Material stacking method, device and system, loading machine, storage medium and program product

Abstract

The invention relates to a material stacking method, device and system, a loading machine, a storage medium and a program product. The material stacking method comprises the following steps: acquiring point cloud data of a material pile; projecting the point cloud data to a two-dimensional plane, and dividing the point cloud data into a plurality of grids; the height and the local volume of a corresponding point of each grid are calculated, and the local volume is the volume of the current grid; determining a plurality of shoveling points and a selection sequence of the plurality of shoveling points from the corresponding points of all the grids according to the height and the local volume of the corresponding point of each grid; and according to the selection sequence of the multiple shoveling points, the material piles of the loading machine are stacked. According to the method, the shoveling priority is optimized by combining physical characteristics (potential energy and volume density) of the material pile, and an efficient path planning algorithm suitable for the low dispersed material pile is developed, so that intelligent stacking of the low dispersed material pile based on two dimensions of potential energy and efficiency is realized.

Description

Technical Field

[0001] The present disclosure relates to the technical field of loaders, and particularly relates to a material stacking method, device and system, loader, storage medium and program product. Background Art

[0002] The material stacking scenario of a loader refers to an engineering scenario where a loader is used to carry out operations such as handling, stacking or shaping of bulk materials (such as sand, ore, coal, etc.). Its core goal is to stack the materials into a regular shape or distribution state according to specific requirements through the loading, transportation and unloading functions of the loader, so as to meet the engineering storage, transportation or construction needs.

[0003] In fields such as mining and construction, loaders are the core equipment for material handling. In related technologies, manual operation depends on experience, which easily leads to out-of-control loading volume and unstable material piles. The accident risk is high under complex terrains or bad weather. There are problems such as insufficient planning accuracy and poor environmental adaptability in action operations, and ineffective actions increase fuel consumption, resulting in high long-term costs. Summary of the Invention

[0004] The inventors found through research that: due to the static modeling assumptions, single-objective optimization limitations and environmental perception blind spots of related technology autonomous path planning systems, it is difficult to adapt to dynamic material distribution and complex scenarios.

[0005] In view of at least one of the above technical problems, the present disclosure provides a material stacking method, device and system, loader, storage medium and program product, which optimize the shoveling priority by combining the physical characteristics (potential energy and volume density) of the material pile, and develop an efficient path planning algorithm suitable for low and scattered material piles, thereby realizing intelligent material stacking of low and scattered material piles based on the two dimensions of potential energy and efficiency.

[0006] According to one aspect of the present disclosure, a material stacking method is provided, including:

[0007] Obtaining point cloud data of the material pile;

[0008] Projecting the point cloud data onto a two-dimensional plane and dividing the point cloud data into multiple grids;

[0009] Calculating the height and local volume of the points corresponding to each grid, where the local volume is the volume of the current grid;

[0010] Determining a plurality of shoveling points and the selection order of the plurality of shoveling points from the points corresponding to all grids according to the height and local volume of the points corresponding to each grid;

[0011] Carrying out material stacking of the material pile by the loader according to the selection order of the plurality of shoveling points.

[0012] In some embodiments of the present disclosure, determining a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids according to the height and local volume of the corresponding points of each grid includes:

[0013] Determine the highest height and the largest local volume of the corresponding points of all grids;

[0014] Determine the scooping weight of the corresponding point of each grid according to the highest height, the largest local volume, the height and the local volume of the corresponding point of each grid;

[0015] Determine a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids according to the scooping weight of the corresponding point of each grid.

[0016] In some embodiments of the present disclosure, determining the scooping weight of the corresponding point of each grid according to the highest height, the largest local volume, the height and the local volume of the corresponding point of each grid includes:

[0017] Obtain the potential energy weight and the efficiency weight;

[0018] Determine the scooping weight of the corresponding point of each grid according to the potential energy weight, the efficiency weight, the highest height, the largest local volume, the height and the local volume of the corresponding point of each grid.

[0019] In some embodiments of the present disclosure, determining the scooping weight of the corresponding point of each grid according to the potential energy weight, the efficiency weight, the highest height, the largest local volume, the height and the local volume of the corresponding point of each grid includes:

[0020] Determine the first weight of the corresponding point of each grid according to the potential energy weight, the highest height and the height of the corresponding point of each grid;

[0021] Determine the second weight of the corresponding point of each grid according to the efficiency weight, the largest local volume and the local volume of the corresponding point of each grid;

[0022] Determine the scooping weight of the corresponding point of the grid according to the first weight and the second weight.

[0023] In some embodiments of the present disclosure, determining a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids according to the scooping weight of the corresponding point of each grid includes:

[0024] Take the corresponding point of the grid with the highest scooping weight as the first scooping point;

[0025] Take the first scooping point as the current scooping point;

[0026] Select the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distances between the current scooping point and all candidate scooping points.

[0027] In some embodiments of the present disclosure, the determining of multiple scooping points and the selection order of the multiple scooping points from the corresponding points of all grids according to the scooping weights of the corresponding points of each grid further includes:

[0028] Judge whether the next scooping point is the last scooping point;

[0029] In the case that the next scooping point is not the last scooping point, use the next scooping point as the current scooping point, and repeat the steps of selecting the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distances between the current scooping point and all candidate scooping points, and judging whether there is a next scooping point;

[0030] In the case that the next scooping point is the last scooping point, end the scooping point selection step.

[0031] In some embodiments of the present disclosure, the selecting of the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distances between the current scooping point and all candidate scooping points includes:

[0032] Take the distance between the current scooping point and each candidate scooping point as the first distance;

[0033] In the case that the scooping weight of the current scooping point is greater than the first weight threshold, take the candidate scooping point with the first distance equal to the first distance threshold as the next scooping point of the current scooping point;

[0034] In the case that there is no candidate scooping point with the first distance equal to the first distance threshold, take the candidate scooping point with the absolute value of the difference between the first distance and the first distance threshold being the smallest as the next scooping point of the current scooping point.

[0035] In some embodiments of the present disclosure, the selecting of the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distances between the current scooping point and all candidate scooping points further includes:

[0036] In the case that the scooping weight of the current scooping point is less than the second weight threshold, take the candidate scooping point with the first distance equal to the second distance threshold as the next scooping point of the current scooping point, where the second weight threshold is less than the first weight threshold, and the second distance threshold is greater than the first distance threshold;

[0037] In the case where there is no candidate scooping point with the first distance equal to the second distance threshold, the candidate scooping point with the smallest absolute value of the difference between the first distance and the second distance threshold is used as the next scooping point of the current scooping point.

[0038] In some embodiments of the present disclosure, the selecting the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distances between the current scooping point and all candidate scooping points further includes:

[0039] In the case where the scooping weight of the current scooping point is greater than or equal to the second weight threshold and less than or equal to the first predetermined threshold, the candidate scooping point with the first distance equal to the third distance threshold is used as the next scooping point of the current scooping point, where the second distance threshold is greater than the first distance threshold, and the third distance threshold is greater than the first distance threshold and less than the second distance threshold;

[0040] In the case where there is no candidate scooping point with the first distance equal to the third weight threshold, the candidate scooping point with the smallest absolute value of the difference between the first distance and the third distance threshold is used as the next scooping point of the current scooping point.

[0041] In some embodiments of the present disclosure, the stockpiling method further includes:

[0042] Determine the weighted centroid of the stockpile;

[0043] Generate a spiraling line that expands outward with the weighted centroid as the center;

[0044] Map all the scooping points onto the spiraling line to form a scooping point order from the outside to the inside.

[0045] In some embodiments of the present disclosure, the determining the weighted centroid of the stockpile includes:

[0046] Weight the centroid position according to the height of the corresponding point of each grid to obtain the weighted centroid of the stockpile.

[0047] In some embodiments of the present disclosure, the stockpiling method further includes:

[0048] Adopt a predetermined algorithm to optimize the scooping point order to determine a target path, where the target path passes through all the scooping points and has the shortest total path length.

[0049] In some embodiments of the present disclosure, the adopting a predetermined algorithm to optimize the scooping point order to determine a target path includes:

[0050] Determine the state transition probability from the current scooping point to each candidate scooping point based on the pheromone heuristic factor, the expected heuristic factor, the distance from the current scooping point to each candidate scooping point, and the pheromone of the path from the current scooping point to each candidate scooping point;

[0051] Determine the next scooping point of the current scooping point according to the state transition probability, so as to optimize the order of the scooping points and determine the target path.

[0052] In some embodiments of the present disclosure, the material stacking method further includes:

[0053] Obtain the rated load and the current load of the loader;

[0054] Determine the traveling distance of the loader according to the rated load and the current load, the scooping amount per unit distance, and the safety factor.

[0055] In some embodiments of the present disclosure, the material stacking method further includes:

[0056] Obtain the rated load and the current load of the loader;

[0057] Determine the depth compensation value according to the rated load and the current load, the cross-sectional area of the bucket, and the material density;

[0058] Adjust the current excavation depth of the bucket according to the depth compensation value.

