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

Abstract

The application relates to a liquid bag grabbing control method. The method comprises the following steps: acquiring capacity information and a grabbing performance index of a target liquid bag to be grabbed; determining a target lane position where the target liquid bag is placed based on the capacity information and a control strategy matched with the grabbing performance index; controlling a grabbing component to move to the target lane position to perform a grabbing operation on the target liquid bag, and acquiring a grabbing result of the target liquid bag; and in the case that 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. By acquiring the capacity information (such as volume and weight distribution) of the target liquid bag and the grabbing performance index in real time, the application can determine a control strategy suitable for the current grabbing scene, which helps to improve the accuracy and efficiency of the grabbing operation; and the need for manual intervention is reduced, thereby reducing the occurrence of human errors and improving the stability and reliability of the grabbing work.

Description

Technical Field

[0001] This application relates to the field of automation control technology, and in particular to a liquid bag gripping control method, device, electronic device and storage medium. Background Technology

[0002] In automated warehousing and logistics systems, the intelligent gripping and handling of liquid bag-type flexible packaging containers has always been a technical challenge. Traditional methods typically rely on static lane allocation strategies and single gripping performance indicators (such as fixed paths for robotic arms or preset gripping accuracy), making it difficult to dynamically adapt to the capacity differences and gripping efficiency requirements of different liquid bags. Static lane allocation is inefficient, while fixed lane allocation rules have significant shortcomings in multi-capacity matching and dynamic path planning, which may lead to congestion or resource waste, affecting overall warehousing efficiency.

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

[0004] Therefore, it is necessary to provide a liquid bag gripping control method, device, computer equipment, and storage medium to address the above-mentioned technical problems.

[0005] In a first aspect, this application provides a liquid bag gripping control method, the method comprising:

[0006] Obtain the capacity information and grasping performance indicators of the target liquid bag to be grasped; wherein, the grasping performance indicators include performance parameters used to measure the alleyway storage space, expected grasping efficiency and / or expected grasping accuracy.

[0007] Based on the capacity information and a control strategy that matches the grasping performance index, the target tunnel location for placing the target liquid bag is determined.

[0008] The gripping component is controlled to move to the target tunnel position to perform a gripping operation on the target liquid bag, and the gripping result of the target liquid bag is obtained;

[0009] If the grasping result is unsuccessful, the grasping component is controlled to repeatedly perform the grasping operation on the target liquid bag until the grasping result is successful.

[0010] In one embodiment, determining the target tunnel location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance indicators includes:

[0011] If the storage space of the lane is less than a first capacity threshold, the expected retrieval time is less than a first time threshold, and / or the expected retrieval accuracy is less than a first value, the capacity information is matched with the capacity mapping table to determine the location of the target lane; wherein, the capacity mapping table indicates the mapping relationship between the physical identifier of the lane and the capacity range.

[0012] In one embodiment, determining the target aisle location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance indicators includes:

[0013] When the storage space in the aisle is greater than or equal to a first capacity threshold and less than a second capacity threshold, the expected retrieval time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected retrieval accuracy is greater than or equal to a first value and less than a second value, the attribute information and location data of each liquid bag placed in each storage aisle are obtained based on radio frequency identification technology; wherein, the attribute information includes the liquid bag capacity, content type and batch number.

[0014] Based on the capacity information and the attribute information, candidate storage lanes are selected from the storage lanes;

[0015] Based on the distance factor, inventory turnover factor, and load factor, the first target storage lane and its corresponding location are determined from the candidate storage lanes.

[0016] In one embodiment, determining the target aisle location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance indicators includes:

[0017] If the storage space of the aisle is greater than or equal to the second capacity threshold, the expected retrieval time is greater than or equal to the first time threshold and less than the second time threshold, and / or the expected retrieval accuracy is greater than or equal to the second value, the first storage aisle 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 aisle;

[0018] Based on the current load status of each first storage lane and the usage status of the grasping component matched with the first storage lane, and combined with the path planning algorithm, the evaluation score is calculated respectively.

[0019] Based on the evaluation score, a second target storage lane is selected from the first storage lane and the corresponding target lane location is determined.

[0020] In one embodiment, the path planning algorithm is constructed in the following ways:

[0021] An initial topology map is constructed based on the location of the storage lanes and the movement paths between them; 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.

[0022] Dynamic attribute information is assigned to each node to obtain a lane network topology map; wherein, the dynamic attribute information includes capacity range, path distance, and the health index of the grasping component corresponding to the storage lane;

[0023] The path planning algorithm is constructed based on the aforementioned alleyway network topology.

