Material extraction method, device and system, electronic equipment and storage medium

Abstract

The invention discloses a material extraction method, device and system, electronic equipment and a storage medium, and relates to the technical field of material extraction, and the method comprises the steps: obtaining material region information and target region information; setting a plurality of scoring factors according to the material area information and the target area information, and allocating a corresponding weight to each scoring factor; obtaining a scoring result according to the summation of the scoring factor of each material area and the corresponding weight product; and selecting an optimal material area according to the scoring result, and extracting materials from the optimal material area to the target area. The problem that the material extraction efficiency is low due to the fact that existing material extraction lacks control logic for optimizing a plurality of material areas can be solved.

Description

Technical Field

[0001] This application relates to the field of material extraction technology, and in particular to a material extraction method, a material extraction device, a material extraction system, an electronic device, and a computer-readable storage medium. Background Technology

[0002] In industrial applications, module materials are often stacked on pallets to form multiple material stacking areas, requiring the transfer of materials and pallets.

[0003] Existing technologies can achieve material transfer using mechanical equipment. For example, patent application CN111017558A designs a material extraction device, including a base, a material carrier, and a suction cup-type material extraction component. The extraction component is controlled by a trigger signal sent by a detection element to move to a preset position and extract material. However, this solution relies solely on trigger signals for material extraction and is only applicable to simple material extraction applications. If there are many material stacking areas, it becomes difficult to determine the optimal order for extracting material from multiple stacking areas, resulting in low material transfer efficiency.

[0004] Therefore, in the field of material extraction, there are currently only simple material extraction scenarios that rely on direct material extraction based on detection signals. Methods for optimal material extraction in multiple regions urgently need to be developed. Summary of the Invention

[0005] To overcome the shortcomings of the prior art, the present invention provides a material extraction method, apparatus, system, electronic device and storage medium, which can solve the problem that the existing material extraction lacks control logic for optimizing multiple material zones, resulting in low material extraction efficiency.

[0006] On one hand, embodiments of the present invention propose a material extraction method, comprising: acquiring material area information and target area information; setting a plurality of scoring factors according to the material area information and the target area information, and assigning a corresponding weight to each scoring factor; obtaining a scoring result by summing the products of the scoring factors and the corresponding weights of each material area; selecting the optimal material area according to the scoring result, and extracting material from the optimal material area to the target area.

[0007] In one embodiment of the present invention, setting several scoring factors includes: based on the material area i Set the movement cost score based on the relationship between the distance to the target area and the maximum distance from all material areas to the target area; based on the material area i The current layer number of the placed material and the material area i The relationship between the total number of layers is used to set the priority score for clearing and replenishing materials; based on the material area. iThe relationship between the distance from empty pallets to empty pallet areas and the maximum distance from empty pallets to empty pallet areas across all material areas is used to set the empty pallet transfer cost score; and based on the material area... i Current material quantity and material area at the top layer i The material density fraction is set according to the relationship between the amount of material that can be placed on each layer.

[0008] In one embodiment of the present invention, assigning a corresponding weight to each of the rating factors includes: dynamically optimizing the weights according to a genetic algorithm to obtain the optimal weights in real time, and assigning the optimal weights to the corresponding rating factors.

[0009] In one embodiment of the present invention, the step of dynamically optimizing the weights during the material extraction task using a genetic algorithm includes: generating an initial population containing several individuals, each individual representing a set of weight parameters corresponding to the scoring factor; obtaining the fitness of each set of weight parameters through multiple rounds of simulation tasks; selecting the parent individuals of the next generation based on the fitness; generating a new individual by crossing over at a certain point between every two parent individuals, and forming a new generation population from the new individuals; repeating the above steps until a set number of generations is reached and then outputting the optimal weights.

[0010] In one embodiment of the present invention, the material extraction method further includes a regeneration mechanism: the optimal weights output by the genetic algorithm are evaluated by a cycle time; if the cycle time requirement is met, the optimal weights are output; if not, the genetic algorithm is restarted for a new round of optimization.