[0059] In some embodiments of the present disclosure, the material stacking method further includes:

[0060] Determine the load deviation according to the rated load and the current load;

[0061] Judge whether the load deviation is greater than a predetermined threshold;

[0062] When the load deviation is not greater than the predetermined threshold, maintain the current excavation depth;

[0063] When the load deviation is greater than the predetermined threshold, execute the steps of determining the depth compensation value according to the rated load and the current load, the cross-sectional area of the bucket, and the material density, and adjusting the current excavation depth of the bucket according to the depth compensation value.

[0064] In some embodiments of the present disclosure, the material stacking method further includes:

[0065] For each scooping point in the scooping point list, determine the corresponding digging point of the scooping point;

[0066] Place the digging point corresponding to the scooping point after the scooping point;

[0067] According to the list of scooping points and the digging points corresponding to each scooping point, a list of digging points is formed;

[0068] According to the list of the digging points, a material stacking planning path is obtained.

[0069] In some embodiments of the present disclosure, determining the digging point corresponding to each scooping point in the list of scooping points includes:

[0070] Determining the current digging depth and direction vector corresponding to each scooping point, where the direction vector is the direction vector from the current scooping point to the centroid point of the stockpile;

[0071] According to the current digging depth and direction vector corresponding to each scooping point, the digging point corresponding to each scooping point is determined.

[0072] In some embodiments of the present disclosure, the material stacking method further includes:

[0073] After completing the scooping operation for every predetermined number of scooping points, recalculate the scooping weights of all un-scooped points;

[0074] Judge whether the new scooping weight of each un-scooped point is greater than the first weight threshold;

[0075] In the case that the new scooping weight of at least one un-scooped point is greater than the first weight threshold, perform path queue-jumping on the un-scooped points whose new scooping weights are greater than the first weight threshold.

[0076] In some embodiments of the present disclosure, recalculating the scooping weights of all un-scooped points includes:

[0077] For each un-scooped point, recalculate the new scooping weight of the un-scooped point according to the remaining volume of the current stockpile, the initial volume of the stockpile, and the old scooping weight of the un-scooped point.

[0078] According to another aspect of the present disclosure, a material stacking device is provided, including:

[0079] A data acquisition module configured to acquire the point cloud data of the stockpile;

[0080] A grid division module configured to project the point cloud data onto a two-dimensional plane and divide the point cloud data into multiple grids;

[0081] A parameter calculation module configured to calculate the height and local volume of the points corresponding to each grid, where the local volume is the volume of the current grid;

[0082] A scooping point determination module configured to determine multiple scooping points and the selection order of the multiple scooping points from the points corresponding to all grids according to the height and local volume of the points corresponding to each grid.

[0083] The material stacking control module is configured to perform the material stacking of the loader according to the selection order of the multiple scooping points.

[0084] According to another aspect of the present disclosure, there is provided a material stacking device, including:

[0085] A memory configured to store instructions;

[0086] A processor configured to execute the instructions, so that the material stacking device implements the material stacking method described in any of the above embodiments.

[0087] According to another aspect of the present disclosure, there is provided a material stacking system, including a data acquisition device and the material stacking device described in any of the above embodiments.

[0088] According to another aspect of the present disclosure, there is provided a loader, including the material stacking system described in any of the above embodiments.

[0089] According to another aspect of the present disclosure, there is provided a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the material stacking method described in any of the above embodiments is implemented.

[0090] According to another aspect of the present disclosure, there is provided a computer program product, including a computer program, wherein when the computer program is executed by a processor, the material stacking method described in any of the above embodiments is implemented.

[0091] The present disclosure optimizes the scooping priority by combining the physical characteristics (potential energy and volume density) of the material pile, and develops an efficient path planning algorithm suitable for low and scattered material piles, thereby realizing the intelligent material stacking of scattered low and short material piles based on the two dimensions of potential energy and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0092] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0093] Figure 1 It is a schematic diagram of some embodiments of the material stacking method of the present disclosure.

[0094] Figure 2 It is a schematic diagram of other embodiments of the material stacking method of the present disclosure.

[0095] Figure 3 It is a schematic diagram of the intelligent material stacking spiral planning path in some embodiments of the present disclosure.

[0096] Figure 4 Schematic diagram of the load-depth adjustment strategy in some embodiments of the present disclosure.

[0097] Figure 5 Schematic diagram of some embodiments of the code material device of the present disclosure.

[0098] Figure 6 Schematic structural diagram of some other embodiments of the code material device of the present disclosure.

[0099] Figure 7 Schematic structural diagram of some embodiments of the loader of the present disclosure. Detailed implementation manners

[0100] Next, the technical solutions in the embodiments of the present disclosure will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and in no way restricts the present disclosure and its application or use. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of the present disclosure.

[0101] Unless otherwise specifically stated, the relative arrangements, numerical expressions and values of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0102] Meanwhile, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn in actual proportional relationship.

[0103] For technologies, methods and devices known to those of ordinary skill in the relevant art, they may not be discussed in detail, but where appropriate, the said technologies, methods and devices should be regarded as part of the authorization specification.

[0104] In all the examples shown and discussed here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values.

[0105] It should be noted that: like reference numerals and letters denote like items in the following drawings, and thus, once an item is defined in one drawing, it does not need to be further discussed in subsequent drawings.

[0106] The inventor found through research that: in the related art, in the technology of loader stockpile code material planning, there is no publicly disclosed design solution among major product mainframe manufacturers.

[0107] The path planning of the related technology is unreasonable: Most of the related technology methods traverse the edge line of the stockpile at a fixed interval, without considering the distribution density and height difference of the stockpile, resulting in repeated paths and wasted time.

[0108] The shoveling sequence of the related technology is inefficient: The related technology strategy gives priority to processing high-potential areas, but the low areas in the low and scattered stockpiles are prone to loss and need to be rehandled, increasing energy consumption.

[0109] The load control of the related technology is extensive: The related technology does not dynamically adjust the shoveling depth according to the real-time height of the stockpile, resulting in overloading or underloading of the bucket and affecting the operation efficiency.

[0110] Technical problems such as insufficient planning accuracy, poor environmental adaptability, and high energy consumption cost in the traditional manual operation in the stockpile stacking scenario of the related technology loader.

[0111] In view of at least one of the above technical problems, the present disclosure provides a stacking method, device and system, loader, storage medium and program product. The present disclosure will be described below through specific embodiments.

[0112] Figure 1 It is a schematic diagram of some embodiments of the stacking method of the present disclosure. Preferably, this embodiment can be executed by the stacking device or the stacking system or the loader of the present disclosure. As Figure 1 shown, Figure 1 The method of the embodiment may include at least one step of step 100 to step 500.

[0113] In step 100, point cloud data of the stockpile is acquired.

[0114] In some embodiments of the present disclosure, step 100 may include: acquiring three-dimensional point cloud data through a lidar.

[0115] In some embodiments of the present disclosure, after step 100, the stacking method may further include: step 150, performing data processing on the point cloud data.

[0116] In some embodiments of the present disclosure, step 150 may include: at least one step of step 151 to step 152.

[0117] In step 151, pass-through filtering is performed: removing invalid points outside the operation area (such as Z-axis <0.1m or >2m).

[0118] In step 152, plane segmentation is performed using the RANSAC (Random Sample And Consensus) algorithm: separating the ground and the stockpile point cloud and extracting the bottom contour.

[0119] In step 200, project the point cloud data onto a two-dimensional plane and divide the point cloud data into multiple grids.

[0120] In some embodiments of the present disclosure, step 200 may include: calculating the characteristic parameters of the stockpile.

[0121] In some embodiments of the present disclosure, step 200 may include at least one of steps 210 to 230.

[0122] In step 210, determine the weighted centroid of the stockpile;

[0123] In some embodiments of the present disclosure, step 210 may include: weighting the centroid position according to the height z of the corresponding point i of each grid i , to obtain the weighted centroid C of the stockpile m .

[0124] In some embodiments of the present disclosure, step 210 may include: determining the weighted centroid C of the stockpile according to formula (1) m , where (x i , y i ) are the abscissa and ordinate of the corresponding point i of each grid in the horizontal plane.

[0125]

[0126] In step 220, project the point cloud data onto a two-dimensional plane.

[0127] In some embodiments of the present disclosure, step 220 may include: projecting the point cloud data of the stockpile after a series of processes (such as point cloud filtering, ground segmentation, etc.) onto the XY plane.

[0128] In step 230, divide the point cloud data into multiple grids.

[0129] In some embodiments of the present disclosure, step 230 may include: constructing a volume density field: dividing the stockpile into multiple 50 cm × 50 cm grids and calculating the volume density of each grid.

[0130] In some embodiments of the present disclosure, step 230 may include: calculating the volume density ρ of each grid according to formula (2) i,j .

[0131]

[0132] In step 300, calculate the height and local volume of the corresponding point of each grid, where the local volume is the volume of the current grid.

[0133] In some embodiments of the present disclosure, step 300 may include: while calculating the average height z corresponding to each grid, calculating the volume of the stockpile using the grid integration method.

