Luggage space area determination method, electronic equipment and storage medium

Abstract

The invention provides a luggage space area determination method, electronic equipment and a storage medium, and relates to the technical field of luggage space area determination, and the method comprises the steps: judging whether there is luggage on a luggage barrow or not; if no luggage exists on the luggage barrow, acquiring a first luggage barrow image corresponding to the luggage barrow; transferring the current luggage code to the original position of the luggage barrow, and acquiring a second luggage barrow image of the luggage barrow; obtaining the coordinate of each pixel point corresponding to the first luggage barrow image and the coordinate of each pixel point corresponding to the second luggage barrow image; according to the coordinate of each pixel point corresponding to the first luggage barrow image and the coordinate of each pixel point corresponding to the second luggage barrow image, determining the space area occupied by the current luggage on the luggage barrow; according to the method, when the space area of the luggage is identified, the two-dimensional image corresponding to the luggage barrow is used, only the coordinates of the pixels in the two-dimensional image are processed, the calculation amount is small, and the luggage area identification efficiency and accuracy are high.

Description

Technical Field

[0001] The present invention relates to the technical field of determining the spatial area of luggage, and particularly to a method for determining the spatial area of luggage, an electronic device, and a storage medium. Background Art

[0002] In the civil aviation field, luggage handling is a major challenge in modern aviation industry. Due to the increasing passenger flow at airports, the number of passengers' luggage is also rising continuously. For luggage handling, in order to improve the handling efficiency of luggage, some airports use automated luggage handling equipment to transfer luggage from the conveyor belt to the luggage cart, and then transport it to the corresponding flight aircraft by the luggage cart for loading and consignment. Before the automated handling equipment transfers the luggage to the luggage cart, it is necessary to identify the luggage area on the luggage cart to determine the subsequent luggage stacking position. In the prior art, a large model is used to identify the luggage area in the luggage cart image. However, this method has a large amount of calculation, and the efficiency and accuracy of luggage area identification are relatively low. Summary of the Invention

[0003] For the above technical problems, the technical solution adopted by the present invention is as follows:

[0004] According to the first aspect of the present application, there is provided a method for determining the spatial area of luggage, the method including the following steps:

[0005] H100, determining whether there is luggage on the luggage cart.

[0006] H200, if there is no luggage on the luggage cart, obtaining the first luggage cart image corresponding to the luggage cart.

[0007] H300, stacking the current luggage to the origin position of the luggage cart, and obtaining the second luggage cart image of the luggage cart; wherein, both the first luggage cart image and the second luggage cart image are two-dimensional images.

[0008] H400, obtaining the coordinates of each pixel point corresponding to the first luggage cart image and the coordinates of each pixel point corresponding to the second luggage cart image.

[0009] H500, determining the spatial area occupied by the current luggage on the luggage cart according to the coordinates of each pixel point corresponding to the first luggage cart image and the coordinates of each pixel point corresponding to the second luggage cart image.

[0010] According to another aspect of the present application, there is also provided a non-transitory computer-readable storage medium, in which at least one instruction or at least one program is stored, and at least one instruction or at least one program is loaded and executed by a processor to implement the above method for determining the spatial area of luggage.

[0011] According to another aspect of the present application, an electronic device is further provided, including a processor and the above-mentioned non-transitory computer-readable storage medium.

[0012] The present invention has at least the following beneficial effects:

[0013] In the method for determining the spatial area of luggage of the present invention, it is determined whether there is luggage on the luggage cart; if there is no luggage on the luggage cart, a first image of the luggage cart is obtained; the current luggage is moved to the origin position of the luggage cart, and a second image of the luggage cart is obtained; the coordinates of each pixel point corresponding to the first image of the luggage cart and the coordinates of each pixel point corresponding to the second image of the luggage cart are obtained; according to the coordinates of each pixel point corresponding to the first image of the luggage cart and the coordinates of each pixel point corresponding to the second image of the luggage cart, the spatial area occupied by the current luggage on the luggage cart is determined; in the present invention, when identifying the spatial area of the luggage, a two-dimensional image corresponding to the luggage cart is used, and only the coordinates of the pixels in the two-dimensional image are processed, with a relatively small amount of calculation, and the efficiency and accuracy of luggage area identification are relatively high. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0015] Figure 1 It is a flowchart of the method for determining the spatial area of luggage provided by the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of the present invention.

[0017] It should be noted that based on the present disclosure, those skilled in the art should understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement the device and / or practice the method. In addition, this device and / or practice this method can be implemented using other structures and / or functions in addition to one or more of the aspects described herein.

[0018] Embodiment 1:

[0019] Before generating the luggage enclosure box, it is necessary to identify the luggage area. The luggage area on the luggage cart can be identified through the following steps:

[0020] S100, obtain the initial point cloud coordinates of each initial point in the point cloud image corresponding to the luggage cart parking area, so as to obtain the initial point coordinate list A = (A 1 , A 2 , …, A i , …, A n ), i = 1, 2, …, n; where A i is the initial point coordinate of the i-th initial point corresponding to the luggage cart parking area, and n is the number of initial points in the point cloud image corresponding to the luggage cart parking area.

[0021] In this embodiment, the luggage carried by the robotic arm from the luggage conveyor needs to be stacked on the luggage cart; there is a preset luggage cart parking area corresponding to the luggage cart, and a point cloud image acquisition device, such as a lidar or a depth camera, is installed above the luggage cart parking area; the point cloud image of the luggage cart parking area can be obtained; it should be noted that the area occupied by the luggage cart parking area is larger than the actual area occupied by the luggage cart, so as to ensure that the image of the luggage cart can be completely captured.

[0022] S200, determine each intermediate point from all the initial points according to the coordinates of the preset luggage cart area, so as to obtain the intermediate point coordinate list B = (B 1 , B 2 , …, B j , …, B m ), j = 1, 2, …, m; where B j is the determined j-th intermediate point, and m is the number of determined intermediate points; B j = (B j，x , B j，y , B j，z ); B j，x is the X-axis coordinate of the j-th intermediate point, B j，y is the Y-axis coordinate of the j-th intermediate point, and B j，z is the Z-axis coordinate of the j-th intermediate point.

[0023] In this embodiment, step S200 may include the following steps:

[0024] S210, obtain the maximum X-axis coordinate PB x，max , the minimum X-axis coordinate PB x，min , the maximum Y-axis coordinate PB y，max and the minimum Y-axis coordinate PB y，min of the preset luggage cart area.

