Object position detection method and device, electronic equipment and readable storage medium

Abstract

This disclosure provides an object location detection method, apparatus, electronic device, and readable storage medium, which can be applied to the fields of computer technology and fintech. The object location detection method includes: in response to detecting an object location detection command from a detection terminal, acquiring first location information, the object location detection command including preset distance information, the first location information corresponding to the detection terminal; determining a first detection range based on the first location information and the preset distance information; in response to receiving a target detection signal from an object to be detected, acquiring second location information, the target detection signal including object identification information of the object to be detected, the second location information being associated with the object identification information; determining a second detection range based on the target detection signal and the first detection range, the second detection range being within the first detection range; and determining an object location detection result corresponding to the object to be detected based on the second location information and the second detection range.

Description

Technical Field

[0001] This disclosure relates to the fields of computer technology and financial technology, and more specifically, to an object location detection method and apparatus, electronic device, computer-readable storage medium and computer program product. Background Technology

[0002] With the development of computer technology, warehouse management can be carried out based on computer technology. Warehouse management refers to the management of warehouses and the materials within them.

[0003] Warehouse management can include archive storage management. An archive storage facility can refer to a dedicated room for storing archives. Archive storage management can be the planning, organization, control, and coordination process undertaken by an archive storage organization to provide efficient storage management services and make full use of its archival resources.

[0004] In realizing the present invention, the inventors discovered at least the following problems in the related technology: the efficiency and accuracy of archive storage management cannot be guaranteed. Summary of the Invention

[0005] In view of this, the present disclosure provides an object location detection method and apparatus, an electronic device, a computer-readable storage medium, and a computer program product.

[0006] According to one aspect of this disclosure, an object location detection method is provided, comprising:

[0007] In response to detecting an object location detection command from a detection terminal, first location information is acquired, wherein the object location detection command includes preset distance information, and the first location information corresponds to the detection terminal;

[0008] Based on the aforementioned first location information and the aforementioned preset distance information, the first detection range is determined;

[0009] In response to receiving a target detection signal from the object to be detected, second location information is obtained, wherein the target detection signal includes object identification information of the object to be detected, and the second location information is associated with the object identification information;

[0010] Based on the target detection signal and the first detection range, a second detection range is determined, wherein the second detection range is within the first detection range; and

[0011] Based on the second location information and the second detection range, the object location detection result corresponding to the object to be detected is determined.

[0012] According to embodiments of this disclosure, the first detection range includes a spherical shape range.

[0013] According to embodiments of this disclosure, determining the first detection range based on the first location information and the preset distance information includes:

[0014] Based on the aforementioned first location information, the first detection positioning point is determined;

[0015] Based on the aforementioned preset distance information, determine the detection radius;

[0016] Based on the aforementioned first detection positioning point and the aforementioned detection radius, the first detection plane range is determined; and

[0017] Based on the preset coefficients and the range of the first detection plane, the range of the sphere shape is determined, wherein the range of the sphere shape is characterized by a three-dimensional coordinate system.

[0018] According to embodiments of this disclosure, the above-mentioned response to receiving a target detection signal from the object to be detected, and obtaining the second location information, includes:

[0019] Based on the first preset mapping relationship and the above object identification information, the target detection object identification information is determined;

[0020] Based on the aforementioned target detection object identification information, determine the target location information corresponding to the aforementioned target detection object identification information; and

[0021] The aforementioned target location information is determined as the aforementioned second location information.

[0022] According to embodiments of this disclosure, the first preset mapping relationship includes a first preset key-value relationship corresponding to at least one preset detection object, and the first preset key-value relationship includes preset detection object identification information and preset location information corresponding to the preset detection object identification information.

[0023] According to embodiments of this disclosure, the second detection range includes a hemispherical shape range.