[0134] In some embodiments of the present disclosure, the height of each corresponding point of the grid is the average value of the heights of all the point cloud data mapping to the current grid.

[0135] In some embodiments of the present disclosure, the local volume is equal to the base area of the current grid multiplied by the height, and the height is the average value of the heights of all the point cloud data mapping to the current grid.

[0136] In some embodiments of the present disclosure, the base area of the current grid may be 50 cm × 50 cm.

[0137] In step 400, according to the height and local volume of each corresponding point of the grid, a plurality of scooping points and the selection order of the plurality of scooping points are determined from the corresponding points of all the grids.

[0138] In some embodiments of the present disclosure, step 400 may include: intelligently generating scooping points.

[0139] In some embodiments of the present disclosure, the selection range of the scooping points is based on the area covered by the entire stockpile point cloud data. Specifically, it is selected within the stockpile area determined by projecting the stockpile point cloud data after a series of processes (such as point cloud filtering, ground segmentation, etc.) onto the XY plane; feature extraction is performed on the stockpile, the centroid is calculated, and a volume density field is constructed; then weights are assigned to the points in the stockpile area according to the potential energy and efficiency two-dimensional weight model, and finally the scooping points are selected according to the weights in the entire stockpile area.

[0140] In some embodiments of the present disclosure, step 400 may include at least one of steps 410 to 430.

[0141] In step 410, determine the maximum height max(z) and the maximum local volume max(V) of the corresponding points of all the grids.

[0142] In step 420, according to the maximum height max(z) and the maximum local volume max(V), the height z of each corresponding point of the grid i and the local volume V i , determine the scooping weight w of each corresponding point of the grid i .

[0143] In some embodiments of the present disclosure, step 420 may include: obtaining the potential energy weight and the efficiency weight; according to the potential energy weight α and the efficiency weight β, the maximum height max(z) and the maximum local volume max(V), the height z of each corresponding point of the gridi and the local volume V i , determine the scooping weight w of each corresponding point of the grid i .

[0144] In some embodiments of the present disclosure, step 420 may include: calculating the scooping weight w of each corresponding point of the grid according to formula (3) i .

[0145]

[0146] In formula (3), z i is the height of the current point, and V i is the volume of the current grid i.

[0147] In formula (3), 0 ≤ α ≤ 1, 0 ≤ β ≤ 1, and thus w i is also in the range of [0, 1]. The larger w i , the higher the scooping weight, and the larger the bulk density of the stockpile corresponding to the point i.

[0148] In some embodiments of the present disclosure, the sum of the potential energy weight α and the efficiency weight β is 1.

[0149] In some embodiments of the present disclosure, α = 0.3, β = 0.7 (empirical coefficients, which can be adjusted according to the operation scenario).

[0150] The above embodiments of the present disclosure consider both the potential energy dimension and the efficiency dimension.

[0151] In some embodiments of the present disclosure, for the potential energy dimension: the higher the stockpile, the greater the gravitational potential energy, so that it can be preferentially scooped to reduce the subsequent handling energy consumption and ensure intensive processing of high-value areas.

[0152] In some embodiments of the present disclosure, for the efficiency dimension: the larger the local volume of the area, the higher the unit scooping amount, thus improving the operation efficiency and reducing the repeated path in low-value areas.

[0153] In some embodiments of the present disclosure, the step of determining the scooping weight of each corresponding point of the grid according to the potential energy weight and the efficiency weight, the highest height and the maximum local volume, the height and the local volume of each corresponding point of the grid may include at least one of steps 421 to 423.

[0154] In step 421, according to the potential energy weight α, the highest height max(z) and the height z of each corresponding point of the grid i , determine the first weight w of each corresponding point i of the grid i1 .

[0155] In some embodiments of the present disclosure, step 421 may include: calculating the first weight w of each grid corresponding point i according to formula (4) i1 .

[0156]

[0157] In step 422, according to the efficiency weight β, the maximum local volume max(V), and the local volume V of each grid corresponding point i , determine the second weight w of each grid corresponding point i2 .

[0158] In some embodiments of the present disclosure, step 422 may include: calculating the second weight w of each grid corresponding point i according to formula (5) i2 .

[0159]

[0160] In step 423, according to the first weight w i1 and the second weight w i2 , determine the scooping weight w of the grid corresponding point i .

[0161] In some embodiments of the present disclosure, step 423 may include: the scooping weight w of the grid corresponding point according to formula (6) i .

[0162] w i = w i1 + w i2 (6)

[0163] In step 430, according to the scooping weight of each grid corresponding point, determine a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids.

[0164] In some embodiments of the present disclosure, step 430 may include at least one of steps 431 to 436.

[0165] In step 431, use the grid corresponding point with the highest scooping weight as the first scooping point p1.

[0166] In some embodiments of the present disclosure, step 431 may include: sorting all points from high to low according to the weight to obtain an ordered list of points {p1, p2,... p n}

[0167] In some embodiments of the present disclosure, the selection of subsequent points of the first scooping point p1 may include steps 432 to 436. The selection of subsequent points is based on the dynamic spacing adjustment algorithm.

[0168] In step 432, the first scooping point p1 is used as the current scooping point.

[0169] In step 433, according to the scooping weight of the current scooping point and the distances between the current scooping point and all candidate scooping points, the next scooping point of the current scooping point is selected from all candidate scooping points.

[0170] In some embodiments of the present disclosure, step 433 may include at least one of steps 4331 to 4333.

[0171] In step 4331, the distance between the current scooping point and each candidate scooping point is used as the first distance.

[0172] In step 4332, when the scooping weight of the current scooping point is greater than the first weight threshold, the candidate scooping point with the first distance equal to the first distance threshold is used as the next scooping point of the current scooping point.

[0173] In some embodiments of the present disclosure, the first weight threshold may be 0.7.

[0174] In some embodiments of the present disclosure, the first distance threshold may be 0.8L_w, where L_w is the width of the loader bucket.

[0175] In step 4333, when there is no candidate scooping point with the first distance equal to the first distance threshold, the candidate scooping point with the minimum absolute value of the difference between the first distance and the first distance threshold is used as the next scooping point of the current scooping point.

[0176] In some embodiments of the present disclosure, steps 4331 to 4333 may include: first select the first point p1, and the corresponding weight value of point p1 can be obtained; if this weight w1 is greater than 0.7, then the selection distance of the next point is the p i point (not necessarily p2) with a path length of 0.8L_w from point p1; if there is no corresponding p i point at this distance, then select the p i point with the path length closest to 0.8L_w from point p1 as the next candidate scooping point.

[0177] In some embodiments of the present disclosure, step 433 may further include at least one of steps 4334 to 4335.

[0178] In step 4334, when the scooping weight at the current scooping point is less than the second weight threshold, a candidate scooping point with the first distance equal to the second distance threshold is used as the next scooping point of the current scooping point, where the second weight threshold is less than the first weight threshold, and the second distance threshold is greater than the first distance threshold.

[0179] In some embodiments of the present disclosure, the second weight threshold may be 0.3.

[0180] In some embodiments of the present disclosure, the second distance threshold may be 1.2L_w.

[0181] In step 4335, when there is no candidate scooping point with the first distance equal to the second distance threshold, a candidate scooping point with the smallest absolute value of the difference between the first distance and the second distance threshold is used as the next scooping point of the current scooping point.

[0182] Steps 4331, 4334 to 4335 may include: first select the first point p1, and the weight value corresponding to the p1 point can be obtained; if this weight w1 is less than 0.3, the selection distance for the next point is the p i point (not necessarily p2) with a path length of 1.2L_w from the p1 point; if there is no corresponding p i point at this distance, select the p1 point with the path length closest to 1.2L_w from the p1 point as the next candidate scooping point.

[0183] In some embodiments of the present disclosure, step 433 may further include at least one of steps 4336 to 4337.

[0184] In step 4336, when the scooping weight at the current scooping point is greater than or equal to the second weight threshold and less than or equal to the first predetermined threshold, a candidate scooping point with the first distance equal to the third distance threshold is used as the next scooping point of the current scooping point, where the second distance threshold is greater than the first distance threshold, and the third distance threshold is greater than the first distance threshold and less than the second distance threshold.

[0185] In some embodiments of the present disclosure, the third distance threshold may be 1L_w.

[0186] In step 4337, when there is no candidate scooping point with the first distance equal to the third weight threshold, a candidate scooping point with the smallest absolute value of the difference between the first distance and the third distance threshold is used as the next scooping point of the current scooping point.

[0187] Steps 4331, 4336 to 4337 may include: First select the first point p1, and the weight value corresponding to the p1 point can be obtained; if this weight w1 is greater than or equal to 0.3 and less than or equal to 0.7, the selection distance for the next point is the p point whose path length from the p1 point is 1L_w (not necessarily p2); if there is no corresponding p point at this distance, select the p point whose path length from the p1 point is closest to this length 1L_w as the next candidate shoveling point. i point; if there is no corresponding p i point at this distance, select the p i point whose path length from the p1 point is closest to this length as the next candidate shoveling point.