[0025] After the luggage cart is parked at the preset position, the maximum X-axis coordinate, minimum X-axis coordinate, maximum Y-axis coordinate, and minimum Y-axis coordinate of the luggage cart are PB x，max , PB x，min , PB y，max and PB y，min .

[0026] S220. If PB x，min ≤ B j，x ≤ PB x，max and PB y，min ≤ B j，y ≤ PB y，max , then determine B j as the midpoint.

[0027] In this embodiment, the parking area of the luggage cart is larger than the actual occupied area of the luggage cart. Therefore, it is necessary to delete the point cloud outside the luggage cart in the point cloud image corresponding to the parking area of the luggage cart, and only retain the point cloud corresponding to the luggage cart to reduce the computational complexity of subsequent luggage area recognition and improve the computational efficiency.

[0028] S300. Traverse B. If YZ min < |B j，z - PB z | < YZ max , then determine B j as the target point to obtain the target point list C = (C 1 , C 2 , …, C p , …, C q ), p = 1, 2, …, q; where C p is the p-th determined target point, and q is the number of determined target points; PB z is the preset height of the luggage cart floor, YZ min is the preset first height difference threshold, and YZ max is the preset second height difference threshold.

[0029] In this embodiment, PB z can be determined through the following steps:

[0030] S310. Obtain the initial height of each luggage cart to obtain the luggage cart initial height list CA = (CA 1 , CA 2 , …, CA c , …, CA d ), c = 1, 2, …, d; where CA c is the initial height of the c-th luggage cart, and d is the number of luggage carts.

[0031] For each luggage cart within the airport, its height is designed according to a preset height. However, during use, the luggage cart will experience wear and tear, and its height will change to a certain extent. It is possible to obtain the height of each known luggage cart through a traversal method to obtain CA.

[0032] S320. According to CA, determine the initial height volatility μ corresponding to CA = (1 / d) × ∑ d c＝1 (CA c - ((1 / d) × ∑ d c＝1 CA c )) 2 。

[0033] S330. If μ < μ', then determine PB z = (1 / d) × ∑ d c＝1 CA c 。

[0034] In this embodiment, if μ is the variance corresponding to CA, the larger μ is, the higher the data difference within CA; the smaller μ is, the smaller the data difference within CA. If μ < μ', then the mean value of the initial heights of the luggage carts in CA can be directly used to determine PB z 。

[0035] Further, after step S330, the method further includes the following steps:

[0036] S340. If μ ≥ μ', then delete the largest several initial heights of the luggage carts and the smallest several initial heights of the luggage carts in CA.

[0037] S350. Determine the mean value of the remaining initial heights of the luggage carts in CA as PB z 。

[0038] If μ ≥ μ', it indicates that the data difference in CA is relatively large. At this time, it is not appropriate to use the mean value of the initial heights of the luggage carts in CA. Therefore, delete the larger and smaller initial heights of the luggage carts in CA, retain the part of the data with smaller differences, and then determine the mean value of the remaining initial heights of the luggage carts in CA as PB z to improve the rationality of the determined PB z and further improve the accuracy of subsequent luggage area recognition.

[0039] S400. According to C, determine the luggage area.

[0040] In this embodiment, step S400 may include the following steps:

[0041] S410. Use a preset clustering algorithm to cluster the target points in C to obtain a cluster list D = (D 1 , D 2 , …, D a , …, D b ), where a = 1, 2, …, b; among them, D a is the a-th cluster obtained by clustering the target points in C, and b is the number of clusters obtained by clustering the target points in C.

[0042] In this embodiment, the preset clustering algorithm can be the DBSCAN clustering algorithm. During the clustering process, the clustering between target points can be used for clustering, and the target points with adjacent distribution positions in C can be clustered into one cluster.

[0043] S420. Obtain the volume of the point cloud corresponding to all the target points in each cluster in D to obtain a point cloud volume list DA = (DA 1 , DA 2 , …, DA a , …, DA b ); where DA a is the volume of the point cloud corresponding to all the target points in D a .

[0044] In this embodiment, the volume of the point cloud corresponding to all the target points in each cluster can be represented by the minimum bounding box. It should be noted that those skilled in the art can use the existing determination method of the minimum bounding box according to actual needs to determine the minimum bounding box of the point cloud corresponding to all the target points in each cluster, so as to obtain the corresponding volume, which will not be elaborated here.

[0045] S430. If DA a < QA, delete all the target points in D a ; where QA is the preset minimum volume threshold of the luggage.

[0046] In this embodiment, under normal circumstances, the luggage has a minimum volume. For the civil aviation field, the user's luggage cannot be too small; therefore, if DA a < QA, it can be determined that the target points in D a are noise points, and the target points in D a need to be deleted to avoid misidentifying the noise points as the luggage area and improve the accuracy of subsequent luggage area recognition.

[0047] S440. Determine the point cloud area corresponding to the remaining target points in C as the luggage area.

[0048] In this embodiment, the initial point cloud coordinates of each initial point in the point cloud image corresponding to the luggage cart parking area are obtained; according to the coordinates of the preset luggage cart area, each intermediate point is determined from all the initial points; according to the height difference between the intermediate point and the luggage cart bottom plate, each target point corresponding to the luggage is determined, and thus the luggage area is further determined according to each target point; the method in the present invention is based on the point cloud image corresponding to the luggage cart parking area, and the calculation amount is small during the entire luggage area recognition process. Therefore, the recognition efficiency of the luggage area is high.

[0049] In addition, in the luggage area recognition method of the present invention, the point cloud coordinates of each initial point in the point cloud image of the luggage cart parking area can be obtained by a lidar, and the accuracy of the point cloud coordinates is very high; therefore, the accuracy of the subsequently recognized luggage area is also high.

[0050] Embodiment Two:

[0051] After determining the luggage area, the following steps can be used to quantify the luggage area for subsequent stacking of luggage:

[0052] Q100, obtain the point cloud image of the luggage area corresponding to the luggage on the luggage cart; wherein, the point cloud image of the luggage area includes a plurality of points, and each point corresponds to coordinate information.

[0053] In this embodiment, the point cloud image of the luggage area corresponding to the luggage on the luggage cart can be obtained through the method steps in Embodiment One, which will not be elaborated here.