[0024] According to embodiments of this disclosure, determining the second detection range based on the target detection signal and the first detection range includes:

[0025] Based on the target detection signals described above, the detection angle range is determined; and

[0026] Based on the aforementioned detection angle range, the aforementioned hemispherical shape range is determined within the aforementioned first detection range, wherein the aforementioned hemispherical shape range is characterized by a three-dimensional coordinate system.

[0027] According to embodiments of this disclosure, the object location detection instruction further includes a terminal detection signal.

[0028] According to embodiments of this disclosure, the above-mentioned response to detecting an object location detection command from a detection terminal to obtain first location information includes:

[0029] Based on the terminal detection signals mentioned above, auxiliary information is determined, wherein the auxiliary information includes at least one of the following: first auxiliary position information and second auxiliary position information; and

[0030] Based on the aforementioned auxiliary information, the first position information is determined.

[0031] According to embodiments of this disclosure, the first auxiliary location information includes Internet of Things (IoT) location information.

[0032] According to embodiments of this disclosure, when the auxiliary information includes first auxiliary location information, determining the first location information based on the auxiliary information includes:

[0033] Based on the aforementioned IoT positioning information, the aforementioned first location information is determined.

[0034] According to embodiments of this disclosure, the second auxiliary location information includes regional location information.

[0035] According to embodiments of this disclosure, when the auxiliary information further includes second auxiliary location information, determining the first location information based on the IoT positioning information includes:

[0036] Based on the aforementioned IoT positioning information and the aforementioned regional positioning information, the aforementioned first location information is determined.

[0037] According to embodiments of this disclosure, determining the object location detection result corresponding to the object to be detected based on the second location information and the second detection range includes:

[0038] Based on the aforementioned second detection range, determine the environmental object identification information;

[0039] Based on the second preset mapping relationship and the above-mentioned environmental object identification information, the target environmental object identification information is determined;

[0040] Based on the aforementioned target environment object identification information, determine the target signal attenuation information corresponding to the aforementioned target environment object identification information; and

[0041] The second detection range is adjusted based on the target signal attenuation information to obtain the adjusted second detection range.

[0042] According to embodiments of this disclosure, the second preset mapping relationship includes a second preset key-value relationship corresponding to at least one preset environment object, and the second preset key-value relationship includes preset environment object identification information and preset signal attenuation information corresponding to the preset environment object identification information.

[0043] According to embodiments of this disclosure, the above method further includes:

[0044] When the adjusted second detection range includes the second location information, the object location detection result representing the successful location detection is determined.

[0045] If the adjusted second detection range does not include the aforementioned second location information, determine the location detection result of the object that failed the location detection; and

[0046] If the aforementioned second position information is located at the critical position of the aforementioned adjusted second detection range, the position detection result of the object that failed the position detection is determined.

[0047] According to embodiments of this disclosure, after determining the object position detection result corresponding to the object to be detected based on the second position information and the second detection range:

[0048] Using a digital twin model, the first location information, the second location information, the second detection range, and the object location detection results are displayed, wherein the digital twin model corresponds to the physical warehouse where the object to be detected is located.

[0049] According to embodiments of this disclosure, a digital twin model is constructed in the following manner:

[0050] Collect physical warehouse information corresponding to the physical warehouse, including warehouse structure information, equipment structure information of at least one physical device located inside the physical warehouse, and positional relationship information between at least one physical device;

[0051] Based on the warehouse structure information and the equipment structure information of at least one physical piece of equipment, a 3D reconstruction of the physical warehouse is performed to obtain a 3D point cloud model; and

[0052] A digital twin model is constructed based on the positional relationship information between the 3D point cloud model and at least one physical device.

[0053] According to another aspect of this disclosure, an object position detection device is provided, comprising:

[0054] The first acquisition module is used to acquire first location information in response to detecting an object location detection command from the detection terminal, wherein the object location detection command includes preset distance information, and the first location information corresponds to the detection terminal.

[0055] The first determining module is used to determine the first detection range based on the first position information and the preset distance information.

