding speed adjustment amount. Based on the speed adjustment amount, the temporary operating speed is adjusted to determine the operating speed with the least overall sorting impact.

[0010] Optionally, controlling the sorting and transporting device to transport the package at the operating speed, and controlling the delivery device to deliver the package at the optimal delivery time at the target sorting location, includes: Adjust the initial transport parameters of the sorting and transporting device according to the operating speed; The sorting and transportation device is controlled to operate according to the initial transportation parameters, and the current package location and current operating speed are obtained during the operation. Calculate the distance to the target sorting location based on the current package location, and determine the remaining transportation time corresponding to the current operating speed; The optimal delivery time is determined based on the distance to the target sorting location and the remaining transportation time, and the delivery device is controlled to deliver the package at the optimal delivery time.

[0011] Optionally, the cross-belt sorting device further includes multiple position sensors; the multiple position sensors are distributed at intervals at multiple node positions along the sorting transport path; The step of calculating the distance to the target sorting location based on the current package location and determining the remaining transportation time corresponding to the current operating speed includes: Obtain the current location coordinates of each package collected by the location sensor; The dynamic path distance for each package is determined based on the current location coordinates and the target sorting location coordinates. Calculate the remaining transportation time based on the current operating speed and the dynamic path distance.

[0012] Optionally, the cross-belt sorting equipment further includes a camera device and a weighing device, which are respectively located at the entrance of the sorting and transport device; The acquisition of the identification information, weight information, and shape information of the packages to be sorted includes: The weight information of each package is obtained through the weighing device; The camera device is used to acquire image information of each package; Analyze the package barcode information and shape contour data in the image information; Determine the shape information corresponding to the shape contour data; The identification information is generated by associating the package barcode information, the weight information, and the shape information.

[0013] Furthermore, to achieve the above objectives, the present invention also provides a control device, the control device comprising: a memory, a processor, and a control program for a cross-belt sorting device stored in the memory and executable on the processor, the control program for the cross-belt sorting device being configured to implement the control method for the cross-belt sorting device as described above.

[0014] In addition, to achieve the above objectives, the present invention also provides a cross-belt sorting device, including the control device described above.

[0015] The control method for a cross-belt sorting device according to this invention is applied to a cross-belt sorting device, which includes a sorting and transport device and a delivery device. The control method acquires the identification information, weight information, and shape information of the packages to be sorted, determines the target sorting position corresponding to the identification information, calculates the optimal delivery time and operating speed of the package on the cross belt based on the weight and shape information, and finally controls the sorting and transport device to transport the package at the operating speed, and controls the delivery device to deliver the package at the optimal delivery time at the target sorting position. Thus, by dynamically acquiring the weight and shape information of the package, and combining it with the calculation of the inertia coefficient and sorting priority, the decision-making process for operating speed and delivery time is optimized. This effectively solves the problems of collision offset, delivery deviation, and insufficient system coordination caused by neglecting the physical characteristics of the package in the prior art, thereby improving sorting accuracy, reducing the risk of cargo damage, and improving system operating efficiency. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart of a control method for a cross-belt sorting device according to an embodiment of the present invention; Figure 2 This is a schematic flowchart of a control method for a cross-belt sorting device according to another embodiment of the present invention; Figure 3 This is a schematic flowchart of a control method for a cross-belt sorting device according to another embodiment of the present invention; Figure 4 This is a schematic flowchart of a control method for a cross-belt sorting device according to another embodiment of the present invention; Figure 5 This is a schematic flowchart of a control method for a cross-belt sorting device according to another embodiment of the present invention; Figure 6 This is a schematic flowchart of a control method for a cross-belt sorting device according to another embodiment of the present invention; Figure 7 This is a schematic flowchart of a control method for a cross-belt sorting device according to another embodiment of the present invention; Figure 8This is a schematic diagram of the control method for a cross-belt sorting device according to another embodiment of the present invention.

[0019] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0020] The technical solutions of 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, not all embodiments. Well-known modules, units, and their connections, links, communications, or operations are not shown or described in detail. Furthermore, the described features, architectures, or functions can be combined in any way in one or more embodiments. Those skilled in the art should understand that the various embodiments described below are only for illustrative purposes and not for limiting the scope of protection of the present invention. It is also readily understood that the modules, units, or processing methods in the various embodiments described herein and shown in the accompanying drawings can be combined and designed in various different configurations. 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.

[0021] The definitions of various terms or methods used in the following embodiments are, except where logically impossible, generally defined as broad concepts that can be implemented under the premise of the content disclosed in the embodiments. Under this understanding, all specific subordinate limitations of the terms or methods should be considered as part of the invention and should not be narrowly interpreted or biased simply because the specification does not disclose such a specific limitation. Similarly, provided that it is logically feasible, the order of the steps in the method is flexible and varied, and all specific subordinate limitations in the broad concepts of various terms or methods fall within the scope of protection of this invention.

[0022] Cross-belt sorting equipment, as a core piece of equipment in modern logistics warehousing systems, achieves efficient and automated sorting of parcels, mail, and other items through sorting trolleys running continuously on a circular track. Its basic workflow is as follows: a barcode scanner obtains the parcel's identification information to determine the target compartment, and then the sorting trolley transports the parcel to the corresponding compartment for placement. However, existing control methods have revealed deep-seated technical flaws in practical applications. Traditional strategies generally employ preset fixed operating speeds or simplified path planning logic, completely ignoring the complex impact of the parcel's physical characteristics on the dynamic sorting process. Specifically, differences in parcel weight distribution, volume, and shape significantly alter their inertial behavior during transportation. For example, heavy goods or irregularly shaped fragile items are highly susceptible to collision, deviation, or even derailment due to centrifugal force or inertial displacement at high speeds, causing physical damage. Furthermore, when the system handles concurrent tasks with parcels of various sizes, the lack of a global coordination mechanism in the transportation process leads to frequent speed interference between trolleys, forcing some parcels to wait or slow down, severely restricting the overall throughput capacity of the system. Furthermore, in the decision-making process for delivery timing, existing methods rely solely on a basic distance-velocity linear model for calculations, failing to effectively model the dynamic displacement deviation caused by package inertia. This results in a significant deviation between the actual delivery location and the target compartment, leading to a persistently high mis-sorting rate. These technical bottlenecks not only reduce the accuracy and safety of sorting operations but also increase equipment maintenance costs and the risk of cargo damage.