[0054] Q200, perform average cutting on the point cloud image of the luggage area along the X-axis direction to obtain the first sub-bounding box list WA = (WA 1 , WA 2 , …, WA e , …, WA f ), e = 1, 2, …, f; wherein, WA e is the e-th first sub-bounding box obtained by performing average cutting on the point cloud image of the luggage area along the X-axis direction, and f is the number of first sub-bounding boxes obtained by performing average cutting on the point cloud image of the luggage area along the X-axis direction; the first sub-bounding boxes in WA are adjacent in sequence.

[0055] Further, step Q200 may include the following steps:

[0056] Q210, obtain the maximum X-axis coordinate QR x，max , minimum X-axis coordinate QR x，min ; maximum Y-axis coordinate QR y，max and minimum Y-axis coordinate QR y，min of the points in the point cloud image of the luggage area.

[0057] In this embodiment, the coordinates of each point in the point cloud image of the luggage area can be obtained. Therefore, the maximum X-axis coordinate QR of the points in the point cloud image of the luggage area can be obtained. x，max , the minimum X-axis coordinate QR x，min ; the maximum Y-axis coordinate QR y，max and the minimum Y-axis coordinate QR y，min .

[0058] Q220, according to QR y，max and QR y，min , determine that the length LR of the initial first sub-bounding box in the Y-axis direction is LR = QR y，max - QR y，min , and according to QR x，max and QR x，min , determine that the width DR of the initial first sub-bounding box in the X-axis direction is DR = (QR x，max - QR x，min ) / f.

[0059] In this embodiment, when cutting along the X-axis direction, it is necessary to determine the length of the initial first sub-bounding box in the Y-axis direction. Using LR as the length in the Y-axis direction to cut the point cloud image of the luggage area can cut all the areas in the Y-axis direction of the point cloud image of the luggage area.

[0060] Q230, use the initial first sub-bounding box to sequentially cut the point cloud image of the luggage area along the X-axis direction from QR x，min to obtain an initial first sub-bounding box list WA’ = (WA’ 1 , WA’ 2 , …, WA’ e , …, WA’ f ); where WA’ e is the e-th initial first sub-bounding box obtained.

[0061] It can be understood that the placement of the luggage is not regular. For example, it is placed in an L shape. Then, when cutting, there may be a large space without point cloud in the Y-axis direction.

[0062] Q240, obtain the maximum Y-axis coordinate GH e e y，max , the minimum Y-axis coordinate GH e y，min and the maximum Z-axis coordinate GH e z，max e of the point cloud inside WA’

[0063] Q250, adjust the maximum Y-axis coordinate of WA’ e to GH e y，max , and adjust the minimum Y-axis coordinate to GHe y，min Adjust the maximum Z-axis coordinate to GH e z，max to obtain WA e .

[0064] In this embodiment, through step Q240 and step Q250, it is possible to make the first sub-bounding box closely adhere to the corresponding point cloud, avoiding the situation where the generated first sub-bounding box is too large, resulting in waste of the space area of the luggage cart, thereby improving the space utilization rate of the luggage cart.

[0065] Q300. Merge several adjacent first sub-bounding boxes in WA that meet the preset merging conditions into a first bounding box to obtain the first bounding box list EA=(EA 1 , EA 2 , …, EA g , …, EA h ), where g = 1, 2, …, h; among them, EA g is the g-th first bounding box obtained by merging the first sub-bounding boxes, and h is the number of first bounding boxes obtained by merging the first sub-bounding boxes.

[0066] Furthermore, step Q300 may include the following steps:

[0067] Q310. Obtain the first preset value BH = 1 and the second preset value HU = 1.

[0068] Q320. If |LE BH -LE BH+1 | ≤ LE’ 1 , |KD BH -KD BH+1 | ≤ LE’ 2 and |HD BH -HD BH+1 | ≤ LE’ 3 , then determine WA BH and WA BH+1 as the first sub-bounding boxes to be merged; and obtain BH = BH + 1, then enter Q320; otherwise, enter Q330; where LE BH is the length of WA BH , KD BH is the width of WA BH , HD BH is the height of WA BH ; LE’ 1 , LE’ 2 and LE’ 3 are the preset length difference threshold, width difference threshold and height difference threshold respectively.

[0069] Q330, merge each first sub - bounding box to be merged into EA HU ; and obtain HU = HU + 1; enter Q320.

[0070] In this embodiment, LE’ 1 、LE’ 2 and LE’ 3 are empirical values, which can be obtained from a large number of experimental data in the actual application process; through steps Q310 - Q330, several first sub - bounding boxes with similar sizes in the first sub - bounding boxes can be merged into one first bounding box. When stacking luggage subsequently, the calculation times of the bounding boxes can be reduced, and the stacking efficiency can be improved.

[0071] Furthermore, the length of EA HU is the maximum length of the corresponding first sub - bounding boxes to be merged, the height of EA HU is the maximum height of the corresponding first sub - bounding boxes to be merged, and the width of EA HU is the sum of the widths of the corresponding first sub - bounding boxes to be merged; thus, it can be ensured that the merged first bounding box can completely enclose the point cloud of the corresponding luggage area, preventing the point cloud from appearing outside the first bounding box.

[0072] Q400, perform average cutting on the point cloud image of the luggage area along the Y - axis direction to obtain a list of second sub - bounding boxes WB=(WB 1 , WB 2 , …, WB k , …, WB r ), k = 1, 2, …, r; where WB k is the k - th second sub - bounding box obtained by performing average cutting on the point cloud image of the luggage area along the Y - axis direction, and r is the number of second sub - bounding boxes obtained by performing average cutting on the point cloud image of the luggage area along the Y - axis direction; the second sub - bounding boxes in WB are adjacent to each other in sequence.

[0073] Furthermore, step Q400 may include the following steps:

[0074] Q410, obtain the maximum X - axis coordinate QR x，max 、the minimum X - axis coordinate QR x，min ; the maximum Y - axis coordinate QR y，max and the minimum Y - axis coordinate QR y，min of the points in the point cloud image of the luggage area.

[0075] Q420, according to QR x，max and QR x，min , determine the length LT of the initial second sub - bounding box in the X - axis direction as LT = QR x，max -QR x，min , and according to QR y，max and QRy，min , determine the width DR of the initial second sub-bounding box in the Y-axis direction as DR = (QR y，max -QR y，min ) / r.

[0076] Q430, use the initial second sub-bounding box to sequentially cut the point cloud image of the luggage area along the Y-axis direction starting from QR y，min to obtain a list of initial second sub-bounding boxes WB’ = (WB’ 1 , WB’ 2 , …, WB’ k , …, WB’ r ); where WB’ k is the k-th initial second sub-bounding box obtained.