[0056] The second acquisition module is used to acquire second location information in response to receiving a target detection signal from the object to be detected, wherein the target detection signal includes object identification information of the object to be detected, and the second location information is associated with the object identification information.

[0057] The second determining module is configured to determine a second detection range based on the target detection signal and the first detection range, wherein the second detection range is within the first detection range; and

[0058] The third determining module is used to determine the object position detection result corresponding to the object to be detected based on the second position information and the second detection range.

[0059] According to another aspect of this disclosure, an electronic device is provided, comprising:

[0060] One or more processors;

[0061] Memory, used to store one or more instructions.

[0062] When one or more of the above instructions are executed by one or more processors, the one or more processors cause the one or more processors to implement the method as described in this disclosure.

[0063] According to another aspect of this disclosure, a computer-readable storage medium is provided having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the methods described in this disclosure.

[0064] According to another aspect of this disclosure, a computer program product is provided, which includes computer-executable instructions that, when executed, are used to perform the methods described in this disclosure.

[0065] According to embodiments of this disclosure, since the first detection range is determined based on first location information and preset distance information, and the first location information is obtained based on an object location detection command, the first detection range can characterize the candidate location range of the object to be detected. Furthermore, since the second detection range is determined based on a target detection signal and the first detection range, and the second location information is obtained based on the target detection signal, the second detection range can characterize the actual location range of the object to be detected, thereby improving the accuracy of object location detection. Based on this, since the object location detection result is determined based on the second location information and the second detection range, object location detection of the object to be detected can be automatically achieved, at least partially overcoming the technical problem in related technologies that cannot guarantee the efficiency and accuracy of archive storage management, improving the efficiency of object location detection, and thus improving the efficiency and accuracy of archive storage management. Attached Figure Description

[0066] The above and other objects, features and advantages of this disclosure will become clearer from the following description of embodiments with reference to the accompanying drawings, in which:

[0067] Figure 1 This illustration schematically shows a system architecture to which an object location detection method can be applied according to an embodiment of the present disclosure;

[0068] Figure 2 A flowchart illustrating an object location detection method according to an embodiment of the present disclosure is shown schematically.

[0069] Figure 3 This illustration schematically shows an example diagram of a virtual warehouse construction process according to an embodiment of the present disclosure;

[0070] Figure 4A This illustration schematically shows an example of a method for obtaining first location information in response to detecting an object location detection command from a detection terminal, according to an embodiment of the present disclosure.

[0071] Figure 4B This illustration schematically shows an example diagram of a method for obtaining first location information in response to detecting an object location detection command from a detection terminal, according to another embodiment of the present disclosure.

[0072] Figure 5 This illustration schematically shows an example of a method for obtaining second location information in response to receiving a target detection signal from an object to be detected, according to an embodiment of the present disclosure.

[0073] Figure 6A This illustration schematically shows an example diagram of a method for determining a first detection range based on first location information and preset distance information according to an embodiment of the present disclosure;

[0074] Figure 6B This illustration schematically shows an example diagram of a method for determining a second detection range based on a target detection signal and a first detection range according to an embodiment of the present disclosure;

[0075] Figure 7 This illustration schematically shows an example diagram of an object location detection process according to an embodiment of the present disclosure;

[0076] Figure 8A An example schematic diagram of an object location detection method according to an embodiment of the present disclosure is shown;

[0077] Figure 8B An example schematic diagram of an object position detection method according to another embodiment of the present disclosure is shown;

[0078] Figure 9 A block diagram schematically illustrates an object position detection apparatus according to an embodiment of the present disclosure; and

[0079] Figure 10 A block diagram of an electronic device suitable for implementing an object position detection method according to an embodiment of the present disclosure is shown schematically. Detailed Implementation

[0080] The embodiments of the present disclosure will now be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the disclosure. In the following detailed description, numerous specific details are set forth to provide a thorough understanding of the embodiments of the present disclosure for ease of explanation. However, it will be apparent that one or more embodiments may be practiced without these specific details. Furthermore, descriptions of well-known structures and techniques are omitted in the following description to avoid unnecessarily obscuring the concepts of the present disclosure.

