Unmanned loader scheduling method and system, industrial personal computer and storage medium

Abstract

The embodiment of the invention provides an unmanned loader scheduling method and system, an industrial personal computer and a storage medium. The method comprises the following steps: determining a target hopper to be loaded from at least one hopper based on a specified scheduling mode; determining a plurality of material piles corresponding to the target hopper based on a preset mapping relation between hoppers and the material piles; obtaining point cloud data, collected by the unmanned loader through a visual sensor, of each material pile; for each material pile, determining a priority score of the material pile based on the point cloud data of the material pile; according to the priority score of each material pile, determining a to-be-fetched target material pile from the plurality of material piles; generating a scheduling task based on the information of the target hopper and the target material pile, and issuing the scheduling task to the unmanned loader; wherein the scheduling task is used for instructing the unmanned loader to take materials from the target material pile and unload the taken materials into the target hopper. According to the method, the intelligent degree of the unmanned loader during feeding operation is improved, so that the operation efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of production resource scheduling, and particularly to a scheduling method, system, industrial control computer and storage medium for an unmanned loader. Background Art

[0002] With the continuous increase of infrastructure construction projects in China, concrete has been widely used. For concrete mixing plants, partial automated production control has been achieved currently, but there are still many intelligent difficulties in some aspects. For example, the replenishment of aggregates during the production process still requires manual control, that is, the loader driver operates the loader to feed materials according to the situation at the operation site, resulting in an increase in the management difficulty and a decrease in the production efficiency of the concrete mixing plant. In response to the problem of manual feeding of aggregates, some manufacturers have developed unmanned loaders with autonomous feeding functions. However, currently, most unmanned loaders still adopt manual scheduling methods to perform feeding operations, resulting in low intelligence and low operation efficiency during the feeding operations of unmanned loaders. Summary of the Invention

[0003] Embodiments of the present application provide a scheduling method, system, industrial control computer and storage medium for an unmanned loader, which are used to improve the problems of low intelligence and low operation efficiency during the feeding operations of unmanned loaders.

[0004] In a first aspect, embodiments of the present application provide a scheduling method for an unmanned loader, including:

[0005] Determining a target hopper to be fed from at least one hopper based on a specified scheduling mode;

[0006] Determining a plurality of stockpiles corresponding to the target hopper based on a pre-set mapping relationship between the hopper and the stockpile;

[0007] Obtaining point cloud data of each stockpile collected by the unmanned loader through a vision sensor;

[0008] For each stockpile, determining a priority score of the stockpile based on the point cloud data of the stockpile;

[0009] Determining a target stockpile to be retrieved from the plurality of stockpiles according to the priority scores of the stockpiles;

[0010] Generating a scheduling task based on the information of the target hopper and the target stockpile, and sending the scheduling task to the unmanned loader; wherein, the scheduling task is used to instruct the unmanned loader to retrieve materials from the target stockpile and unload the retrieved materials into the target hopper.

[0011] Second aspect, an unmanned loader scheduling system provided by an embodiment of the present application includes: a human-computer interaction module, a communication module, and an industrial control computer respectively connected to the human-computer interaction module and the communication module;

[0012] The human-computer interaction module is used for information interaction with an external object, and the information at least includes hopper information of a mixing plant, material information corresponding to the hopper, a mapping relationship between the hopper and the stockpile, and target hopper information to be loaded;

[0013] The communication module is used for communication between the industrial control computer and the unmanned loader, and between the industrial control computer and the production control system of the mixing plant;

[0014] The industrial control computer is used to execute the steps of the unmanned loader scheduling method provided in the first aspect of the embodiment of the present application.

[0015] Third aspect, an industrial control computer provided by an embodiment of the present application includes a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, the steps of the unmanned loader scheduling method provided in the first aspect of the embodiment of the present application are implemented.

[0016] Fourth aspect, a computer-readable storage medium provided by an embodiment of the present application stores a computer program thereon. When the computer program is executed by a processor, the steps of the unmanned loader scheduling method provided in the first aspect of the embodiment of the present application are implemented.

[0017] The technical solution provided by the embodiment of the present application determines a target hopper to be loaded from at least one hopper through a specified scheduling mode. At the same time, it can also obtain the point cloud data of the stockpile corresponding to the target hopper collected by the unmanned loader through a vision sensor, determine the priority score of each stockpile based on the point cloud data of each stockpile, automatically determine the target stockpile to be retrieved based on the priority score of each stockpile, and automatically generate a scheduling task of retrieving materials from the target stockpile and loading them onto the target hopper based on the information of the target hopper and the target stockpile, thereby realizing the automatic generation of the unmanned loader loading operation scheduling task, reducing the degree of manual participation in the unmanned loader loading operation scheduling process, reducing the risk of loading the wrong material due to manual loading, improving the intelligent level during the unmanned loader loading operation, and thus improving the operation efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 is a schematic flowchart of an unmanned loader scheduling method provided by an embodiment of the present application;

[0019] Figure 2 is a schematic flowchart of a process for determining the priority score of a stockpile provided by an embodiment of the present application;

[0020] Figure 3 Another schematic flowchart of the unmanned loader scheduling method provided by the embodiment of the present application;

