Method for determining luggage spatial area, electronic device and storage medium

Abstract

The present invention provides a method for determining a spatial area of ​​luggage, an electronic device, and a storage medium, and relates to the technical field of determining the spatial area of ​​luggage. The method comprises: determining whether there is luggage on a luggage cart; if there is no luggage on the luggage cart, obtaining a first luggage cart image corresponding to the luggage cart; marking the current luggage to the origin position of the luggage cart and obtaining a second luggage cart image of the luggage cart; 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; and determining the spatial area occupied by the current luggage on the luggage cart based on 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. 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, resulting in a small amount of calculation and high efficiency and accuracy in luggage area identification.

Description

Technical Field

[0001] The present invention relates to the technical field of luggage spatial area determination, and in particular to a luggage spatial area determination method, electronic equipment, and storage medium. Background Art

[0002] In the civil aviation sector, baggage handling is a major challenge for the modern aviation industry. As airport passenger traffic continues to increase, the amount of luggage carried by passengers is also increasing. To improve baggage handling efficiency, some airports use automated baggage handling equipment to move luggage from conveyor belts to baggage carts, which are then transported to the corresponding aircraft for loading and check-in. Before the automated handling equipment transfers the luggage to the cart, it is necessary to identify the luggage areas on the cart to determine the subsequent stacking locations of the luggage. Existing technologies use large models to identify luggage areas in cart images. However, this method is computationally intensive and results in low efficiency and accuracy in baggage area recognition. Summary of the Invention

[0003] In view of the above technical problems, the technical solution adopted by the present invention is:

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

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

[0006] H200: If there is no luggage on the luggage cart, obtain a first luggage cart image corresponding to the luggage cart.

[0007] 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.

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

[0009] H500 , determine the spatial area currently occupied by the luggage on the luggage cart based on the coordinates of each pixel corresponding to the first luggage cart image and the coordinates of each pixel corresponding to the second luggage cart image.

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

[0011] According to another aspect of the present application, an electronic device is 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] The method for determining the spatial area of ​​luggage of the present invention determines whether there is luggage on a luggage cart; if there is no luggage on the luggage cart, obtains a first luggage cart image corresponding to the luggage cart; codes the current luggage to the origin position of the luggage cart and obtains a second luggage cart image of the luggage cart; obtains 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; and determines the spatial area occupied by the current luggage on the luggage cart based on 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. 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, resulting in a small amount of calculation and high efficiency and accuracy in luggage area identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0015] Figure 1 This is a flowchart of a method for determining a spatial area of ​​luggage provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making any creative efforts shall fall within the scope of protection of the present invention.

[0017] It should be noted that, based on this disclosure, those skilled in the art will appreciate that an aspect described herein can be implemented independently of any other aspect, and that two or more of these aspects can be combined in various ways. For example, any number of the aspects described herein can be used to implement an apparatus and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement such an apparatus and / or practice such a method.

[0018] Example 1:

[0019] Before generating the luggage bounding box, the luggage area needs to be identified. The luggage area on the luggage cart can be identified by the following steps:

[0020] S100, obtaining the initial point cloud coordinates of each initial point in the point cloud image corresponding to the luggage trolley parking area to obtain an initial point coordinate list A = (A1, A2, ..., 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 a luggage cart. Each luggage cart has a preset parking area. A point cloud image acquisition device, such as a lidar or a depth camera, is installed above the parking area to acquire a point cloud image of the parking area. It should be noted that the area occupied by the parking area is larger than the actual area occupied by the luggage cart, thereby ensuring that a complete image of the luggage cart is captured.

[0022] S200, according to the coordinates of the preset luggage cart area, determine each intermediate point from all the initial points to obtain an intermediate point coordinate list B = (B1, B2, ..., B j ,…,B m ), j = 1, 2, ..., m; where B j is the jth intermediate point determined, m is the number of intermediate points determined; B j =(B j，x , B j，y , B j，z );B j，x is the X-axis coordinate of the j-th midpoint, B j，y is the Y-axis coordinate of the j-th midpoint, B j，z is the Z-axis coordinate of the j-th midpoint.