[0077] Q440, obtain the maximum Y-axis coordinate EH k , the minimum Y-axis coordinate EH e y，max , and the maximum Z-axis coordinate EH e y，min of the point cloud within WB’. e z，max .

[0078] Q450, adjust the maximum Y-axis coordinate of WB’ k to EH e y，max , adjust the minimum Y-axis coordinate to EH e y，min , and adjust the maximum Z-axis coordinate to EH e z，max to obtain WB k .

[0079] In this embodiment, the cutting of the point cloud image of the luggage area along the Y-axis is the same as the cutting method of the corresponding point cloud image of the luggage area along the X-axis described above, and will not be elaborated here.

[0080] Q500, merge several adjacent second sub-bounding boxes in WB that meet the preset merging conditions into a second bounding box to obtain a list of second bounding boxes EB = (EB 1 , EB 2 , …, EB u , …, EB v ), u = 1, 2, …, v; where EB u is the u-th second bounding box obtained by merging the second sub-bounding boxes, and v is the number of second bounding boxes obtained by merging the second sub-bounding boxes.

[0081] Further, step Q500 may include the following steps:

[0082] Q510, obtain the third preset value TY = 1 and the fourth preset value RU = 1.

[0083] Q520, if |ME TY - ME TY+1 | ≤ LE’, 1 |ND TY - ND TY+1 | ≤ LE’ 2 and |FD TY - FD TY+1 | ≤ LE’, 3 then determine WB TY and WB TY+1 as the second sub - bounding boxes to be merged; and obtain TY = TY + 1, enter Q520; otherwise, enter Q530; where, ME TY is the length of WB TY ND TY is the width of WB TY FD TY is the height of WB TY LE’ 1 LE’ 2 and LE’ 3 are the preset length difference threshold, width difference threshold and height difference threshold respectively.

[0084] Q530, merge each second sub - bounding box to be merged into EB RU ; and obtain RU = RU + 1; enter Q520.

[0085] Through steps Q510 - Q530, several second sub - bounding boxes with similar sizes in the second sub - bounding boxes can be merged into one second bounding box. When stacking luggage subsequently, the number of calculations of the bounding box can be reduced, improving the stacking efficiency.

[0086] Furthermore, the length of EB RU is the maximum length of the corresponding second sub - bounding boxes to be merged, the height of EB RU is the maximum height of the corresponding second sub - bounding boxes to be merged, and the width of EB RU is the sum of the widths of the corresponding second sub - bounding boxes to be merged; thus, it can be ensured that the merged second bounding box can completely enclose the point cloud of the corresponding luggage area, preventing the point cloud from appearing outside the second bounding box.

[0087] In this embodiment, a point cloud image of the luggage area on the luggage cart is obtained; the point cloud image of the luggage area is respectively cut along the X-axis and the Y-axis to obtain a first sub-bounding box list WA and a second sub-bounding box list WB; several adjacent first sub-bounding boxes in WA that meet the preset merging condition are merged into a first bounding box to obtain a first bounding box list EA corresponding to the luggage area, and several adjacent second sub-bounding boxes in WB that meet the preset merging condition are merged into a second bounding box to obtain a second bounding box list EB corresponding to the luggage area; both the first bounding box and the second bounding box correspond to specific position and size information, so as to achieve accurate quantification of the luggage on the X-axis and the Y-axis.

[0088] In addition, through the method of this embodiment, not only can the bounding box of the luggage area on the X-axis be obtained, but also the bounding box of the luggage area on the Y-axis can be obtained. When stacking luggage subsequently, the bounding box in the X-axis direction or the bounding box in the Y-axis direction can be used according to the position and orientation of the luggage placement.

[0089] Embodiment Three:

[0090] In Embodiment Two, when generating the bounding box of the luggage, the height of the bottom plate of the luggage cart is not considered; in order to make the space utilization rate of the luggage cart higher, the bottom plate of the luggage cart can be removed through the following steps:

[0091] T100, obtain each first bounding box corresponding to the point cloud image of the luggage area to obtain a first bounding box list EA = (EA 1 , EA 2 , …, EA g , …, EA h ), g = 1, 2, …, h; where EA g is the g-th first bounding box corresponding to the point cloud image of the luggage area, and h is the number of first bounding boxes corresponding to the point cloud image of the luggage area; the length of the first bounding box is along the Y-axis direction.

[0092] Furthermore, EA can be obtained through the following steps:

[0093] T110, obtain the point cloud image of the luggage area corresponding to the luggage cart; where the point cloud image of the luggage area includes several points, and each point corresponds to coordinate information.

[0094] In this embodiment, the luggage area on the luggage cart can be obtained through the method steps in Embodiment One, which will not be elaborated here.

[0095] T120, perform average cutting on the point cloud image of the luggage area along the X-axis direction to obtain a first sub-bounding box list WA = (WA 1 , WA 2 , …, WA e, …, WA f ), e = 1, 2, …, f; where, WA e is the e-th first sub-enclosing box obtained by averaging the cutting of the luggage area point cloud image along the X-axis direction, and f is the number of first sub-enclosing boxes obtained by averaging the cutting of the luggage area point cloud image along the X-axis direction; the first sub-enclosing boxes in WA are adjacent to each other in sequence.

[0096] In this embodiment, T120 may include the following steps:

[0097] T121, obtain the maximum X-axis coordinate QR x，max and the minimum X-axis coordinate QR x，min of the points in the luggage area point cloud image; the maximum Y-axis coordinate QR y，max and the minimum Y-axis coordinate QR y，min .

[0098] In this embodiment, the coordinates of each point in the luggage area point cloud image can be obtained. Therefore, the maximum X-axis coordinate QR x，max and the minimum X-axis coordinate QR x，min of the points in the luggage area point cloud image can be obtained; the maximum Y-axis coordinate QR y，max and the minimum Y-axis coordinate QR y，min .

[0099] T122, according to QR y，max and QR y，min , determine the length LR of the initial first sub-enclosing box in the Y-axis direction = QR y，max - QR y，min , and according to QR x，max and QR x，min , determine the width DR of the initial first sub-enclosing box in the X-axis direction = (QR x，max - QR x，min ) / f.

[0100] In this embodiment, when cutting along the X-axis direction, it is necessary to determine the length of the first sub-enclosing box in the Y-axis direction. Using LR as the length in the Y-axis direction to cut the luggage area point cloud image can cut all the areas in the Y-axis direction of the luggage area point cloud image.