[0024] In one embodiment, the evaluation score is calculated based on the load status of each first storage aisle at the current moment and the usage status of the grasping component matched with the first storage aisle, combined with a path planning algorithm, including:

[0025] Based on the number of liquid bags stored in the first storage aisle at the current moment, the total weight of the liquid bags, the space occupancy rate, the expiration date, and the occupancy status of the gripping component, candidate storage aisles are selected from the first storage aisles; based on the dynamic attribute information, the evaluation score of each candidate storage aisle is determined;

[0026] The step of selecting a second target storage lane from the first storage lane based on the evaluation score includes:

[0027] The candidate storage lane corresponding to the highest value in the evaluation score is determined as the second target storage lane.

[0028] In one embodiment, obtaining the grasping result of the target liquid bag includes:

[0029] The first sensing signal value of the grasping component is obtained through the main detection unit; wherein, the main detection unit includes at least two proximity switches arranged in orthogonal directions; the first sensing signal value is used to indicate the working state of the grasping component;

[0030] The second sensing signal value of the gripping component is obtained through a secondary detection unit; wherein, the secondary detection unit includes a position sensor; both the main detection unit and the secondary detection unit are disposed at the contact portion between the gripping component and the target liquid bag; the second sensing signal value is used to indicate the detection distance between the gripping component and the target liquid bag;

[0031] The grasping result is determined based on the first sensor signal value and / or the second sensor signal value.

[0032] Secondly, this application also provides a liquid bag gripping control device, the device comprising:

[0033] The acquisition module 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 used to measure the alleyway storage space, expected grasping efficiency and / or expected grasping accuracy.

[0034] The screening module is used to determine the target tunnel location for placing the target liquid bag based on the capacity information and a control strategy that matches the grasping performance index.

[0035] The grasping module is used to control the grasping component to move to the target tunnel position to grasp the target liquid bag and obtain the grasping result of the target liquid bag;

[0036] The processing module is configured to control the grasping component to repeatedly perform the grasping operation on the target liquid bag when the grasping result is unsuccessful, until the grasping result is successful.

[0037] Thirdly, this application also provides a computer device, including 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 described in any embodiment of this application.

[0038] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the methods described in any embodiment of this application.

[0039] In the aforementioned liquid bag grasping control method, by acquiring the target liquid bag's capacity information (such as volume and weight distribution) and grasping performance indicators in real time, a control strategy adapted to the current grasping scenario can be determined, which helps improve the accuracy and efficiency of the grasping operation. On the one hand, it can reduce losses caused by misgrabbing or missed grasping; on the other hand, it can speed up processing and improve operational efficiency. Furthermore, if the grasping operation fails, the target liquid bag can be repeatedly grasped until the target is met, ensuring that each liquid bag is grasped correctly and efficiently and automatically, reducing the need for manual intervention, thereby reducing the occurrence of human error and improving the stability and reliability of the grasping operation. Attached Figure Description

[0040] Figure 1 This is an application environment diagram illustrating a liquid bag gripping control method according to an exemplary embodiment;

[0041] Figure 2 This is a flowchart illustrating a liquid bag gripping control method according to an exemplary embodiment;

[0042] Figure 3 This is a flowchart illustrating a liquid bag gripping control method according to an exemplary embodiment;

[0043] Figure 4 This is a structural block diagram of a liquid bag gripping control device according to an exemplary embodiment;

[0044] Figure 5 This is an internal structural diagram of a computer device according to an exemplary embodiment. Detailed Implementation

[0045] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0046] The terms "first," "second," and "third" used in the embodiments of this application are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0047] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0048] In some embodiments, the liquid bag gripping control method provided in this application can be applied to, for example... Figure 1In the illustrated application environment, computer device 102 communicates with grasping component 104 and data acquisition component 106 via a network. Computer device 102 can control grasping component 104 to grasp liquid bags stored in the storage aisle, and data acquisition component 106 can collect relevant data that computer device 102 needs to process in real time (e.g., attribute information and location data of each liquid bag placed in the storage aisle). Computer device 102 can be any mobile terminal or fixed terminal. A terminal can be a device that provides voice and / or data connectivity to a user. For example, a terminal can be an Internet of Things (IoT) terminal, such as a sensor device, a mobile phone or so-called "cellular" phone, and a computer with an IoT terminal; for example, it can be a fixed, portable, pocket-sized, handheld, or computer-embedded device. Data acquisition component can include at least one of Radio Frequency Identification (RFID), various types of sensors (such as weight sensors), proximity switches, and image acquisition devices.

[0049] In some embodiments, the computer device and the data acquisition component can be connected via network communication; the network communication connection can include wired and wireless connections. For example, the data acquisition component and the computer device can be connected via a wired connection through a physical medium, where data transmission occurs over a physical line, offering higher stability and speed. Alternatively, the data acquisition component and the computer device can be connected wirelessly via wireless technology, where data transmission is not limited by physical lines, providing greater flexibility.

