Liquid bag grabbing control method and device, electronic equipment and storage medium

Abstract

The invention relates to a liquid bag grabbing control method. The method comprises the steps that capacity information and grabbing performance indexes of a to-be-grabbed target liquid bag are obtained; based on the capacity information and a control strategy matched with the grabbing performance index, a target roadway position where the target liquid bag is placed is determined; the grabbing assembly is controlled to move to the target roadway position to conduct grabbing operation on the target liquid bag, and the grabbing result of the target liquid bag is obtained; and under the condition that the grabbing result is that grabbing is not successful, the grabbing assembly is controlled to repeatedly execute grabbing operation on the target liquid bag till the grabbing result is that grabbing is successful. According to the method, by obtaining the capacity information (such as volume and weight distribution) and the grabbing performance index of the target liquid bag in real time, the control strategy matched with the current grabbing scene can be determined, and the accuracy and efficiency of grabbing operation can be improved; and moreover, the requirement for manual intervention is reduced, so that human errors are reduced, and the stability and reliability of grabbing work are improved.

Description

Technical Field

[0001] The present application relates to the field of automated control technology, and in particular to a liquid bag grabbing control method, device, electronic equipment, and storage medium. Background Art

[0002] In automated warehousing and logistics systems, the intelligent grasping and handling of flexible packaging containers, such as liquid bags, has always been a technical challenge. Traditional methods typically rely on static lane allocation strategies and single grasping performance indicators (such as a fixed robotic arm path or preset grasping accuracy), making it difficult to dynamically adapt to the varying capacities and grasping efficiency requirements of different liquid bags. Static lane allocation is inefficient, while fixed lane allocation rules have significant deficiencies in multi-capacity matching and dynamic path planning, potentially leading to congestion and resource waste, impacting overall warehousing efficiency.

[0003] Therefore, how to achieve efficient and accurate grasping of liquid bags is an urgent problem that needs to be solved. Summary of the Invention

[0004] Based on this, it is necessary to provide a liquid bag grabbing control method, device, computer equipment and storage medium to address the above technical problems.

[0005] In a first aspect, the present application provides a liquid bag grabbing control method, the method comprising: Obtaining capacity information and grasping performance indicators of the target liquid bag to be grasped; wherein the grasping performance indicators include performance parameters for measuring lane storage space, expected grasping efficiency and / or expected grasping accuracy; Determining a target lane location for placing the target liquid bag based on the capacity information and a control strategy that matches the grasping performance index; Controlling the grabbing assembly to move to the target lane position to perform a grabbing operation on the target liquid bag, and obtaining a grabbing result of the target liquid bag; When the grasping result is an unsuccessful grasping, the grasping component is controlled to repeatedly perform the grasping operation on the target liquid bag until the grasping result is a successful grasping.

[0006] In one embodiment, determining the target lane position for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: When the lane storage space is less than a first capacity threshold, the expected grabbing time is less than a first time threshold, and / or the expected grabbing accuracy is less than a first value, the capacity information is matched with a capacity mapping table to determine the target lane position; wherein, the capacity mapping table indicates a mapping relationship between the lane physical identification and the capacity interval.

[0007] In one embodiment, determining the target lane location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: Acquire attribute information and location data of each liquid bag placed in each storage lane based on radio frequency identification technology, if the lane storage space is greater than or equal to a first capacity threshold and less than a second capacity threshold, the expected grabbing time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grabbing accuracy is greater than or equal to a first value and less than a second value; wherein the attribute information includes the liquid bag capacity, content type, and batch number; Based on the capacity information and the attribute information, screening candidate storage lanes from the storage lanes; According to the distance factor, the inventory turnover factor and the load factor, a first target storage lane and the corresponding target lane position are determined from the candidate storage lanes.

[0008] In one embodiment, determining the target lane location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: If the lane storage space is greater than or equal to a second capacity threshold, the expected grabbing time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grabbing accuracy is greater than or equal to a second value, the first storage lane is selected from the storage dynamic database based on the capacity information; wherein the storage dynamic database is used to record and store the liquid bag capacity, number of liquid bags, location data, and expiration date of each liquid bag in each storage lane; Based on the load of each first storage lane at the current moment and the usage of the grabbing components matching the first storage lane, and in combination with the path planning algorithm, an evaluation score is calculated respectively; Based on the evaluation score, a second target storage lane is selected from the first storage lanes and a corresponding position of the target lane is determined.

[0009] In one embodiment, the path planning algorithm is constructed in the following manner: Based on the lane positions of the storage lanes and the movement paths between the storage lanes, an initial topology map is constructed; wherein the nodes in the initial topology map are used to represent the storage lanes; and the links between the nodes in the initial topology map are used to represent the movement paths between the storage lanes; Assigning dynamic attribute information to each node to obtain a lane network topology diagram; wherein the dynamic attribute information includes capacity interval, path distance, and health index of the grabbing component corresponding to the storage lane; Based on the lane network topology map, the path planning algorithm is constructed.