[0023] The main solution of this application embodiment is: by obtaining the identification information, weight information and shape information of the package to be sorted, then determining the target sorting position corresponding to the identification information, and calculating the best delivery time and running speed of the package on the cross belt based on the weight information and shape information, finally controlling the sorting and transportation device to transport the package according to the running speed, and controlling the delivery device to deliver the package at the best delivery time at the target sorting position.

[0024] In this embodiment, for ease of description, the following description will focus on the control device as the executing entity.

[0025] This application provides a solution that dynamically acquires the weight and shape information of packages, combines the calculation of inertia coefficient and sorting priority, and optimizes the decision-making process for running speed and delivery timing. This effectively solves the problems of collision offset, delivery deviation and insufficient system coordination caused by ignoring the physical characteristics of packages in the prior art, and can improve sorting accuracy, reduce the risk of cargo damage and improve system operating efficiency.

[0026] Therefore, this invention proposes a control method for a cross-belt sorting device; it is understood that the cross-belt sorting device is equipped with a control device for storing and executing the following method. The control device can be implemented using a main controller, such as an MCU (Micro Controller Unit), a DSP (Digital Signal Processor), an FPGA (Field Programmable Gate Array), or a SOC (System-on-Chip).

[0027] In traditional cross-belt sorting equipment control methods, insufficient sorting accuracy and the risk of package damage persist due to the lack of dynamic consideration of the physical characteristics of the packages to be sorted. Specifically, the control strategy relies solely on preset speeds or simple path planning for transportation, failing to compensate for inertial effects based on weight information or adjust stability control based on shape information. This leads to displacement deviations during the delivery phase, resulting in missorting. Furthermore, the system lacks collaborative optimization of the operating states of multiple packages, making speed interference prone to occur when packages are transported independently, thus reducing the overall throughput efficiency of the system.

[0028] For example, when handling mixed parcel flows containing electronics and books in a logistics center, the electronic products, due to their irregular shape and fragility, often break upon impact when the sorting carts, not adjusting their speed according to their physical characteristics, collide with the parcels during high-speed operation on the circular track. Books, due to their weight, fail to land accurately in their designated compartments due to inertial displacement compensation, and may even be thrown off the track. Furthermore, when multiple parcels enter the sorting area densely, the independent speed settings of each parcel cause mutual interference, forcing some sorting carts to slow down and wait, resulting in discontinuous transportation and hindering the sorting task.

[0029] If the above problems are not solved, sorting accuracy will remain insufficient, the risk of package damage will increase, especially for heavy or irregularly shaped items; the overall efficiency of the system will not be improved, speed interference will lead to a decrease in throughput, and operation may be interrupted during peak package traffic periods, equipment reliability will be reduced, and the continuous and stable operation of the logistics system will be affected.

[0030] Reference Figure 1 In one embodiment of the present invention, the cross-belt sorting equipment includes a sorting and transport device and a delivery device, and the control method of the cross-belt sorting equipment includes steps S100-S300, wherein: S100: Obtain the identification information, weight information, and shape information of the packages to be sorted; S200: Determine the target sorting position corresponding to the identification information, and calculate the optimal delivery time and running speed of the package on the cross belt based on the weight information and shape information; S300: Control the sorting and transporting device to transport the package at the operating speed, and control the delivery device to deliver the package at the optimal delivery time at the target sorting location.

[0031] The identification information refers to the information that can uniquely identify each package to be sorted, such as barcodes, QR codes, or RFID tags. This identification information contains detailed information about the package and relevant data such as its target location to be sorted. The weight information is the accurate weight of the package obtained by weighing equipment. This is crucial for calculating the package's running speed on the cross belt and the timing of its placement, because packages of different weights will move differently under the same power. The shape information is the size, shape, and other characteristics of the package obtained through image recognition or other shape detection methods. Packages with irregular shapes require special consideration in terms of their running speed and placement method during the sorting process to avoid problems such as collisions, jams, or inaccurate placement.

[0032] The target sorting location is the designated compartment where the package should be delivered. This location is determined by parsing the identification information and precisely matched with the logistics delivery route. The optimal delivery time is dynamically calculated based on the package's current speed, its relative position to the target compartment, and the package's weight and shape characteristics, ensuring a smooth and accurate delivery upon arrival at the target location. The operating speed is adaptively adjusted according to the package's characteristics and path planning to avoid deviations caused by inertia or external interference. The optimal delivery time refers to the precise moment when the delivery device activates when the package arrives at the target sorting location. Its coordinated control with the operating speed effectively reduces the centrifugal force and vibration effects of packages at high speeds. Especially for fragile or irregular items, the real-time dynamic adjustment of the cart's acceleration and deceleration curve ensures that the package enters the target compartment area at the optimal time and with the optimal posture.

[0033] In this embodiment, obtaining the identification information of the packages to be sorted refers to the process of determining the unique identification code of the package. This can be achieved using barcode scanning or RFID technology, such as capturing barcode data through a fixed scanning device at the entrance, or manually entering it through a handheld terminal. Its main purpose is to quickly locate the sorting destination. Obtaining weight information refers to the process of measuring the mass of the package. This can be achieved using a weighing platform or pressure sensor. For example, a weighing module integrated at the entrance of the sorting and transport device can acquire data in real time, or historical records can be queried through a preset database. Its main purpose is to assess the inertial effect of the package. Obtaining shape information refers to the process of acquiring the size and shape characteristics of the package. This can be achieved using a 3D vision system or a laser profilometer. For example, the shape contour can be reconstructed through multi-angle scanning, or geometric parameters can be extracted based on structured light technology. Its main purpose is to characterize the stability of the package. Calculating the optimal placement time and running speed of the package on the cross belt based on the weight and shape information refers to the process of dynamically optimizing sorting parameters. This can be achieved using empirical formulas or lookup tables. For example, a speed threshold can be set based on weight and volume, or running parameters can be matched using a preset classification table. Its main purpose is to compensate for motion deviations caused by differences in physical characteristics. Controlling the sorting and transporting device to transport packages according to its operating speed refers to the process of adjusting the conveyor belt speed. This can be achieved using a variable frequency drive or servo motor control, such as changing the transport speed by adjusting the motor frequency, or setting a fixed rotation speed based on an open-loop control system. The main purpose is to match the calculated operating parameters. Controlling the delivery device to deliver packages at the optimal delivery time at the target sorting position refers to triggering the delivery mechanism's action. This can be achieved using timing control or encoder feedback mechanisms, such as initiating delivery at a precise moment based on the system clock, or synchronously triggering the mechanism through a position encoding signal. The main purpose is to ensure the synchronization between the delivery action and the package position. Therefore, this application, by deeply integrating the physical characteristics of packages and dynamic operating parameters, solves the problems of insufficient sorting accuracy, high risk of package damage, and low overall system efficiency in traditional cross-belt sorting equipment caused by neglecting weight and shape factors.