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

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

[0025] When the luggage cart is parked at the preset position, the maximum X-axis coordinate, the minimum X-axis coordinate, the maximum Y-axis coordinate, and the minimum Y-axis coordinate of the luggage cart are PB respectively.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 B j Determine the midpoint.

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

[0028] S300, traverse B, if YZ min <|B j，z -PB z |<YZ max , then B j Determine as the target point to obtain the target point list C = (C1, C2, ..., C p ,…,C q ), p=1, 2, ..., q; where C p is the p target points determined, q is the number of target points determined; PB z is the height of the preset luggage trolley floor, YZ min is the preset first height difference threshold, YZ max is the preset second height difference threshold.

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

[0030] S310, obtaining the initial height of each luggage cart to obtain a luggage cart initial height list CA = (CA1, CA2, ..., CA c ,…,CA d ), c=1, 2, ..., d; where CA c is the initial height of the cth luggage cart, and d is the number of luggage carts.

[0031] The height of each luggage cart in the airport is designed according to a preset height. However, the luggage cart will wear out during use, and its height will change to a certain extent. The height of each known luggage cart can be obtained by traversing to obtain CA.

[0032] S320, based on 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 in CA is, and the smaller μ is, the smaller the data difference in CA is; if μ<μ', the mean of the initial height of the luggage cart in CA can be used to directly determine PB z .

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

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

[0037] S350, determine the average of the initial heights of the remaining luggage carts in CA as PB z .

[0038] If μ ≥ μ', it means that the data in CA have large differences. At this time, it is not appropriate to use the mean of the initial heights of the luggage carts in CA. Therefore, the larger and smaller initial heights of the luggage carts in CA are deleted, and the data with smaller differences are retained. Then the mean of the remaining initial heights of the luggage carts in CA is determined as PB. z , to improve PB z The rationality of the determination can further improve the accuracy of subsequent baggage area identification.

[0039] S400: Determine the luggage area according to C.

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

[0041] S410, clustering the target points in C using a preset clustering algorithm to obtain a cluster list D = (D1, D2, ..., D a ,…,D b ), a=1, 2, …, b; where D ais the ath 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 may be a DBSCAN clustering algorithm. In the clustering process, clustering between target points may be used to cluster target points with adjacent distribution positions in C into one cluster.

[0043] S420, obtain the volume of the point cloud corresponding to all target points in each cluster in D to obtain a point cloud volume list DA = (DA1, DA2, ..., DA a ,…,DA b ), among which, DA a D a The volume of the point cloud corresponding to all target points within.

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

[0045] S430, if DA a <QA, then D a All destination points within are deleted; where QA is the preset minimum baggage volume threshold.

[0046] In this embodiment, under normal circumstances, the volume of luggage has a minimum volume. For the civil aviation field, the user's luggage cannot be too small; therefore, if DA a <QA, then we can determine D a The target point inside is a noise point, so D a The target points within the noise area are deleted to avoid misidentifying the noise points as the luggage area, so as to 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; based on the preset coordinates of the luggage cart area, each intermediate point is determined from all the initial points; based on the height difference between the intermediate point and the luggage cart floor, each target point corresponding to the luggage is determined, and the luggage area is further determined based on each target point. The method of the present invention is based on the point cloud image corresponding to the luggage cart parking area. The computational complexity of the entire luggage area recognition process is relatively low, and therefore the luggage area recognition efficiency is relatively 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 laser radar, and the accuracy of the point cloud coordinates is very high; therefore, the accuracy of the subsequently recognized luggage area is also high.