[0010] In one embodiment, the evaluation scores are calculated based on the load of each first storage lane at the current moment and the usage of the gripping assembly matching the first storage lane, in combination with the path planning algorithm, including: Filtering candidate storage lanes from the first storage lanes based on the number of liquid bags, total weight of the liquid bags, space occupancy rate, expiration date, and occupancy status of the grabbing assembly stored in the first storage lane at the current moment; and determining the evaluation score for each candidate storage lane based on the dynamic attribute information; The selecting a second target storage lane from the first storage lane based on the evaluation score includes: The candidate storage lane corresponding to the highest value of the evaluation scores is determined as the second target storage lane.

[0011] In one embodiment, obtaining the grabbing result of the target liquid bag includes: Acquiring a first sensor signal value of the gripping component through a main detection unit; wherein the main detection unit includes at least two proximity switches arranged in orthogonal directions; the first sensor signal value is used to indicate the working state of the gripping component; obtaining a second sensor signal value of the gripping assembly through a secondary detection unit; wherein the secondary detection unit includes a position sensor; the main detection unit and the secondary detection unit are both disposed at a contact portion between the gripping assembly and the target fluid bag; and the second sensor signal value is used to indicate a detection distance between the gripping assembly and the target fluid bag; The grasping result is determined based on the first sensor signal value and / or the second sensor signal value.

[0012] In a second aspect, the present application further provides a liquid bag grabbing control device, the device comprising: An acquisition module, configured to acquire capacity information and a grasping performance index of a target liquid bag to be grasped; wherein the grasping performance index includes performance parameters for measuring lane storage space, expected grasping efficiency, and / or expected grasping accuracy; a screening module, configured to determine a target lane location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index; a grabbing module, configured to control the grabbing assembly to move to the target lane position to perform a grabbing operation on the target liquid bag, and obtain a grabbing result of the target liquid bag; The processing module is used for controlling the grabbing component to repeatedly perform the grabbing operation on the target liquid bag when the grabbing result is an unsuccessful grabbing, until the grabbing result is a successful grabbing.

[0013] In a third aspect, the present application also provides a computer device comprising a processor and a memory for storing a computer program of the processor; wherein the processor is configured to: when executing the computer program, implement the steps of the method execution described in any embodiment of the present application.

[0014] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method execution described in any embodiment of the present application.

[0015] In the above-mentioned liquid bag grasping control method, by obtaining the capacity information (such as volume and weight distribution) and grasping performance indicators of the target liquid bag in real time, a control strategy suitable for the current grasping scenario can be determined, which helps to improve the accuracy and efficiency of the grasping operation. On the one hand, it can reduce the losses caused by misgrasping or missing grasping, and on the other hand, it can speed up the processing speed and improve the operation efficiency. In addition, if the grasping is not successful, the grasping operation can be repeated on the target liquid bag until the target is met. This can ensure that each liquid bag is grasped correctly and efficiently automatically, reducing the need for manual intervention, thereby reducing the occurrence of human errors and improving the stability and reliability of the grasping work. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 is an application environment diagram of a liquid bag grabbing control method according to an exemplary embodiment; Figure 2 is a flow chart of a liquid bag grabbing control method according to an exemplary embodiment; Figure 3 is a flow chart of a liquid bag grabbing control method according to an exemplary embodiment; Figure 4 is a structural block diagram of a liquid bag grabbing control device according to an exemplary embodiment; Figure 5 The figure shows the internal structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0018] The terms "first", "second" and "third" in the embodiments of the present application are only used for descriptive purposes and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second" and "third" may explicitly or implicitly include at least one of the features. In the description of the present application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, method, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally also include steps or units that are not listed, or may optionally also include other steps or units inherent to these processes, methods, products or devices.

[0019] References to "embodiments" herein mean that a particular feature, structure, or characteristic described in connection with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0020] In some embodiments, the liquid bag grabbing control method provided in the embodiments of the present application can be applied to Figure 1 In the illustrated application environment, a computer device 102 communicates with a grabbing component 104 and a data acquisition component 106 via a network. The computer device 102 can control the grabbing component 104 to grab liquid bags stored in a storage lane, and the data acquisition component 106 can collect relevant data (e.g., attribute information and location data of each liquid bag placed in the storage lane) in real time for the computer device 102 to process. The computer device 102 can be any mobile terminal or a fixed terminal. A terminal can be a device that provides voice and / or data connectivity to a user. Exemplarily, the terminal can be an Internet of Things terminal, such as a sensor device, a mobile phone or so-called "cellular" phone, and a computer with an Internet of Things terminal. For example, the terminal can be a fixed, portable, pocket-sized, handheld, or computer-built-in device. The data acquisition component can include at least one of a radio frequency identification (RFID) reader / writer array, various types of sensors (e.g., weight sensors), a proximity switch, and an image acquisition device.

[0021] In some embodiments, the computer device and the data acquisition component may be connected via a network communication connection; the network communication connection may include both wired and wireless connections. For example, the data acquisition component and the computer device may be connected via a physical medium, with data transmission occurring over the physical line, which provides greater stability and speed. Alternatively, the data acquisition component and the computer device may be connected wirelessly via wireless technology, with data transmission not being restricted by physical lines and offering greater flexibility.