[0034] In the control method of cross-belt sorting equipment, the identification information, weight information, and shape information of the packages to be sorted are first acquired. The identification information is used to quickly locate the sorting target, while the weight and shape information serve as physical characteristic inputs, providing basic data support for subsequent dynamic calculations. Specifically, the target sorting position corresponding to the identification information is determined, and the optimal delivery time and running speed of the package on the cross-belt are calculated based on the weight and shape information. This calculation process dynamically compensates for motion deviations caused by weight differences and trajectory offsets caused by irregular shapes by integrating the inertial effect reflected by the weight information and the stability characteristics represented by the shape information, thereby accurately predicting the delivery window and optimizing speed allocation. Thus, the sorting and transporting device transports packages according to the calculated running speed, and at the target sorting position, the delivery device performs the delivery action at the optimal delivery time, ensuring the smoothness of the transport process and the synchronization of the delivery action. This avoids the collision risk caused by sudden speed changes in heavy or fragile goods and reduces speed interference when multiple packages are running within the system.

[0035] In one preferred embodiment, for example, when handling a regular rectangular package weighing 1.5 kg and with dimensions of 250 mm × 180 mm × 120 mm, the control device calculates a running speed of 1.0 m / s based on the weight and shape information, with the optimal delivery time being 0.3 seconds before the package reaches the target sorting position. In this embodiment, the running speed setting fully considers the physical characteristics of the package, ensuring a stable transportation process and precise matching of the delivery action with the target sorting position, effectively avoiding displacement deviations caused by inertial interference.

[0036] By employing the above methods, the physical characteristics of packages are dynamically incorporated into the control parameters, thereby improving sorting accuracy, significantly reducing the risk of package damage, and optimizing the overall throughput efficiency of the control device. This effectively overcomes the problems of delivery deviations and package damage caused by neglecting weight and shape factors in traditional methods, achieving precise control of the sorting process and a synergistic improvement in system efficiency.

[0037] The control method for the cross-belt sorting equipment in this embodiment is applied to the cross-belt sorting equipment, which includes a sorting and transport device and a delivery device. The control method acquires the identification information, weight information, and shape information of the packages to be sorted, determines the target sorting position corresponding to the identification information, calculates the optimal delivery time and running speed of the package on the cross belt based on the weight and shape information, and finally controls the sorting and transport device to transport the package at the running speed, and controls the delivery device to deliver the package at the optimal delivery time at the target sorting position. Thus, by dynamically acquiring the weight and shape information of the packages, and combining the calculation of the inertia coefficient and sorting priority, the decision-making process for running speed and delivery time is optimized. This effectively solves the problems of collision offset, delivery deviation, and insufficient system coordination caused by neglecting the physical characteristics of the packages in the prior art, thereby improving sorting accuracy, reducing the risk of cargo damage, and improving system operating efficiency.

[0038] Optionally, refer to Figure 2 Another embodiment of the present invention provides a control method for a cross-belt sorting device, based on the above. Figure 1 The illustrated embodiment determines the target sorting location corresponding to the identification information and calculates the optimal delivery time and running speed of the package on the cross belt based on the weight and shape information, including steps S210-S240, wherein: S210. Calculate the inertia coefficient and sorting priority of the package based on the weight and shape information. S220. Based on the inertia coefficient and sorting priority, the operating speed is calculated using a dynamic speed balance algorithm; S230. Query the target sorting location in the preset sorting database that corresponds to the identification information; S240. Calculate the optimal delivery time corresponding to the running speed and the target sorting position.

[0039] Among them, the inertia coefficient refers to a quantitative parameter characterizing the package's resistance to velocity changes during movement. It can be implemented using analytical calculations based on physical models or neural network prediction models, aiming to transform the package's mass distribution and geometric shape into quantifiable dynamic behavior indicators. Sorting priority can be understood as a level parameter reflecting the urgency of package sorting tasks. It can be implemented using a weighted scoring mechanism based on business rules or a real-time scheduling strategy, aiming to allocate differentiated system resources to packages of different importance. The dynamic velocity balancing algorithm is an optimization method that can dynamically adjust operating parameters according to the real-time state of the system. It can be implemented using genetic algorithms or particle swarm optimization strategies, aiming to coordinate the operating states of multiple packages to minimize the overall system impact. The preset sorting database refers to a data set that stores the mapping relationship between package identifiers and target sorting locations. It can be implemented using distributed databases or memory caching technology, aiming to provide low-latency, high-reliability location query services. The optimal delivery time can be understood as the time point when a package arrives at the target sorting location for precise delivery. It can be implemented using a prediction model based on kinematic equations or a closed-loop feedback control mechanism, aiming to compensate for displacement deviations caused by package inertia.

[0040] In this embodiment, the solution first calculates the inertia coefficient and sorting priority of the package based on its weight and shape information, transforming the physical properties of the package into quantifiable dynamic parameters. Then, based on these parameters, a dynamic speed balancing algorithm calculates the operating speed. This algorithm integrates the real-time operating status of all packages and adjusts the speed distribution using the inertia coefficient to minimize overall impact. It also queries a preset sorting database to obtain the target sorting location, ensuring the reliability of the location data. Finally, combining the dynamically optimized operating speed and the precise target location, the optimal delivery time is calculated, dynamically compensating for displacement deviations caused by inertia. These steps are executed sequentially and are interconnected, forming a closed-loop optimization system. This ensures that the operating speed setting considers not only the characteristics of individual packages but also the overall system state, effectively avoiding collisions of heavy or fragile items, improving system throughput efficiency, and enhancing delivery accuracy.