[0050] In some embodiments, such as Figure 2 As shown, a liquid bag gripping control method is provided, the method comprising the following steps:

[0051] S201, Obtain the capacity information and grasping performance indicators of the target liquid bag to be grasped; wherein, the grasping performance indicators include performance parameters used to measure the alleyway storage space, expected grasping efficiency and / or expected grasping accuracy.

[0052] In this embodiment of the application, the capacity information may include, but is not limited to, at least one of the following: liquid bag size, liquid bag weight, and liquid bag shape.

[0053] In this embodiment of the application, the aisle storage space indicates the maximum amount of liquid that the storage aisle can provide for the liquid bag.

[0054] In this embodiment, the expected grasping efficiency indicator is a prediction and assessment of the successful execution speed of grasping operations in an automated warehousing or logistics system. Expected grasping efficiency can be used to measure the ability to accurately and efficiently complete a grasping operation within a given time.

[0055] In some embodiments, the expected crawling efficiency may include, but is not limited to, at least one parameter among expected crawling time and failure / success rate.

[0056] In this embodiment, the expected grasping accuracy is a metric used to measure the accuracy of grasping operations in an automated warehousing or logistics system. Expected grasping accuracy characterizes the ability of a grasping system to successfully and accurately grasp a target liquid bag from a target aisle location and place it at the correct destination.

[0057] S202, based on the capacity information and a control strategy that matches the grasping performance index, determine the target tunnel location for placing the target liquid bag.

[0058] In one embodiment, the computer device can perform a preliminary screening of storage lanes based on the specific attributes of the liquid bag (such as capacity, shape, etc.) to determine the third storage lane; and based on the performance parameter matching control strategy of the grasping component, select the target storage lane from the third storage lane to determine the location of the target lane.

[0059] S203, control the gripping component to move to the target tunnel position to perform a gripping operation on the target liquid bag, and obtain the gripping result of the target liquid bag.

[0060] In one embodiment, before controlling the gripping component to move to the target aisle location, the computer device can determine whether the target storage aisle corresponding to the target aisle currently stores a target liquid bag; if the target storage aisle stores a target liquid bag, the gripping component is controlled to move to the target aisle location to grip the target liquid bag.

[0061] In some embodiments, obtaining the grasping result of the target liquid bag includes:

[0062] The first sensing signal value of the grasping component is obtained through the main detection unit; wherein, the main detection unit includes at least two proximity switches arranged in orthogonal directions; the first sensing signal value is used to indicate the working state of the grasping component;

[0063] The second sensing signal value of the gripping component is obtained through a secondary detection unit; wherein, the secondary detection unit includes a position sensor; both the main detection unit and the secondary detection unit are disposed at the contact portion between the gripping component and the target liquid bag; the second sensing signal value is used to indicate the detection distance between the gripping component and the target liquid bag;

[0064] The grasping result is determined based on the first sensor signal value and / or the second sensor signal value.

[0065] In this embodiment, the proximity switch can be used to detect the position, limit, and count of mechanical moving parts. The proximity switch may include, but is not limited to, at least one of capacitive proximity switches, inductive proximity switches, and photoelectric proximity switches.

[0066] In some embodiments, the first sensor signal value indicates the operating state of the gripping component. For example, a first sensor signal value of 1 indicates that the gripping component has successfully gripped the target liquid bag, while a first sensor signal value of 0 indicates that the gripping component has failed to grip the target liquid bag or has released the target liquid bag. The computer device can acquire one or more first sensor signal values ​​in real time through a main detection unit mounted on the gripping component. For example, a first switch in the main detection unit is used to confirm whether the target liquid bag has been successfully gripped, and a second switch is used to detect the risk of the target liquid bag falling off. When multiple first sensor signal values ​​indicate successful gripping, it can be determined that the gripping component has successfully gripped the target liquid bag. Thus, by using multi-directional redundant detection, such as installing multiple proximity switches in orthogonal directions, the occurrence of single-point failures can be reduced, ensuring the accuracy of the detection.

[0067] In this embodiment, the secondary detection unit can be used to detect grasping force, grasping posture, and detection distance. The secondary detection unit may include, but is not limited to, at least one of piezoelectric / capacitive force sensors and position sensors.

[0068] In some embodiments, when the secondary detection unit includes a force sensor, the second sensing signal value can also be used to indicate the gripping force of the gripping component. A computer device can acquire one or more second sensing signal values ​​in real time through the secondary detection unit disposed on the gripping component. If the second sensing signal value representing the gripping force is greater than a detection force threshold and / or the second sensing signal value representing the detection distance is less than or equal to a detection distance threshold, it can be determined that the gripping result is consistent with the expected target, and the gripping component has successfully gripped the target liquid bag.

[0069] 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.

[0070] For example, the expression for the mapping function between detection distance and liquid bag size characteristics is: Wherein, D indicates the detection distance; V bag Indicates the capacity of the liquid bag; k1 and k2 indicate the calibration coefficients; ΔD indicates the safety margin; S indicates the size characteristics of the liquid bag.