[0022] In some embodiments, as Figure 2 As shown, a liquid bag grabbing control method is provided, the method comprising the following steps: S201, obtaining capacity information and grasping performance indicators of the target liquid bag to be grasped; wherein the grasping performance indicators include performance parameters for measuring lane storage space, expected grasping efficiency and / or expected grasping accuracy.

[0023] In the embodiment of the present application, the capacity information may include but is not limited to at least one of the size of the liquid bag, the weight of the liquid bag, and the shape of the liquid bag.

[0024] In the embodiment of the present application, the lane storage space indicates the maximum amount of liquid that the storage lane can provide for the liquid bag.

[0025] In the embodiments of the present application, the expected grasping efficiency indicates the prediction and evaluation of the speed at which a grasping operation can be successfully executed in an automated warehousing or logistics system. The expected grasping efficiency can be used to measure the ability to accurately and efficiently complete a grasping operation within a given time.

[0026] In some embodiments, the expected grasping efficiency may include but is not limited to at least one parameter of expected grasping time and failure / success rate.

[0027] In the embodiments of the present application, the expected grasping accuracy rate indicates an indicator for measuring the accuracy of grasping operations in an automated warehousing or logistics system. The expected grasping accuracy rate can represent the grasping system's ability to successfully and accurately grasp the target liquid bag from the target lane location and place it at the correct destination.

[0028] S202 : Determine a target lane position for placing the target liquid bag based on the capacity information and a control strategy that matches the grasping performance index.

[0029] In one embodiment, the computer device can perform an initial screening of the storage lanes based on the specific properties of the liquid bag (such as capacity, shape, etc.) to determine the third storage lane; based on the performance parameter matching control strategy of the grasping component, the target storage lane is screened out from the third storage lane, thereby determining the location of the target lane.

[0030] S203 , controlling the grabbing component to move to the target lane position to perform a grabbing operation on the target liquid bag, and obtaining a grabbing result of the target liquid bag.

[0031] In one embodiment, before controlling the grabbing assembly to move to the target lane position, the computer device can determine whether the target storage lane corresponding to the target lane stores the target liquid bag at the current moment; if the target storage lane stores the target liquid bag, the grabbing assembly is controlled to move to the target lane position to grab the target liquid bag.

[0032] In some embodiments, obtaining the grabbing result of the target fluid bag includes: Acquiring a first sensor signal value of the gripping component through a main detection unit; wherein the main detection unit includes at least two proximity switches arranged in orthogonal directions; the first sensor signal value is used to indicate the working state of the gripping component; obtaining a second sensor signal value of the gripping assembly through a secondary detection unit; wherein the secondary detection unit includes a position sensor; the main detection unit and the secondary detection unit are both disposed at a contact portion between the gripping assembly and the target fluid bag; and the second sensor signal value is used to indicate a detection distance between the gripping assembly and the target fluid bag; The grasping result is determined based on the first sensor signal value and / or the second sensor signal value.

[0033] In the embodiment of the present application, the proximity switch can be used to detect the position, limit and count of mechanical moving parts. The proximity switch can include but is not limited to at least one of a capacitive proximity switch, an inductive proximity switch and a photoelectric proximity switch.

[0034] In some embodiments, the first sensor signal value indicates the working status of the gripping component. For example, when the first sensor signal value is 1, it can indicate that the gripping component has successfully gripped the target liquid bag. When the first sensor signal value is 0, it can indicate that the gripping component has not successfully gripped the target liquid bag or that the gripping component has dropped the target liquid bag. The computer device can obtain one or more first sensor signal values ​​in real time through a main detection unit provided on the gripping component. For example, the first switch in the main detection unit is used to confirm whether the target liquid bag has been successfully gripped, and the second switch is used to detect the risk of the target liquid bag falling off. When multiple first sensor signal values ​​all indicate successful gripping, it can be determined that the gripping component has successfully gripped the target liquid bag. In this way, through multi-directional redundant detection, such as installing multiple proximity switches in orthogonal directions, the occurrence of single point failures can be reduced and the accuracy of detection can be guaranteed.

[0035] In the embodiment of the present application, the auxiliary detection unit can be used to detect the grasping force, grasping posture, detection distance, etc. The auxiliary detection unit can include but is not limited to at least one of a piezoelectric / capacitive force sensor and a position sensor.

[0036] In some embodiments, when the secondary detection unit includes a force sensor, the second sensor signal value can also be used to indicate the gripping force of the gripping assembly. The computer device can obtain one or more second sensor signal values ​​in real time through the secondary detection unit provided on the gripping assembly. If the second sensor signal value representing the gripping force is greater than a detection force threshold and / or the second sensor signal value representing the detection distance is less than or equal to a detection distance threshold, the computer device can determine that the gripping result is consistent with the expected target and that the gripping assembly has successfully gripped the target liquid bag.

[0037] In one embodiment, the computer device can establish a mapping function between the detection distance and the size characteristics of the liquid bag, and dynamically adjust the detection distance threshold according to the mapping function to assign a reasonable detection distance threshold to liquid bags of different sizes.