[0188] In step 434, it is judged whether the next shoveling point is the last shoveling point.

[0189] In step 435, when the next shoveling point is not the last shoveling point, use the next shoveling point as the current shoveling point, and repeat steps 433 and 434.

[0190] In step 436, when the next shoveling point is the last shoveling point, end the shoveling point selection step.

[0191] The shoveling point sequence finally generated in the above embodiments of the present disclosure not only preferentially processes high-value areas, but also maintains a reasonable spacing, avoiding overcrowding or sparseness.

[0192] In step 500, according to the selection order of the multiple shoveling points, the loader stacks the material pile.

[0193] The above embodiments of the present disclosure adopt a potential energy and efficiency two-dimensional weight model, comprehensively considering the material pile height (potential energy) and volume density (shoveling efficiency), and dynamically generating shoveling priorities; it can maximize the operation efficiency (density dimension) while ensuring the stability of the material pile (potential energy dimension).

[0194] Figure 2 It is a schematic diagram of other embodiments of the material stacking method of the present disclosure. Figure 2 It is a schematic diagram of the spiral material pile stacking path planning point generation algorithm in some embodiments of the present disclosure. Preferably, this embodiment can be executed by the material stacking device of the present disclosure or the material stacking system of the present disclosure or the loader of the present disclosure. As Figure 2 shown, Figure 2 The method of the embodiment may include at least one of steps 1 to 8.

[0195] Step 1, multi-source data acquisition.

[0196] In some embodiments of the present disclosure, step 1 may include: Figure 1 Step 100 of the embodiment.

[0197] In some embodiments of the present disclosure, step 1 may include: collecting multi-source data through a data collection device, wherein the data collection device includes a lidar, a camera, and a force sensor.

[0198] In some embodiments of the present disclosure, step 1 may include: obtaining three-dimensional point cloud data and the pose of the loading position through a lidar; identifying the type of material through a camera to assist in density correction; through a force sensor: real-time monitoring of the bucket load.

[0199] Step 2, preprocessing of point cloud data.

[0200] In some embodiments of the present disclosure, step 2 may include: Figure 1 Step 150 of the embodiment.

[0201] Step 3, calculation of characteristic parameters.

[0202] In some embodiments of the present disclosure, step 3 may include: intelligent generation of scooping points.

[0203] In some embodiments of the present disclosure, step 3 may include: Figure 1 At least one step from step 200 to step 400 of the embodiment.

[0204] Step 4, generation of spiral path.

[0205] In some embodiments of the present disclosure, step 4 may include: determining the weighted centroid of the stockpile; generating a spirally expanding spiral line centered on the weighted centroid; mapping all the scooping points onto the spiral line to form a scooping point order from the outside to the inside.

[0206] In some embodiments of the present disclosure, the step of determining the weighted centroid of the stockpile may include: weighting the centroid position according to the height of the corresponding points of each grid to obtain the weighted centroid of the stockpile.

[0207] In some embodiments of the present disclosure, step 4 may include: adopting a spiral convergence path planning path generation algorithm for path planning.

[0208] In some embodiments of the present disclosure, step 4 may include: taking the weighted centroid C m as the center to generate a spirally expanding spiral line trajectory.

[0209] In some embodiments of the present disclosure, step 4 may include: constructing a spiral line according to formula (7).

[0210]

[0211] In formula (7), the starting radius r0 = (maximum width of the stockpile / 2) + 1 m, and a safety distance is reserved to ensure that it starts from the outermost periphery of the stockpile. The pitch coefficient k = (maximum width of the stockpile / (2πn)), where n = 3, so that the helix can cover the entire stockpile in about 3 turns. Parameter dynamic adjustment: When the distribution of the stockpile is discrete, increase the value of k to expand the spiral coverage range for high-weight areas, and superimpose a local scanning path on the basis of the helix.

[0212] In some embodiments of the present disclosure, step 4 may include: mapping all scooping points onto the helix, sorting them according to their polar angle θ or radius r on the helix, and arranging the points with larger radii in front, thus forming an initial scooping point order from the outside to the inside. By adopting such a spiral gathering path point, it spirally advances from the periphery to the center, reducing the repeated path and improving the compactness of the stockpile.

[0213] In step 3 of the above embodiments of the present disclosure, all points are sorted in descending order of weight, and a series of candidate scooping points are obtained according to the magnitude of the weight based on the "potential energy - efficiency" two-dimensionality and the rule of candidate point selection. In step 4, these subsequent scooping points are mapped onto the helix. The helix spirally diverges from the inside to the outside, with higher-weight points inside and lower-weight points outside. Considering the actual operation scenario, the loader can only start operating from the outside of the stockpile and operate towards the inside. Therefore, an initial scooping point order from the outside to the inside is formed, as Figure 3 shown. Figure 3 It is a schematic diagram of the intelligent stacking spiral planning path in some embodiments of the present disclosure.

[0214] The helix trajectory generation algorithm in the above embodiments of the present disclosure is combined with ant colony optimization, which reduces the repeated path and improves the compactness of the stockpile compared with the traditional straight back-and-forth path in the related art, and reduces the energy consumption.

[0215] Step 5, ant colony algorithm optimization.

[0216] In some embodiments of the present disclosure, step 5 may include: optimizing the path using the ant colony algorithm.

[0217] In some other embodiments of the present disclosure, step 5 may include: using other optimization algorithms, such as particle swarm optimization algorithm, genetic algorithm, simulated annealing algorithm, etc., for path optimization.

[0218] In some embodiments of the present disclosure, step 5 may include: optimizing the scooping point order using a predetermined algorithm to determine the target path, where the target path passes through all scooping points and has the shortest total path length, and the predetermined algorithm is the ant colony algorithm.

[0219] In some embodiments of the present disclosure, in the spiral path planning and optimization, the ant colony algorithm mainly optimizes the access order of the scooping points, aiming to find a path that passes through all the scooping points and has the shortest total path length. The ant colony algorithm mainly optimizes the order in which the loader accesses each scooping point. In the spiral path planning, a series of scooping points have been determined according to the spiral line generation model, but the initial arrangement order of these points may not be the optimal path order. In the above embodiments of the present disclosure, the ant colony algorithm searches for the optimal access order among these scooping points by simulating the behavior of ants searching for food, so that the total path length traveled by the loader during the material stacking process is the shortest, thereby improving the operation efficiency and reducing the energy consumption.

[0220] In some embodiments of the present disclosure, step 5 may include at least one of steps 51 to 52.

[0221] In step 51, according to the pheromone heuristic factor α, the expected heuristic factor β, the distance d from the current scooping point to each candidate scooping point ij , and the pheromone τ of the path from the current scooping point to each candidate scooping point ij , the state transition probability p from the current scooping point to each candidate scooping point is determined i,j .

[0222] In some embodiments of the present disclosure, the state transition probability p i,j is used to determine the possibility that the ant transfers from the current point i to the next point j.

[0223] In some embodiments of the present disclosure, step 51 may include: determining the state transition probability p from the current scooping point to each candidate scooping point according to formula (8) i,j .

[0224]

[0225] In formula (8), η ij = 1 / d ij , η ij is the distance heuristic value. The shorter the distance, the greater the tendency of the ant to choose this path. The pheromone heuristic factor α = 1.5, which controls the influence degree of the pheromone on the ant's path selection. The expected heuristic factor β = 2, which controls the influence degree of the distance on the ant's path selection. The pheromone update τ ij = (1 - ρ)τ ij + 100Δτ i The pheromone evaporation coefficient η = 0.1, and the pheromone increment Δτ = 100 for each iteration.

[0226] In step 52, according to the state transition probability, the next scooping point of the current scooping point is determined to optimize the scooping point order and determine the target path.

[0227] In some embodiments of the present disclosure, step 52 may further include: considering the kinematic constraints of the loader, adding a curvature limit when selecting the next point. When the ant selects the next point, add a curvature constraint condition. If selecting a certain point will cause the curvature of the path to exceed the curvature corresponding to the minimum turning radius of the loader, then the ant is prohibited from selecting that point.

[0228] In some embodiments of the present disclosure, when the ant selects the next access point, it will randomly select according to the state transition probability. For a path with a high pheromone concentration and a short distance, its state transition probability will be greater, and thus it is more likely to be selected by the ant. After each ant completes a path search, it will leave pheromone on the path it has passed. The shorter the path, the more pheromone the ant leaves. At the same time, the pheromone on all paths will volatilize at a certain ratio. In this way, after multiple iterations, the pheromone on the shorter path will gradually accumulate, while the pheromone on the longer path will decrease due to volatilization. As the pheromone is continuously updated, the ant will be more and more inclined to select the path with a high pheromone concentration (i.e., the shorter path), so that the entire ant colony gradually converges to the optimal path.

[0229] In the above embodiments of the present disclosure, the scooping points can be arranged in the order of "periphery → sub-periphery → center" according to the priority weight; in the above embodiments of the present disclosure, the ant colony algorithm is used to optimize the path order to ensure the shortest distance between adjacent points.