[0081] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. The terms “comprising,” “including,” etc., as used herein indicate the presence of the stated features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0082] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein are to be interpreted in a manner consistent with the context of this specification, and not in an idealized or overly rigid way.

[0083] When using expressions such as "at least one of A, B, and C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, and C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.). Similarly, when using expressions such as "at least one of A, B, or C," the expression should generally be interpreted in accordance with the meaning commonly understood by a person skilled in the art (e.g., "a system having at least one of A, B, or C" should include, but is not limited to, systems having A alone, having B alone, having C alone, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0084] In the technical solution disclosed herein, the acquisition, storage, and application of user personal information comply with the provisions of relevant laws and regulations, necessary confidentiality measures have been taken, and there is no violation of public order and good morals.

[0085] In the technical solution disclosed herein, the user's authorization or consent is obtained before acquiring or collecting the user's personal information.

[0086] The layout of an archive storage room can include zones, groups, columns, sections, and layers. A zone can refer to a specific area. A group can refer to a set of mobile shelving units or shelves. A column can refer to a column within a set of mobile shelving units or shelves. A section can refer to a vertical coordinate marker within a column within a set of mobile shelving units or shelves. A layer can refer to a horizontal coordinate marker within a column within a set of mobile shelving units or shelves.

[0087] Archive storage managers can use a PDA (Personal Digital Assistant) or a hand-pushed pallet cart to select the area, group, and column of the storage room, enter the area of ​​that column, walk back and forth, emit detection waves through the PDA, and receive return information. They can then use the return information to detect the items in that column.

[0088] However, because the detection waves emitted by the handheld computer are penetrating, they can penetrate to multiple shelves behind it when there are no metal partitions to block them. Furthermore, since the detection waves are typically emitted in a fan-shaped pattern, the detection signal cannot be transmitted accurately.

[0089] In summary, in the process of realizing the present invention, the inventors have discovered at least the following problems in the related technologies: the efficiency and accuracy of archive storage management cannot be guaranteed.

[0090] To at least partially address the technical problems existing in related technologies, this disclosure provides an object location detection method and apparatus, electronic device, and readable storage medium, which can be applied to the fields of computer technology and fintech. The object location detection method includes: in response to detecting an object location detection command from a detection terminal, acquiring first location information, wherein the object location detection command includes preset distance information, and the first location information corresponds to the detection terminal; determining a first detection range based on the first location information and the preset distance information; in response to receiving a target detection signal from an object to be detected, acquiring second location information, wherein the target detection signal includes object identification information of the object to be detected, and the second location information is associated with the object identification information; determining a second detection range based on the target detection signal and the first detection range, wherein the second detection range is within the first detection range; and determining an object location detection result corresponding to the object to be detected based on the second location information and the second detection range.

[0091] It should be noted that the object location detection method and apparatus provided in this disclosure can be used in the fields of computer technology and fintech, such as in the field of network technology. The object location detection method and apparatus provided in this disclosure can also be used in any field other than computer technology and fintech, such as in the field of warehouse management. The application fields of the object location detection method and apparatus provided in this disclosure are not limited.

[0092] Figure 1 The illustration schematically depicts a system architecture to which an object location detection method can be applied according to embodiments of the present disclosure. It should be noted that... Figure 1 The examples shown are merely examples of system architectures that can be applied to the embodiments of this disclosure, in order to help those skilled in the art understand the technical content of this disclosure, but do not mean that the embodiments of this disclosure cannot be used in other devices, systems, environments or scenarios.

[0093] like Figure 1 As shown, the system architecture 100 according to this embodiment may include a first terminal device 101, a second terminal device 102, a third terminal device 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the first terminal device 101, the second terminal device 102, the third terminal device 103, and the server 105. The network 104 may include various connection types, such as wired or wireless communication links, or fiber optic cables, etc.