[0038] For example, the expression of the mapping function between the detection distance and the liquid bag size characteristic is: Where D indicates the detection distance; V bag Indicates the capacity of the fluid bag; k1 and k2 indicate the calibration coefficients; ΔD indicates the safety margin; S indicates the size characteristics of the fluid bag.

[0039] In one embodiment, external interference factors such as mechanical vibration, accidental jumps in current and voltage may lead to misjudgment of the working state of the grasping component; for example, mechanical vibration causes fluctuations in the collected first sensor signal value and / or second sensor signal value. In order to more accurately judge the working state of the grasping component, the computer device can delay the acquisition of the first sensor signal value and / or the second sensor signal value after the grasping operation is completed, thereby reducing misjudgment caused by the grasping component not being able to fully grasp the target liquid bag due to shaking during grasping; or, the computer device can repeatedly acquire multiple corresponding sensor signal values ​​when the first sensor signal value is inconsistent with the first expected value, and / or the second sensor signal value is inconsistent with the second expected value, thereby reducing the interference of external interference factors in the detection of the working state of the grasping component.

[0040] In one embodiment, when both the first sensor signal value and the second sensor signal value indicate that the grasping component successfully grasps the target liquid bag, the grasping result is determined to be a successful grasping; when either sensor signal value indicates that the grasping component fails to successfully grasp the target liquid bag, the grasping result is determined to be a failed grasping.

[0041] S204 , when the grasping result is an unsuccessful grasping, controlling the grasping component to repeatedly perform the grasping operation on the target liquid bag until the grasping result is a successful grasping.

[0042] In some embodiments, the computer device can control the grasping component to repeat the grasping action on the target liquid bag when the last grasping result was an unsuccessful grasping; after completing the grasping action, the first sensor signal value and / or the second sensor signal value are re-acquired, and the grasping result is judged based on the first sensor signal value and / or the second sensor signal value until the grasping result is a successful grasping. The computer device controls the grasping component to stop the grasping action and move the successfully grasped target liquid bag to the destination.

[0043] In the above-mentioned liquid bag grasping control method, by obtaining the capacity information (such as volume and weight distribution) and grasping performance indicators of the target liquid bag in real time, a control strategy suitable for the current grasping scenario can be determined, which helps to improve the accuracy and efficiency of the grasping operation. On the one hand, it can reduce the losses caused by misgrasping or missing grasping, and on the other hand, it can speed up the processing speed and improve the operation efficiency. In addition, if the grasping is not successful, the grasping operation can be repeated on the target liquid bag until the target is met. This can ensure that each liquid bag is grasped correctly and efficiently automatically, reducing the need for manual intervention, thereby reducing the occurrence of human errors and improving the stability and reliability of the grasping work.

[0044] In some embodiments, determining the target lane location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: When the lane storage space is less than a first capacity threshold, the expected grabbing time is less than a first time threshold, and / or the expected grabbing accuracy is less than a first value, the capacity information is matched with a capacity mapping table to determine the target lane position; wherein, the capacity mapping table indicates a mapping relationship between the lane physical identification and the capacity interval.

[0045] In the embodiment of the present application and the following embodiments, the first capacity threshold indicates that the lane storage space is relatively small; the second capacity threshold indicates that the lane storage space is relatively large.

[0046] In the embodiment of the present application and the following embodiments, the first time threshold indicates that the expected crawling time is relatively short; the second time threshold indicates that the expected crawling time is relatively long.

[0047] In the embodiment of the present application and the following embodiments, the first numerical value indicates that the expected grasping accuracy is moderate; the second numerical value indicates that the expected grasping accuracy is high.

[0048] In some embodiments, the computer device divides the storage lanes into multiple logical partitions based on the capacity information of the liquid bag, the storage space and load-bearing information of the storage lanes, and each partition corresponds to a unique capacity interval; a capacity mapping table of the storage lanes and the capacity intervals is established, and the capacity mapping table is used to indicate the correspondence between the lane physical identification and the capacity interval; in response to receiving a grab operation instruction containing the target liquid bag capacity information, when the lane storage space is less than a first capacity threshold, the expected grab time is greater than or equal to the first time threshold and / or the expected grab accuracy rate is less than a first value, a capacity information parsing operation is performed; the capacity information is matched with the capacity mapping table, and the physical identification of the lane with successful matching is determined as the target lane position.

[0049] In an embodiment of the present application, in a small-scale, relatively concentrated warehousing and logistics scenario or one that requires a high-frequency response, the physical identification of the aisle that matches the capacity information is obtained by searching the capacity mapping table. Without the need for complex calculations, the grasping path can be determined through a simple table query, and the response speed is fast. The system structure is clear and simple, with low creation and maintenance costs and high stability, and is suitable for high-frequency liquid bag grasping scenarios.

[0050] In some embodiments, determining the target lane location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: Acquire attribute information and location data of each liquid bag placed in each storage lane based on radio frequency identification technology, if the lane storage space is greater than or equal to a first capacity threshold and less than a second capacity threshold, the expected grabbing time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grabbing accuracy is greater than or equal to a first value and less than a second value; wherein the attribute information includes the liquid bag capacity, content type, and batch number; Based on the capacity information and the attribute information, screening candidate storage lanes from the storage lanes; According to the distance factor, the inventory turnover factor and the load factor, a first target storage lane and the corresponding target lane position are determined from the candidate storage lanes.