[0071] In one embodiment, external interference factors such as mechanical vibration and accidental jumps in current and voltage can lead to misjudgments of the working status of the gripping component; for example, mechanical vibration can cause fluctuations in the acquired first and / or second sensor signal values. To more accurately determine the working status of the gripping component, the computer device can delay acquiring the first and / or second sensor signal values ​​after the gripping operation is completed, reducing misjudgments caused by the shaking of the target liquid bag during gripping, which may result in the gripping component not being able to fully grasp the object. Alternatively, if 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, the computer device can repeatedly acquire multiple corresponding sensor signal values ​​to reduce the interference of external interference factors on the detection of the working status of the gripping component.

[0072] In one embodiment, if both the first and second sensor signal values ​​indicate that the gripping component has successfully gripped the target liquid bag, the gripping result is determined to be successful; if either sensor signal value indicates that the gripping component has failed to grip the target liquid bag, the gripping result is determined to be unsuccessful.

[0073] S204, if the grasping result is unsuccessful, control the grasping component to repeatedly perform the grasping operation on the target liquid bag until the grasping result is successful.

[0074] In some embodiments, if the previous grasping result was unsuccessful, the computer device can control the grasping component to repeatedly perform the grasping action on the target liquid bag; after completing the grasping action, it can reacquire the first sensor signal value and / or the second sensor signal value, and judge the grasping result based on the first sensor signal value and / or the second sensor signal value, until the grasping result is successful, at which point the computer device controls the grasping component to stop the grasping action and move the successfully grasped target liquid bag to the destination.

[0075] In the aforementioned liquid bag grasping control method, by acquiring the target liquid bag's capacity information (such as volume and weight distribution) and grasping performance indicators in real time, a control strategy adapted to the current grasping scenario can be determined, which helps improve the accuracy and efficiency of the grasping operation. On the one hand, it can reduce losses caused by misgrabbing or missed grasping; on the other hand, it can speed up processing and improve operational efficiency. Furthermore, if the grasping operation fails, the target liquid bag can be repeatedly grasped until the target is met, ensuring that each liquid bag is grasped correctly and efficiently and automatically, reducing the need for manual intervention, thereby reducing the occurrence of human error and improving the stability and reliability of the grasping operation.

[0076] In some embodiments, determining the target aisle location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance indicators includes:

[0077] If the storage space of the lane is less than a first capacity threshold, the expected retrieval time is less than a first time threshold, and / or the expected retrieval accuracy is less than a first value, the capacity information is matched with the capacity mapping table to determine the location of the target lane; wherein, the capacity mapping table indicates the mapping relationship between the physical identifier of the lane and the capacity range.

[0078] In the embodiments of this application and the following embodiments, the first capacity threshold indicates that the roadway storage space is relatively small; the second capacity threshold indicates that the roadway storage space is relatively large.

[0079] In the embodiments of this application and the following embodiments, the first time threshold indicates that the expected capture time is relatively short; the second time threshold indicates that the expected capture time is relatively long.

[0080] In the embodiments of this application and the following embodiments, the first numerical value indicates that the expected capture accuracy is moderate; the second numerical value indicates that the expected capture accuracy is high.

[0081] In some embodiments, the computer device divides the storage aisle into multiple logical partitions based on the liquid bag capacity information, the storage space of the storage aisle, and the load-bearing information, with each partition corresponding to a unique capacity range; establishes a capacity mapping table between the storage aisle and the capacity range, the capacity mapping table indicating the correspondence between the physical identifier of the aisle and the capacity range; when the aisle storage space is less than a first capacity threshold, the expected grasping time is greater than or equal to a first time threshold, and / or the expected grasping accuracy is less than a first value, in response to receiving a grasping operation instruction containing the target liquid bag capacity information, performs a capacity information parsing operation; matches the capacity information with the capacity mapping table, and determines the successfully matched aisle physical identifier as the target aisle location.

[0082] In this embodiment, in small-scale, relatively concentrated, or high-frequency warehousing and logistics scenarios, the physical identifier of the lane matching the capacity information is obtained by looking up the capacity mapping table. No complex calculations are required, and the grabbing path can be determined by a simple table query, resulting in fast response speed. The system has a clear and simple structure, low creation and maintenance costs, and high stability, making it suitable for high-frequency grabbing of liquid bags.

[0083] In some embodiments, determining the target aisle location for placing the target liquid bag based on the capacity information and a control strategy matched with the grasping performance indicators includes:

[0084] When the storage space in the aisle is greater than or equal to a first capacity threshold and less than a second capacity threshold, the expected retrieval time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected retrieval accuracy is greater than or equal to a first value and less than a second value, the attribute information and location data of each liquid bag placed in each storage aisle are obtained based on radio frequency identification technology; wherein, the attribute information includes the liquid bag capacity, content type and batch number.