[0050] Example 2:

[0051] After determining the baggage area, you can quantify the baggage area by following the steps below to facilitate subsequent baggage stacking:

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

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

[0054] Q200, perform average cutting on the baggage area point cloud image along the X-axis direction to obtain the first sub-bounding box list WA=(WA1, WA2, ..., WA e ,…,WA f ), e=1, 2,..., f; among them, WA e is the e-th first sub-bounding box obtained by averaging 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 averaging the point cloud image of the luggage area along the X-axis direction. The first sub-bounding boxes in WA are adjacent to each other.

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

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

[0057] In this embodiment, the coordinates of each point in the baggage area point cloud image can be obtained, so the maximum X-axis coordinate QR of the point in the baggage area point cloud image can be obtained. x，max , minimum X-axis coordinate QR x，min ; 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 the length of the initial first sub-bounding box in the Y-axis direction LR = QRy，max -QR y，min , and according to QR x，max and QR x，min , determine the initial width of the first sub-bounding box in the X-axis direction 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 first sub-bounding box in the Y-axis direction. The baggage area point cloud image is cut using LR as the length in the Y-axis direction, so that the entire area of ​​the baggage area point cloud image in the Y-axis direction can be cut.

[0060] Q230, using the initial first sub-bounding box from QR x，min The point cloud image of the luggage area is cut in sequence along the X-axis to obtain the initial first sub-bounding box list WA'=(WA'1, WA'2, ..., WA' e ,…,WA' f ); among them, WA' e is the obtained e-th initial first sub-bounding box.

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

[0062] Q240, Get WA' e The maximum Y-axis coordinate GH of the inner point cloud e y，max , minimum Y-axis coordinate GH e y，min and the maximum Z-axis coordinate GH e z，max .

[0063] Q250, will WA' e The maximum Y-axis coordinate is adjusted to GH e y，max , the minimum Y-axis coordinate is adjusted to GH e y，min and the maximum Z-axis coordinate is adjusted to GH e z，max , to get WA e .

[0064] In this embodiment, through steps Q240 and Q250, the first sub-bounding box can be closely attached to the corresponding point cloud, thereby avoiding the situation where the generated first sub-bounding box is too large and the space area of ​​the luggage cart is wasted, thereby improving the space utilization 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 a first bounding box list EA corresponding to the luggage area = (EA1, EA2, ..., EA g ,…,EA h ), g=1, 2, …, h; where EA g is the gth 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, obtaining a first preset value BH=1 and a 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 WA BH and WA BH+1 Determine the first sub-bounding box to be merged; and obtain BH=BH+1, enter Q320; otherwise, enter Q330; where LE BH for WA BH Length, KD BH for WA BH Width, HD BH for WA BH LE'1, LE'2 and LE'3 are respectively the preset length difference threshold, width difference threshold and height difference threshold.

[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 ​​that can be obtained based on a large amount of experimental data in actual applications. Through steps Q310-Q330, several first sub-bounding boxes of similar sizes in the first sub-bounding box can be merged into a single first bounding box. This can reduce the number of bounding box calculations during subsequent baggage stacking, thereby improving stacking efficiency.

[0071] Furthermore, EA HU The length of the corresponding first sub-bounding box to be merged is the maximum length, EA HU The height of the corresponding first sub-bounding box to be merged is the maximum height, EA HUThe width is the sum of the widths of the corresponding first sub-bounding boxes to be merged; thus, 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 luggage area point cloud image along the Y-axis direction to obtain a second sub-bounding box list WB = (WB1, WB2, ..., WB k ,…,WB r ), k = 1, 2, ..., r; where WB k is the kth second sub-bounding box obtained by averaging the point cloud image of the luggage area along the Y-axis direction, r is the number of second sub-bounding boxes obtained by averaging the point cloud image of the luggage area along the Y-axis direction; the second sub-bounding boxes in WB are adjacent in sequence.

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

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

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

[0076] Q430, using the initial second sub-bounding box from QR y，min The point cloud image of the luggage area is cut in sequence along the Y-axis to obtain the initial second sub-bounding box list WB'=(WB'1, WB'2, ..., WB' k ,…,WB' r ); among them, WB' k is the kth initial second sub-bounding box obtained.