[0051] In the embodiment of the present application, the distance factor may indicate the distance between the storage lane and the destination of the target liquid bag after it is grabbed. The distance factor may be determined based on an algorithm such as Euclidean distance, Chebyshev distance, or Manhattan distance.

[0052] In the embodiment of the present application, the inventory turnover factor may indicate the inventory turnover efficiency, that is, the number of times the liquid bag is deposited or retrieved within a predetermined time window.

[0053] In the embodiment of the present application, the load factor may indicate the load condition of the gripping assembly corresponding to the storage lane, or may indicate the ratio of the total weight of the liquid bags stored in the storage lane to the maximum rated load-bearing capacity of the lane.

[0054] In some embodiments, each liquid bag is configured with a unique RFID tag that stores the bag's attribute information; the attribute information includes the bag's capacity, content type, and batch number. An array of RFID readers is deployed at intervals within the storage lanes to form a spatial positioning network, enabling real-time collection of the liquid bag's location data and movement trajectory. In response to receiving a capture operation instruction containing target liquid bag capacity information, a computer device matches the capacity information with the attribute information and selects candidate storage lanes that meet the corresponding capacity information requirements. A weighted scoring model is established by assigning weight coefficients to the distance factor, inventory turnover factor, and load factor based on their importance. The distance factor, inventory turnover factor, and load factor of each candidate storage lane are collected in real time, and an evaluation score is calculated based on the weighted scoring model. The candidate storage lane corresponding to the highest evaluation score is determined as the first target storage lane; the location of the first target storage lane is determined as the target lane location.

[0055] In some embodiments, the computer device can dynamically adjust the weight coefficients corresponding to each factor based on the characteristics of the operating period; for example, when it is detected that the current time is in the peak period, the weight coefficients corresponding to the distance factor and the load factor can be dynamically increased to ensure that the needs of efficient and high-frequency capture of the target liquid bag are met.

[0056] In the embodiments of the present application, for medium-sized warehousing and logistics scenarios with high inventory accuracy requirements, RFID technology can be used to obtain the attribute information (capacity, expiration date, etc.) of the liquid bag in real time, improving the accuracy of grasping. The screening rules can be configured to screen by distance factor, inventory turnover factor, and load factor, and decisions can be made from multiple dimensions. Compared with screening the storage lanes by only a single factor, the adaptability and accuracy of the determined target lane location are further improved. In addition, the weight can be dynamically adjusted according to the operational data (for example, the shortest path is emphasized during peak hours, and the lowest energy consumption is emphasized during low-peak hours such as nighttime), thereby reducing energy consumption while ensuring grasping efficiency.

[0057] In some embodiments, determining the target lane location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: If the lane storage space is greater than or equal to a second capacity threshold, the expected grabbing time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grabbing accuracy is greater than or equal to a second value, the first storage lane is selected from the storage dynamic database based on the capacity information; wherein the storage dynamic database is used to record and store the liquid bag capacity, number of liquid bags, location data, and expiration date of each liquid bag in each storage lane; Based on the load of each first storage lane at the current moment and the usage of the grabbing components matching the first storage lane, and in combination with the path planning algorithm, an evaluation score is calculated respectively; Based on the evaluation score, a second target storage lane is selected from the first storage lanes and a corresponding position of the target lane is determined.

[0058] In some embodiments, a computer device constructs a dynamic warehouse database, using Structured Query Language (SQL) or a non-relational database (NoSQL) to store storage lane status information and liquid bag attribute information. Status information may include, but is not limited to, gripper component occupancy information, real-time load rate, and equipment health index; attribute information may include, but is not limited to, location data (three-dimensional coordinates), capacity information, number of liquid bags, expiration date, and batch code. Based on the gripper component occupancy information in the status information, the current usage status of the gripper component (e.g., robotic arm) matching each storage lane can be determined; based on the real-time load rate, the current load status of each storage lane can be determined. The computer device can update data changes in real time using a publish-subscribe model.

[0059] In some embodiments, the path planning algorithm is constructed in the following manner: Based on the lane positions of the storage lanes and the movement paths between the storage lanes, an initial topology map is constructed; wherein the nodes in the initial topology map are used to represent the storage lanes; and the links between the nodes in the initial topology map are used to represent the movement paths between the storage lanes; Assigning dynamic attribute information to each node to obtain a lane network topology diagram; wherein the dynamic attribute information includes capacity interval, path distance, and health index of the grabbing component corresponding to the storage lane; Based on the lane network topology map, the path planning algorithm is constructed.

[0060] In the embodiment of the present application, the path distance indicates the actual path length between the storage lane and the destination of the target liquid bag.

[0061] In some embodiments, the computer device can calculate the health index of the grasping component based on historical failure rates, maintenance records, etc.; when the health index is less than the health threshold, the weight assignment of the lane where the grasping component is located is dynamically reduced.