[0011] On the other hand, embodiments of the present invention also propose a material extraction device, comprising: an information acquisition module for acquiring material area information and target area information; a scoring factor setting module for setting a plurality of scoring factors according to the material area information and the target area information, and assigning a corresponding weight to each scoring factor; a scoring result obtaining module for obtaining a scoring result by summing the products of the scoring factors and the corresponding weights of each material area; and a material area selection module for selecting the optimal material area according to the scoring result, and extracting material from the optimal material area to the target area.

[0012] Furthermore, this invention also proposes a material extraction system, comprising: a material sensing device and a material extraction device; the material sensing device includes: a material zone sensing unit, including at least two reflective photoelectric sensors, respectively used to detect the presence status of each layer of material and tray in the material zone; an empty tray zone sensing unit, including at least one reflective photoelectric sensor, used to detect the presence status of each layer of tray in the empty tray zone; the reflective photoelectric sensors are fixed to a column by a mounting plate and are respectively aligned with specific positions of the material or tray for reflective detection; the material sensing device sends the detected information to the material extraction device, and the material extraction device executes the material extraction method as described in any of the above embodiments.

[0013] In one embodiment of the present invention, the material area sensing unit and / or the empty pallet area sensing unit further includes a reflective photoelectric sensor mounted on the base for secondary confirmation of the presence status of the pallet.

[0014] In another aspect, embodiments of the present invention also provide an electronic device, comprising: a memory and one or more processors connected to the memory, the memory storing a computer program, and the processors executing the computer program to implement the material extraction method as described in any of the above embodiments.

[0015] In another aspect, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions for performing the material extraction method as described in any of the above embodiments.

[0016] As can be seen from the above, the embodiments of the present invention, compared with the prior art, can have at least one or more of the following beneficial effects: 1) By acquiring material area information and target area information, setting scoring factors and corresponding weights to characterize the selection priority of each material area, the equipment can find the optimal area when performing material extraction tasks, thereby improving material extraction and operation efficiency. 2) A genetic algorithm is used to dynamically optimize the weight of each scoring factor during the material extraction task, so as to accurately evaluate the material area score under the current situation in real time, and select the optimal material extraction area based on the scoring results. 3) By improving the genetic algorithm and introducing a rebirth mechanism, multiple starting points are used to try to escape local optima, which increases the fault tolerance mechanism and improves the probability of global optima. This reduces the impact of traditional genetic algorithms getting stuck in local optima, especially when the search space is complex and the evaluation is random. In addition, the algorithm incorporates a key cycle robustness check to ensure that the algorithm can be applied to industrial deployment and avoid the situation where the output does not meet the cycle requirements but is put into production, thus affecting production. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings: Figure 1 A flowchart of a material extraction method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the execution logic of the improved genetic algorithm provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the structure of a material extraction device provided in an embodiment of the present invention; Figure 4a This is a schematic diagram of the structure of a material sensing device provided in an embodiment of the present invention; Figure 4b This is a schematic diagram of a multi-layer material placement structure provided in an embodiment of the present invention; Figure 5a This is a schematic diagram of the structure of an empty pallet sensing device provided in an embodiment of the present invention; Figure 5b This is a schematic diagram of a multi-layer empty pallet placement structure provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention; Figure 7 This is a schematic diagram of the structure of a computer-readable storage medium provided in an embodiment of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described with reference to the accompanying drawings and embodiments.

[0019] To enable those skilled in the art to better understand the technical solutions of the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments, and should all fall within the protection scope of the present invention.

[0020] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are applicable in distinguishing similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such terms can be used interchangeably where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or applicable to such processes, methods, products, or apparatus.

[0021] It should also be noted that the division of multiple embodiments in this invention is only for the convenience of description and should not constitute a special limitation. Features in various embodiments can be combined and referenced in each other without contradiction.