[0085] Based on the capacity information and the attribute information, candidate storage lanes are selected from the storage lanes;

[0086] Based on the distance factor, inventory turnover factor, and load factor, the first target storage lane and its corresponding location are determined from the candidate storage lanes.

[0087] In this embodiment, the distance factor can indicate the distance between the storage aisle and the destination after the target liquid bag is grasped. The distance factor can be determined according to algorithms such as Euclidean distance, Chebyshev distance, or Manhattan distance.

[0088] In this embodiment of the application, the inventory turnover rate factor can indicate the inventory turnover efficiency, that is, the number of times the liquid bag is stored or retrieved within a predetermined time window.

[0089] In this embodiment of the application, the load factor can indicate the load status of the gripping component corresponding to the storage aisle, or it can indicate the ratio of the total weight of the liquid bags stored in the storage aisle to the maximum rated load of the aisle.

[0090] In some embodiments, each liquid bag is equipped with a unique RFID tag, which stores the bag's attribute information, including bag capacity, contents type, and batch number. RFID reader arrays are deployed at intervals within the storage aisles to form a spatial positioning network, enabling real-time collection of liquid bag location data and movement trajectories. Upon receiving a grabbing command containing target liquid bag capacity information, the computer equipment matches the capacity information with the attribute information, filtering out candidate storage aisles that meet the corresponding capacity requirements. Weighted coefficients are assigned to distance factors, inventory turnover factors, and load factors according to their importance, establishing a weighted scoring model. The distance factors, inventory turnover factors, and load factors of each candidate storage aisle are collected in real-time, and an evaluation score is calculated based on the weighted scoring model. The candidate storage aisle corresponding to the highest evaluation score is determined as the first target storage aisle; the location of the first target storage aisle is the target aisle location.

[0091] In some embodiments, the computer device can dynamically adjust the weight coefficients of each factor according to the characteristics of the operating period; for example, when it is detected that the current time is during a peak period, the weight coefficients of the distance factor and the load factor can be dynamically increased to ensure that the requirements for efficient and high-frequency grasping of target liquid bags are met.

[0092] In this embodiment, for medium-sized warehousing and logistics scenarios with high inventory accuracy requirements, RFID technology can acquire real-time attribute information (capacity, expiration date, etc.) of liquid bags, improving the accuracy of grasping. The filtering rules are configurable, allowing for filtering based on distance factors, inventory turnover rate factors, and load factors. This multi-dimensional decision-making further improves the adaptability and accuracy of the determined target aisle location compared to filtering based on a single factor. Furthermore, the weights can be dynamically adjusted based on operational data (e.g., prioritizing the shortest path during peak periods and prioritizing the lowest energy consumption during off-peak periods such as nighttime), reducing energy consumption while ensuring grasping efficiency.

[0093] In some embodiments, determining the target aisle location for placing the target liquid bag based on the capacity information and a control strategy matched with the grasping performance indicators includes:

[0094] If the storage space of the aisle is greater than or equal to the second capacity threshold, the expected retrieval time is greater than or equal to the first time threshold and less than the second time threshold, and / or the expected retrieval accuracy is greater than or equal to the second value, the first storage aisle 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 aisle;

[0095] Based on the current load status of each first storage lane and the usage status of the grasping component matched with the first storage lane, and combined with the path planning algorithm, the evaluation score is calculated respectively.

[0096] Based on the evaluation score, a second target storage lane is selected from the first storage lane and the corresponding target lane location is determined.

[0097] In some embodiments, the computer device constructs a dynamic warehouse database, using Structured Query Language (SQL) or NoSQL to store the status information of the warehouse aisles and the attribute information of the liquid bags. The status information may include, but is not limited to, gripper component occupancy indicators, real-time load rates, and equipment health indices. The attribute information may include, but is not limited to, location data (3D coordinates), capacity information, number of liquid bags, expiration dates, and batch codes. Based on the gripper component occupancy indicators in the status information, the usage status of the gripper components (such as robotic arms) matched to each warehouse aisle at the current moment can be determined. Based on the real-time load rate, the load status of each warehouse aisle at the current moment can be determined. The computer device can update data changes in real time using a publish-subscribe model.

[0098] In some embodiments, the path planning algorithm is constructed in the following ways:

[0099] An initial topology map is constructed based on the location of the storage lanes and the movement paths between them; 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.

[0100] Dynamic attribute information is assigned to each node to obtain a lane network topology map; wherein, the dynamic attribute information includes capacity range, path distance, and the health index of the grasping component corresponding to the storage lane;

[0101] The path planning algorithm is constructed based on the aforementioned alleyway network topology.

[0102] In this embodiment of the application, the path distance indicates the actual path length between the storage aisle and the destination of the target liquid bag.