[0094] Users can interact with server 105 via network 104 using at least one of the first terminal device 101, second terminal device 102, and third terminal device 103 to receive or send messages, etc. Various communication client applications can be installed on the first terminal device 101, second terminal device 102, and third terminal device 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0095] The first terminal device 101, the second terminal device 102, and the third terminal device 103 can be various electronic devices with displays and support web browsing, including but not limited to smartphones, tablets, laptops, desktop computers, radio frequency identification devices, image acquisition devices, etc.

[0096] Server 105 can be a server that provides various services, such as a backend management server that supports websites browsed by users using the first terminal device 101, the second terminal device 102, and the third terminal device 103 (this is just an example). The backend management server can analyze and process data such as received user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0097] It should be noted that the object location detection method provided in this embodiment can generally be executed by server 105. Correspondingly, the object location detection device provided in this embodiment can generally be located in server 105. The object location detection method provided in this embodiment can also be executed by a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105. Correspondingly, the object location detection device provided in this embodiment can also be located in a server or server cluster that is different from server 105 and capable of communicating with the first terminal device 101, the second terminal device 102, the third terminal device 103, and / or server 105.

[0098] Alternatively, the object location detection method provided in this embodiment of the present disclosure can also be executed by the first terminal device 101, the second terminal device 102, or the third terminal device 103, or by other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103. Correspondingly, the object location detection device provided in this embodiment of the present disclosure can also be disposed in the first terminal device 101, the second terminal device 102, or the third terminal device 103, or in other terminal devices different from the first terminal device 101, the second terminal device 102, or the third terminal device 103.

[0099] It should be understood that Figure 1 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0100] It should be noted that the sequence numbers of the operations in the following methods are for descriptive purposes only and should not be considered as indicating the execution order of the operations. Unless explicitly stated otherwise, the method does not need to be executed in the exact order shown.

[0101] Figure 2 A flowchart illustrating an object location detection method according to an embodiment of the present disclosure is shown schematically.

[0102] like Figure 2 As shown, the object position detection method 200 includes operations S210 to S250.

[0103] In operation S210, in response to detecting an object position detection command from the detection terminal, first position information is obtained, wherein the object position detection command includes preset distance information, and the first position information corresponds to the detection terminal.

[0104] In operation S220, the first detection range is determined based on the first position information and the preset distance information.

[0105] In operation S230, in response to receiving a target detection signal from the object to be detected, second location information is acquired, wherein the target detection signal includes object identification information of the object to be detected, and the second location information is associated with the object identification information.

[0106] In operation S240, a second detection range is determined based on the target detection signal and the first detection range, wherein the second detection range is part of the first detection range.

[0107] In operation S250, the object position detection result corresponding to the object to be detected is determined based on the second position information and the second detection range.

[0108] According to embodiments of this disclosure, code for generating object location detection instructions can be pre-written into a first script. In response to detecting an object location verification operation initiated by a user using a detection terminal, the detection terminal can run the first script to generate object location detection instructions. The object location detection instructions can be used to detect the location of an object to be detected. For example, object location detection can be applied to an archive storage room. The archive storage room may include at least one object to be detected. The detection terminal can send the object location detection instructions to a server so that the server can obtain first location information based on the object location detection instructions.

[0109] According to embodiments of this disclosure, an object location detection instruction may include at least one of the following: preset distance information and a terminal detection signal. The preset distance information can be used to characterize the detection scanning distance of the detection terminal. The numerical range of the preset distance information can be configured according to actual business needs and is not limited herein. For example, the preset distance information may be between 0 and 20 meters. The terminal detection signal can be used to characterize the detection signal emitted by the detection terminal. After detecting an object location detection instruction from the detection terminal, first location information corresponding to the detection terminal can be obtained according to the object location detection instruction. The first location information can be used to characterize the position of the detection terminal.