[0101] T123, use the initial first sub-enclosing box to sequentially cut the luggage area point cloud image along the X-axis direction starting from QR x，min to obtain an initial first sub-enclosing box list WA’ = (WA’ 1 , WA’ 2 , …, WA’ e , …, WA’ f ); where, WA’ e is the e-th initial first sub-enclosing box obtained.

[0102] It can be understood that the placement of the luggage is not regular. For example, if it is placed in an L shape, then when cutting, there may be a relatively large space without point clouds in the Y-axis direction.

[0103] T124, obtain WA' e The maximum Y-axis coordinate GH of the internal point cloud e y，max and the minimum Y-axis coordinate GH e y，min and the maximum Z-axis coordinate GH e z，max .

[0104] T125, adjust the maximum Y-axis coordinate of WA' e to GH e y，max and the minimum Y-axis coordinate to GH e y，min and the maximum Z-axis coordinate to GH e z，max to obtain WA e .

[0105] In this embodiment, through step Q240 and step Q250, it is possible to make the first sub-bounding box close to the corresponding point cloud, avoiding the situation where the generated first sub-bounding box is too large, resulting in waste of the space area of the luggage cart, thereby improving the space utilization rate of the luggage cart.

[0106] T130, merge several adjacent first sub-bounding boxes in WA that meet the preset merging conditions into a first bounding box to obtain the first bounding box list EA corresponding to the luggage area.

[0107] Further, step T130 may include the following steps:

[0108] T131, obtain the first preset value BH = 1 and the second preset value HU = 1.

[0109] T132, if |LE BH - LE BH+1 | ≤ LE' 1 , |KD BH - KD BH+1 | ≤ LE' 2 and |HD BH - HD BH+1 | ≤ LE' 3 , then determine WA BH and WA BH+1 as the first sub-bounding boxes to be merged; and obtain BH = BH + 1, enter T132; otherwise, enter T133; where LE BH is WABH The length, KD BH is WA BH The width, HD BH is WA BH The height; LE’ 1 、LE’ 2 and LE’ 3 are respectively a preset length difference threshold, a width difference threshold, and a height difference threshold.

[0110] T133, merge each first sub-bounding box to be merged into EA HU ; and obtain HU = HU + 1; enter T132.

[0111] In this embodiment, LE’ 1 、LE’ 2 and LE’ 3 are empirical values, which can be obtained based on a large amount of experimental data in the actual application process; through steps T131 - T133, several first sub-bounding boxes with similar sizes in the first sub-bounding boxes can be merged into one first bounding box, and when stacking luggage subsequently, the calculation times of the bounding boxes can be reduced, improving the stacking efficiency.

[0112] Furthermore, the length of EA HU is the maximum length of the corresponding first sub-bounding boxes to be merged, the height of EA HU is the maximum height of the corresponding first sub-bounding boxes to be merged, and the width of EA HU is the sum of the widths of the corresponding first sub-bounding boxes to be merged; thus, it can be ensured that the merged first bounding box can completely enclose the point cloud of the corresponding luggage area, avoiding the point cloud from appearing outside the first bounding box.

[0113] T200, obtain each second bounding box corresponding to the point cloud image of the luggage area to obtain a second bounding box list EB = (EB 1 , EB 2 , …, EB u , …, EB v ), u = 1, 2, …, v; where EB u is the u-th second bounding box corresponding to the point cloud image of the luggage area, and v is the number of second bounding boxes corresponding to the point cloud image of the luggage area; the length of the second bounding box is along the x-axis direction.

[0114] EB is obtained through the following steps:

[0115] T210, perform an average cut on the point cloud image of the luggage area along the Y-axis direction to obtain a second sub-bounding box list WB = (WB 1 , WB 2 , …, WB k , …, WBr ), k = 1, 2, …, r; where, WB k is the k-th second sub-bounding box obtained by averaging the cutting of the point cloud image of the luggage area along the Y-axis direction, and r is the number of second sub-bounding boxes obtained by averaging the cutting of the point cloud image of the luggage area along the Y-axis direction; the second sub-bounding boxes in WB are adjacent to each other in sequence.

[0116] T220, merge several adjacent second sub-bounding boxes in WB that meet the preset merging conditions into a second bounding box to obtain a second bounding box list EB corresponding to the luggage area.

[0117] In this embodiment, the acquisition method of EB is the same as that of EA, and will not be elaborated here.

[0118] T300, split the overlapping part and non-overlapping part of the first bounding box in EA and the second bounding box in EB into third bounding boxes to obtain a third bounding box list BN = (BN 1 , BN 2 , …, BN α , …, BN β ), α = 1, 2, …, β; where, BN α is the α-th third bounding box obtained by splitting, and β is the number of third bounding boxes obtained by splitting.

[0119] In this embodiment, it can be understood that the first bounding box is obtained by cutting along the X-axis direction, and the second bounding box is obtained by cutting along the Y-axis direction. When the luggage is stacked, it may not necessarily be stacked into a rectangle, and may be in an L shape, and the heights of the luggage are different; therefore, there may be spaces without point clouds in the first bounding box and the second bounding box, and it is necessary to split the first bounding box and the second bounding box to further remove the bounding boxes without point clouds.

[0120] Furthermore, step T300 may include the following steps:

[0121] T310, obtain a fifth preset value WF = 1.

[0122] T311, obtain a sixth preset value WK = 1.

[0123] T312, if there is an overlapping part between EA WF and EB WF+WK-1 , then determine the overlapping part and non-overlapping part of EA WF and EB WF+WK-1 as the third bounding box; otherwise, determine EA WF and EB WF+WK-1 as the third bounding box.

[0124] T313. If WK < v, then obtain WK = WK + 1; enter T312; otherwise, enter T314.

[0125] T314. If WF < h, then obtain WF = WF + 1; enter T311; otherwise, jump out of the current process.

[0126] Through the above steps T310 - T314, the overlapping and non - overlapping parts between the first bounding box and the second bounding box can be split into the third bounding box.

[0127] After step T314, the method further includes the following steps:

[0128] T315. Traverse all the third bounding boxes, delete the third bounding boxes without point clouds inside to obtain BN.

[0129] In this embodiment, there may not be point clouds in all the third bounding boxes. The third bounding boxes without point clouds are empty bounding boxes and there is no luggage inside; therefore, it is necessary to delete them to release the unused space of the luggage cart and improve the space utilization rate.