[0041] In one implementation, in a cross-belt sorting device, when a package enters the sorting system, the control device acquires its weight and shape information through a weighing device and a camera device. The processing unit uses an embedded system based on a microcontroller such as an ARM Cortex-M7 to calculate the inertia coefficient based on the acquired weight and shape information. This inertia coefficient comprehensively considers the density distribution and contour characteristics of the package. The processing unit determines the sorting priority based on the timeliness requirements information transmitted from the business system. Subsequently, the dynamic speed balancing algorithm module calculates the optimal running speed based on the inertia coefficient and sorting priority, combined with the running trajectories of other packages in the current system. The control device queries the sorting database stored in solid-state memory to obtain the target sorting position. Finally, based on the running speed and target position, the optimal delivery time is calculated, and at that time, the electromagnetic delivery device is controlled to release the package, ensuring that the package accurately falls into the designated slot.

[0042] Existing technologies simply calculate based on weight and shape information without considering the inertia coefficient and sorting priority of packages. This results in unreasonable operating speed settings, failure to optimize the impact and efficiency of the overall sorting system, and causes problems such as violent collisions of heavy or fragile goods during sorting, low system throughput efficiency, and insufficient delivery accuracy.

[0043] Through the above solution, this embodiment can dynamically adjust the operating parameters according to the physical characteristics of the package, effectively avoiding violent collisions caused by inertia during the sorting of heavy or fragile goods; and through multi-package collaborative optimization, it significantly improves the overall throughput efficiency of the system; in addition, based on the dynamically optimized operating speed and accurate target location, the optimal delivery time is calculated, which greatly improves the delivery accuracy and reduces the missorting rate.

[0044] Optionally, refer to Figure 3 Another embodiment of the present invention provides a control method for a cross-belt sorting device, based on the above. Figure 2 The illustrated embodiment calculates the package's inertia coefficient and sorting priority based on the weight and shape information, including steps S211-S215, wherein: S211. Determine the mass factor of the package corresponding to the weight information; S212. Based on the shape information, calculate the volume factor and stability index of the package; S213. Determine the inertia coefficient by using the mass factor, the volume factor, and the stability index according to a preset calculation formula; S214. Obtain the sorting urgency corresponding to the identification information; S215. The inertia coefficient and the sorting urgency are calculated by weighting the two factors together to determine the sorting priority.

[0045] Among them, the mass factor refers to a quantitative indicator that converts weight information into standardized physical parameters. It can be achieved through weight value normalization or logarithmic transformation, aiming to ensure a direct mapping of weight to inertia and avoid inertia estimation distortion caused by weight differences. The volume factor is a parameter characterizing the three-dimensional dimensional properties of the package. It can be calculated using the product of length, width, and height or projected area, aiming to quantify the impact of package size on transportation stability. The stability index is a measure of the package's resistance to disturbances during dynamic transportation. It can be calculated using the ratio of center of gravity height to base area or the shape regularity index. The purpose is to prevent irregularly shaped packages from shifting or tipping over during high-speed operation; the preset calculation formula refers to a mathematical model that integrates multi-dimensional physical characteristics, which can be implemented using linear combination functions or nonlinear regression equations, with the aim of comprehensively characterizing the motion inertia characteristics of the packages; sorting urgency refers to a scheduling parameter that reflects the priority of business needs, which can be implemented using preset priority labels or time deadline thresholds, with the aim of ensuring that high-priority tasks receive timely responses; the weighted ratio refers to an adjustment coefficient that balances physical characteristics and business needs, which can be implemented using fixed weight coefficients or dynamic adjustment factors, with the aim of achieving global optimization of the sorting process.

[0046] In this embodiment, the solution first converts weight data into standardized physical parameters using a mass factor, directly mapping the impact of weight on inertia. Then, based on shape information, it calculates a volume factor and a stability index; the former quantifies size, and the latter assesses resistance to disturbances, both jointly characterizing the physical stability of the package. Subsequently, the mass factor, volume factor, and stability index are input into a preset calculation formula to generate an inertia coefficient representing the package's motion inertia. Based on this, the sorting urgency associated with the identification information is obtained, reflecting the urgent needs of the task. Finally, the inertia coefficient and sorting urgency are fused using a weighted ratio to form a sorting priority that balances physical stability and business requirements. This process, through the systematic decomposition and fusion of multi-dimensional factors, ensures that the inertia coefficient accurately reflects the dynamic behavior of the package during sorting, thereby ensuring that the sorting priority conforms to both physical laws and business logic, providing a reliable basis for subsequent speed optimization and delivery timing control.

[0047] In one implementation method, during the operation of the cross-belt sorting equipment, when a package enters the sorting and transport device entrance, the weighing device acquires its weight information and converts it into a mass factor. The camera device collects image information and analyzes the shape contour data, then calculates the volume factor and stability index. The processing unit substitutes the mass factor, volume factor, and stability index into a preset calculation formula to obtain the inertia coefficient, and simultaneously extracts the sorting urgency from the identification information. Subsequently, a weighted ratio such as 0.6:0.4 is used to fuse the inertia coefficient and sorting urgency to generate sorting priority data. This sorting priority data is transmitted to the dynamic speed balancing algorithm module to calculate the operating speed and optimal delivery timing. For example, for an irregular package with a high center of gravity and large weight, its stability index is low while its mass factor is high. After processing with the preset calculation formula, a high inertia coefficient is obtained. Combined with the high urgency business requirements, it is determined to be of medium priority through weighted fusion, thereby appropriately reducing the operating speed and adjusting the delivery timing in advance during speed control.

[0048] In the above-described scheme of this embodiment, the inertia coefficient and sorting priority of the package are calculated based on weight and shape information to optimize the sorting process. However, in this process, there is a lack of refined decomposition and systematic integration of weight and shape information, which makes it impossible to accurately quantify the differences in the physical characteristics of the package. In particular, for packages with large weight and irregular shape, relying solely on simple rules for calculation can easily lead to deviations in inertial behavior prediction. At the same time, the sorting priority determination does not fully combine physical stability and business needs, which causes the optimization of running speed and the control of delivery timing to fail, resulting in an increased risk of collision or missorting rate of packages at the moment of sorting.

[0049] Through the above technical solution, this embodiment can accurately quantify the differences in the physical characteristics of packages, especially for packages with large weight and irregular shape, to accurately predict the inertial behavior; at the same time, it organically combines physical stability with business needs, making the optimization of operating speed and the control of delivery timing more reliable, effectively reducing the collision risk and missorting rate of packages at the moment of sorting, and significantly improving the physical stability of the sorting process and the system throughput efficiency.