[0021] Figure 4 Yet another schematic flowchart of the unmanned loader scheduling method provided by the embodiment of the present application;

[0022] Figure 5 A schematic structural diagram of the unmanned loader scheduling system provided by the embodiment of the present application;

[0023] Figure 6 Another schematic structural diagram of the unmanned loader scheduling system provided by the embodiment of the present application;

[0024] Figure 7 A schematic structural diagram of the industrial control computer provided by the embodiment of the present application. Detailed implementation manners

[0025] In order to make the purpose, technical solutions and advantages of the present application clearer, the technical solutions in the embodiments of the present application will be further described in detail through the following embodiments in combination with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application. Those skilled in the art can adjust it as needed to suit the specific application scenarios. Additionally, it should be noted that for the sake of convenience of description, only parts related to the present application rather than all structures are shown in the accompanying drawings.

[0026] For the convenience of understanding by those skilled in the art, some concepts involved in the embodiments of the present application are introduced first:

[0027] Stockpile: The place where raw materials (mostly aggregates) of the mixing plant are stacked.

[0028] Hopper: A funnel-shaped container installed on the production line of the mixing plant for feeding.

[0029] Router: A hardware device that connects two or more networks, acting as a gateway between networks. It is a dedicated intelligent network device that reads the address in each data packet and then decides how to transmit.

[0030] AC: The full name is Access Controller, that is, an access controller. It is a network device used to centrally control several controllable wireless APs within a local area network.

[0031] AP: The full name is Access Point, that is, a wireless access point. The main function of the AP is to convert a wired network into a wireless network to achieve wireless coverage of the network.

[0032] Mixing plant production control system: It adopts an industrial control computer, I / O acquisition, and a high-precision weighing system. According to the concrete production process and quality requirements, it realizes data acquisition and full-automatic production control through control software, and records production data information in real time. The data management module can be used to query / print various production reports.

[0033] Construction mix information: It refers to the proportional relationship between the various constituent materials in concrete.

[0034] LiDAR: A radar that uses a laser as a radiation source. LiDAR is a product of the combination of laser technology and radar technology, and is composed of a transmitter, an antenna, a receiver, a tracking frame, and information processing, etc.

[0035] CAN: It is the abbreviation of Controller Area Network (hereinafter referred to as CAN), and is an ISO international standard serial communication protocol. CANET is a CAN data converter.

[0036] Switch: It means "switch" and is a network device used for electrical (optical) signal forwarding. It can provide an exclusive electrical signal path for any two network nodes connected to the switch.

[0037] Ethernet: It is the most widely used local area network, including standard Ethernet (10Mbit / s), Fast Ethernet (100Mbit / s), and 10G (10Gbit / s) Ethernet.

[0038] Pad: That is, a tablet computer, which is a small and portable personal computer with a touch screen as the basic input device.

[0039] Unmanned loader control system: That is, a vehicle electronic control system, which is composed of sensors, electronic controllers, control program software, etc., is used in conjunction with the mechanical system on the vehicle, and uses cables or radio waves to transmit messages to each other for "mechatronics integration".

[0040] Point cloud: A set of point data on the product appearance surface obtained by a measuring instrument in reverse engineering.

[0041] Farthest Point Sampling: Uniformly sample m points on a point cloud of n points so that these points can better represent the overall contour of the point cloud. Its basic idea is to select a starting point from the point cloud, and then select the point with the farthest distance from the selected point among the remaining points as the next selected point.

[0042] Figure 1It is a schematic flowchart of an unmanned loader scheduling method provided by an embodiment of this application. This method can be applied to an industrial control computer. Hereinafter, taking the execution subject as an industrial control computer as an example, as Figure 1 shown, this method may include:

[0043] S101. Determine a target hopper to be loaded from at least one hopper based on a specified scheduling mode.

[0044] In this embodiment, the unmanned loader supports multiple scheduling modes. For example, the first scheduling mode and the second scheduling mode. The first scheduling mode can be a full-automatic scheduling mode, that is, both the target hopper to be loaded and the target stockpile to be retrieved are intelligently identified through algorithms. The second scheduling mode can be a semi-automatic scheduling mode, etc., that is, the target stockpile to be retrieved can be intelligently identified through algorithms, and the target hopper to be loaded can be obtained through user specification. Therefore, the industrial control computer can determine the target hopper to be loaded from at least one hopper based on the currently specified scheduling mode of the unmanned loader.

[0045] Exemplarily, when the currently specified scheduling mode of the unmanned loader is the first scheduling mode, the industrial control computer can intelligently match the target hopper to be loaded currently based on a certain algorithm. When the currently specified scheduling mode of the unmanned loader is the second scheduling mode, the industrial control computer can obtain the information of the hopper specified by the user through the human-computer interaction module, and use the hopper specified by the user as the target hopper to be loaded. Optionally, the above human-computer interaction module can be a display terminal, such as a large display screen or a computer (such as a Pad).

[0046] S102. Determine multiple stockpiles corresponding to the target hopper based on the pre-set mapping relationship between the hopper and the stockpile.