[0103] In some embodiments, the computer device can calculate the health index of the grasping component based on historical failure rates, maintenance records, etc.; if the health index is less than the health threshold, the weight of the roadway where the grasping component is located can be dynamically reduced.

[0104] In some embodiments, the computer device uses storage aisles as nodes, and each node is associated with dynamic attributes; the movement path between storage aisles is a link, and the link weight is initialized to the path distance; the topology graph is represented by an adjacency list or adjacency matrix, which supports dynamic attribute updates; the link weight is dynamically adjusted in real time according to the space occupancy rate in the storage aisles. For example, when the space occupancy rate is high and exceeds the occupancy rate threshold, the link weight can be increased to reduce the overload of the storage aisles.

[0105] In some embodiments, the step of calculating evaluation scores based on the load status of each first storage aisle at the current moment and the usage status of the grasping component matched with the first storage aisle, combined with a path planning algorithm, includes: selecting candidate storage aisles from the first storage aisles based on the number of liquid bags stored in the first storage aisles at the current moment, the total weight of the liquid bags, the space occupancy rate, the expiration date, and the occupancy status of the grasping component; and determining the evaluation score of each candidate storage aisle based on the dynamic attribute information.

[0106] The step of selecting a second target storage lane from the first storage lane based on the evaluation score includes:

[0107] The candidate storage lane corresponding to the highest value in the evaluation score is determined as the second target storage lane.

[0108] In some embodiments, in response to receiving a grasping operation instruction containing target liquid bag capacity information, the computer device filters out a first storage aisle from a dynamic storage database based on the capacity information. For example, if the capacity information is 750ml, a set of candidate liquid bags with a capacity between 700ml and 800ml can be filtered out, and the storage aisle where the candidate liquid bag set is located is determined as the first storage aisle. From the first storage aisle, candidate storage aisles with short expiration dates, a large number of liquid bags, and high space occupancy rates are filtered out based on the number / total weight of liquid bags, the space occupancy rate of the aisle, and the expiration date. Based on the real-time load rate and grasping component occupancy indicator of the candidate storage aisles, combined with a path planning algorithm, an evaluation score is calculated for each candidate storage aisle. The candidate storage aisle with the highest evaluation score is the second target storage aisle, and the location of the second target storage aisle is the target aisle location.

[0109] For example, one way to determine the evaluation score of candidate storage lanes is as follows: Among them, MJ indicates the assessment score; D path Indicates path distance; M fit Indicator capacity matching; E dev Indicator of health index; w i Indicator weighting coefficient.

[0110] In this embodiment of the application, in some large-scale warehousing and logistics scenarios with high requirements for efficiency, resource utilization and / or accuracy, optimal scheduling is achieved by comprehensively considering multiple factors (current usage of the grasping component, lane load, path length, capacity matching, etc.); it has strong scalability, can meet the collaborative operation of multiple grasping components, and support complex business logic, such as concurrent grasping and processing of multiple liquid bags, and emergency task queueing, thus meeting the liquid bag grasping needs in complex scenarios.

[0111] In this application embodiment, specific examples are provided below in conjunction with any of the above embodiments:

[0112] Specific example 1: Figure 3 This is a schematic flowchart illustrating a liquid bag gripping control method implemented by a computer device as an example; such as Figure 3 As shown, when a processor in a computer device executes a computer program, it performs the following steps:

[0113] S301, Obtain the capacity information and grasping performance indicators of the target liquid bag to be grasped.

[0114] In one alternative embodiment, the crawling performance metrics include performance parameters used to measure laneway storage space, expected crawling efficiency, and / or expected crawling accuracy.

[0115] S302 determines the target tunnel location for placing the target liquid bag based on capacity information and a control strategy that matches the grasping performance indicators.

[0116] In one optional embodiment, a control strategy adapted to the current application scenario is determined based on the capture performance indicators; the target tunnel location is determined based on the capacity information and the control strategy.

[0117] S303, Determine whether the target liquid bag is stored at the target roadway location.

[0118] In an alternative embodiment, if yes, proceed to S304; otherwise, proceed to S306.

[0119] S304, control the gripping component to move to the target tunnel position to perform a gripping operation on the target liquid bag, and obtain the gripping result of the target liquid bag.

[0120] In an alternative embodiment, the computer device can perform dual detection of the target liquid bag grasping result through a main detection unit / sub-detection unit disposed on the grasping assembly.

[0121] S305, if the grasping result is unsuccessful, control the grasping component to repeatedly perform the grasping operation on the target liquid bag until the grasping result is successful.

[0122] In an optional embodiment, if the grasping result is successful, the grasping component is controlled to adsorb the target liquid bag and move it to the destination.

[0123] S306, outputs a warning message. The warning message is used to remind the user that the target liquid bag does not exist at the target tunnel location.