[0077] Q440, Get WB' k The maximum Y-axis coordinate EH of the inner point cloud e y，max , minimum Y-axis coordinate EH e y，min and the maximum Z-axis coordinate EHe z，max .

[0078] Q450, will WB' k The maximum Y-axis coordinate is adjusted to EH e y，max , the minimum Y-axis coordinate is adjusted to EH e y，min And the maximum Z axis coordinate is adjusted to EH e z，max , to get WB k .

[0079] In this embodiment, the method for cutting the luggage area point cloud image along the Y axis is the same as the method for cutting the luggage area point cloud image along the X axis, and is not further described 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 second bounding box list EB corresponding to the luggage area = (EB1, EB2, ..., EB u ,…,EB v ), u=1, 2, …, v; where EB u is the uth 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] Furthermore, step Q500 may include the following steps:

[0082] Q510, obtaining a third preset value TY=1 and a 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 WB TY and WB TY+1 Determine the second sub-bounding box to be merged; and obtain TY=TY+1, enter Q520; otherwise, enter Q530; where ME TY For WB TY Length, ND TY For WB TY Width, FD TY For WB TY LE'1, LE'2 and LE'3 are respectively the preset length difference threshold, width difference threshold and height difference threshold.

[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 to Q530, several second sub-bounding boxes of similar size in the second sub-bounding box can be merged into one second bounding box. When subsequently stacking the luggage, the number of bounding box calculations can be reduced, thereby improving the stacking efficiency.

[0086] Furthermore, EB RU The length of the corresponding second sub-bounding box to be merged is the maximum length, EB RU The height of the corresponding second sub-bounding box to be merged is the maximum height, EB RU The width is the sum of the widths of the corresponding second sub-bounding boxes to be merged; thus, 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 luggage area point cloud image corresponding to the luggage area on the luggage cart is obtained; the luggage area point cloud image corresponding to the luggage area is segmented along the X-axis and the Y-axis respectively to obtain a first sub-bounding box list WA and a second sub-bounding box list WB; a plurality of adjacent first sub-bounding boxes in WA that meet a preset merging condition are merged into a first bounding box to obtain a first bounding box list EA corresponding to the luggage area; and a plurality of adjacent second sub-bounding boxes in WB that meet a 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, thereby achieving accurate quantification of the luggage along the X-axis and the Y-axis.

[0088] In addition, the method of this embodiment can obtain not only the bounding box of the luggage area on the X-axis, but also the bounding box of the luggage area on the Y-axis. When stacking the luggage later, 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.

[0089] Example 3:

[0090] In the second embodiment, the height of the luggage cart's floor is not considered when generating the luggage's bounding box. To improve the luggage cart's space utilization, the following steps can be used to remove the luggage cart's floor:

[0091] T100, obtain each first bounding box corresponding to the baggage area point cloud image to obtain a first bounding box list EA=(EA1, EA2, ..., EA g ,…,EA h ), g=1, 2, …, h; where EA gis the gth first bounding box corresponding to the point cloud image of the luggage area, 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, the EA can be obtained by following the steps below:

[0093] T110, obtaining a luggage area point cloud image corresponding to the luggage area on the luggage cart; wherein the luggage area point cloud image includes a plurality of points, each of which has corresponding coordinate information.

[0094] In this embodiment, the luggage area on the luggage cart can be obtained by the method and steps in the first embodiment, which will not be described in detail here.

[0095] T120, perform average cutting on the baggage area point cloud image along the X-axis direction to obtain the first sub-bounding box list WA = (WA1, WA2, ..., WA e ,…,WA f ), e=1, 2,..., f; among them, WA e is the e-th first sub-bounding box obtained by averaging 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 averaging the point cloud image of the luggage area along the X-axis direction. The first sub-bounding boxes in WA are adjacent to each other.