[0130] T400. Obtain the maximum Z - axis coordinate of the point cloud in each third bounding box in BN to obtain the BN maximum Z - axis coordinate list PA z =(PA z，1 , PA z，2 , …, PA z，α , …, PA z，β ); where PA z，α is the maximum Z - axis coordinate of the point cloud in BN α .

[0131] T500. Adjust the Z - axis coordinate of BN α to PA z，α .

[0132] In this embodiment, the first sub - bounding box and the second sub - bounding box are both in the shape of a cuboid; the first bounding box and the second bounding box are larger bounding boxes, and their heights are determined based on the maximum height of the corresponding luggage. If the upper surface of the corresponding luggage is not a plane but a convex surface, then there will also be a relatively large space without luggage in the corresponding first bounding box or second bounding box. Therefore, in order to make the third bounding box fit more closely to the point cloud of the luggage, the Z - axis coordinate of the third bounding box is adjusted to the maximum Z - axis coordinate of the point cloud inside it, so that the third bounding box can fit closely to the corresponding point cloud and improve the space utilization rate of the luggage cart.

[0133] In this embodiment, each first bounding box corresponding to the point cloud image of the luggage area is obtained to obtain the first bounding box list EA, and each second bounding box corresponding to the point cloud image of the luggage area is obtained to obtain the second bounding box list EB; the overlapping and non-overlapping parts of the first bounding box in EA and the second bounding box in EB are split into third bounding boxes to obtain the third bounding box list BN; the Z-axis coordinate of each third bounding box in the third bounding box list BN is adjusted to the maximum Z-axis coordinate of the internal point cloud therein; so that the height of the third bounding box is the same as the height of the corresponding luggage, and when the luggage is stacked later, the space of the luggage cart can be fully utilized, thereby improving the utilization rate of the space of the luggage cart.

[0134] Embodiment 4:

[0135] When there is no luggage on the luggage cart, the luggage area can be determined by the method for determining the space area of the luggage as shown in Figure 1 to improve the efficiency of determining the luggage area:

[0136] H100, determine whether there is luggage on the luggage cart.

[0137] In this embodiment, when the luggage cart arrives at the luggage cart parking area, there may or may not be luggage on the luggage cart. First, it is judged whether there is luggage on the luggage cart. Specifically, it can be judged through the following steps:

[0138] H111, obtain the Z-axis coordinate of each initial pixel point of the initial luggage cart image.

[0139] H112, if the volatility of the Z-axis coordinates of all the initial pixel points is less than the preset volatility threshold, it is determined that there is no luggage on the luggage cart; otherwise, it is determined that there is luggage on the luggage cart.

[0140] In this embodiment, the volatility of the Z-axis coordinates of all the initial pixel points can be the variance corresponding to the Z-axis coordinates of all the initial pixel points; it can be understood that when there is no luggage placed on the luggage cart, the bottom plate of the luggage cart is a plane, and the Z-axis coordinates of the pixels corresponding to the bottom plate are equal or have very small differences; when the volatility of the Z-axis coordinates of all the initial pixel points is greater than the preset volatility threshold, it means that the Z-axis coordinates of all the initial pixel points fluctuate greatly, indicating that there is luggage placed on the luggage cart.

[0141] H200, if there is no luggage on the luggage cart, obtain the first luggage cart image corresponding to the luggage cart.

[0142] In this embodiment, the first luggage cart image can be obtained by an industrial camera; it should be noted that the industrial camera corresponds to a camera coordinate system, and the luggage cart corresponds to a luggage cart coordinate system, and the two can perform coordinate conversion to determine the coordinate information of the pixel points in the first luggage cart image.

[0143] Further, if there is luggage on the luggage cart, the spatial area occupied by the current luggage on the luggage cart is determined through the point cloud image corresponding to the luggage cart.

[0144] In this embodiment, the method steps in Embodiment 1 can be used to determine the spatial area occupied by the current luggage on the luggage cart; details are not described herein.

[0145] H300, stack the current luggage to the origin position of the luggage cart and obtain the second luggage cart image; wherein, both the first luggage cart image and the second luggage cart image are two-dimensional images.

[0146] In this embodiment, when there is no luggage on the luggage cart, the luggage handling system stacks the current luggage to the origin position of the luggage cart, for example: the center point position of the luggage cart.

[0147] H400, obtain the coordinates of each pixel point corresponding to the first luggage cart image and the coordinates of each pixel point corresponding to the second luggage cart image.

[0148] In this embodiment, an industrial camera is installed at a preset position above the luggage cart. The industrial camera corresponds to a known camera coordinate system, and the luggage cart corresponds to a known luggage cart coordinate system. The two can perform coordinate transformation to determine the coordinate information of the pixel points in the first luggage cart image and the second luggage cart image; it should be noted that those skilled in the art can, according to actual needs, use existing coordinate transformation methods to obtain the coordinates of each pixel point corresponding to the first luggage cart image and the coordinates of each pixel point corresponding to the second luggage cart image, details are not described herein.

[0149] H500, determine the spatial area occupied by the current luggage on the luggage cart according to the coordinates of each pixel point corresponding to the first luggage cart image and the coordinates of each pixel point corresponding to the second luggage cart image.

[0150] Further, step H500 may include the following steps:

[0151] H510, divide the first luggage cart image into several adjacent image regions to be compared to obtain the first list of image regions to be compared UA = (UA 1 , UA 2 , …, UA θ , …, UA ω ), θ = 1, 2, …, ω; where UA θ is the θth first image region to be compared obtained by dividing the first luggage image, and ω is the number of the first image regions to be compared obtained by dividing the first luggage image.

[0152] H520, divide the second luggage cart image into several adjacent image regions to be compared, so as to obtain the second list of image regions to be compared UB = (UB 1 , UB 2 , …, UB θ , …, UB ω ); where UB θ is the θ-th second image region to be compared obtained by dividing the second luggage image; UA θ and UB θ correspond to the same region of the luggage cart.

[0153] In this embodiment, the first luggage cart image and the second luggage cart image can be divided into several rectangular image regions to be compared, and the size of each image region to be compared can be determined according to actual needs.

[0154] H530, obtain the first target height coordinates of each first image region to be compared in UA, so as to obtain the first list of target height coordinates UC = (UC 1 , UC 2 , …, UC θ , …, UC ω ); where UC θ is the first target height coordinate of UA θ ; UC θ is obtained through the Z-axis coordinates of several pixel points in UA θ .