[0110] According to embodiments of this disclosure, the first location information can be acquired in real time, for example, by taking a picture or scanning the detection terminal. Alternatively, the first location information can be pre-stored in a database; for example, the first location information corresponding to the terminal identification information can be obtained based on the terminal identification information of the detection terminal. Alternatively, the first location information can also be received from other terminal devices. Embodiments of this disclosure do not limit the method of acquiring the first location information.

[0111] According to embodiments of this disclosure, after obtaining the first location information, a first detection range can be determined based on the first location information and preset distance information. The first detection range can be used to characterize the candidate range where the location of the object to be detected is located. The specific shape of the first detection range can be configured according to actual business needs and is not limited herein. For example, the shape of the first detection range may include at least one of the following: cuboid, cube, cylinder, sphere, hemisphere, and cone.

[0112] According to embodiments of this disclosure, the object to be detected may have a first radio frequency identification (RFID) tag. The first RFID tag may include one of the following: a first RFID tag based on a Bluetooth device, a first RFID tag based on a WiFi (Wireless Fidelity) device, a first RFID tag based on a UWB (Ultra Wide Band) device, a first RFID tag based on a ZigBee device, and a first RFID (Radio Frequency Identification) tag.

[0113] According to embodiments of this disclosure, after receiving a terminal detection signal, the first RFID tag of the object to be detected can return a target detection signal. The target detection signal can be used to characterize the detection signal emitted by the object to be detected. The target detection signal may include object identification information. The object identification information can be used to identify the object to be detected. After receiving the target detection signal from the object to be detected, second location information associated with the object identification information can be obtained from a data source based on the object identification information in the target detection signal. The data source may include at least one of the following: a local database, a cloud database, and network resources. The second location information can be used to characterize a preset location of the object to be detected. For example, the second location information may be a row, column, and section of a shelf in a warehouse.

[0114] According to embodiments of this disclosure, after receiving a target detection signal from an object to be detected, a second detection range can be determined based on the target detection signal and a first detection range. The second detection range can be used to characterize the area where the object to be detected is located. The specific shape of the second detection range can be configured according to actual business needs and is not limited here, as long as it falls within the first detection range. For example, the shape of the second detection range can include at least one of the following: cuboid, cube, cylinder, sphere, hemisphere, and cone.

[0115] According to embodiments of this disclosure, after obtaining the second location information and the second detection range, an object location detection result corresponding to the object to be detected can be determined based on the second location information and the second detection range. For example, the object location detection result can be obtained by determining whether the second location information includes the second location information. Alternatively, the object location detection result can be obtained by determining whether the second location information is located at a critical position of the second detection range. The object location detection result can include one of the following: location detection failed and location detection passed.

[0116] According to embodiments of this disclosure, since the first detection range is determined based on first location information and preset distance information, and the first location information is obtained based on an object location detection command, the first detection range can characterize the candidate location range of the object to be detected. Furthermore, since the second detection range is determined based on a target detection signal and the first detection range, and the second location information is obtained based on the target detection signal, the second detection range can characterize the actual location range of the object to be detected, thereby improving the accuracy of object location detection. Based on this, since the object location detection result is determined based on the second location information and the second detection range, object location detection of the object to be detected can be automatically achieved, at least partially overcoming the technical problem in related technologies that cannot guarantee the efficiency and accuracy of archive storage management, improving the efficiency of object location detection, and thus improving the efficiency and accuracy of archive storage management.

[0117] The following is for reference. Figure 3 , Figure 4A , Figure 4B , Figure 5 , Figure 6A , Figure 6B , Figure 7 , Figure 8A and Figure 8B The object position detection method 200 according to an embodiment of the present invention will be further described.

[0118] According to embodiments of this disclosure, a digital twin model can be constructed in the following manner.

[0119] Information about the physical warehouse corresponding to the physical warehouse is collected. This information includes the warehouse structure, the individual structural information of at least one piece of equipment located within the warehouse, and the positional relationships between these pieces of equipment. Based on the warehouse structure and the individual structural information of the at least one piece of equipment, a 3D reconstruction of the physical warehouse is performed to obtain a 3D point cloud model. A digital twin model is then constructed based on the 3D point cloud model and the positional relationships between the at least one piece of equipment.