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

[0097] T121, obtain the maximum X-axis coordinate QR of the point in the baggage area point cloud image x，max , minimum X-axis coordinate QR x，min ; 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 baggage area point cloud image can be obtained, so the maximum X-axis coordinate QR of the point in the baggage area point cloud image can be obtained. x，max , minimum X-axis coordinate QR x，min ; 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 of the initial first sub-bounding box in the Y-axis direction LR = QR y，max -QR y，min , and according to QR x，max and QR x，min , determine the initial width of the first sub-bounding box in the X-axis direction DR = (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-bounding box in the Y-axis direction. The baggage area point cloud image is cut using LR as the length in the Y-axis direction, so that the entire area of ​​the baggage area point cloud image in the Y-axis direction can be cut.

[0101] T123, using the initial first sub-bounding box from QR x，min The point cloud image of the luggage area is cut in sequence along the X-axis to obtain the initial first sub-bounding box list WA'=(WA'1, WA'2, ..., WA' e ,…,WA' f ); among them, WA' e is the obtained e-th initial first sub-bounding box.

[0102] It can be understood that the luggage is not placed in a regular pattern, for example, in an L-shape. Then, when cutting, there may be a large space without point clouds in the Y-axis direction.

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

[0104] T125, will WA' e The maximum Y-axis coordinate is adjusted to GH e y，max , the minimum Y-axis coordinate is adjusted to GH e y，min and the maximum Z-axis coordinate is adjusted to GH e z，max , to get WA e .

[0105] In this embodiment, through steps Q240 and Q250, the first sub-bounding box can be closely attached to the corresponding point cloud, thereby avoiding the situation where the generated first sub-bounding box is too large and the space area of ​​the luggage cart is wasted, thereby improving the space utilization of the luggage cart.

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

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

[0108] T131 , obtaining a first preset value BH=1 and a 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 WA BH and WA BH+1 Determine the first sub-bounding box to be merged; and obtain BH=BH+1, enter T132; otherwise, enter T133; where LE BH for WA BH Length, KD BH for WA BH Width, HD BH for WA BH LE'1, LE'2 and LE'3 are respectively the preset length difference threshold, width difference threshold and 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 ​​that can be obtained based on a large amount of experimental data in actual applications. Through steps T131-T133, several first sub-bounding boxes of similar sizes in the first sub-bounding box can be merged into one first bounding box. This can reduce the number of bounding box calculations during subsequent baggage stacking, thereby improving stacking efficiency.

[0112] Furthermore, EA HU The length of the corresponding first sub-bounding box to be merged is the maximum length, EA HU The height of the corresponding first sub-bounding box to be merged is the maximum height, EA HU The width is the sum of the widths of the corresponding first sub-bounding boxes to be merged; thus, 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.

[0113] T200, obtain each second bounding box corresponding to the baggage area point cloud image to obtain a second bounding box list EB = (EB1, EB2, ..., EB u ,…,EB v ), u=1, 2, …, v; where EB uis the u-th second bounding box corresponding to the point cloud image of the luggage area, 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.

[0114] EB is obtained by the following steps:

[0115] T210, perform average cutting on the luggage area point cloud image along the Y-axis direction to obtain a second sub-bounding box list WB = (WB1, WB2, ..., WB k ,…,WB r ), k = 1, 2, ..., r; where WB k is the kth second sub-bounding box obtained by averaging the point cloud image of the luggage area along the Y-axis direction, r is the number of second sub-bounding boxes obtained by averaging the point cloud image of the luggage area along the Y-axis direction; the second sub-bounding boxes in WB are adjacent in sequence.

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

[0117] In this embodiment, the method for obtaining EB is the same as the method for obtaining EA, and will not be described in detail 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 = (BN1, BN2, ..., BN α ,…,BN β ), α=1, 2,...,β; among them, BN α is the αth third bounding box obtained by splitting, and β is the number of third bounding boxes obtained by splitting.