[0230] In the above embodiments of the present disclosure, a spiral convergence path planning is adopted: a spiral trajectory that expands outward is generated with the weighted centroid as the center, and the ant colony algorithm is superimposed to optimize the path order.

[0231] In the above embodiments of the present disclosure, the ant colony algorithm is used to optimize the path order, combined with the spiral operation mode from the outside to the inside, reducing the start and stop times of the loader and improving the operation efficiency.

[0232] Step 6, path execution.

[0233] In some embodiments of the present disclosure, step 6 may include: dynamically calculating the travel distance.

[0234] In some embodiments of the present disclosure, step 6 may include: obtaining the rated load and the current load of the loader; determining the travel distance of the loader according to the rated load, the current load, the scooping amount per unit distance, and the safety factor.

[0235] In some embodiments of the present disclosure, step 6 may include: determining the travel distance of the loader according to formula (9).

[0236] Travel distance = ((rated load - current load) / scooping amount per unit distance) × k (9)

[0237] In formula (9), k is a safety factor, k = 0.9, and the amount of material shoveled per unit distance is obtained through learning historical data.

[0238] Step 7, real-time feedback.

[0239] In some embodiments of the present disclosure, step 7 may include: real-time feedback and adaptive adjustment.

[0240] In some embodiments of the present disclosure, step 7 may include: load-depth closed-loop control.

[0241] In some embodiments of the present disclosure, step 7 may include at least one of steps 70 to 72.

[0242] In step 70, obtain the rated load and the current load of the loader.

[0243] In step 71, determine the depth compensation value Δh according to the rated load, the current load, the cross-sectional area of the bucket, and the material density. Figure 3 A schematic diagram of the depth compensation value Δh in some embodiments of the present disclosure is also given.

[0244] In some embodiments of the present disclosure, step 72 may include: determining the depth compensation value Δh according to formula (10).

[0245] Travel distance = (rated load - current load) / (cross-sectional area of bucket × material density) × k (10)

[0246] In step 72, adjust the current excavation depth of the bucket according to the depth compensation value Δh.

[0247] In some embodiments of the present disclosure, the depth adjustment range is: h min ≤ h current + Δh ≤ h max ; h min = 0.2 m, to prevent touching the ground; h max = 1.2 m, to set the maximum excavation depth of the bucket.

[0248] The above embodiments of the present disclosure adopt a dynamic load compensation algorithm, which can adjust the shoveling depth according to the real-time load, and can control the load deviation to reduce ineffective round trips.

[0249] Figure 4 It is a schematic diagram of the load-depth adjustment strategy in some embodiments of the present disclosure. Preferably, this embodiment can be executed by the material coding device, the material coding system, or the loader of the present disclosure. As Figure 4 shown, Figure 4 the method of the embodiment (for example Figure 2Step 7) of the embodiment may include at least one of steps 73 to 79.

[0250] In step 73, real-time load detection is performed; according to the rated load and the current load, the load deviation is determined.

[0251] In some embodiments of the present disclosure, the load deviation is defined as the rated load of the current loader - the current load. It reflects the gap between the current load of the loader and the rated load.

[0252] In step 74, it is determined whether the load deviation is greater than a predetermined threshold; if the load deviation is not greater than the predetermined threshold, step 79 is executed; otherwise, if the load deviation is greater than the predetermined threshold, step 75 is executed.

[0253] In some embodiments of the present disclosure, the predetermined threshold is set to 15%, which is based on the empirical threshold in practice.

[0254] In step 75, real-time load detection is performed.

[0255] In step 76, the depth compensation value Δh is calculated and determined.

[0256] In some embodiments of the present disclosure, step 76 may include: determining the depth compensation value according to the rated load, the current load, the cross-sectional area of the bucket, and the material density.

[0257] In step 77, depth adjustment is performed.

[0258] In some embodiments of the present disclosure, step 77 may include: adjusting the current digging depth of the bucket according to the depth compensation value.

[0259] In step 78, new point cloud data is collected. Then step 73 is executed.

[0260] In the above embodiments of the present disclosure, when the load deviation is greater than the predetermined threshold (e.g., 15%), it means that the gap between the current load and the rated load is significant. Adjusting the loading amount (digging depth) can make the load closer to the rated value, thereby optimizing the operation efficiency and avoiding inefficient operation of the equipment.

[0261] In step 79, the current digging depth is maintained.

[0262] In the above embodiments of the present disclosure, when the load deviation is not greater than the predetermined threshold (e.g., 15%), no adjustment is made, indicating that the current load is already relatively close to the rated load at this time, and the necessity for adjustment is relatively low. If adjusted frequently, it may increase the operation complexity and even affect the operation continuity and equipment stability. Therefore, the above embodiments of the present disclosure choose not to adjust to maintain smooth operation.

[0263] Step 8, the optimized path.

[0264] In some embodiments of the present disclosure, step 8 may include: a digging point list determination mechanism.

[0265] In some embodiments of the present disclosure, the digging point list determination mechanism may include at least one of steps 81 to 84.

[0266] In step 81, for each digging point p in the digging point list {p1, p2,... p n}, determine the corresponding digging point of this digging point p i . i Corresponding digging point

[0267] In some embodiments of the present disclosure, the digging point Refers to: starting from the current candidate point, along the direction vector pointing to the centroid point C of the stockpile m , a point calculated in combination with the digging depth. It represents the specific position determined in this digging direction and depth, comprehensively reflecting the influence of the two key factors of direction (pointing to the centroid C m ) and the digging depth Δh on the position p_dri, as Figure 3 Shown.

[0268] In some embodiments of the present disclosure, step 81 may include: determining the current digging depth and direction vector corresponding to each digging point, where the direction vector is the direction vector from the current digging point to the centroid point of the stockpile; determining the digging point corresponding to each digging point according to the current digging depth and direction vector corresponding to each digging point.

[0269] In some embodiments of the present disclosure, step 81 may include: the current candidate point p i Digging in the direction of the centroid point C of the stockpile m , and obtaining this point according to this direction vector and the digging depth

[0270] In step 82, place the digging point corresponding to this digging point p i After this digging point p . i After.

[0271] In step 83, according to the digging point list {p1, p2,... p n} and the digging point corresponding to each digging point Form a digging point list

[0272] In step 84, obtain the stockpiling planning path according to the digging point list .

[0273] In some embodiments of the present disclosure, step 8 may further include: a path dynamic correction mechanism.

[0274] In some embodiments of the present disclosure, the path dynamic correction mechanism may include at least one of steps 85 to 87.

[0275] In step 85, after completing the shoveling operation at every predetermined number of shoveling points, recalculate the shoveling weights of all unshoveled points.

[0276] In some embodiments of the present disclosure, the predetermined number may be 3.

[0277] In some embodiments of the present disclosure, the step of recalculating the shoveling weights of all unshoveled points may include: for each unshoveled point, recalculate the new shoveling weight of this unshoveled point according to the remaining volume of the current stockpile, the initial volume of the stockpile, and the old shoveling weight of this unshoveled point.

[0278] In some embodiments of the present disclosure, step 85 may include: determining the depth compensation value Δh according to formula (11).

[0279] w new =w old ×(1 + V current / V o ) (11)

[0280] In formula (11), V current represents the remaining volume of the current stockpile, and V o represents the initial volume of the stockpile.

[0281] In step 86, determine whether the new shoveling weight of each unshoveled point is greater than the first weight threshold.

[0282] In step 87, in the case where the new shoveling weight of at least one unshoveled point is greater than the first weight threshold, perform path queue-jumping on the unshoveled points whose new shoveling weights are greater than the first weight threshold.

[0283] Through the above embodiments of the present disclosure, by adjusting the shoveling depth in real-time based on load feedback and combining with the high-weight point queue-jumping mechanism, the risk of tipping caused by excessive single loading can be avoided.

[0284] In the above embodiments of the present disclosure, path queue-jumping is triggered for high-weight points w > 0.7 that have not been shoveled in the stockpile.

[0285] In the above embodiments of the present disclosure, after completing the shoveling operation at every predetermined number (for example, 3) of shoveling points, recalculate the priorities of the remaining points based on the new point cloud data. In the above embodiments of the present disclosure, path queue-jumping is performed on the unshoveled high-weight areas to ensure priority processing.

[0286] The scooping point p of the above-mentioned embodiment of the present disclosure i and the digging point are in one-to-one correspondence.

[0287] The scooping point p of the above-mentioned embodiment of the present disclosure i is the digging point optimized by combining the ant colony algorithm. Its generation is based on the intelligent generation of the scooping point ( Figure 1 at least one step among steps 200 to 400 of the embodiment, Figure 2 step 3) of the embodiment, the spiral gathering path planning path generation algorithm ( Figure 2 step 4) of the embodiment, the ant colony algorithm optimized path ( Figure 3 step 5) of the embodiment. In the spiral path planning and optimization, the ant colony algorithm mainly optimizes the access order of the scooping points, aiming to find a path that passes through all the scooping points and has the shortest total path length. The final result is a series of points p i , where i = 1, 2, 3....