[0022] In industrial applications, materials are often stacked on pallets to form material stacking areas. During production, materials need to be extracted from these areas, while empty pallet stacking areas exist. The empty pallets after material extraction must be transferred to these empty pallet areas. Existing material extraction solutions only determine the location of materials by detecting signals and then control the equipment to move to that location to extract the materials. This lacks optimal control logic for multiple material stacking areas, resulting in low material extraction efficiency.

[0023] The first embodiment of this invention relates to a material extraction method, which can be applied to various material transfer equipment (such as robots with automatic gripping and transfer functions). Figure 1 As shown, the method includes: step S1, obtaining material area information and target area information; step S2, setting several scoring factors according to the material area information and the target area information, and assigning a corresponding weight to each scoring factor; step S3, obtaining a scoring result by summing the products of the scoring factors and the corresponding weights of each material area; step S4, selecting the optimal material area according to the scoring result, and extracting materials from the optimal material area to the target area.

[0024] The material extraction method proposed in the first embodiment of this invention obtains material area information and target area information, sets scoring factors and corresponding weights to characterize the selection priority of each material area, enabling the material transfer equipment to find the optimal area when performing material extraction tasks, thus achieving efficient and continuous material handling. The following is a detailed description of the implementation of a material extraction method according to an embodiment of this invention. The following content is only for ease of understanding and is not essential for implementing this solution.

[0025] Specifically, in step S1, the material area information obtained by the material transfer equipment includes, for example, the location of the material area, the number of material area layers, the quantity of materials, and the quantity of empty pallets; the target area information includes, for example, the target area location to which the materials need to be transported and the empty pallet area location to which the empty pallets need to be transported.

[0026] In step S2, based on the above material area information and target area information, for example, the following four scoring factors are set: Moving cost score The closer the material in the material area is to the target area, the higher the score. The calculation formula is as follows: ; in, For material area i Distance to the target area; This represents the maximum distance from all material areas to the target area.

[0027] Clear replenishment priority score The fewer layers of materials currently placed in the material area, the higher the priority of replenishment and the higher the score. The calculation formula is as follows: ; in, For material area i The current layer number of the placed material; For material area i Total number of floors.

[0028] Empty pallet transfer cost score The closer the distance between empty pallets in the material area and the empty pallet area, the higher the score. The calculation formula is as follows: ; in, For material area i Distance between empty pallets and empty pallet areas; This represents the maximum distance between empty pallets in all material areas.

[0029] Material density fraction The lower the material density in the uppermost layer of the material zone, the higher the score. The calculation formula is as follows: ; in, For material area i Current quantity of materials at the top layer; For material area i The number of materials that can be placed on each floor.

[0030] Therefore, the score for each material zone can be expressed as: ; In the formula, These are the weights of the four scoring items.

[0031] Furthermore, during material handling, the quantity of materials changes in real time, making it impossible to accurately assess the score of the material area under the current circumstances using fixed weights. In one embodiment of the present invention, a genetic algorithm is used to dynamically optimize the weights during the material extraction task to obtain the optimal weights in real time; these optimal weights are then assigned to the corresponding scoring factors for subsequent real-time scoring of each material area, and the optimal material area is selected based on the results of the real-time scoring.

[0032] In one embodiment of the present invention, the specific steps of the genetic algorithm include: 1) Initialize the population Generate an initial population containing N individuals (solutions), each individual It is a vector of length 4, representing a set of weight parameters: ,

[0033] 2) Fitness assessment Each individual The average fitness value will be obtained by substituting it into the following fitness function and simulating the task multiple times. In other words, the performance of this set of weights:

[0034] Where K represents the number of rounds of the simulation task, and N represents the number of material zones.

[0035] 3) Select The next generation's parent is selected using a roulette wheel selection method, based on fitness values. Higher fitness individuals are more likely to be selected, and the selection probability is expressed as:

[0036] 4) Cross From two parent individuals A new individual is generated by crossing at a certain point in the middle:

[0037] in, It is a random intersection point.