[0155] Furthermore, UC θ is determined through the following steps:

[0156] H531, obtain the Z-axis coordinates of each pixel point at a preset position in UA θ , so as to obtain the list of pixel point coordinates ZP θ corresponding to UA θ = (ZP θ，1 , ZP θ，2 , …, ZP θ，γ , …, ZP θ，δ ), γ = 1, 2, …, δ; where ZP θ，γ is the Z-axis coordinate of the γ-th pixel point at a preset position in UA θ , and δ is the number of pixel points at a preset position in UA θ .

[0157] H532, according to ZP θ , determine UC θ = (1 / δ) × ∑ δ γ＝1 ZP θ，γ .

[0158] In this embodiment, the preset position can be UA θ The pixel points corresponding to the four vertices, the center point, and the midpoints of each side; it is possible to obtain the Z-axis coordinates of each pixel point at the preset position within UA θ In the Z-axis coordinate of each pixel point at the preset position within UA

[0159] H540, obtain the second target height coordinates of each second image region to be compared in UB, so as to obtain the second target height coordinate list UD = (UD 1 , UD 2 , …, UD θ , …, UD ω ); where UD θ is the second target height coordinate of UB θ ; UD θ is obtained through the Z-axis coordinates of several pixel points within UB θ in the Z-axis coordinate of each pixel point at the preset position within UA

[0160] In this embodiment, the determination method of UD θ is the same as that of UC θ ; it should be noted that each pixel point at the preset position within UA θ is the same as each pixel point at the preset position within UB θ in the Z-axis coordinate of each pixel point at the preset position within UA

[0161] H550, according to UC and UD, determine the space area occupied by the current luggage on the luggage cart.

[0162] Furthermore, step H550 may include the following steps:

[0163] H551, traverse UC and UD, if |UC θ - UD θ | > SG, then determine UC θ as the target first image region to be compared, and determine UD θ as the target second image region to be compared; where SG is a preset target height difference threshold.

[0164] In this embodiment, if |UC θ - UD θ | > SG, it means that there is a large change in the Z-axis coordinates of the pixel points at the preset position within UA θ and UB θ . It can be determined that there is newly stacked luggage in the luggage cart area corresponding to UC θ ; thus, it is possible to filter out all the areas where there is no newly stacked luggage; when filtering out most of the areas where there is no newly stacked luggage, only some pixel points are used, and the calculation amount is extremely small, thus greatly improving the efficiency of image processing.

[0165] H552, Obtain each pixel point within each target first image region to be compared, so as to obtain the first pixel point list JC = (JC 1 , JC 2 , …, JC ε , …, JC σ ); where JC ε is the ε-th pixel point within the overall region corresponding to all the target first image regions to be compared, and σ is the number of pixel points within the overall region corresponding to all the target first image regions to be compared.

[0166] H553, Obtain each pixel point within each target second image region to be compared, so as to obtain the second pixel point list JD = (JD 1 , JD 2 , …, JD ε , …, JD σ ); where JD ε is the ε-th pixel point within the overall region corresponding to all the target second image regions to be compared; JC ε and JD ε are at the same position on the luggage cart.

[0167] H554, If |JC ε _Z - JD ε _Z| > UZ, then determine JD ε as the target pixel point; where JC ε _Z is the Z-axis coordinate of JC ε , and JD ε _Z is the Z-axis coordinate of JD ε ; UZ is the preset threshold of the Z-axis coordinate difference of the pixel point.

[0168] Through the above steps, all pixel points with a large change in the Z-axis coordinate can be determined.

[0169] H555, Determine the spatial region formed by all the target pixel points as the spatial region occupied by the current luggage on the luggage cart.

[0170] The method for determining the spatial region of the luggage in this embodiment determines whether there is any luggage on the luggage cart; if there is no luggage on the luggage cart, a first image of the luggage cart is obtained; the current luggage code is moved to the origin position of the luggage cart, and a second image of the luggage cart is obtained; the coordinates of each pixel point corresponding to the first image of the luggage cart and the coordinates of each pixel point corresponding to the second image of the luggage cart are obtained; according to the coordinates of each pixel point corresponding to the first image of the luggage cart and the coordinates of each pixel point corresponding to the second image of the luggage cart, the spatial region occupied by the current luggage on the luggage cart is determined; in the present invention, when identifying the spatial region of the luggage, a two-dimensional image corresponding to the luggage cart is used, and only the coordinates of the pixels in the two-dimensional image are processed, with a relatively small amount of calculation, and the efficiency and accuracy of luggage region identification are relatively high.

[0171] In addition, although the steps of the methods in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in that specific order, or that all of the shown steps must be performed to achieve the desired result. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step for execution, and / or one step may be decomposed into multiple steps for execution, etc.

[0172] An embodiment of the present invention also provides a non-transitory computer-readable storage medium, which can be disposed in an electronic device to store at least one instruction or at least one segment of a program related to a method for implementing a method in the method embodiment, and the at least one instruction or the at least one segment of the program is loaded and executed by the processor to implement the method provided in the above embodiment.

[0173] The program product can adopt any combination of one or more readable media. The readable media can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0174] A computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. The readable signal medium may also be any readable medium other than a readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.

[0175] The program code contained on the readable medium can be transmitted with any appropriate medium, including but not limited to wireless, wired, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0176] The program code for performing the operations of this application can be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, etc., and also including conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as a stand-alone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (e.g., by using an Internet service provider to connect through the Internet).

[0177] Embodiments of the present invention also provide an electronic device, including a processor and the foregoing non-transitory computer-readable storage medium.

[0178] The electronic device is merely an example and should not impose any limitation on the functions and usage scope of the embodiments of this application.

[0179] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include but are not limited to: at least one of the foregoing processors, at least one of the foregoing memories, and a bus connecting different system components (including the memory and the processor).

[0180] Wherein, the memory stores program code, and the program code can be executed by the processor, so that the processor executes the steps in various embodiments described in this specification.

[0181] The memory may include a readable medium in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read-only memory (ROM).

[0182] The memory may also include program / utility with a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may include an implementation of a network environment.

[0183] The bus may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of a variety of bus structures.