[0047] In the actual operation process, there may be multiple hoppers and multiple stockpiles. The industrial control computer can obtain the mapping relationship between the hopper and the stockpile set by the user through the human-computer interaction module, and save this mapping relationship in the database. After determining the target hopper to be loaded, the industrial control computer queries multiple stockpiles corresponding to the target hopper from the above mapping relationship based on the identifier of the target hopper.

[0048] S103. Obtain the point cloud data of each stockpile collected by the unmanned loader through the vision sensor.

[0049] The above visual sensor can be a lidar, a depth camera, a structured light sensor, a 3D laser scanner, etc. The above visual sensor is installed at the vehicle end of the unmanned loader, and the unmanned loader can collect the point cloud data of the material piles in the mixing plant through the visual sensor. In practical applications, before the unmanned loader executes the operation task for the first time, the unmanned loader can be controlled to scan each material pile in the mixing plant through the visual sensor, and store the point cloud data of the scanned material piles in the database; during the walking process of the unmanned loader when executing the operation task, the material piles within the visual range can also be scanned through the visual sensor, and the point cloud data stored in the database can be updated based on the latest scanned point cloud data of the material piles to ensure that the point cloud data of each material pile stored in the database is the latest.

[0050] In this way, after determining multiple material piles corresponding to the target hopper, the industrial control computer can obtain the point cloud data of the multiple material piles corresponding to the target hopper from the database.

[0051] S104. For each material pile, determine the priority score of the material pile based on the point cloud data of the material pile.

[0052] S105. According to the priority scores of the material piles, determine the target material pile to be taken from among the multiple material piles.

[0053] Specifically, the industrial control computer receives the point cloud data of each material pile sent by the unmanned loader. For each material pile, by analyzing the point cloud data of the material pile, the priority score of the material pile is obtained, and the priority scores of the material piles are sorted in descending order, and the material pile with the highest priority score is determined as the target material pile to be taken.

[0054] In some embodiments, the priority score of the material pile can be obtained by weighted average calculation of the parameters of interest. Among them, the parameters of interest can include the remaining material quantity of the material pile, the distance between the material pile and the unmanned loader, etc.

[0055] S106. Based on the information of the target hopper and the target material pile, generate a scheduling task and send the scheduling task to the unmanned loader.

[0056] Among them, the scheduling task is used to instruct the unmanned loader to take materials from the target material pile and unload the taken materials into the target hopper.

[0057] After determining the target hopper and the target material pile, the industrial control computer generates a scheduling task of taking materials from the target material pile and feeding materials to the target hopper, and sends the scheduling task to the unmanned loader through the communication module, so that the unmanned loader automatically plans the driving path based on the scheduling task and executes the scheduling task.

[0058] The unmanned loader scheduling method provided by the embodiments of the present application determines a target hopper to be loaded from at least one hopper through a specified scheduling mode. At the same time, it can also obtain the point cloud data of the stockpile corresponding to the target hopper collected by the unmanned loader through a vision sensor, determine the priority scores of each stockpile based on the point cloud data of each stockpile, automatically determine the target stockpile to be fetched based on the priority scores of each stockpile, and automatically generate a scheduling task of fetching materials from the target stockpile and loading them into the target hopper based on the information of the target hopper and the target stockpile. Thus, the automatic generation of the unmanned loader loading operation scheduling task is realized, the degree of manual participation in the unmanned loader loading operation scheduling process is reduced, the risk of loading the wrong materials due to manual loading is reduced, the degree of intelligence during the unmanned loader loading operation is improved, and thus the operation efficiency is improved.

[0059] In one embodiment, optionally, as Figure 2 shown, the process of S104 above may be:

[0060] S201. For each stockpile, process the point cloud data through a point cloud volume algorithm to obtain the remaining material volume of the stockpile.

[0061] S202. Determine the second remaining material percentage of the stockpile based on the remaining material volume and the total material volume of the stockpile.

[0062] After obtaining the point cloud data of the stockpile, the industrial control computer performs filtering processing on the point cloud data to remove noise and unnecessary interference information in the point cloud data. Further, call the point cloud volume algorithm to process the filtered point cloud data to obtain the remaining material volume of the stockpile, and combine the total material volume parameter of the stockpile to calculate the second remaining material percentage of the stockpile. Exemplarily, the ratio of the remaining material volume to the total material volume of the stockpile can be determined as the second remaining material percentage of the stockpile.

[0063] S203. Obtain the outer contour point cloud of the stockpile from the point cloud data.

[0064] S204. Extract multiple target points from the outer contour point cloud by the farthest point sampling method.

[0065] S205. Determine the priority score of the stockpile according to the second remaining material percentage and the distances from the multiple target points to the unmanned loader.

[0066] The industrial control computer filters the point cloud data again to obtain the outer contour point cloud of the stockpile materials. Further, by calling the farthest point sampling method, multiple target points are extracted from the outer contour point cloud of the stockpile materials. Based on the position information of each target point and combined with the current position of the unmanned loader, the distance from each target point to the unmanned loader is calculated in the horizontal plane (xy plane). Based on the above-mentioned second remaining material percentage and the distances from multiple target points to the unmanned loader, the priority score of the stockpile is determined.