[0050] Optionally, refer to Figure 4 In another embodiment of the present invention, a control method for a cross-belt sorting device is provided, based on the above. Figure 3 The embodiment shown calculates the operating speed based on the inertia coefficient and sorting priority using a dynamic speed balancing algorithm, including steps S221-S224, wherein: S221. Obtain the running status data of multiple packages in the current sorting system; S222. Based on the operating status data and the sorting priority, allocate a temporary operating speed for each package using a weighted average method; S223. Adjust the temporary operating speed using the inertia coefficient to determine the operating speed with the least overall sorting impact; S224. The operating speed with the least impact in the overall sorting process shall be taken as the operating speed.

[0051] The dynamic speed balancing algorithm is a calculation method for optimizing the operating speed of a sorting system. It can be implemented using a numerical algorithm based on global optimization, aiming to coordinate speed allocation during concurrent transport of multiple packages to minimize overall sorting impact. Acquiring operational status data of multiple packages in the current sorting system refers to real-time collection of motion parameters for each package during sorting and transport. This can be achieved using a distributed sensor network or a central monitoring system, providing a global view of the system's real-time operation. Allocating temporary operating speed for each package using a weighted average method refers to the calculation process of speed allocation based on sorting priority as a weighting factor. This can be implemented using linear weighted average or other equivalent weighted calculation methods, ensuring that high-priority packages receive better transport resources. Adjusting temporary operating speed through the inertia coefficient involves using the inertia coefficient to reflect the influence of the package's physical characteristics on motion stability to correct speed parameters. This can be achieved using proportional adjustment, nonlinear compensation, or other equivalent adjustment strategies, aiming to accurately compensate for displacement deviations caused by inertia. Determining the operating speed that minimizes the overall sorting impact means selecting the speed value that minimizes the overall sorting impact of the system. This can be achieved using iterative optimization algorithms or heuristic search methods, with the aim of achieving synergistic optimization of sorting efficiency and operational safety.

[0052] In this embodiment, the solution first acquires the operational status data of multiple packages in the current sorting system, which provides real-time system status for subsequent calculations. Then, based on the operational status data and sorting priority, a weighted average method is used to allocate a temporary operating speed for each package, where sorting priority serves as a weighting factor to ensure that high-priority packages receive a better speed. Next, the temporary operating speed is adjusted using an inertia coefficient to compensate for the motion effects caused by the physical characteristics of the packages. Finally, the operating speed with the least overall sorting impact is determined as the final operating speed, forming a closed-loop dynamic optimization mechanism to achieve precise coordination of speed allocation in multi-package concurrent scenarios.

[0053] In one implementation, the control unit of the cross-belt sorting equipment includes a processor, which can be an ARM Cortex-M7 microcontroller. Position sensors collect the position information of each package in real time and transmit it to the processor. Based on the operating status data and sorting priority, the processor calculates a temporary operating speed using a weighted average method; for packages with a high inertia coefficient, its operating speed is appropriately reduced; finally, the operating speed with the least overall sorting impact is determined, and the sorting and transport device is controlled accordingly.

[0054] In some of the above implementations of this embodiment, a method for optimizing the sorting process is proposed to calculate the running speed based on the inertia coefficient and sorting priority. However, in its implementation, there is a lack of dynamic integration of the real-time running status of multiple packages in the current sorting system. As a result, the speed allocation relies solely on static parameters and cannot adapt to the concurrent scenarios of multiple packages. This can easily lead to speed interference and sorting impact between packages, resulting in a decrease in system throughput efficiency and an increase in the risk of cargo damage.

[0055] Through the above solution, this embodiment can dynamically integrate the real-time operating status of multiple packages in the current sorting system, avoid speed allocation relying solely on static parameters, effectively adapt to multi-package concurrent scenarios, reduce speed interference and sorting impact between packages, thereby improving system throughput efficiency and reducing the risk of cargo damage.

[0056] Optionally, refer to Figure 5 The present invention also provides a control method for a cross-belt sorting device, based on the above. Figure 4 The embodiment shown adjusts the temporary operating speed using the inertia coefficient to determine the operating speed with the least overall sorting impact, including steps S2231-S2233, wherein: S2231. Obtain the current operating data of each package on the sorting and transport device, wherein the current operating data includes the current speed, position deviation and sorting impact force index; S2232. Calculate the optimal speed correction value for each package corresponding to the current running data using the minimum impact optimization algorithm, and substitute the optimal speed correction value and the inertia coefficient into the current running data to calculate and determine the corresponding speed adjustment amount; S2233. Adjust the temporary operating speed according to the speed adjustment amount, and determine the operating speed with the least overall sorting impact.

[0057] Among them, the current operating data refers to the dynamic status information of the packages monitored in real time during the sorting process. It can be realized by combining position sensors, speed encoders and force sensors, with the aim of providing accurate instantaneous operating condition input to support subsequent optimization decisions; the minimum impact optimization algorithm can be understood as a mathematical optimization method based on dynamic programming or quadratic programming, with the aim of solving for the optimal adjustment parameters by constructing an objective function; the optimal speed correction value specifically refers to the speed fine-tuning amount output by the algorithm, which can be expressed in floating-point numerical form, with the aim of quantifying the compensation for displacement deviation caused by package inertia; the speed adjustment amount refers to the final correction amount after inertia coefficient fusion, which can be realized through weighted fusion, with the aim of ensuring that the adjustment process takes into account both the physical characteristics of the package and its real-time status.

[0058] In this embodiment, the solution first acquires the current operating data of each package on the sorting and transport device, including current speed, positional deviation, and sorting impact force indicators. This data provides a dynamic and accurate input basis for the optimization process. Since the package status continuously changes during sorting, static parameters alone cannot reflect the instantaneous operating conditions. Real-time data acquisition ensures that adjustment decisions closely align with the current actual operating environment. Based on this, the optimal speed correction value is calculated using a minimum impact optimization algorithm. This correction value, along with the inertia coefficient, is then substituted into the current operating data to determine the speed adjustment amount. This process fully utilizes the inertia coefficient's characterization of the package's physical properties, enabling the speed correction to dynamically adapt to the differences in inertial response among different packages. Finally, the temporary operating speed is adjusted based on the calculated speed adjustment amount to determine the operating speed with the minimum overall sorting impact. This achieves multi-package collaborative optimization, dynamically coordinating the motion states of each package, reducing mutual interference caused by speed interference, and thus forming a complete technical closed loop.