[0119] In this embodiment, it is understandable 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 luggage is stacked, it is not necessarily stacked in a rectangular shape, but may be L-shaped, and the height of the luggage may be different. Therefore, there may be spaces without point clouds between the first bounding box and the second bounding box. The first bounding box and the second bounding box need to be split to further remove the bounding boxes without point clouds.

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

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

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

[0123] T312, if EA WFWith EB WF+WK-1 If there is an overlap, the EA WF With EB WF+WK-1 The overlapping part and the non-overlapping part of EA are determined as the third bounding box; otherwise, WF With EB WF+WK-1 Determine the third bounding box.

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

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

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

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

[0128] T315, traverse all third bounding boxes and delete the third bounding boxes that do not contain point clouds to obtain BN.

[0129] In this embodiment, not all third bounding boxes have point clouds. Third bounding boxes without point clouds are empty bounding boxes with no luggage inside. Therefore, they need to be deleted to release unused space on the luggage cart and improve space utilization.

[0130] T400, obtain the maximum Z-axis coordinate of each point cloud in the third bounding box in BN to obtain the BN maximum Z-axis coordinate list PA z =(PA z，1 , P.A. z，2 ,…,PA z，α ,…,PA z，β ); among them, PA z，α BN α The maximum Z-axis coordinate of the inner point cloud;

[0131] T500, BN α The Z-axis coordinate is adjusted to PA z，α .

[0132] In this embodiment, the first and second sub-bounding boxes are both cuboid in shape. The first and second sub-bounding boxes are relatively large, and their heights are determined based on the maximum height of the corresponding luggage. If the upper surface of the corresponding luggage is not flat but convex, then a large space without luggage will also exist in the corresponding first or second bounding box. Therefore, in order to make the third bounding box more closely fit the point cloud corresponding to the luggage, the Z-axis coordinate of the third bounding box is adjusted to the maximum Z-axis coordinate of the point cloud within it, so that the third bounding box can fit closely to the corresponding point cloud, thereby improving 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 a first bounding box list EA, and each second bounding box corresponding to the point cloud image of the luggage area is obtained to obtain a second bounding box list EB. The overlapping and non-overlapping portions of the first bounding boxes in EA and the second bounding boxes in EB are split into third bounding boxes to obtain a 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 obtained by the point cloud therein. This ensures that the height of the third bounding box is the same as the height of the corresponding luggage. When the luggage is subsequently stacked, the space in the luggage cart can be fully utilized, thereby improving the space utilization rate of the luggage cart.

[0134] Example 4:

[0135] If there is no luggage on the luggage cart, you can Figure 1 The baggage spatial area determination method shown is used to determine the baggage area to improve the efficiency of baggage area determination:

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

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

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

[0139] 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.

[0140] In this embodiment, the fluctuation rate of the Z-axis coordinates of all the initial pixel points may be the variance corresponding to the Z-axis coordinates of all the initial pixel points. It is understandable that when there is no luggage placed on the luggage cart, the bottom plate of the luggage cart is flat, and the Z-axis coordinates of the pixels corresponding to the bottom plate are equal or have very little difference. When the fluctuation rate of the Z-axis coordinates of all the initial pixel points is greater than a preset fluctuation rate threshold, it indicates 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 a 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. The two can be converted into coordinate systems to determine the coordinate information of the pixel points in the first luggage cart image.

[0143] Furthermore, 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.

[0144] In this embodiment, the method and steps in the first embodiment can be used to determine the space area currently occupied by the luggage on the luggage cart; details are not repeated here.

[0145] 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.

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

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

[0148] In this embodiment, a 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 system conversion 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 use existing coordinate conversion 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 according to actual needs, and the details are not repeated here.

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

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

[0151] H510, divide the first luggage cart image into a number of adjacent image areas to be compared, to obtain a first image area 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 luggage image, and ω is the number of first image regions to be compared obtained by dividing the first luggage image.