[0062] In some embodiments, the computer device uses storage lanes as nodes, and each node is associated with dynamic attributes; the moving paths between storage lanes are links, and the link weights are initialized to the path distance; an adjacency list or adjacency matrix is ​​used to represent the topology graph, and dynamic attribute updates are supported; the link weights are adjusted in real time according to the space occupancy rate in the storage lanes. For example, when the space occupancy rate is higher than the occupancy rate threshold, the link weight can be increased to reduce the overload of the storage lanes.

[0063] In some embodiments, the evaluation scores are calculated based on the load of each first storage lane at the current moment and the usage of the grabbing assembly matching the first storage lane, in combination with a path planning algorithm, including: selecting candidate storage lanes from the first storage lanes based on the number of liquid bags stored in the first storage lane at the current moment, the total weight of the liquid bags, the space occupancy rate, the expiration date, and the occupancy status of the grabbing assembly; and determining the evaluation score of each candidate storage lane based on the dynamic attribute information; The selecting a second target storage lane from the first storage lane based on the evaluation score includes: The candidate storage lane corresponding to the highest value of the evaluation scores is determined as the second target storage lane.

[0064] In some embodiments, in response to receiving a grabbing operation instruction containing target liquid bag capacity information, the computer device selects a first storage lane from the storage dynamic database based on the capacity information. For example, if the capacity information is 750ml, a set of candidate liquid bags that meet the requirements of 700ml to 800ml can be selected, and the storage lane where the candidate liquid bag set is located is determined to be the first storage lane; from the first storage lane, based on the number / total weight of the liquid bags, the space occupancy rate and the validity period of the lane, alternative storage lanes with short validity periods, large numbers and high space occupancy rates of the liquid bags are selected; based on the real-time load rate and grabbing component occupancy mark corresponding to the alternative storage lanes, combined with the path planning algorithm, the evaluation score corresponding to each alternative storage lane is calculated; the alternative storage lane corresponding to the highest value in the evaluation score is the second target storage lane, and the location of the second target storage lane is the target lane location.

[0065] For example, one way to determine the evaluation score of the candidate storage aisle is: Wherein, MJ indicates the evaluation score; D path Indicates the path distance; M fit Indicates capacity matching; Edev Indicates health index; w i Indicates the weight coefficient.

[0066] In the embodiments of the present application, in some large-scale warehousing and logistics scenarios with high efficiency and resource utilization and / or high precision requirements, optimal scheduling is achieved by comprehensively considering multi-dimensional factors (current usage of the grabbing component, aisle load, path length, capacity matching, etc.); it has strong scalability, can meet the collaborative operation of multiple grabbing components, and support complex business logic, such as concurrent grabbing and processing of multiple liquid bags, queue jumping for emergency tasks, etc., to meet the liquid bag grabbing needs in complex scenarios.

[0067] In the embodiments of the present application, the following provides specific examples in combination with any of the above embodiments: Specific example 1: Figure 3 FIG. 1 is a flow chart showing an exemplary computer device implementing a liquid bag grabbing control method; FIG. Figure 3 As shown, when the processor in the computer device executes the computer program, the following steps are implemented: S301, obtaining the capacity information and grasping performance index of the target liquid bag to be grasped.

[0068] In an optional embodiment, the grasping performance indicator includes performance parameters for measuring lane storage space, expected grasping efficiency and / or expected grasping accuracy.

[0069] S302 : Determine the target lane location for placing the target liquid bag based on the capacity information and a control strategy that matches the grabbing performance index.

[0070] In an optional embodiment, a control strategy adapted to the current application scenario is determined based on the grasping performance index; and a target lane position is determined based on the capacity information and the control strategy.

[0071] S303: Determine whether the target liquid bag is stored at the target lane position.

[0072] In an optional embodiment, if yes, proceed to S304; if no, proceed to S306.

[0073] S304: Control the grabbing component to move to the target lane position to perform a grabbing operation on the target liquid bag, and obtain a grabbing result of the target liquid bag.

[0074] In an optional embodiment, the computer device can implement dual detection of the target liquid bag grabbing result through the main detection unit / secondary detection unit provided on the grabbing component.

[0075] S305 , when the grabbing result is an unsuccessful grabbing, controlling the grabbing component to repeatedly perform the grabbing operation on the target liquid bag until the grabbing result is a successful grabbing.

[0076] In an optional embodiment, when the grasping result is successful, the grasping component is controlled to absorb the target liquid bag and move it to the destination.

[0077] S306: Output a warning prompt, which is used to remind the user that the target liquid bag does not exist at the target lane position.

[0078] In the above-mentioned liquid bag grasping control method, by obtaining the capacity information (such as volume and weight distribution) and grasping performance indicators of the target liquid bag in real time, a control strategy suitable for the current grasping scenario can be determined, which helps to improve the accuracy and efficiency of the grasping operation. On the one hand, it can reduce the losses caused by misgrasping or missing grasping, and on the other hand, it can speed up the processing speed and improve the operation efficiency. In addition, if the grasping is not successful, the grasping operation can be repeated on the target liquid bag until the target is met. This can ensure that each liquid bag is grasped correctly and efficiently automatically, reducing the need for manual intervention, thereby reducing the occurrence of human errors and improving the stability and reliability of the grasping work.