[0059] In a preferred embodiment, in a cross-belt sorting device, the control unit acquires package position information in real time through position sensors along the sorting transport path and monitors the current speed using a speed encoder. For each package, the control unit calculates its positional deviation and sorting impact force index, and this data is input into a minimum impact optimization algorithm module. This algorithm module, executed by the processor in the control unit, uses dynamic programming to calculate the optimal speed correction value. Subsequently, the optimal speed correction value is weighted and fused with a pre-calculated inertia coefficient to determine the speed adjustment amount. The processor dynamically adjusts the speed of the drive motor of the sorting transport device according to this adjustment amount, ensuring that the package travels to the target sorting position with minimal impact.

[0060] In some of the solutions described above in this embodiment, the temporary operating speed is adjusted by the inertia coefficient to determine the operating speed with the least overall sorting impact. However, in this process, the real-time operating status data of each package is not fully combined for fine adjustment, resulting in rough sorting impact calculation. It is impossible to accurately compensate for the dynamic deviation caused by the inertia of the package, which can easily cause the package to collide or be thrown out at the moment of sorting, affecting sorting accuracy and system reliability.

[0061] Through the above solution, this embodiment can accurately compensate for the dynamic deviation caused by the inertia of the package, significantly reduce the risk of collision during sorting, and improve the delivery accuracy and the reliability of system operation.

[0062] Optionally, refer to Figure 6 Another embodiment of the present invention provides a control method for a cross-belt sorting device, based on the above. Figure 1The illustrated embodiment controls the sorting and transporting device to transport the package at the operating speed, and controls the delivery device to deliver the package at the optimal delivery time at the target sorting location, including steps S310-S340, wherein: S310. Adjust the initial transport parameters of the sorting and transporting device according to the operating speed; S320. Control the sorting and transportation device to operate according to the initial transportation parameters, and obtain the current package position and current operating speed during the operation; S330. Calculate the distance to the target sorting location based on the current package location, and determine the remaining transportation time corresponding to the current operating speed; S340. Determine the optimal delivery time based on the distance to the target sorting location and the remaining transportation time, and control the delivery device to deliver the package at the optimal delivery time.

[0063] The initial transportation parameters refer to the basic operating settings when the sorting and transportation device starts. These can be achieved through one or more combinations of speed settings, acceleration thresholds, or track tension parameters. The purpose is to establish a unified operating benchmark for the transportation process, avoiding cumulative errors in subsequent dynamic adjustments caused by initial state deviations. The current package position can be understood as the real-time spatial coordinates of the package within the sorting and transportation path. This can be achieved through a non-contact ranging module or encoder feedback signals, aiming to capture the actual displacement state of the package and provide basic data input for dynamic path calculation. The remaining transportation time refers to the theoretical time required for the package to reach the target sorting position from its current location. This can be calculated based on the ratio of the current operating speed to the dynamic path distance, aiming to establish an accurate time-dimensional prediction model and effectively compensate for timing deviations caused by speed fluctuations. Furthermore, the optimal delivery timing can be understood as the precise time point to trigger the delivery action. This can be determined by the difference between the remaining transportation time and the preset safety buffer time, aiming to ensure that the release operation is performed when the package's physical position is perfectly aligned with the target compartment, thereby eliminating delivery errors caused by inertia.

[0064] In this embodiment, the solution achieves precise control of delivery timing by constructing a dynamic feedback mechanism. First, the control device sets initial transportation parameters based on a preset operating speed, enabling the sorting and transportation device to start from a stable baseline state. Second, during operation, it continuously monitors the real-time location and speed data of the packages, generating dynamic operating status feedback. Subsequently, it calculates the dynamic path distance based on the real-time location coordinates and the target sorting location coordinates, and derives the remaining transportation time by combining the current operating speed. Finally, by integrating the dynamic path distance and the remaining transportation time, it determines the optimal delivery timing and triggers the delivery device to execute its action. This process forms a closed-loop control chain from parameter setting and status monitoring to timing decision-making, with strict temporal dependencies between each step: initial parameter setting provides a baseline for subsequent dynamic adjustments, real-time data acquisition provides input for distance and time calculations, and the dynamic calculation results of distance and time directly drive the precise determination of the delivery timing. This design avoids dependence on static models, enabling the control device to adapt to real-time changes in the package's operating status, fundamentally solving the delivery accuracy problem caused by inertial deviation.

[0065] In one implementation method, when the sorting and transporting device is started, the control system sets the motor drive frequency to an initial value according to the running speed command, allowing the trolley to enter the transport track at a reference speed. During operation, a laser ranging module installed on the side wall of the track continuously scans the outline of the package to obtain the real-time position coordinates of the package, and simultaneously collects the current running speed fed back by the motor speed encoder. The control device performs vector calculations on the current position coordinates and the target sorting position coordinates to obtain the dynamic path distance, and then calculates the remaining transport time based on the current running speed. When the remaining transport time reaches a preset threshold, the control system sends a trigger signal to the delivery device, causing the electromagnetic pusher to release the package at a precise moment. In this process, the laser ranging module avoids interfering with the package's movement in a non-contact manner, while the vector calculation process automatically compensates for the influence of track curvature on the path distance, ensuring that the time prediction closely matches the actual running trajectory.

[0066] In some of the above embodiments of this example, it is proposed to control the sorting and transportation device to transport packages at the operating speed and control the delivery device at the target sorting position to deliver packages at the optimal delivery time to achieve sorting operation. However, in its implementation process, the dynamic changes of operating parameters are not fully incorporated into the calculation framework, which makes the delivery timing determination method based on preset parameters unable to adapt to the real-time fluctuations of package position and speed, and thus causes a decrease in delivery accuracy and the risk of missorting due to inertial deviation.

[0067] Through the above technical solution, this embodiment effectively solves the problem of delivery accuracy caused by dynamic changes in operating parameters, significantly reduces the risk of missorting caused by inertial deviation, and substantially improves the physical alignment accuracy of packages at the target sorting position, thereby ensuring the reliability and standardization of sorting operations.

[0068] Optionally, refer to Figure 7 Another embodiment of the present invention provides a control method for a cross-belt sorting device, based on the above. Figure 6 The illustrated embodiment further includes multiple position sensors; these position sensors are spaced apart at multiple nodes along the sorting transport path. The step of calculating the distance to the target sorting location based on the current package location and determining the remaining transport time corresponding to the current operating speed includes steps S331-S333, wherein: S331. Obtain the current position coordinates of each package collected by the position sensor; S332. Determine the dynamic path distance for each package based on the current location coordinates and the target sorting location coordinates; S333. Calculate the remaining transportation time based on the current operating speed and the dynamic path distance.