[0067] In some embodiments, the higher the second remaining material percentage of the stockpile and the closer the distance between the stockpile and the unmanned loader, the higher the priority score of the stockpile; the lower the second remaining material percentage of the stockpile and the farther the distance between the stockpile and the unmanned loader, the lower the priority score of the stockpile. By preferentially processing the stockpiles with more remaining materials and easier access, the operation efficiency of the unmanned loader can be improved, and the timeliness of material replenishment can also be ensured.

[0068] Optionally, the process of S205 may include the following steps:

[0069] S2051. Determine the average distance and the farthest distance between multiple target points and the unmanned loader.

[0070] For each target point, based on the position of the target point and the current position of the unmanned loader, the distance from the target point to the unmanned loader is calculated in the horizontal plane (xy plane). Further, the farthest distance is determined from the obtained multiple distances and the average distance of the multiple distances is calculated.

[0071] S2052. Determine the distance ratio between the average distance and the farthest distance.

[0072] S2053. Determine the priority score of the stockpile based on the second remaining material percentage, the distance ratio, and their respective weight coefficients.

[0073] Specifically, the industrial control computer can perform weighted summation on the second remaining material percentage and the distance ratio based on the weight coefficients corresponding to the second remaining material percentage and the distance ratio, so as to obtain the priority score of the stockpile.

[0074] Exemplarily, assuming that the target hopper is ① and the corresponding stockpiles are ④, ⑤, and ⑥, the priority calculation of the stockpiles is as follows:

[0075] Ⅰ. For each stockpile, calculate the second remaining material percentage of the stockpile according to the point cloud data. For example, after calculation, the second remaining material percentages of stockpiles ④, ⑤, and ⑥ are a 4 、a 5 、a 6 .

[0076] II. For each stockpile, extract multiple target points from the outer contour point cloud of the stockpile by the farthest point sampling method, and calculate the average distance and the farthest distance from the target points of the stockpile to the unmanned loader in combination with the positions of the target points and the unmanned loader. For example, the average distances from the target points of stockpiles ④, ⑤, and ⑥ to the unmanned loader are D 4 , D 5 , D 6 , and the corresponding farthest distances are d m4 , d m5 , d m6 .

[0077] III. Calculate the distance ratio k i between the average distance D mi from the target points of stockpiles ④, ⑤, and ⑥ to the unmanned loader and the farthest distance d i . For example, the distance ratios corresponding to stockpiles ④, ⑤, and ⑥ are: k 4 , k 5 , k 6 .

[0078] IV. Assign weight coefficients X i , X i (optionally, X mi = 0.9, X i = 0.1) to the second remaining material percentage a a , the average distance D k from the target points of the stockpile to the loader and the distance ratio k a between the average distance D k from the target points of the stockpile to the loader and the farthest distance d i . Calculate the priority score T i of each stockpile according to T a = a i * X k + k i .

[0079] In this embodiment, by comprehensively considering the remaining materials of the stockpile and the distance between the stockpile and the unmanned loader, the priority score for stockpile reclamation is determined, making the determined priority score for stockpile reclamation more comprehensive and accurate, ensuring the timeliness of material replenishment, and also improving the operation efficiency of the unmanned loader.

[0080] In one embodiment, optionally, as Figure 3 shown, when the specified scheduling mode is the first scheduling mode, the industrial control computer can perform the feeding operation scheduling for the unmanned loader according to the following process. Optionally, the following S301 - S303 are further refinements of S101 in the above embodiment:

[0081] S301. Obtain production task information, construction mix ratio information, and the remaining material quantities in each hopper through the mixing plant production control system.

[0082] Among them, the production task information refers to information related to the concrete production task, including the concrete production task volume, concrete density, etc. The construction mix ratio information refers to the proportional relationship between the various constituent materials in the concrete. For example, river sand: small stones: medium stones: large stones: ultra-fine sand = a: b: c: d: e.

[0083] The industrial control computer can obtain the concrete production task information, construction mix ratio information, and the current remaining material quantities in each hopper from the mixing plant production control system through the communication module.

[0084] S302. For each hopper, determine the priority score of the hopper based on the production task information, construction mix ratio information, the remaining material quantity in the hopper, and the material information corresponding to the pre-set hopper.

[0085] Specifically, the industrial control computer can obtain the materials and material information corresponding to each hopper set by the user through the man-machine interaction module. The material information can include material density and material mixing time, etc. For example, the mixing plant contains 5 hoppers, and the material corresponding to hopper ① is set as river sand, the material corresponding to hopper ② is small stones, the material corresponding to hopper ③ is medium stones, the material corresponding to hopper ④ is large stones, and the material corresponding to hopper ⑤ is ultra-fine sand.

[0086] The industrial control computer can determine whether the remaining material quantity in the hopper can meet the material consumption speed (or called the material falling demand speed) through the concrete production task information, construction mix ratio information, the remaining material quantity in the hopper, and the material information corresponding to the pre-set hopper. Furthermore, determine the priority score of the hopper based on the evaluation result of whether the remaining material quantity in the hopper can meet the material consumption speed. In some embodiments, if the remaining material quantity in the hopper can fully meet the material consumption speed, it indicates that the replenishment demand of the hopper is not high, then the priority score of the hopper can be determined to be lower. If the remaining material quantity in the hopper cannot fully meet the material consumption speed, it indicates that the replenishment demand of the hopper is high, then the priority score of the hopper can be determined to be higher.