[0079] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0080] Based on the same inventive concept, embodiments of the present application also provide a liquid bag grabbing control device for implementing the aforementioned liquid bag grabbing control method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more embodiments of the liquid bag grabbing control device provided below can be found in the above-described limitations of the liquid bag grabbing control method and will not be further elaborated here.

[0081] In one embodiment, Figure 4 As shown, a liquid bag grabbing control device is provided, the device comprising: An acquisition module 10 is used to acquire the capacity information and grasping performance indicators of the target liquid bag to be grasped; wherein the grasping performance indicators include performance parameters for measuring the lane storage space, expected grasping efficiency and / or expected grasping accuracy; A screening module 20 is configured to determine a target lane location for placing the target liquid bag based on the capacity information and a control strategy that matches the grabbing performance index; The grabbing module 30 is used to control the grabbing component to move to the target lane position to grab the target liquid bag and obtain the grabbing result of the target liquid bag; The processing module 40 is configured to control the grabbing component to repeatedly perform the grabbing operation on the target liquid bag when the grabbing result is an unsuccessful grabbing, until the grabbing result is a successful grabbing.

[0082] In one embodiment, the screening module 20 is used to match the capacity information with the capacity mapping table to determine the target lane location when the lane storage space is less than a first capacity threshold, the expected capture time is less than a first time threshold, and / or the expected capture accuracy is less than a first value; wherein the capacity mapping table indicates the mapping relationship between the lane physical identification and the capacity interval.

[0083] In one embodiment, the screening module 20 is configured to perform the following steps: Acquire attribute information and location data of each liquid bag placed in each storage lane based on radio frequency identification technology, if the lane storage space is greater than or equal to a first capacity threshold and less than a second capacity threshold, the expected grabbing time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grabbing accuracy is greater than or equal to a first value and less than a second value; wherein the attribute information includes the liquid bag capacity, content type, and batch number; Based on the capacity information and the attribute information, screening candidate storage lanes from the storage lanes; According to the distance factor, the inventory turnover factor and the load factor, a first target storage lane and the corresponding target lane position are determined from the candidate storage lanes.

[0084] In one embodiment, the screening module 20 includes: a first screening unit configured to screen out first storage lanes from a storage dynamic database based on the capacity information, if the lane storage space is greater than or equal to a second capacity threshold, the expected grasping time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grasping accuracy is greater than or equal to a second value; wherein the storage dynamic database is configured to record and store the liquid bag capacity, number of liquid bags, location data, and expiration date of each liquid bag in each storage lane; and a scoring unit configured to calculate evaluation scores based on the current load status of each first storage lane and the usage status of the grasping assembly matching the first storage lane, in combination with a path planning algorithm. The second screening unit is configured to screen out a second target storage lane from the first storage lanes based on the evaluation score and determine a corresponding position of the target lane.

[0085] In one embodiment, the path planning algorithm is constructed in the following manner: Based on the lane positions of the storage lanes and the movement paths between the storage lanes, an initial topology map is constructed; wherein the nodes in the initial topology map are used to represent the storage lanes; and the links between the nodes in the initial topology map are used to represent the movement paths between the storage lanes; Assigning dynamic attribute information to each node to obtain a lane network topology diagram; wherein the dynamic attribute information includes capacity interval, path distance, and health index of the grabbing component corresponding to the storage lane; Based on the lane network topology map, the path planning algorithm is constructed.

[0086] In one embodiment, the scoring unit is configured to perform the following steps: Selecting an alternative storage lane from the first storage lane based on the number of liquid bags stored in the first storage lane at the current moment, the total weight of the liquid bags, the space occupancy rate, the expiration date, and the occupancy status of the grabbing assembly; Determining the evaluation score of each candidate storage lane based on the dynamic attribute information; The selecting a second target storage lane from the first storage lane based on the evaluation score includes: The candidate storage lane corresponding to the highest value of the evaluation scores is determined as the second target storage lane.

[0087] In one embodiment, the capture module 30 is configured to perform the following steps: Acquiring a first sensor signal value of the gripping component through a main detection unit; wherein the main detection unit includes at least two proximity switches arranged in orthogonal directions; the first sensor signal value is used to indicate the working state of the gripping component; obtaining a second sensor signal value of the gripping assembly through a secondary detection unit; wherein the secondary detection unit includes a position sensor; the main detection unit and the secondary detection unit are both disposed at a contact portion between the gripping assembly and the target fluid bag; and the second sensor signal value is used to indicate a detection distance between the gripping assembly and the target fluid bag; The grasping result is determined based on the first sensor signal value and / or the second sensor signal value.

[0088] Each module in the above-mentioned liquid bag grabbing control device can be implemented in whole or in part through software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor of the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of the above-mentioned modules.

[0089] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown. The computer device includes a processor, a memory, a communication interface, a display unit and an input device connected via a method bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating method and a computer program. The internal memory provides an environment for the operation of the operating method and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, an image processing method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0090] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0091] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0092] In one embodiment, a computer program product is provided, comprising a computer program, which implements the steps performed by a processor of a computer device when the computer program is executed by a processor.

[0093] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0094] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, and the like.