[0184] The electronic device may also communicate with one or more external devices (such as a keyboard, a pointing device, a Bluetooth device, etc.), may also communicate with one or more devices enabling a user to interact with the electronic device, and / or may communicate with any device enabling the electronic device to communicate with one or more other computing devices (such as a router, a modem, etc.). Such communication may be carried out through an input / output (I / O) interface. Also, the electronic device may communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter. The network adapter communicates with other modules of the electronic device through the bus. It should be understood that although not shown in the figures, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0185] Through the description of the above embodiments, those skilled in the art can easily understand that the exemplary embodiments described herein can be implemented by software, or can be implemented by the way of software combined with necessary hardware. Therefore, the technical solutions according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which may be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions for causing a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0186] The embodiments of the present invention also provide a computer program product, which includes program code, and when the program product runs on an electronic device, the program code is used to cause the electronic device to execute the steps in the methods according to various exemplary embodiments of the present invention described above in this specification.

[0187] Although some specific embodiments of the present invention have been described in detail by way of examples, those skilled in the art should understand that the above examples are for illustrative purposes only and not for limiting the scope of the present invention. Those skilled in the art should also understand that various modifications can be made to the embodiments without departing from the scope and spirit of the present invention.

Claims

1. A method for determining a spatial area of ​​luggage, characterized in that: The method comprises the following steps: H100, determine whether there is luggage on the luggage cart; H200, if there is no luggage on the luggage cart, obtain a first luggage cart image corresponding to the luggage cart; H300, mark the current luggage to the origin position of the luggage cart, and obtain a second luggage cart image of the luggage cart; wherein the first luggage cart image and the second luggage cart image are both two-dimensional images; H400, obtaining the coordinates of each pixel point corresponding to the first luggage cart image and the coordinates of each pixel point corresponding to the second luggage cart image; H500, determine the space area currently occupied by the luggage on the luggage cart according to the coordinates of each pixel point corresponding to the first luggage cart image and the coordinates of each pixel point corresponding to the second luggage cart image.

2. The method for determining the spatial area of ​​luggage according to claim 1, characterized in that: Step H500 includes the following steps: H510, divide the first luggage cart image into a plurality of adjacent image regions to be compared, so as to obtain a first image region list UA=(UA1, UA2, ..., UA θ ,…,UA ω ), θ=1, 2,...,ω; among them, UA θ is the θth first image region to be compared obtained by dividing the first baggage image, and ω is the number of first image regions to be compared obtained by dividing the first baggage image; H520, divide the second luggage cart image into a plurality of adjacent image regions to be compared, so as to obtain a second image region list UB=(UB1, UB2, ..., UB θ ,…,UB ω ), where UB θ is the θth second image area to be compared obtained by dividing the second luggage image; UA θ and UB θ The same area as the luggage cart; H530, obtain the first target height coordinates of each first image area to be compared in UA to obtain a first target height coordinate list UC = (UC1, UC2, ..., UC θ ,…,UC ω );UC θ For UA θ The first target height coordinate; UC θ By UA θ The Z-axis coordinates of several pixel points within are obtained; H540, obtain the second target height coordinates of each second to-be-compared image area in UB to obtain a second target height coordinate list UD=(UD1, UD2, ..., UD θ ,…,UD ω ), where UD θ For UB θ The second target height coordinate; UD θ Via UB θ The Z-axis coordinates of several pixel points within are obtained; H550, based on UC and UD, determines the space area currently occupied by the luggage on the luggage cart.

3. The method for determining the spatial area of ​​luggage according to claim 2, characterized in that: Step H550 includes the following steps: H551, traverse UC and UD, if |UC θ -UD θ |>SG, then UC θ Determine the first image area to be compared as the target, and set UD θ Determine the target second image area to be compared; wherein SG is a preset target height difference threshold; H552, obtain each pixel point in the first to-be-compared image area of ​​each target to obtain a first pixel point list JC=(JC1, JC2, ..., JC ε , …, JC σ ), ε=1, 2,...,σ; among them, JC ε is the εth pixel point in the overall area corresponding to all the target first image areas to be compared, and σ is the number of pixels in the overall area corresponding to all the target first image areas to be compared; H553, obtain each pixel point in the second to-be-compared image area of ​​each target to obtain a second pixel point list JD=(JD1, JD2, ..., JD ε , …, J.D. σ );JD ε is the εth pixel point in the overall area corresponding to the second image area to be compared for all targets; JC ε With JD ε The corresponding luggage carts have the same position; H554, if | JC ε _Z-JD ε _Z|>UZ, then JD ε Determined as the target pixel; among them, JC ε _Z is JC ε The Z-axis coordinate, JD ε _Z stands for JD ε The Z-axis coordinate of the pixel point; UZ is the preset Z-axis coordinate difference threshold of the pixel point; H555, determine the spatial area formed by all target pixels as the spatial area currently occupied by the luggage on the luggage cart.

4. The method for determining the spatial area of ​​luggage according to claim 2, characterized in that: UC θ Determine by following these steps: H531, Get UA θ The Z-axis coordinate of each preset pixel point in the θ Corresponding preset position pixel point coordinate list ZP θ =(ZP θ，1 , ZP θ，2 , …, ZP θ，γ , …, ZP θ，δ ), γ=1, 2,..., δ; where, ZP θ，γ For UA θ The Z-axis coordinate of the pixel point at the γth preset position, δ is UA θ The number of pixels at preset positions within the H532, according to ZP θ , determine UC θ =(1 / δ)×∑ δ γ＝1 ZP θ，γ .

5. The method for determining the spatial area of ​​luggage according to claim 4, characterized in that: UA θ Each preset pixel point is evenly distributed in UA θ Inside.

6. The method for determining the spatial area of ​​luggage according to claim 1, characterized in that: Step H100 includes the following steps: H111, obtaining the Z-axis coordinate of each initial pixel point corresponding to the initial luggage cart image of the luggage cart; H112, if the fluctuation rate of the Z-axis coordinates of all the initial pixel points is less than the preset fluctuation rate threshold, it is determined that there is no luggage on the luggage cart; otherwise, it is determined that there is luggage on the luggage cart.

7. The method for determining the spatial area of ​​luggage according to claim 1, characterized in that: After step H100, the method further comprises the following steps: H113, if there is luggage on the luggage cart, the space area currently occupied by the luggage on the luggage cart is determined through the point cloud image corresponding to the luggage cart.

8. A non-transitory computer-readable storage medium, wherein at least one instruction or at least one program is stored in the storage medium, characterized in that: The at least one instruction or the at least one program is loaded and executed by the processor to implement the method for determining the spatial area of ​​luggage according to any one of claims 1 to 7.

9. An electronic device, characterized in that: Includes a processor and the non-transitory computer-readable storage medium of claim 8.

Images