[0087] As an optional embodiment, the above S302 may include the following steps:

[0088] S3021. For each hopper, determine the material demand of the hopper based on the production task information and the construction mix ratio information.

[0089] Specifically, the industrial control computer determines the material demand of the hopper based on the concrete production task volume, concrete density, and the construction mix ratio information.

[0090] Exemplarily, assume that hopper No. 1 contains river sand, hopper No. 2 contains small stones, hopper No. 3 contains medium stones, hopper No. 4 contains large stones, hopper No. 5 contains ultra-fine sand, the concrete production task volume is n cubic meters, and the concrete density is ρ 混 , the construction mix information is: river sand: small stones: medium stones: large stones: ultra-fine sand = a: b: c: d: e, then the material demand quantity of hopper No. 1 required for the current task is The material demand quantity of hopper No. 2 is The material demand quantity of hopper No. 3 is The material demand quantity of hopper No. 4 is The material demand quantity of hopper No. 5 is

[0091]

[0092] S3022. Determine the required material falling speed of the hopper based on the material demand quantity, material density, and material mixing time.

[0093] Specifically, the industrial control computer can determine the required material falling speed ν of the hopper based on the material demand quantity m i , material density ρ 物料 , and material mixing time t through the following formula or a variant of the formula i .

[0094]

[0095] Continuing with the example in S3021 above, the required material falling speed of hopper No. 1 for the current task can be determined through the above formula as The required material falling speed of hopper No. 2 for the current task is The required material falling speed of hopper No. 3 for the current task is The required material falling speed of hopper No. 4 for the current task is The required material falling speed of hopper No. 5 for the current task is

[0096] S3023. Determine the priority score of the hopper based on the required material falling speed and the remaining material quantity.

[0097] Specifically, the industrial control computer can determine the priority score of the hopper based on whether the remaining material quantity in the hopper can meet the required material falling speed. For example, if the remaining material quantity in the hopper can fully meet the required material falling speed, it reflects to a certain extent that the material replenishment requirement of the hopper is not high, then the priority score of the hopper can be determined to be lower; if the remaining material quantity in the hopper cannot fully meet the required material falling speed, it reflects to a certain extent that the material replenishment requirement of the hopper is high, then the priority score of the hopper can be determined to be higher.

[0098] Optionally, the above S3023 may include: determining the average required material falling speed based on the required material falling speeds of each hopper; determining the percentage of the required material falling speed of the hopper based on the required material falling speed of the hopper and the average required material falling speed; determining the first remaining material percentage of the hopper based on the remaining material quantity, material density, and the material volume when the hopper is full; determining the priority score of the hopper based on the percentage of the required material falling speed, the first remaining material percentage, and their respective weight coefficients.

[0099] Specifically, the industrial control computer may, based on the remaining material quantity m i , material density ρ 物料 , and the material volume v when the hopper is full i , determine the first remaining material percentage p of the hopper through the following formula or a variant of the formula i :

[0100]

[0101] The industrial control computer may calculate the average value of the required material falling speeds of each hopper to obtain the average required material falling speed Among them, the average value may be an algorithm average value, a weighted average value, a root mean square average value, etc. Continuing with the example in the above S3021, the average required material falling speed of 5 hoppers For each hopper, the industrial control computer may, based on the required material falling speed ν of the hopper i , the average required material falling speed , determine the percentage w of the required material falling speed of the hopper through the following formula or a variant of the formula i :

[0102]

[0103] Furthermore, the industrial control computer may perform a weighted sum of the percentage of the required material falling speed and the first remaining material percentage based on the weight coefficients corresponding to the percentage of the required material falling speed and the first remaining material percentage, so as to obtain the priority score of the hopper. For example, the industrial control computer may determine the priority score D of the hopper through the following formula or a variant of the formula i :

[0104] D i = w i *X w + p i *X p ;

[0105] Among them, X w , X pare the weight coefficients corresponding to the material falling required speed percentage and the first remaining material percentage, respectively, and X w and X p The specific values of can be set based on actual requirements, and X w and X p The sum of is equal to 1.

[0106] Based on the production task information of concrete, the construction mix ratio information, the remaining amount of materials in the hopper, and the pre-set material information corresponding to the hopper, the feeding priority score of the hopper is determined, so that the determined feeding priority score of the hopper is more comprehensive and accurate, improving the accuracy of identifying the hopper lacking materials, thus ensuring the timeliness of material replenishment, and further improving the production efficiency of concrete.

[0107] S303. Based on the priority scores of each hopper, determine the target hopper to be fed from multiple hoppers.

[0108] Specifically, the industrial control computer can sort the priority scores of each hopper in descending order, and determine the hopper with the highest priority score as the target hopper to be fed.

[0109] S304. Based on the pre-set mapping relationship between the hopper and the stockpile, determine multiple stockpiles corresponding to the target hopper.

[0110] S305. Obtain the point cloud data of each stockpile collected by the unmanned loader through the vision sensor.