[0095] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0096] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A liquid bag grabbing control method, characterized in that: The method comprises: Obtaining capacity information and grasping performance indicators of the target liquid bag to be grasped; wherein the grasping performance indicators include performance parameters for measuring lane storage space, expected grasping efficiency and / or expected grasping accuracy; Determining a target lane location for placing the target liquid bag based on the capacity information and a control strategy that matches the grasping performance index; Controlling the grabbing assembly to move to the target lane position to perform a grabbing operation on the target liquid bag, and obtaining a grabbing result of the target liquid bag; When the grasping result is an unsuccessful grasping, the grasping component is controlled to repeatedly perform the grasping operation on the target liquid bag until the grasping result is a successful grasping.

2. The method according to claim 1, characterized in that The determining of the target lane position for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: When the lane storage space is less than a first capacity threshold, the expected grabbing time is less than a first time threshold, and / or the expected grabbing accuracy is less than a first value, the capacity information is matched with a capacity mapping table to determine the target lane position; wherein, the capacity mapping table indicates a mapping relationship between the lane physical identification and the capacity interval.

3. The method according to claim 1, characterized in that The determining of the target lane position for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: Acquire attribute information and location data of each liquid bag placed in each storage lane based on radio frequency identification technology, if the lane storage space is greater than or equal to a first capacity threshold and less than a second capacity threshold, the expected grabbing time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grabbing accuracy is greater than or equal to a first value and less than a second value; wherein the attribute information includes the liquid bag capacity, content type, and batch number; Based on the capacity information and the attribute information, screening candidate storage lanes from the storage lanes; According to the distance factor, the inventory turnover factor and the load factor, a first target storage lane and the corresponding target lane position are determined from the candidate storage lanes.

4. The method according to claim 1, wherein The determining of the target lane position for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index includes: If the lane storage space is greater than or equal to a second capacity threshold, the expected grabbing time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected grabbing accuracy is greater than or equal to a second value, the first storage lane is selected from the storage dynamic database based on the capacity information; wherein the storage dynamic database is used to record and store the liquid bag capacity, number of liquid bags, location data, and expiration date of each liquid bag in each storage lane; Based on the load of each first storage lane at the current moment and the usage of the grabbing components matching the first storage lane, and in combination with the path planning algorithm, an evaluation score is calculated respectively; Based on the evaluation score, a second target storage lane is selected from the first storage lanes and a corresponding position of the target lane is determined.

5. The method according to claim 4, characterized in that The path planning algorithm is constructed in the following ways: Based on the lane positions of the storage lanes and the movement paths between the storage lanes, an initial topology map is constructed; wherein the nodes in the initial topology map are used to represent the storage lanes; and the links between the nodes in the initial topology map are used to represent the movement paths between the storage lanes; Assigning dynamic attribute information to each node to obtain a lane network topology diagram; wherein the dynamic attribute information includes capacity interval, path distance, and health index of the grabbing component corresponding to the storage lane; Based on the lane network topology map, the path planning algorithm is constructed.

6. The method according to claim 5, characterized in that The evaluation scores are calculated based on the load conditions of each first storage lane at the current moment and the usage conditions of the grabbing components matching the first storage lanes, in combination with the path planning algorithm, including: Selecting an alternative storage lane from the first storage lane based on the number of liquid bags stored in the first storage lane at the current moment, the total weight of the liquid bags, the space occupancy rate, the expiration date, and the occupancy status of the grabbing assembly; Determining the evaluation score of each candidate storage lane based on the dynamic attribute information; The selecting a second target storage lane from the first storage lane based on the evaluation score includes: The candidate storage lane corresponding to the highest value of the evaluation scores is determined as the second target storage lane.

7. The method according to claim 1, characterized in that The obtaining of the grabbing result of the target liquid bag includes: Acquiring a first sensor signal value of the gripping component through a main detection unit; wherein the main detection unit includes at least two proximity switches arranged in orthogonal directions; the first sensor signal value is used to indicate the working state of the gripping component; obtaining a second sensor signal value of the gripping assembly through a secondary detection unit; wherein the secondary detection unit includes a position sensor; the main detection unit and the secondary detection unit are both disposed at a contact portion between the gripping assembly and the target fluid bag; and the second sensor signal value is used to indicate a detection distance between the gripping assembly and the target fluid bag; The grasping result is determined based on the first sensor signal value and / or the second sensor signal value.

8. A liquid bag grabbing control device, characterized in that: The device comprises: An acquisition module, configured to acquire capacity information and a grasping performance index of a target liquid bag to be grasped; wherein the grasping performance index includes performance parameters for measuring lane storage space, expected grasping efficiency, and / or expected grasping accuracy; a screening module, configured to determine a target lane location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index; a grabbing module, configured to control the grabbing assembly to move to the target lane position to perform a grabbing operation on the target liquid bag, and obtain a grabbing result of the target liquid bag; The processing module is used for controlling the grabbing component to repeatedly perform the grabbing operation on the target liquid bag when the grabbing result is an unsuccessful grabbing, until the grabbing result is a successful grabbing.

9. A computer device, characterized in that: The method comprises a processor and a memory for storing a computer program of the processor; wherein the processor is configured to implement the method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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