[0038] 5) Mutation Each new individual has a small probability of perturbing a certain gene (vector), introducing diversity and causing it to mutate. This ensures that the algorithm does not get trapped in local optima too early, and is represented as: ,

[0039] 6) Update the population and iterate. The new individuals generated by crossover mutation form a new generation, represented as:

[0040] Repeat the above steps until the maximum number of generations is reached, and output the optimal weights of this genetic algorithm. However, since the genetic algorithm is a heuristic algorithm, it cannot guarantee a global optimum and may obtain a local optimum. In one embodiment of the present invention, as... Figure 2 As shown, a rebirth mechanism is added to the genetic algorithm: the optimal output weights are evaluated over time, and the evaluation formula is as follows:

[0041] in, This represents the total time taken for the robot to move. The time required for the robot to grasp materials; The time required to place materials on the robot.

[0042] Calculate the total time (i.e., cycle time) for each robot to pick up material from the material area to the target area. If the preset cycle time requirement is met, the weight is output as the final weight. If the requirement is not met, the robot will respawn, returning to the starting point to try to find the optimal solution again. There may be cases where the robot escapes local optima, finds the global optimum, and completes the search, in which case the optimal weight is output. If, after reaching the set number of respawns, an optimal solution that meets the cycle time requirement cannot be found, the algorithm terminates, and a message indicating a mismatch between the cycle time setting and the material setting is output.

[0043] In step S3, the improved algorithm based on the genetic algorithm described above can be used to score each material zone in real time. The scoring method is the same as the simulation task described above. The scoring result can be obtained by summing the product of the scoring factor and the corresponding weight of each material zone. The scoring result can represent the selection priority of each material zone. The higher the score, the higher the selection priority.

[0044] In step S4, the optimal material zone can be selected based on the scoring results, and materials can be extracted from the optimal material zone to the target zone. In summary, the first embodiment of this invention proposes a material extraction method. By acquiring material area information and target area information, and setting scoring factors and corresponding weights to characterize the selection priority of each material area, the device can find the optimal area when performing material extraction tasks, thereby improving the efficiency of material extraction and operation. A genetic algorithm is used to dynamically optimize the weights of each scoring factor during the material extraction process, thereby enabling real-time and accurate evaluation of the material area score under the current situation, and selecting the optimal material extraction area based on the scoring results through game theory. By improving the genetic algorithm and introducing a rebirth mechanism, multiple starting points are used to try to escape local optima, increasing the fault tolerance mechanism and improving the probability of global optima, thereby reducing the impact of traditional genetic algorithms getting stuck in local optima, especially in cases where the search space is complex and the evaluation has randomness. Furthermore, the algorithm incorporates a key cycle robustness check to ensure that the algorithm can be applied to industrial deployment, avoiding situations where the output results do not meet the cycle requirements but are still put into production, thus affecting production.

[0045] In addition, such as Figure 3 As shown, the second embodiment of the present invention also proposes a material extraction device 20, including: an information acquisition module 201, a scoring factor setting module 202, a priority characterization module 203, and a material zone selection module 204. The information acquisition module 201 is used to acquire material zone information and target zone information; the scoring factor setting module 202 is used to set several scoring factors according to the material zone information and the target zone information, and assign corresponding weights to each scoring factor; the scoring result obtaining module 203 is used to obtain a scoring result by summing the products of the scoring factors and corresponding weights for each material zone; the material zone selection module 204 is used to select the optimal material zone according to the scoring result, and extract material from the optimal material zone to the target zone.

[0046] It should be noted that the material extraction method implemented by the material extraction device 20 disclosed in the second embodiment of the present invention is as described in the first embodiment above, and therefore will not be described in detail here. Optionally, each module and the other operations or functions described above are for implementing the method described in the first embodiment, and the beneficial effects of the material extraction device 20 provided in this embodiment are the same as the beneficial effects of the material extraction method provided in the first embodiment above. For the sake of brevity, they will not be described in detail here.

[0047] A third embodiment of the present invention provides a material extraction system, including a material sensing device and a material extraction device. The material sensing device includes a material area sensing unit and an empty tray area sensing unit. For example... Figure 4a The diagram shows material area A, which consists of two stacked layers with two materials per layer. Pallets 1 and 2 are stacked on material area A, and materials 3 and 4 are placed on pallet 2.