[0111] S306. For each stockpile, determine the priority score of the stockpile based on the point cloud data of the stockpile.

[0112] S307. According to the priority scores of each stockpile, determine the target stockpile to be retrieved from multiple stockpiles.

[0113] S308. Based on the information of the target hopper and the target stockpile, generate a scheduling task, and send the scheduling task to the unmanned loader.

[0114] It should be noted that the specific processes of the above S304 - S308 can refer to the description in the above embodiments, and will not be repeated here in this embodiment.

[0115] After receiving the scheduling task, the unmanned loader executes the scheduling task, retrieves materials from the designated target stockpile, and feeds materials to the designated target hopper. After the feeding task is completed, it feeds back the task execution result to the industrial control computer. After receiving the task completion result, the industrial control computer stores the scheduling task in the database and enters the next round of tasks.

[0116] In this embodiment, the industrial control computer automatically identifies the target hopper to be loaded with materials based on the production task information of the concrete, the construction mix ratio information, the remaining amount of materials in the hopper, and the material information corresponding to the preset hopper, and automatically identifies the target stockpile to be retrieved based on the remaining material information of the stockpile corresponding to the target hopper and the distance between the stockpile and the unmanned loader, and generates a scheduling task for retrieving materials from the target stockpile and loading them into the target hopper, realizing the automatic scheduling of the loading operation of the unmanned loader, thereby improving the operation efficiency.

[0117] In one embodiment, optionally, as Figure 4 shown, when the specified scheduling mode is the second scheduling mode, the industrial control computer can schedule the loading operation of the unmanned loader according to the following process:

[0118] S401. Determine the target hopper to be loaded with materials specified by the user through the man-machine interaction module.

[0119] Specifically, the industrial control computer can obtain the relevant information of the target hopper to be loaded with materials based on the triggering operation of the user on the man-machine interaction module. For example, the number of the target hopper to be loaded with materials, the material information corresponding to the target hopper, the stockpile information, and the number of loading times, etc.

[0120] S402. Determine multiple stockpiles corresponding to the target hopper based on the pre-set mapping relationship between the hopper and the stockpile.

[0121] S403. Obtain the point cloud data of each stockpile collected by the unmanned loader through the vision sensor.

[0122] S404. For each stockpile, determine the priority score of the stockpile based on the point cloud data of the stockpile.

[0123] S405. Determine the target stockpile to be retrieved from the multiple stockpiles according to the priority scores of the stockpiles.

[0124] S406. Generate a scheduling task based on the information of the target hopper and the target stockpile, and send the scheduling task to the unmanned loader.

[0125] It should be noted that the specific processes of the above S402 - S406 can refer to the descriptions in the above embodiments, and will not be elaborated here in this embodiment.

[0126] After receiving the scheduling task, the unmanned loader executes the scheduling task, retrieves materials from the specified target stockpile, and loads them into the specified target hopper. After the loading task is completed, it feeds back the task execution result to the industrial control computer. After receiving the result of the task completion, the industrial control computer stores the scheduling task in the database and enters the next round of tasks based on the number of loading times of the target hopper.

[0127] In this embodiment, the industrial control computer can support multiple scheduling modes. For example, it supports the scheduling mode of manually specifying the target hopper to be loaded. Based on the remaining material information of the material pile corresponding to the target hopper and the distance between the material pile and the unmanned loader, it can automatically identify the target material pile to be retrieved and generate a scheduling task for retrieving materials from the target material pile and loading them onto the target hopper. That is, it can select the corresponding scheduling mode as needed, achieving the flexibility of the unmanned loader loading operation scheduling.

[0128] Figure 5 FIG. is a schematic structural diagram of an unmanned loader scheduling system provided by an embodiment of the present application. As Figure 5 shown, the system may include a human-machine interaction module 501, a communication module 502, and an industrial control computer 503 respectively connected to the human-machine interaction module 501 and the communication module 502;

[0129] Specifically, the human-machine interaction module 501 is used for information interaction with external objects. The information at least includes the hopper information of the mixing plant, the material information corresponding to the hopper, the mapping relationship between the hopper and the material pile, and the target hopper information to be loaded;

[0130] The communication module 502 is used for communication between the industrial control computer 503 and the unmanned loader, and between the industrial control computer 503 and the mixing plant production control system;

[0131] The industrial control computer 503 is used to execute the steps of the unmanned loader scheduling method provided in any of the above embodiments.

[0132] Optionally, as Figure 6 shown, the human-machine interaction module 501 may be a display terminal (such as a large display screen) or a computer (such as a Pad).

[0133] Optionally, the communication method of the communication module 502 may be a wireless communication method or a wired communication method, etc. In some embodiments, as Figure 6 shown, the communication module 502 may include a router and a switch, etc. The router may include an AC and an AP. The AC is connected to the switch, and the AP is connected to the AC. By deploying multiple APs within the unmanned loader operation area, full coverage of the operation area network is achieved.