[0069] The dynamic path distance refers to the actual distance a package travels along the sorting and transportation path. It can be achieved by using an interpolation algorithm based on the coordinates of the path nodes or by looking up a table of pre-stored path topology data. The purpose is to accurately reflect the physical trajectory that the package needs to travel and avoid errors in straight-line distance calculation caused by track curvature or node distribution.

[0070] By distributing multiple location sensors at intervals along the sorting and transportation path, the system can obtain the current location coordinates of the package in real time, replacing the indirect estimation method that relies on time estimation. Based on this coordinate data, the system accurately calculates the dynamic path distance from the package to the target sorting location, fully considering the curve characteristics of the actual transportation path. Combined with the current operating speed, the system dynamically calculates the remaining transportation time, ensuring that the timing of delivery decisions and the package's operating status are adaptively matched, thus forming a complete closed-loop control logic from location monitoring to time prediction.

[0071] In one implementation, the position sensor can be a specific infrared photoelectric sensor, installed at key node positions of the circular track; the control device captures package coordinate information in real time through the sensor network, performs dynamic path distance calculation using the path topology database, and dynamically updates the remaining transportation time based on the current speed.

[0072] In some of the above embodiments of this example, the distance to the target sorting location is calculated based on the current package location and the remaining transportation time is determined to determine the optimal delivery time. However, in this process, due to the lack of a real-time and accurate location monitoring mechanism, the acquisition of the current package location relies on rough estimation or fixed point detection, which leads to deviations in the dynamic path distance calculation and inaccurate estimation of the remaining transportation time. Consequently, the optimal delivery time is not accurately determined, and the missorting rate increases.

[0073] Through the above solution, this embodiment effectively eliminates the cumulative positioning error caused by inaccurate location monitoring, improves the decision-making accuracy of delivery timing, and reduces the missorting rate.

[0074] Optionally, refer to Figure 8 In another embodiment of the present invention, a control method for a cross-belt sorting device is provided, based on the above. Figure 1 The illustrated embodiment further includes a camera device and a weighing device, which are respectively located at the entrance of the sorting and transport device; the acquisition of the identification information, weight information, and shape information of the packages to be sorted includes steps S110-S150, wherein: S110. Obtain the weight information of each package through the weighing device; S120. Acquire image information of each package using the camera device; S130. Parse the package barcode information and shape contour data in the image information; S140. Determine the shape information corresponding to the shape contour data; S150. The package barcode information, the weight information, and the shape information are associated to generate the identification information.

[0075] Among them, parsing the package barcode information and shape contour data in the image information refers to the technical process of extracting structured data from the original image. It can be achieved by using image recognition algorithms based on convolutional neural networks, edge detection technology, or template matching methods. Its purpose is to avoid recognition errors caused by manual input and ensure the reliability of the source of barcode information and contour features. Determining the shape information corresponding to the shape contour data can be understood as a technical means of converting continuous contour data into quantifiable parameters. It can be achieved by using three-dimensional point cloud reconstruction, polygon fitting, or feature vector extraction. Its purpose is to enable shape features to directly participate in the calculation of inertia coefficient, making up for the insufficient accuracy caused by relying solely on simple classification in traditional methods.

[0076] In this embodiment, the solution integrates a camera and a weighing device at the entrance of the sorting and transportation unit, creating a closed-loop mechanism for real-time package information acquisition and processing. When a package enters the system, the weighing device directly measures its weight and transmits it to the control system. Simultaneously, the camera captures multi-angle images of the package, and the control system automatically parses the barcode and outline data from the images. The weight, barcode, and outline data are then correlated to generate unified identification information. This collaborative data acquisition and processing process ensures the immediate acquisition and structured transformation of physical characteristic data, providing a complete and consistent information foundation for subsequent calculations of optimal delivery timing and operating speed. This effectively avoids decision-making biases caused by delayed information acquisition or reliance on external input.

[0077] In one implementation, an industrial-grade strain gauge load cell and a global shutter CMOS camera are installed at the entrance of the sorting and transport device. As a package passes through the entrance area, the load cell measures its weight in real time and generates a digital signal; the camera captures images of the package surface at a fixed frame rate, and the control device uses a pre-trained deep learning model to identify barcode information in the image and extracts the package's two-dimensional projected contour using a contour tracking algorithm. Subsequently, the control device timestamps and fuses the weight data, decoded barcode information, and contour feature vectors to generate identification information containing multi-dimensional features for subsequent sorting decision-making processes.

[0078] In some of the above-described embodiments of this example, the weight and shape information of the packages to be sorted are proposed to calculate the optimal delivery time and running speed. However, in the process of implementation, due to the lack of dedicated weighing and camera equipment at the entrance of the sorting and transportation device, the weight and shape data are not obtained in a timely manner, are incomplete, or have errors, which leads to inaccurate calculation of the inertia coefficient, resulting in deviations in delivery time, increased risk of package collision, and increased missorting rate.

[0079] Through the above technical solution, this embodiment effectively solves the problems of untimely, incomplete or erroneous acquisition of package information, ensures the accuracy of inertia coefficient calculation, thereby reducing the timing deviation of delivery, reducing the risk of collision caused by inertia during package sorting, and improving the accuracy of sorting process and the stability of system operation.

[0080] The present invention also proposes a control device, the control device comprising: a memory, a processor, and a control program for a cross-belt sorting device stored in the memory and executable on the processor, the control program for the cross-belt sorting device being configured to implement the control method for the cross-belt sorting device as described above.

[0081] The core innovation of this embodiment lies in dynamically optimizing the combination of package weight and shape information with system operating status data. This avoids collision risks caused by large weight or irregular shape during speed decision-making, dynamically balances speed interference and waiting time, and accurately compensates for inertial displacement, thereby improving sorting accuracy, reducing cargo damage, and optimizing overall throughput efficiency. Specifically, the memory stores the control program and operating data, enabling the control device to calculate the inertia coefficient based on the package weight and shape information. The processor executes the control program in real time, allocating temporary operating speeds using a weighted average method based on the operating status data and sorting priorities of multiple packages in the current sorting device, and adjusting the speed using the inertia coefficient to minimize overall sorting impact. The control program for the cross-belt sorting equipment is configured to determine the dynamic path distance based on the current position coordinates and target sorting position coordinates obtained from the position sensors, and calculates the remaining transportation time based on the current operating speed to accurately determine the optimal delivery time. This effectively solves the problems of cargo damage caused by not dynamically considering the physical characteristics of packages, low throughput efficiency due to a lack of overall collaborative optimization in system operation, and high missorting rates due to inaccurate delivery timing.