[0048] On the left side of material area A is a material sensing device. A reflective photoelectric sensor 12 is mounted on a column 13 via a connecting mounting plate 11 (all reflective photoelectric sensors on the column are connected and installed in this way). The photoelectric signal emitted by the photoelectric sensor is aimed at the enclosure of the tray 1 to detect the presence of the tray 1. When the tray 1 is present, the photoelectric signal emitted by the reflective photoelectric sensor 12 is reflected by the tray, thereby receiving a signal and sensing the presence of the tray. When there is no tray, there is no signal.

[0049] In one embodiment, a reflective photoelectric sensor 14 is installed on the base of material area A. The photoelectric signal emitted by the sensor is aligned with the bottom of the tray to provide secondary confirmation of whether the tray 1 is detected and to confirm whether material area A has been emptied.

[0050] A reflective photoelectric sensor 10 is also installed on the column 13. This sensor is aimed at one of the materials on the tray 1 to detect its presence. The detection of the other material in the same layer is achieved by a reflective photoelectric sensor 6 installed on the column 7. Thus, the presence of the tray and the two materials in that layer can be successfully detected. Similarly, the tray 2 is detected by a reflective photoelectric sensor 9 installed on the column 13, and the materials 3 and 4 placed on it are detected by reflective photoelectric sensors 8 and 5, respectively. This embodiment describes a case with only two layers and two materials per layer. In practice, this solution can be applied to cases with more material layers and more materials per layer, such as… Figure 4b As shown, simply adding or removing the same layer configuration is sufficient to achieve the sensing of the quantity of materials in each layer and the number of pallets in each layer.

[0051] like Figure 5a The diagram shows an empty pallet placement area B that can be stacked in two layers. A reflective photoelectric sensor 3 is mounted on a column 4 via a connecting mounting plate 2 to detect the presence of the bottom layer pallets. In one embodiment, a reflective photoelectric sensor 5 is installed on the base of the empty pallet area B for secondary confirmation of the presence or absence of the bottom layer pallets, confirming whether the empty pallet area B has been emptied. A reflective photoelectric sensor 1 is also installed on the column 4 to detect the presence of the upper layer pallets, thus successfully sensing the number of pallet layers in the empty pallet area B. Similarly, this embodiment describes the case of only two stacked empty pallets; in practice, this solution can be applied to cases with multiple layers of empty pallets, such as... Figure 5b As shown, the number of empty tray layers can be detected simply by adding or removing the same layer configuration.

[0052] The material sensing device sends the detected information to the material extraction device, and the material extraction device performs the material extraction method as described in the first embodiment.

[0053] It should be noted that the material extraction method implemented by the material extraction system disclosed in the third embodiment of the present invention is as described in the first embodiment above, and therefore will not be described in detail here. Optionally, each module and the other operations or functions described above in the second embodiment are for implementing the method described in the first embodiment, and the beneficial effects of the material extraction system provided in this embodiment are the same as the beneficial effects of the material extraction method provided in the first embodiment above. For the sake of brevity, they will not be described again here.

[0054] like Figure 6 As shown, the fourth embodiment of the present invention also proposes an electronic device 30, which includes, for example, at least one processing unit 31 and at least one storage unit 32, wherein the storage unit 32 stores a computer program, and when the computer program is executed by the processing unit 31, the processing unit 31 performs the method described in the first embodiment, and the beneficial effects of the electronic device 30 provided in this embodiment are the same as the beneficial effects of the material extraction method provided in the first embodiment.

[0055] like Figure 7 As shown, the fifth embodiment of the present invention also provides a computer-readable storage medium 40, on which a computer program is stored. When the program is executed by a processor, it implements the steps of the above-described method. The beneficial effects of the computer-readable storage medium 40 provided in this embodiment are the same as those of the material extraction method provided in the first embodiment.