[0288] The digging point is generated through the dynamic calculation of the travel distance ( Figure 2 step 6) of the embodiment, real-time feedback and adaptive adjustment ( Figure 2 steps 7 and 8 of the embodiment). The digging point and the scooping point p i are in one-to-one correspondence. Starting from the scooping point p i (the current candidate point) and digging towards the centroid point C of the stockpile m , the digging depth Δh is adjusted according to the load-depth closed-loop control to obtain the digging point as shown in Figure 3 .

[0289] The above-mentioned embodiment of the present disclosure designs an intelligent stacking method for dispersed low stockpiles based on the potential-energy and efficiency dual dimensions, which can optimize the scooping priority by combining the physical characteristics of the stockpile (potential energy and volume density), develop an efficient path planning algorithm suitable for low and dispersed stockpiles, and establish a dynamic compensation mechanism for the digging depth and load, thereby improving the operation stability.

[0290] In the above-mentioned embodiment of the present disclosure, (1) the spiral trajectory generation algorithm is combined with ant colony optimization,

[0291] (2) the path order is optimized by the ant colony algorithm and combined with the spiral operation mode from the outside to the inside, (3) the potential-energy and efficiency dual-dimension weight model, and (4) the real-time load feedback adjusts the digging depth and combines the high-weight point queue-jumping mechanism. These four inventive points cooperate with each other and jointly serve to improve the overall performance of the intelligent stacking system for dispersed low stockpiles.

[0292] The (1st) and (2nd) inventive points optimize from the perspective of path planning, reduce repeated paths and start / stop times, and improve efficiency and compactness.

[0293] The (3rd) inventive point balances stability and operation efficiency through the "potential energy and efficiency two-dimensional weight model", providing an evaluation dimension for path planning and selection of scooping points.

[0294] The (4th) inventive point ensures operation safety and avoids tipping risks through real-time load feedback and high-weight point queue-jumping mechanism. At the same time, it coordinates with other inventive points to ensure the efficient operation of the system under the premise of safety. They jointly optimize the intelligent material stacking method and system from different levels (path, evaluation model, safety control).

[0295] The (1st) to (3rd) inventive points are integrated and interact with each other during the determination process of the scooping point order:

[0296] The (3rd) inventive point "potential energy - efficiency two-dimensional weight model" provides an evaluation criterion for the selection of scooping points, measures the comprehensive weight of each point in terms of stability (potential energy) and operation efficiency (density), and determines the priority of the points.

[0297] The spiral trajectory generation algorithm (the (1st) inventive point) and the ant colony algorithm for path optimization (the (2nd) inventive point) further plan the access order based on the scooping points evaluated by the weight model. For example, the path order is optimized through the ant colony algorithm, and the access logic from outside to inside is determined by the spiral operation mode.

[0298] In the above embodiments of the present disclosure, the weight model is first used to participate in the evaluation of the priority of scooping points, and then the spiral trajectory and the ant colony algorithm are used to optimize the access order on this basis. The two complement each other and jointly achieve efficient and stable material stacking operations.

[0299] Figure 5 It is a schematic diagram of some embodiments of the material stacking device of the present disclosure. As Figure 5 shown, the material stacking device of the present disclosure may include a data acquisition module 501, a grid division module 502, a parameter calculation module 503, a scooping point determination module 504, and a material stacking control module 505.

[0300] The data acquisition module 501 is configured to acquire the point cloud data of the material pile.

[0301] The grid division module 502 is configured to project the point cloud data onto a two-dimensional plane and divide the point cloud data into multiple grids.

[0302] The parameter calculation module 503 is configured to calculate the height and local volume of the points corresponding to each grid, where the local volume is the volume of the current grid.

[0303] The scooping point determination module 504 is configured to determine a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids according to the height and local volume of the corresponding points of each grid.

[0304] In some embodiments of the present disclosure, the scooping point determination module 504 may be configured to determine the highest height and the maximum local volume of the corresponding points of all grids; determine the scooping weight of the corresponding point of each grid according to the highest height and the maximum local volume, the height and the local volume of the corresponding point of each grid; and determine a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids according to the scooping weight of the corresponding point of each grid.

[0305] In some embodiments of the present disclosure, when the scooping point determination module 504 determines the scooping weight of the corresponding point of each grid according to the highest height and the maximum local volume, the height and the local volume of the corresponding point of each grid, it may be configured to obtain a potential energy weight and an efficiency weight; and determine the scooping weight of the corresponding point of each grid according to the potential energy weight and the efficiency weight, the highest height and the maximum local volume, the height and the local volume of the corresponding point of each grid.

[0306] In some embodiments of the present disclosure, when the scooping point determination module 504 determines the scooping weight of the corresponding point of each grid according to the potential energy weight and the efficiency weight, the highest height and the maximum local volume, the height and the local volume of the corresponding point of each grid, it may be configured to determine a first weight of the corresponding point of each grid according to the potential energy weight, the highest height and the height of the corresponding point of each grid; determine a second weight of the corresponding point of each grid according to the efficiency weight, the maximum local volume and the local volume of the corresponding point of each grid; and determine the scooping weight of the corresponding point of the grid according to the first weight and the second weight.

[0307] In some embodiments of the present disclosure, when the scooping point determination module 504 determines a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids according to the scooping weight of the corresponding point of each grid, it may be configured to use the corresponding point of the grid with the highest scooping weight as the first scooping point; use the first scooping point as the current scooping point; and select the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points.

[0308] In some embodiments of the present disclosure, when the scooping point determination module 504 determines a plurality of scooping points and the selection order of the plurality of scooping points from the corresponding points of all grids according to the scooping weights of the corresponding points of each grid, it may further be configured to determine whether the next scooping point is the last scooping point; when the next scooping point is not the last scooping point, use the next scooping point as the current scooping point, and repeat the operations of selecting the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points, and determining whether there is a next scooping point; when the next scooping point is the last scooping point, end the scooping point selection operation.

[0309] In some embodiments of the present disclosure, when the scooping point determination module 504 selects the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points, it may be configured to use the distance between the current scooping point and each candidate scooping point as the first distance; when the scooping weight of the current scooping point is greater than the first weight threshold, use the candidate scooping point with the first distance equal to the first distance threshold as the next scooping point of the current scooping point; when there is no candidate scooping point with the first distance equal to the first distance threshold, use the candidate scooping point with the smallest absolute value of the difference between the first distance and the first distance threshold as the next scooping point of the current scooping point.

[0310] In some embodiments of the present disclosure, when the scooping point determination module 504 selects the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points, it may further be configured to, when the scooping weight of the current scooping point is less than the second weight threshold, use the candidate scooping point with the first distance equal to the second distance threshold as the next scooping point of the current scooping point, where the second weight threshold is less than the first weight threshold, and the second distance threshold is greater than the first distance threshold; when there is no candidate scooping point with the first distance equal to the second distance threshold, use the candidate scooping point with the smallest absolute value of the difference between the first distance and the second distance threshold as the next scooping point of the current scooping point.

[0311] In some embodiments of the present disclosure, when the scooping point determination module 504 selects the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distances between the current scooping point and all candidate scooping points, it may further be configured to, when the scooping weight of the current scooping point is greater than or equal to a second weight threshold and less than or equal to a first predetermined threshold, use a candidate scooping point with a first distance equal to a third distance threshold as the next scooping point of the current scooping point, where the second distance threshold is greater than the first distance threshold, and the third distance threshold is greater than the first distance threshold and less than the second distance threshold; and when there is no candidate scooping point with a first distance equal to the third weight threshold, use a candidate scooping point with the smallest absolute value of the difference between the first distance and the third distance threshold as the next scooping point of the current scooping point.

[0312] The material stacking control module 505 is configured to perform material stacking of the loader according to the selection order of the multiple scooping points.

[0313] In some embodiments of the present disclosure, the material stacking device of the present disclosure may further be configured to determine the weighted centroid of the material stack; generate a spiral line extending outward with the weighted centroid as the center; map all the scooping points onto the spiral line to form a scooping point order from the outside to the inside.

[0314] In some embodiments of the present disclosure, when the material stacking device of the present disclosure determines the weighted centroid of the material stack, it may be configured to weight the centroid position according to the height of the corresponding point of each grid to obtain the weighted centroid of the material stack.

[0315] In some embodiments of the present disclosure, the material stacking device of the present disclosure may further be configured to optimize the scooping point order by adopting a predetermined algorithm to determine a target path, where the target path passes through all the scooping points and has the shortest total path length.

[0316] In some embodiments of the present disclosure, when the material stacking device of the present disclosure optimizes the scooping point order by adopting a predetermined algorithm to determine a target path, it may be configured to determine the state transition probability from the current scooping point to each candidate scooping point according to the pheromone heuristic factor, the expected heuristic factor, the distance from the current scooping point to each candidate scooping point, and the pheromone of the path from the current scooping point to each candidate scooping point; and determine the next scooping point of the current scooping point according to the state transition probability so as to optimize the scooping point order and determine the target path.