[0124] In the aforementioned liquid bag grasping control method, by acquiring the target liquid bag's capacity information (such as volume and weight distribution) and grasping performance indicators in real time, a control strategy adapted to the current grasping scenario can be determined, which helps improve the accuracy and efficiency of the grasping operation. On the one hand, it can reduce losses caused by misgrabbing or missed grasping; on the other hand, it can speed up processing and improve operational efficiency. Furthermore, if the grasping operation fails, the target liquid bag can be repeatedly grasped until the target is met, ensuring that each liquid bag is grasped correctly and efficiently and automatically, reducing the need for manual intervention, thereby reducing the occurrence of human error and improving the stability and reliability of the grasping operation.

[0125] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0126] Based on the same inventive concept, this application also provides a liquid bag gripping control device for implementing the liquid bag gripping control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of the one or more liquid bag gripping control device embodiments provided below can be found in the limitations of the liquid bag gripping control method described above, and will not be repeated here.

[0127] In one embodiment, such as Figure 4 As shown, a liquid bag gripping control device is provided, the device comprising:

[0128] The 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 used to measure the alleyway storage space, expected grasping efficiency and / or expected grasping accuracy.

[0129] The screening module 20 is used to determine the target tunnel location for placing the target liquid bag based on the capacity information and a control strategy that matches the grasping performance index.

[0130] The grasping module 30 is used to control the grasping component to move to the target tunnel position to grasp the target liquid bag and obtain the grasping result of the target liquid bag;

[0131] The processing module 40 is used to control the gripping component to repeatedly perform the gripping operation on the target liquid bag when the gripping result is unsuccessful, until the gripping result is successful.

[0132] In one embodiment, the filtering module 20 is used to match the capacity information with a capacity mapping table to determine the location of the target lane when the lane storage space is less than a first capacity threshold, the expected retrieval time is less than a first time threshold, and / or the expected retrieval accuracy is less than a first value; wherein, the capacity mapping table indicates the mapping relationship between lane physical identifiers and capacity ranges.

[0133] In one embodiment, the filtering module 20 is configured to perform the following steps:

[0134] When the storage space in the aisle is greater than or equal to a first capacity threshold and less than a second capacity threshold, the expected retrieval time is greater than or equal to a first time threshold and less than a second time threshold, and / or the expected retrieval accuracy is greater than or equal to a first value and less than a second value, the attribute information and location data of each liquid bag placed in each storage aisle are obtained based on radio frequency identification technology; wherein, the attribute information includes the liquid bag capacity, content type and batch number.

[0135] Based on the capacity information and the attribute information, candidate storage lanes are selected from the storage lanes;

[0136] Based on the distance factor, inventory turnover factor, and load factor, the first target storage lane and its corresponding location are determined from the candidate storage lanes.

[0137] In one embodiment, the filtering module 20 includes:

[0138] The first filtering unit is used to filter out the first storage lane from the storage dynamic database based on the capacity information when the lane storage space is greater than or equal to the second capacity threshold, the expected grasping time is greater than or equal to the first time threshold and less than the second time threshold, and / or the expected grasping accuracy is greater than or equal to the second value; 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; the scoring unit is used to calculate the evaluation score based on the load status of each first storage lane at the current time and the usage status of the grasping component matched with the first storage lane, and in combination with the path planning algorithm.

[0139] The second screening unit is used to screen out a second target storage lane from the first storage lane based on the evaluation score and determine the corresponding location of the target lane.

[0140] In one embodiment, the path planning algorithm is constructed in the following ways:

[0141] An initial topology map is constructed based on the location of the storage lanes and the movement paths between them; 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.

[0142] Dynamic attribute information is assigned to each node to obtain a lane network topology map; wherein, the dynamic attribute information includes capacity range, path distance, and the health index of the grasping component corresponding to the storage lane;

[0143] The path planning algorithm is constructed based on the aforementioned alleyway network topology.

[0144] In one embodiment, the scoring unit is configured to perform the following steps:

[0145] Based on the number of liquid bags stored in the first storage aisle at the current moment, the total weight of the liquid bags, the space occupancy rate, the expiration date, and the occupancy status of the gripping component, candidate storage aisles are selected from the first storage aisles.

[0146] Based on the dynamic attribute information, the evaluation score of each candidate storage lane is determined;

[0147] The step of selecting a second target storage lane from the first storage lane based on the evaluation score includes:

[0148] The candidate storage lane corresponding to the highest value in the evaluation score is determined as the second target storage lane.

[0149] In one embodiment, the grasping module 30 is configured to perform the following steps:

[0150] The first sensing signal value of the grasping component is obtained through the main detection unit; wherein, the main detection unit includes at least two proximity switches arranged in orthogonal directions; the first sensing signal value is used to indicate the working state of the grasping component;

[0151] The second sensing signal value of the gripping component is obtained through a secondary detection unit; wherein, the secondary detection unit includes a position sensor; both the main detection unit and the secondary detection unit are disposed at the contact portion between the gripping component and the target liquid bag; the second sensing signal value is used to indicate the detection distance between the gripping component and the target liquid bag;

[0152] The grasping result is determined based on the first sensor signal value and / or the second sensor signal value.