[0152] H520, divide the second luggage cart image into a number of adjacent image regions to be compared, to obtain a second image region list UB=(UB1, UB2, ..., UB θ ,…,UB ω ); among them, 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.

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

[0154] 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 ); Among them, UC θ UA θ The first target height coordinate; UC θ Through UA θ The Z-axis coordinates of several pixel points within are obtained.

[0155] Furthermore, UC θ Determine this by following these steps:

[0156] H531, get UA θ The Z-axis coordinate of each preset pixel point in the UA θ Corresponding preset position pixel coordinate list ZP θ =(ZP θ，1 , ZPθ，2 ,…,ZP θ，γ ,…,ZP θ，δ ), γ=1, 2,..., δ; where, ZP θ，γ UA θ The Z-axis coordinate of the pixel point at the γth preset position, δ is UA θ The number of pixels at the preset position.

[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 four vertices, center point and pixel points corresponding to the midpoint of each side can be obtained θ The Z-axis coordinate of each preset pixel point.

[0159] H540, obtain the second target height coordinates of each second image area to be compared in UB to obtain a second target height coordinate list UD=(UD1, UD2, ..., UD θ ,…,UD ω ); where UD θ UB θ The second target height coordinate; UD θ via UB θ The Z-axis coordinates of several pixel points within are obtained.

[0160] In this embodiment, UD θ The determination method of UC θ The determination method is the same; it should be noted that UA θ Each preset pixel point and UB θ The pixels at each preset position are the same.

[0161] H550 determines the space area currently occupied by the luggage on the luggage cart based on UC and UD.

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

[0163] 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 θ Determine the target second image area to be compared; wherein SG is a preset target height difference threshold.

[0164] In this embodiment, if |UC θ -UD θ |>SG, means UA θ With UB θ The Z-axis coordinate of the preset position pixel point within the UC is changed significantly, which can be determined θ There is newly stacked luggage in the corresponding luggage cart area; thus, all areas without newly stacked luggage can be filtered out; when filtering most areas without newly stacked luggage, only a portion of the pixels are used, and the amount of calculation is extremely small, which can greatly improve the efficiency of image processing.

[0165] H552, obtain each pixel point in the first image area to be compared 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 target first image areas to be compared, and σ is the number of pixels in the overall area corresponding to all target first image areas to be compared.

[0166] H553, obtain each pixel point in the second image area to be compared of each target to obtain a second pixel point list JD=(JD1, JD2, ..., JD ε ,…,JD σ ); among them, 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 positions on the luggage carts are the same.

[0167] H554, if | JC ε _Z-JD ε _Z|>UZ, then JD ε Determined as the target pixel; among them, JC ε _Z stands for JC ε The Z-axis coordinate, JD ε _Z stands for JD ε UZ is the preset pixel point Z-axis coordinate difference threshold.

[0168] Through the above steps, all the pixel points with large changes in Z coordinates can be determined.

[0169] H555, determine the spatial area formed by all target pixels as the spatial area currently occupied by the luggage on the luggage cart.

[0170] The luggage spatial area determination method of this embodiment determines whether there is luggage on a luggage cart; if there is no luggage on the luggage cart, obtains a first luggage cart image corresponding to the luggage cart; marks the current luggage to the origin of the luggage cart and obtains a second luggage cart image of the luggage cart; obtains the coordinates of each pixel corresponding to the first luggage cart image and the coordinates of each pixel corresponding to the second luggage cart image; and determines the spatial area occupied by the current luggage on the luggage cart based on the coordinates of each pixel corresponding to the first luggage cart image and the coordinates of each pixel corresponding to the second luggage cart image. In the present invention, the two-dimensional image corresponding to the luggage cart is used when identifying the spatial area of ​​the luggage, and only the coordinates of the pixels in the two-dimensional image are processed, which reduces the computational complexity and improves the efficiency and accuracy of luggage area identification.