[0056] The computer-readable storage medium may include, but is not limited to, any type of disk, including floppy disks, optical disks, DVDs, CD-ROMs, microdrives, as well as magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic cards or optical cards, nanosystems (including molecular memory ICs), or any type of medium or device suitable for storing instructions and / or data.

[0057] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0058] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0059] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some service interface; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0060] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0061] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0062] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0063] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0064] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Those skilled in the art will readily conceive of embodiments of this disclosure upon considering the specification and practicing the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

[0065] 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.

[0066] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A method for extracting materials, characterized in that, include: Obtain material area information and target area information; Several scoring factors are set based on the material area information and the target area information, and a corresponding weight is assigned to each scoring factor; The scoring result is obtained by summing the products of the scoring factors and the corresponding weights for each material zone; The optimal material zone is selected based on the scoring results, and materials are extracted from the optimal material zone to the target zone.

2. The material extraction method according to claim 1, characterized in that, The step of setting several scoring factors based on the material area information and the target area information includes: According to the material area i The relationship between the distance to the target area and the maximum distance from all material areas to the target area is used to set the movement cost score; According to the material area i The current layer number of the placed material and the material area i The relationship between the total number of layers is set to clear the priority score for material replenishment; According to the material area i The relationship between the distance from empty pallets to empty pallet areas and the maximum distance from empty pallets to empty pallet areas across all material areas is used to set an empty pallet transfer cost score; and... According to the material area i Current material quantity and material area at the top layer i The material density fraction is set according to the relationship between the amount of material that can be placed on each layer.

3. The material extraction method according to claim 1, characterized in that, Assigning a corresponding weight to each of the scoring factors includes: The weights are dynamically optimized using a genetic algorithm to obtain the optimal weights in real time, and then the optimal weights are assigned to the corresponding scoring factors.

4. The material extraction method according to claim 3, characterized in that, The step of dynamically optimizing the weights using a genetic algorithm includes: Generate an initial population containing a number of individuals, each of which represents a set of weight parameters corresponding to the scoring factor; The fitness of each set of weight parameters is obtained by performing multiple rounds of simulation tasks. The parent individuals of the next generation are selected based on the fitness. A new individual is generated by crossing over at a certain point between every two parent individuals, and the new individuals form a new generation of the population. Repeat the above steps until the set number of algebras is reached, at which point the optimal weight is output.

5. The material extraction method according to claim 4, characterized in that, Also includes: The optimal weights output by the genetic algorithm are evaluated using cycle time. If the cycle time requirement is met, then the optimal weight is output; If the conditions are not met, the genetic algorithm is restarted for a new round of optimization.

6. A material extraction device, characterized in that, include: The information acquisition module is used to acquire information about the material area and the target area. The scoring factor setting module is used to set several scoring factors based on the material area information and the target area information, and to assign corresponding weights to each scoring factor; The scoring result acquisition module is used to obtain the scoring result by summing the products of the scoring factors and the corresponding weights for each material zone; The material selection module is used to select the optimal material area based on the scoring results, and extract materials from the optimal material area to the target area.

7. A material extraction system, characterized in that, include: Material sensing device and material extraction device; The material sensing device includes: The material area sensing unit includes at least two reflective photoelectric sensors, which are used to detect the presence status of materials and trays in each layer of the material area. The empty pallet area sensing unit includes at least one reflective photoelectric sensor for detecting the presence status of each layer of pallets in the empty pallet area; The reflective photoelectric sensor is fixed to the column by a mounting plate and is aligned with a specific position of the material or pallet for reflective detection. The material sensing device sends the detected information to the material extraction device, and the material extraction device performs the material extraction method as described in any one of claims 1-5.

8. The material extraction system according to claim 7, characterized in that, The material area sensing unit and / or the empty pallet area sensing unit further include a reflective photoelectric sensor mounted on the base for secondary confirmation of the pallet's presence status.

9. An electronic device, characterized in that, include: A memory and one or more processors connected to the memory, the memory storing a computer program, the processors being configured to execute the computer program to implement the material extraction method as described in any one of claims 1-5.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable commands for performing the material extraction method as described in any one of claims 1-5.

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