[0134] Taking the communication module 502 including a router and a switch as an example, the industrial control computer 503 in the unmanned loader scheduling system is connected to the mixing plant production control system and the unmanned loader control system through the switch, router (AC), and router (AP). Exemplarily, the unmanned loader control system accesses the local area network of the unmanned loader scheduling system through the router on the vehicle end, realizing the interconnection and intercommunication between the unmanned loader control system and the unmanned loader scheduling system. At the same time, the router (AC) of the unmanned loader scheduling system is also connected to the mixing plant server, ensuring smooth network communication between the mixing plant production control system and the unmanned loader scheduling system.

[0135] The above unmanned loader control system may include vehicle sensors, an unmanned controller, and a router. The vehicle sensors scan the stockpile to obtain point cloud data. The unmanned controller reads the vehicle status through the CAN line and sends the vehicle status and point cloud data to the industrial computer 503 in the unmanned loader scheduling system through the router.

[0136] According to the production process and production task requirements, the above mixing plant production control system sends the remaining material information of the mixing plant hopper and the construction mix ratio information of the current task to the mixing plant server. The mixing plant server sends the obtained data information to the industrial computer 503 in the unmanned loader scheduling system through the Ethernet.

[0137] Optionally, the unmanned loader scheduling system may further include an emergency stop device, a controller, and a CANET. The emergency stop device sends an emergency stop signal to the controller through the CAN line. The controller sends the emergency stop information to the CANET according to the communication protocol. The CANET converts the CAN information into a network information flow to the switch and sends the emergency stop information to the vehicle-end unmanned controller through the router (AC). After parsing according to the communication protocol, the unmanned controller sends the emergency stop instruction to the vehicle-end execution unit to enable the execution unit to execute the emergency stop instruction, realizing the remote emergency stop function. Further, the human-machine interaction module 501 can also send instructions such as start and stop to the switch through the industrial computer 503, and then send them to the vehicle-end through the router, realizing functions such as remote start and stop. The unmanned loader control system automatically generates a real-time path according to the scheduling task and sends the path information to the unmanned loader scheduling system through the router, and displays it on the human-machine interaction module 501 (such as a display terminal) of the scheduling system, realizing the real-time path tracking function.

[0138] Further, the Pad can also schedule the unmanned loader. For example, the Pad can also send a scheduling instruction to the unmanned loader control system through the router. After parsing according to the communication protocol, the unmanned loader control system executes the scheduling instruction, realizing the intelligent scheduling function of the unmanned loader loading operation.

[0139] Figure 7 A schematic structural diagram of the industrial computer provided by the embodiment of the present application is as Figure 7 shown. The industrial computer includes a processor 70, a memory 71, an input device 72, and an output device 73. The number of processors 70 in the industrial computer can be one or more, Figure 7 taking one processor 70 as an example. The processor 70, memory 71, input device 72, and output device 73 in the industrial computer can be connected through a bus or other means, Figure 7 taking connection through the bus as an example.

[0140] The memory 71, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the unmanned loader scheduling method in the embodiments of the present application. The processor 70 executes various functional applications and data processing of the device by running the software programs, instructions, and modules stored in the memory 71, that is, to implement the unmanned loader scheduling method provided in any of the above embodiments.

[0141] The memory 71 may mainly include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created during the unmanned loader scheduling process, etc. In addition, the memory 71 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some instances, the memory 71 may further include a memory remotely set relative to the processor 70, and these remote memories can be connected to the device / terminal / server through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0142] The input device 72 can be used to receive input digital or character information, and generate key signal inputs related to the user settings and function control of the industrial control computer. The output device 73 may include display devices such as a display screen.

[0143] In one embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0144] Determine a target hopper to be loaded from at least one hopper based on a specified scheduling mode;

[0145] Based on the pre-set mapping relationship between the hopper and the stockpile, determine multiple stockpiles corresponding to the target hopper;

[0146] Obtain the point cloud data of each stockpile collected by the unmanned loader through a vision sensor;

[0147] For each stockpile, determine the priority score of the stockpile based on the point cloud data of the stockpile;

[0148] According to the priority scores of the stockpiles, determine a target stockpile to be retrieved from the multiple stockpiles;

[0149] Generate a scheduling task based on the information of the target hopper and the target stockpile, and send the scheduling task to the unmanned loader; wherein, the scheduling task is used to instruct the unmanned loader to retrieve materials from the target stockpile and unload the retrieved materials into the target hopper.

[0150] In one embodiment, a computer program product is further provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0151] Determine a target hopper to be loaded from at least one hopper based on a specified scheduling mode;

[0152] Based on a pre-set mapping relationship between the hopper and the stockpile, determine a plurality of stockpiles corresponding to the target hopper;

[0153] Obtain the point cloud data of each stockpile collected by the unmanned loader through a vision sensor;

[0154] For each stockpile, determine a priority score of the stockpile based on the point cloud data of the stockpile;

[0155] According to the priority scores of the stockpiles, determine a target stockpile to be retrieved from the plurality of stockpiles;

[0156] Generate a scheduling task based on the information of the target hopper and the target stockpile, and send the scheduling task to the unmanned loader; wherein, the scheduling task is used to instruct the unmanned loader to retrieve materials from the target stockpile and unload the retrieved materials into the target hopper.

[0157] The unmanned loader scheduling system, industrial control computer, computer-readable storage medium, and computer program product provided in the above embodiments can execute the unmanned loader scheduling method provided in any embodiment of the present application, and have corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the above embodiments can be found in the unmanned loader scheduling method provided in any embodiment of the present application.