[0317] In some embodiments of the present disclosure, the material stacking device of the present disclosure may further be configured to obtain the rated load and the current load of the loader; determine the traveling distance of the loader according to the rated load, the current load, the scooping amount per unit distance, and the safety factor.

[0318] In some embodiments of the present disclosure, the stockpiling device of the present disclosure may further be configured to obtain the rated load and the current load of the loader; determine a depth compensation value according to the rated load, the current load, the cross-sectional area of the bucket, and the material density; and adjust the current excavation depth of the bucket according to the depth compensation value.

[0319] In some embodiments of the present disclosure, the stockpiling device of the present disclosure may further be configured to determine a load deviation according to the rated load and the current load; determine whether the load deviation is greater than a predetermined threshold; keep the current excavation depth when the load deviation is not greater than the predetermined threshold; and perform the steps of determining a depth compensation value according to the rated load, the current load, the cross-sectional area of the bucket, and the material density, and adjusting the current excavation depth of the bucket according to the depth compensation value when the load deviation is greater than the predetermined threshold.

[0320] In some embodiments of the present disclosure, the stockpiling device of the present disclosure may further be configured to, for each scooping point in the scooping point list, determine the corresponding digging point of the scooping point; place the corresponding digging point of the scooping point after the scooping point; form a digging point list according to the scooping point list and the corresponding digging point of each scooping point; and obtain a stockpiling planning path according to the digging point list.

[0321] In some embodiments of the present disclosure, when the stockpiling device of the present disclosure determines the corresponding digging point of each scooping point in the scooping point list, it may be configured to determine the current excavation depth and the direction vector corresponding to each scooping point, where the direction vector is the direction vector from the current scooping point to the centroid point of the stockpile; and determine the corresponding digging point of each scooping point according to the current excavation depth and the direction vector corresponding to each scooping point.

[0322] In some embodiments of the present disclosure, the stockpiling device of the present disclosure may further be configured to, after each completion of the scooping operation of a predetermined number of scooping points, recalculate the scooping weights of all un-scooped points; determine whether the new scooping weight of each un-scooped point is greater than a first weight threshold; and perform path cutting-in on the un-scooped points whose new scooping weights are greater than the first weight threshold when the new scooping weights of at least one un-scooped point are greater than the first weight threshold.

[0323] In some embodiments of the present disclosure, when the stockpiling device of the present disclosure recalculates the scooping weights of all un-scooped points, it may be configured to, for each un-scooped point, recalculate the new scooping weight of the un-scooped point according to the remaining volume of the current stockpile, the initial volume of the stockpile, and the old scooping weight of the un-scooped point.

[0324] In some embodiments of the present disclosure, the stockpiling device of the present disclosure may further be configured to execute the stockpiling method described in any one of the above embodiments of the present disclosure.

[0325] The above embodiments of the present disclosure provide an efficient material stacking method and device for a loader in scenarios where the remaining material has a small volume, low height, and discrete distribution.

[0326] For the material stacking scenario of the loader, the above embodiments of the present disclosure are committed to constructing a multi-modal perception fusion framework, developing a multi-objective dynamic programming algorithm, designing an environment adaptive mechanism, breaking through the difficulties of planning accuracy and environmental adaptation, and expecting to improve the operation efficiency and planning accuracy, providing key technical support for intelligent operation under complex working conditions.

[0327] Figure 6 It is a schematic structural diagram of some other embodiments of the material stacking device of the present disclosure. As Figure 6 shown, the material stacking device includes a memory 601 and a processor 602.

[0328] The memory 601 is used to store instructions, and the processor 602 is coupled to the memory 601. The processor 602 is configured to execute the material stacking method described in any embodiment of the present disclosure based on the instructions stored in the memory.

[0329] As Figure 6 shown, the material stacking device further includes a communication interface 603 for information interaction with other devices. At the same time, the material stacking device further includes a bus 604, and the processor 602, the communication interface 603, and the memory 601 complete mutual communication through the bus 604.

[0330] The memory 601 may include a high-speed RAM memory, and may also include a non-volatile memory, such as at least one disk memory. The memory 601 may also be a memory array. The memory 601 may also be partitioned, and the partitions may be combined into virtual volumes according to certain rules.

[0331] In addition, the processor 602 may be a central processing unit CPU, or may be an application specific integrated circuit ASIC, or may be one or more integrated circuits configured to implement the embodiments of the present disclosure.

[0332] According to another aspect of the present disclosure, a material stacking system is provided, including a data acquisition device and the material stacking device described in any of the above embodiments.

[0333] According to another aspect of the present disclosure, a loader is provided, including the material stacking system described in any of the above embodiments.

[0334] Figure 7 It is a schematic structural diagram of some embodiments of the loader of the present disclosure. As Figure 7As shown, the loader of the present disclosure may include a material stacking device 701, an inertial navigation system 702, a lidar 703, a camera 704, and a force sensor 705.

[0335] The material stacking device 701 may be the material stacking device described in any of the above embodiments.

[0336] In some embodiments of the present disclosure, the material stacking device 701 may be implemented as an industrial control computer.

[0337] The lidar 703 is configured to obtain three-dimensional point clouds and the pose of the loader.

[0338] The camera 704 is configured to identify the type of material and assist in density correction.

[0339] In some embodiments of the present disclosure, the camera 704 may be implemented as a camera.

[0340] The force sensor 705 is configured to monitor the load of the bucket in real time.

[0341] In some embodiments of the present disclosure, the lidar 703, the camera 704, and the force sensor 705 form a data acquisition device.

[0342] The above embodiments of the present disclosure provide an intelligent material stacking method, device, and system based on the dual dimensions of potential energy and efficiency for dispersed low-lying material piles.

[0343] The above embodiments of the present disclosure aim to solve the problems of insufficient planning accuracy, poor environmental adaptability, high energy consumption costs, etc. existing in traditional manual operations in the material stacking scenario of loaders.

[0344] The above embodiments of the present disclosure break through the planning difficulties under dynamic material distribution and complex scenarios by constructing a multi-modal perception fusion framework, developing a multi-objective dynamic programming algorithm, and designing an environment adaptive mechanism, so as to improve the operation efficiency, accuracy, and safety, and provide key technical support for intelligent operations under complex working conditions.

[0345] The above embodiments of the present disclosure have developed an efficient path planning algorithm suitable for low-lying and dispersed material piles, and established a dynamic compensation mechanism for the digging depth and load, improving the operation stability.

[0346] According to another aspect of the present disclosure, there is provided a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the material stacking method described in any of the above embodiments is implemented.

[0347] According to another aspect of the present disclosure, there is provided a computer program product, including a computer program, wherein when the computer program is executed by a processor, the material stacking method described in any of the above embodiments is implemented.

[0348] In some embodiments of the present disclosure, the computer-readable storage medium may be a non-transitory computer-readable storage medium.

[0349] Those skilled in the art should understand that the embodiments of the present disclosure may be provided as a method, an apparatus, or a computer program product. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable non-transitory storage media

[0350] (including but not limited to disk memories, CD-ROMs, optical memories, etc.).

[0351] The present disclosure is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, and the combination of flows and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processors of general-purpose computers, special-purpose computers, embedded processors, or other programmable data processing devices to generate a machine, so that the instructions executed by the processors of the computer or other programmable data processing devices generate means for realizing the functions specified in one Figure 1 flow or multiple flows and / or one Figure 1 block or multiple blocks.

[0352] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means realizes the functions specified in one Figure 1 flow or multiple flows and / or one Figure 1 block or multiple blocks.

[0353] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one Figure 1 flow or multiple flows and / or one Figure 1 block or multiple blocks.

[0354] The material coding device, data acquisition module, mesh generation module, parameter calculation module, digging point determination module, and material coding control module described above can be implemented as a general-purpose processor, programmable logic controller (PLC), digital signal processor

[0355] (DSP), application specific integrated circuit (ASIC), field programmable gate array (FPGA), or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, or any suitable combination thereof.

[0356] So far, the present disclosure has been described in detail. To avoid obscuring the concept of the present disclosure, some details well known in the art have not been described. Those skilled in the art can fully understand how to implement the technical solutions disclosed herein based on the above description.

[0357] Those of ordinary skill in the art can understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or can be completed by a program instructing relevant hardware. The program can be stored in a non-transitory computer-readable storage medium. The storage media mentioned above can be a read-only memory, a magnetic disk, an optical disk, or the like.

[0358] The description of the present disclosure is given for purposes of illustration and description, and is not intended to be exhaustive or to limit the present disclosure to the disclosed form. Many modifications and variations are obvious to those of ordinary skill in the art. The embodiments are chosen and described in order to better explain the principles and practical applications of the present disclosure, and to enable those of ordinary skill in the art to understand the present disclosure and design various embodiments with various modifications suitable for specific purposes.

Claims

1. A material stacking method, comprising: Obtaining point cloud data of a material pile; Projecting the point cloud data onto a two-dimensional plane and dividing the point cloud data into multiple grids; Calculating the height and local volume of the points corresponding to each grid, where the local volume is the volume of the current grid; Determining multiple scooping points and the selection order of the multiple scooping points from the points corresponding to all grids according to the height and local volume of the points corresponding to each grid; Performing material pile stacking of a loader according to the selection order of the multiple scooping points.