[0153] Each module in the above-mentioned liquid bag grasping control device can be implemented in whole or in part through software, hardware or a combination thereof. Each module can be embedded in the processor of the computer device in hardware form or independent of the processor, or it can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0154] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5 As shown, the computer device includes a processor, memory, communication interface, display unit, and input device connected via a method bus. The processor provides computational and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores operating methods and computer programs. The internal memory provides an environment for the operation of the operating methods and computer programs stored in the non-volatile storage medium. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements an image processing method. The display screen can be an LCD screen or an e-ink display screen. The input device can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the computer device casing, or an external keyboard, touchpad, or mouse.

[0155] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0156] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0157] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps performed by the processor of the computer device of any of the above.

[0158] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0159] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0160] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0161] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for controlling the gripping of a liquid bag, characterized in that, The method includes: Obtain the capacity information and grasping performance indicators of the target liquid bag to be grasped; wherein, the grasping performance indicators include performance parameters used to measure the alleyway storage space, expected grasping efficiency, and expected grasping accuracy. Based on the capacity information and a control strategy matching the grasping performance indicators, the target aisle location for placing the target liquid bag is determined, including: when the aisle storage space is greater than or equal to a second capacity threshold, and 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, a first storage aisle 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 aisle; based on the load status of each first storage aisle at the current moment and the usage status of the grasping components matched with the first storage aisle, and combined with a path planning algorithm, an evaluation score is calculated respectively; based on the evaluation score, a second target storage aisle is selected from the first storage aisles and the corresponding target aisle location is determined; The gripping component is controlled to move to the target tunnel position to perform a gripping operation on the target liquid bag, and the gripping result of the target liquid bag is obtained; If the grasping result is unsuccessful, the grasping component is controlled to repeatedly perform the grasping operation on the target liquid bag until the grasping result is successful.

2. The liquid bag gripping control method according to claim 1, characterized in that, The determination of the target tunnel location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance indicators includes: If the storage space of the lane is less than a first capacity threshold, or the expected retrieval time is less than a first time threshold, or the expected retrieval accuracy is less than a first value, the capacity information is matched with the capacity mapping table to determine the location of the target lane; wherein, the capacity mapping table indicates the mapping relationship between the physical identifier of the lane and the capacity range.

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

4. The liquid bag gripping control method according to claim 1, characterized in that, The path planning algorithm is constructed in the following ways: An initial topology map is constructed based on the location of the storage lanes and the movement paths between them; 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. Dynamic attribute information is assigned to each node to obtain a lane network topology map; wherein, the dynamic attribute information includes capacity range, path distance, and the health index of the grasping component corresponding to the storage lane; The path planning algorithm is constructed based on the aforementioned alleyway network topology.

5. The liquid bag gripping control method according to claim 4, characterized in that, The evaluation score is calculated based on the load status of each first storage aisle at the current moment and the usage status of the grasping component matched with the first storage aisle, combined with the path planning algorithm, including: Based on the number of liquid bags stored in the first storage aisle at the current moment, the total weight of the liquid bags, the space occupancy rate, the expiration date, and the occupancy status of the gripping component, candidate storage aisles are selected from the first storage aisle. Based on the dynamic attribute information, the evaluation score of each candidate storage lane is determined; The step of 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 in the evaluation score is determined as the second target storage lane.

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

7. A liquid bag gripping control device, characterized in that, The device includes: The acquisition module 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 used to measure the alleyway storage space, expected grasping efficiency, and expected grasping accuracy. A filtering module is used to determine the target aisle location for placing the target liquid bag based on the capacity information and a control strategy matching the grasping performance index. This includes: filtering a first storage aisle from a dynamic storage database based on the capacity information, provided that the aisle storage space is greater than or equal to a second capacity threshold, and 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 dynamic storage database records and stores the liquid bag capacity, number of liquid bags, location data, and expiration date of each liquid bag in each storage aisle; calculating evaluation scores based on the current load of each first storage aisle and the usage of the grasping components matched with the first storage aisle, combined with a path planning algorithm; and filtering a second target storage aisle from the first storage aisles based on the evaluation scores and determining the corresponding target aisle location. The grasping module is used to control the grasping component to move to the target tunnel position to grasp the target liquid bag and obtain the grasping result of the target liquid bag; The processing module is configured to control the grasping component to repeatedly perform the grasping operation on the target liquid bag when the grasping result is unsuccessful, until the grasping result is successful.

8. A computer device, characterized in that, The device includes a processor and a memory for storing a computer program for the processor; wherein the processor is configured to, when executing the computer program, implement the liquid bag gripping control method as described in any one of claims 1 to 6.

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

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