[0082] It is worth noting that since the control device of the present invention is based on the control method of the cross-belt sorting equipment described above, the embodiments of the control device of the present invention include all the technical solutions of all embodiments of the control method of the cross-belt sorting equipment described above, and the technical effects achieved are exactly the same, so they will not be repeated here.

[0083] The present invention also proposes a cross-belt sorting device, which includes the control device as described in the above embodiments.

[0084] The core innovation of this embodiment lies in combining the weight and shape information of the package with a dynamic speed balancing algorithm. This allows for dynamic adjustment of the running speed and precise compensation of inertial displacement based on the calculated inertia coefficient and sorting priority. This achieves the effect of significantly avoiding damage to goods, improving system throughput efficiency, and reducing missorting rate while ensuring sorting efficiency.

[0085] It is worth noting that since the cross-belt sorting equipment of the present invention is based on the above-mentioned control device, the embodiments of the cross-belt sorting equipment of the present invention include all the technical solutions of all the embodiments of the above-mentioned control device, and the technical effects achieved are exactly the same, so they will not be repeated here.

[0086] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0087] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0088] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0089] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A control method for a cross-belt sorting device, the cross-belt sorting device comprising a sorting and transport device and a delivery device, characterized in that, The control method for the cross-belt sorting equipment includes: Obtain the identification information, weight information, and shape information of the packages to be sorted; Determine the target sorting location corresponding to the identification information, and calculate the optimal delivery time and running speed of the package on the cross belt based on the weight and shape information; The sorting and transporting device is controlled to transport the package at the operating speed, and the delivery device is controlled to deliver the package at the optimal delivery time at the target sorting location.

2. The control method for the cross-belt sorting equipment as described in claim 1, characterized in that, The process of determining the target sorting location corresponding to the identification information and calculating the optimal delivery time and operating speed of the package on the cross belt based on the weight and shape information includes: Based on the weight and shape information, calculate the inertia coefficient and sorting priority of the package; The operating speed is calculated based on the inertia coefficient and sorting priority using a dynamic speed balancing algorithm. Query the target sorting location in the preset sorting database that corresponds to the identification information; Calculate the optimal delivery time corresponding to the running speed and the target sorting location.

3. The control method for the cross-belt sorting equipment as described in claim 2, characterized in that, The step of calculating the inertia coefficient and sorting priority of the package based on the weight and shape information includes: Determine the mass factor of the package corresponding to the weight information; Based on the shape information, the volume factor and stability index of the package are calculated. The inertia coefficient is determined by the mass factor, the volume factor, and the stability index according to a preset calculation formula; Obtain the sorting urgency corresponding to the identification information; The sorting priority is determined by combining the inertia coefficient and the sorting urgency according to a weighted ratio.

4. The control method for the cross-belt sorting equipment as described in claim 3, characterized in that, The calculation of the operating speed based on the inertia coefficient and sorting priority using a dynamic speed balancing algorithm includes: Obtain the operational status data of multiple packages in the current sorting system; Based on the operational status data and the sorting priority, a weighted average method is used to allocate a temporary operating speed for each package; The temporary operating speed is adjusted by the inertia coefficient to determine the operating speed with the least overall sorting impact; The operating speed is defined as the operating speed that minimizes the overall sorting impact.

5. The control method for the cross-belt sorting equipment as described in claim 4, characterized in that, The step of adjusting the temporary operating speed using the inertia coefficient to determine the operating speed with the least overall sorting impact includes: Obtain the current operating data of each package on the sorting and transport device, including the current speed, position deviation, and sorting impact force index; The optimal speed correction value corresponding to the current running data for each package is calculated using the minimum impact optimization algorithm. The optimal speed correction value and the inertia coefficient are then substituted into the current running data to calculate and determine the corresponding speed adjustment amount. Based on the speed adjustment amount, the temporary operating speed is adjusted to determine the operating speed with the least overall sorting impact.

6. The control method for the cross-belt sorting equipment as described in claim 1, characterized in that, The control of the sorting and transporting device to transport the package at the operating speed, and the control of the delivery device to deliver the package at the optimal delivery time at the target sorting location, includes: Adjust the initial transport parameters of the sorting and transporting device according to the operating speed; The sorting and transportation device is controlled to operate according to the initial transportation parameters, and the current package location and current operating speed are obtained during the operation. Calculate the distance to the target sorting location based on the current package location, and determine the remaining transportation time corresponding to the current operating speed; The optimal delivery time is determined based on the distance to the target sorting location and the remaining transportation time, and the delivery device is controlled to deliver the package at the optimal delivery time.

7. The control method for the cross-belt sorting equipment as described in claim 6, characterized in that, The cross-belt sorting equipment also includes multiple position sensors; the multiple position sensors are distributed at intervals at multiple node positions of the sorting and transport path; The step of calculating the distance to the target sorting location based on the current package location and determining the remaining transportation time corresponding to the current operating speed includes: Obtain the current location coordinates of each package collected by the location sensor; The dynamic path distance for each package is determined based on the current location coordinates and the target sorting location coordinates. Calculate the remaining transportation time based on the current operating speed and the dynamic path distance.

8. The control method for the cross-belt sorting equipment as described in claim 1, characterized in that, The cross-belt sorting equipment also includes a camera device and a weighing device, which are respectively located at the entrance of the sorting and transporting device; The acquisition of the identification information, weight information, and shape information of the packages to be sorted includes: The weight information of each package is obtained through the weighing device; The camera device is used to acquire image information of each package; Analyze the package barcode information and shape contour data in the image information; Determine the shape information corresponding to the shape contour data; The identification information is generated by associating the package barcode information, the weight information, and the shape information.

9. A control device, characterized in that, The control device includes: a memory, a processor, and a control program for the cross-belt sorting device stored in the memory and executable on the processor, the control program for the cross-belt sorting device being configured to implement the control method for the cross-belt sorting device as described in any one of claims 1 to 8.

10. A cross-belt sorting device, characterized in that, Includes the control device as described in claim 9.

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