2. The method of coding materials according to claim 1, wherein, The determining multiple scooping points and the selection order of the multiple scooping points from the points corresponding to all grids according to the height and local volume of the points corresponding to each grid includes: Determining the highest height and the largest local volume of the points corresponding to all grids; Determining the scooping weight of the points corresponding to each grid according to the highest height, the largest local volume, the height and local volume of the points corresponding to each grid; Determining multiple scooping points and the selection order of the multiple scooping points from the points corresponding to all grids according to the scooping weight of the points corresponding to each grid.

3. The method of coding materials according to claim 2, wherein, The determining the scooping weight of the points corresponding to each grid according to the highest height, the largest local volume, the height and local volume of the points corresponding to each grid includes: Obtaining a potential energy weight and an efficiency weight; Determining the scooping weight of the points corresponding to each grid according to the potential energy weight, the efficiency weight, the highest height, the largest local volume, the height and local volume of the points corresponding to each grid.

4. The method of coding materials according to claim 3, wherein, The determining the scooping weight of the points corresponding to each grid according to the potential energy weight, the efficiency weight, the highest height, the largest local volume, the height and local volume of the points corresponding to each grid includes: Determining the first weight of the points corresponding to each grid according to the potential energy weight, the highest height and the height of the points corresponding to each grid; Determining the second weight of the points corresponding to each grid according to the efficiency weight, the largest local volume and the local volume of the points corresponding to each grid; Determining the scooping weight of the points corresponding to the grid according to the first weight and the second weight.

5. The coding method according to any one of claims 2 to 4, wherein The determining multiple scooping points and the selection order of the multiple scooping points from the points corresponding to all grids according to the scooping weight of the points corresponding to each grid includes: Taking the point corresponding to the grid with the highest scooping weight as the first scooping point; Taking the first scooping point as the current scooping point; Selecting the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points.

6. The method for coding materials according to claim 5, wherein The determining multiple scooping points and the selection order of the multiple scooping points from the points corresponding to all grids according to the scooping weight of the points corresponding to each grid further includes: Judging whether the next scooping point is the last scooping point; In the case where the next scooping point is not the last scooping point, taking the next scooping point as the current scooping point, and repeating the steps of selecting the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points, and judging whether there is a next scooping point; In the case where the next scooping point is the last scooping point, end the scooping point selection step.

7. The method for coding materials according to claim 5, wherein, The selection of the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points includes: Taking the distance between the current scooping point and each candidate scooping point as the first distance; In the case where the scooping weight of the current scooping point is greater than the first weight threshold, taking the candidate scooping points with the first distance equal to the first distance threshold as the next scooping point of the current scooping point; In the case where there are no candidate scooping points with the first distance equal to the first distance threshold, taking the candidate scooping point with the smallest absolute value of the difference between the first distance and the first distance threshold as the next scooping point of the current scooping point.

8. The method of coding materials according to claim 7, wherein, The selection of the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points further includes: In the case where the scooping weight of the current scooping point is less than the second weight threshold, taking the candidate scooping points with the first distance equal to the second distance threshold as the next scooping point of the current scooping point, where the second weight threshold is less than the first weight threshold, and the second distance threshold is greater than the first distance threshold; In the case where there are no candidate scooping points with the first distance equal to the second distance threshold, taking the candidate scooping point with the smallest absolute value of the difference between the first distance and the second distance threshold as the next scooping point of the current scooping point.

9. The method for coding materials according to claim 8, wherein The selection of the next scooping point of the current scooping point from all candidate scooping points according to the scooping weight of the current scooping point and the distance between the current scooping point and all candidate scooping points further includes: In the case where the scooping weight of the current scooping point is greater than or equal to the second weight threshold and less than or equal to the first predetermined threshold, taking the candidate scooping points with the first distance equal to the third distance threshold as the next scooping point of the current scooping point, where the second distance threshold is greater than the first distance threshold, and the third distance threshold is greater than the first distance threshold and less than the second distance threshold; In the case where there are no candidate scooping points with the first distance equal to the third weight threshold, taking the candidate scooping point with the smallest absolute value of the difference between the first distance and the third distance threshold as the next scooping point of the current scooping point.

10. The stacking method according to any one of claims 1 to 4, further comprising: Determining the weighted centroid of the stockpile; Generating a spiraling line that expands outward with the weighted centroid as the center; Mapping all the scooping points onto the spiraling line to form a scooping point order from the outside to the inside.

11. The method for coding materials according to claim 10, wherein, The determining of the weighted centroid of the stockpile includes: Weighting the centroid position according to the height of the corresponding point of each grid to obtain the weighted centroid of the stockpile.

12. The stacking method according to claim 10, further comprising: Adopting a predetermined algorithm to optimize the scooping point order to determine a target path, where the target path passes through all the scooping points and has the shortest total path length.

13. The method for coding materials according to claim 12, wherein The adopting of a predetermined algorithm to optimize the scooping point order to determine a target path includes: Determine the state transition probability from the current scooping point to each candidate scooping point according to the pheromone heuristic factor, the expected heuristic factor, the distance from the current scooping point to each candidate scooping point, and the pheromone of the path from the current scooping point to each candidate scooping point; Determine the next scooping point of the current scooping point according to the state transition probability, so as to optimize the scooping point sequence and determine the target path.

14. The material stacking method according to any one of claims 1 to 4 further includes: Obtain the rated load and the current load of the loader; Determine the travel distance of the loader according to the rated load, the current load, the scooping amount per unit distance, and the safety factor.

15. The material stacking method according to any one of claims 1 to 4 further includes: Obtain the rated load and the current load of the loader; Determine the depth compensation value according to the rated load, the current load, the cross-sectional area of the bucket, and the material density; Adjust the current excavation depth of the bucket according to the depth compensation value.

16. The material stacking method according to claim 15 further includes: Determine the load deviation according to the rated load and the current load; Judge whether the load deviation is greater than a predetermined threshold; Keep the current excavation depth when the load deviation is not greater than the predetermined threshold; When the load deviation is greater than the predetermined threshold, perform the steps of determining the depth compensation value according to the rated load, the current load, the cross-sectional area of the bucket, and the material density, and adjusting the current excavation depth of the bucket according to the depth compensation value.

17. The material stacking method according to any one of claims 1 to 4 further includes: For each scooping point in the scooping point list, determine the corresponding digging point of the scooping point; Place the digging point corresponding to the scooping point after the scooping point; According to the scooping point list and the digging point corresponding to each scooping point, form a digging point list; Obtain the material stacking planning path according to the digging point list.

18. The method of coding materials according to claim 17, wherein, The step of determining the corresponding digging point of each scooping point in the scooping point list includes: Determine the current excavation depth and direction vector corresponding to each scooping point, where the direction vector is the direction vector from the current scooping point to the centroid point of the stockpile; Determine the corresponding digging point of each scooping point according to the current excavation depth and direction vector corresponding to each scooping point.

19. The material stacking method according to any one of claims 2 to 4 further includes: After each completion of the scooping operation of a predetermined number of scooping points, recalculate the scooping weights of all un-scooped points; Judge whether the new scooping weight of each un-scooped point is greater than the first weight threshold; When the new scooping weight of at least one un-scooped point is greater than the first weight threshold, perform path cutting-in on the un-scooped points with new scooping weights greater than the first weight threshold.

20. In the material stacking method according to claim 19, the step of recalculating the scooping weights of all un-scooped points includes: For each un-scooped point, recalculate the new scooping weight of the un-scooped point according to the remaining volume of the current stockpile, the initial volume of the stockpile, and the old scooping weight of the un-scooped point.

21. A material stacking device includes: A data acquisition module configured to acquire the point cloud data of the stockpile; The meshing module is configured to project the point cloud data onto a two-dimensional plane and divide the point cloud data into multiple meshes; The parameter calculation module is configured to calculate the height and local volume of the points corresponding to each mesh, where the local volume is the volume of the current mesh; The scooping point determination module is configured to determine multiple scooping points and the selection order of the multiple scooping points from the points corresponding to all meshes according to the height and local volume of the points corresponding to each mesh; The stockpiling control module is configured to perform stockpiling of the loader's stockpile according to the selection order of the multiple scooping points.

22. A stockpiling device, comprising: A memory configured to store instructions; A processor configured to execute the instructions, such that the user equipment executes the stockpiling method according to any one of claims 1-20.

23. A stockpiling system, comprising a data acquisition device and the stockpiling device according to claim 21 or 22.

24. A loader, comprising the stockpiling system according to claim 23.

25. A computer-readable storage medium, wherein, The computer-readable storage medium stores computer instructions, and when the instructions are executed by a processor, the stockpiling method according to any one of claims 1-20 is implemented.

26. A computer program product, comprising a computer program, wherein, When the computer program is executed by a processor, the stockpiling method according to any one of claims 1-20 is implemented.

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