[0158] From the above description of the embodiments, those skilled in the art can clearly understand that the present application can be implemented by means of software and necessary general-purpose hardware. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk, or optical disc of a computer, and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods of various embodiments of the present application.

[0159] It should be noted that the various units and modules included in the above embodiments are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present application.

[0160] Note that the above is only a preferred embodiment of the present application and the technical principles applied. Those skilled in the art will understand that the present application is not limited to the specific embodiments here, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present application. Therefore, although the present application has been described in more detail through the above embodiments, the present application is not limited to the above embodiments only. Without departing from the concept of the present application, more other equivalent embodiments can be included, and the scope of the present application is determined by the scope of the appended claims.

Claims

1. A method for dispatching an unmanned loader, characterized in that: include: Determine a target hopper to be loaded with materials from at least one hopper based on a specified scheduling mode; Based on a preset mapping relationship between the hopper and the material pile, determining a plurality of material piles corresponding to the target hopper; Obtain point cloud data of each material pile collected by the unmanned loader through the visual sensor; For each material pile, determining a priority score of the material pile based on the point cloud data of the material pile; Determining a target material pile to be taken from the plurality of material piles according to the priority scores of the material piles; Based on the information of the target hopper and the target stockpile, a scheduling task is generated and sent to the unmanned loader; wherein the scheduling task is used to instruct the unmanned loader to take materials from the target stockpile and unload the taken materials into the target hopper.

2. The method according to claim 1, characterized in that: The step of determining a target hopper to be loaded with materials from at least one hopper based on a specified scheduling mode includes: When the designated dispatching mode is the first dispatching mode, the production task information, the construction mix ratio information and the remaining amount of materials in each hopper are obtained through the production control system of the mixing station; For each hopper, based on the production task information, the construction mix ratio information, the remaining amount of material in the hopper, and the pre-set material information corresponding to the hopper, determine the priority score of the hopper; Based on the priority scores of the hoppers, a target hopper to be loaded is determined from the plurality of hoppers.

3. The method according to claim 2, characterized in that The material information includes the material density and material mixing time of the material corresponding to the hopper; The step of determining the priority score of each hopper based on the production task information, the construction mix ratio information, the remaining amount of material in the hopper, and the preset material information corresponding to the hopper includes: For each hopper, based on the production task information and the construction mix ratio information, determine the material requirement of the hopper; Determining the required material falling speed of the hopper based on the required material quantity, the material density and the material stirring time; Based on the required material falling speed and the remaining amount of the material, the priority score of the hopper is determined.

4. The method according to claim 3, characterized in that The step of determining the priority score of the hopper based on the required material falling speed and the remaining amount of the material includes: Based on the material falling required speed of each hopper, determine the average required material falling speed; Determining a percentage of the material falling speed required for the hopper based on the material falling speed required for the hopper and the average material falling speed required; Determining a first remaining material percentage of the hopper based on the remaining amount of the material, the density of the material, and the volume of the material when the hopper is full; The priority score of the hopper is determined based on the percentage of the material falling speed requirement, the first remaining material percentage, and the respective corresponding weight coefficients.

5. The method according to claim 1, characterized in that: The step of determining a target hopper to be loaded with materials from at least one hopper based on a specified scheduling mode includes: When the designated dispatching mode is the second dispatching mode, the hopper designated by the user is determined as the target hopper to be loaded with materials through the human-computer interaction module.

6. The method according to claim 1, characterized in that The step of determining, for each material pile, a priority score of the material pile based on the point cloud data of the material pile comprises: For each material pile, the point cloud data is processed by a point cloud volume algorithm to obtain the remaining material volume of the material pile; determining a second remaining material percentage of the material pile based on the remaining material volume and the total material volume of the material pile; Acquire the outer edge contour point cloud of the pile from the point cloud data; Extracting multiple target points from the outer edge contour point cloud by using the farthest point sampling method; The priority score of the material pile is determined according to the second remaining material percentage and the distances between the multiple target points and the unmanned loader.

7. The method according to claim 6, characterized in that The step of determining the priority score of the stockpile according to the second remaining material percentage and the distances between the plurality of target points and the unmanned loader includes: Determine an average distance and a maximum distance between the plurality of target points and the unmanned loader; determining a distance ratio between the average distance and the farthest distance; The priority score of the stockpile is determined based on the second remaining material percentage, the distance ratio, and the respective corresponding weight coefficients.

8. An unmanned loader dispatching system, characterized in that: include: A human-computer interaction module, a communication module, and an industrial computer connected to the human-computer interaction module and the communication module respectively; The human-computer interaction module is used to exchange information with external objects, and the information at least includes the hopper information of the mixing station, the material information corresponding to the hopper, the mapping relationship between the hopper and the material pile, and the target hopper information to be loaded; The communication module is used for the industrial computer to communicate with the unmanned loader, and the industrial computer to communicate with the production control system of the mixing station; The industrial computer is used to execute the steps of the unmanned loader scheduling method as described in any one of claims 1 to 7.

9. An industrial computer, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

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

Images