[0171] Furthermore, although the steps of the method of the present disclosure are described in a particular order in the accompanying drawings, this does not require or imply that the steps must be performed in this particular order, or that all steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

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

[0173] The program product may be implemented in any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media 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 thereof.

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

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

[0176] The program code for performing the operations of the present application can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user 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 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., via the Internet using an Internet service provider).

[0177] An embodiment of the present invention further provides an electronic device including a processor and the aforementioned non-transitory computer-readable storage medium.

[0178] The electronic device is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0179] The electronic device is implemented as a general-purpose computing device. Components of the electronic device may include, but are not limited to, the aforementioned at least one processor, the aforementioned at least one memory, and a bus connecting different system components (including the memory and the processor).

[0180] The memory stores program codes, which can be executed by the processor, so that the processor performs the steps of various embodiments described in this specification.

[0181] The memory may include readable media 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 a program / utility having 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 or some combination 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, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0184] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface. Furthermore, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) via a network adapter. The network adapter communicates with other modules of the electronic device via a 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.

[0185] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution 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 can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can 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] An embodiment of the present invention further provides a computer program product comprising program code. When the program product is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the method 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, it should be understood by those skilled in the art that the above examples are for illustration only and are not intended to limit the scope of the present invention. It should also be understood by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention.

Claims

1. A method for determining a luggage spatial area, characterized in that: The method comprises the following steps: H100, determines 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 corresponding to the first luggage cart image and the coordinates of each pixel corresponding to the second luggage cart image; H500, determining a spatial area currently occupied by the luggage on the luggage cart based on the coordinates of each pixel corresponding to the first luggage cart image and the coordinates of each pixel corresponding to the second luggage cart image; Step H500 includes the following steps: H510, divide the first luggage cart image into a number of adjacent image areas to be compared, so as to obtain a first image area 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 luggage image, and ω is the number of first image regions to be compared obtained by dividing the first luggage image; H520, divide the second luggage cart image into a number of adjacent image regions to be compared, to obtain a second image region list UB = (UB1, UB2, ..., UB θ ,…,UB ω ); Among them, 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 ); Among them, UC θ UA θ The first target height coordinate; UC θ Through UA θ The Z-axis coordinates of several pixel points within are obtained; H540, obtain the second target height coordinates of each second image area to be compared in UB to obtain a second target height coordinate list UD = (UD1, UD2, ..., UD θ ,…,UD ω ); where UD θ UB θ The second target height coordinate; UD θ via UB θ The Z-axis coordinates of several pixel points within are obtained; H550 determines the space area currently occupied by the luggage on the luggage cart based on UC and UD.

2. The method for determining the spatial area of ​​luggage according to claim 1, 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 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 image area to be compared 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 the first target image area to be compared, and σ is the number of pixels in the overall area corresponding to the first target image area to be compared; H553, obtain each pixel point in the second image area to be compared of each target to obtain a second pixel point list JD = (JD1, JD2, ..., JD ε ,…,JD σ ); Among them, 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 stands for 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.

3. The method for determining the spatial area of ​​luggage according to claim 1, characterized in that: UC θ Determine this by following these steps: H531, get UA θ The Z-axis coordinate of each preset pixel point in the UA θ Corresponding preset position pixel coordinate list ZP θ =(ZP θ，1 , ZP θ，2 ,…,ZP θ，γ ,…,ZP θ，δ ), γ=1, 2,..., δ; among them, ZP θ，γ 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 .

4. The method for determining the spatial area of ​​luggage according to claim 3, wherein: UA θ Each preset pixel point is evenly distributed in UA θ Inside.

5. The method for determining the spatial area of ​​luggage according to claim 1, wherein: 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.

6. The method for determining the spatial area of ​​luggage according to claim 1, characterized in that: After step H100, the method further includes 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 using the point cloud image corresponding to the luggage cart.

7. 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 6.

8. An electronic device, characterized in that: The method comprises a processor and the non-transitory computer-readable storage medium of claim 7.

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