[0120] According to embodiments of this disclosure, a physical warehouse can refer to a warehouse used to store the object to be inspected. A physical warehouse can correspond to physical warehouse information. In this case, the physical warehouse information may include warehouse structure information. The warehouse structure information can be used to characterize the structure of the physical warehouse. For example, if the object to be inspected is an archive, the physical warehouse may be a physical archive warehouse. Alternatively, if the object to be inspected is data, the physical warehouse may be a physical data warehouse.

[0121] According to embodiments of this disclosure, the interior of a physical warehouse may contain at least one physical device. The physical device may refer to equipment in the physical warehouse used for storing objects to be inspected. The physical device may include at least one of the following: automated shelving, mobile shelving, containers, file boxes, and file containers. In this case, the physical warehouse information may further include the equipment structure information of each of the at least one physical device located within the physical warehouse and the positional relationship information between the at least one physical device and each other. The equipment structure information can be used to characterize the structure of the equipment inside the physical warehouse. The positional relationship information can be used to characterize the positional association relationship between the at least one physical device and each other.

[0122] According to embodiments of this disclosure, after obtaining physical warehouse information, a 3D point cloud model can be obtained by reconstructing the physical warehouse based on its structural information and the structural information of at least one physical device. For example, point cloud data conversion processing can be performed on the warehouse structural information and the structural information of at least one physical device to obtain point cloud data to be registered. Point cloud registration processing is then performed on the point cloud data to be registered to obtain target point cloud data. A 3D point cloud model is generated based on the target point cloud data. The 3D point cloud model can refer to a dataset of points of the physical warehouse and at least one physical device located in a certain coordinate system.

[0123] According to embodiments of this disclosure, the point cloud registration processing method can be configured according to actual business needs, and is not limited herein. For example, the point cloud registration processing method may include at least one of the following: a coarse registration method and a fine registration method. A coarse registration method may, for example, include the 4-Point Congruent Sets (4PCS) method. A fine registration method may, for example, include Discriminative Optimization (DO) and Iterative ClosestPoint (ICP) algorithms, etc.

[0124] According to embodiments of this disclosure, after obtaining a 3D point cloud model, a digital twin model can be constructed based on digital twin technology, using the positional relationship information between the 3D point cloud model and at least one physical device. The digital twin technology may include at least one of the following: digital twin technology based on non-uniform rational B-splines (NURBS) and digital twin technology based on polygonal meshes.

[0125] According to embodiments of this disclosure, since the 3D point cloud model is obtained by 3D reconstruction of the physical warehouse based on the warehouse structure information and the equipment structure information of at least one physical device, the 3D point cloud model can accurately represent the structure of the physical warehouse and the structure of the physical equipment. Furthermore, since the digital twin model is constructed based on the 3D point cloud model and the positional relationship information between at least one physical device, the digital twin model can achieve virtual modeling of the physical warehouse, facilitating the intuitive display of object location detection results to the user, thus improving the efficiency of object location detection.

[0126] Figure 3 The illustration shows an example schematic diagram of a digital twin model construction process according to an embodiment of the present disclosure.

[0127] like Figure 3As shown, in 300, physical warehouse information 302 corresponding to physical warehouse 301 can be collected. Physical warehouse information 302 may include warehouse structure information 302_1, equipment structure information 302_2 of at least one physical device located inside physical warehouse 301, and positional relationship information 302_3 between at least one physical device.

[0128] After obtaining the physical warehouse information 302, the physical warehouse 301 can be reconstructed in three dimensions based on the warehouse structure information 302_1 and the equipment structure information 302_2 of at least one physical device, to obtain a three-dimensional point cloud model 303.

[0129] After obtaining the 3D point cloud model 303, a digital twin model 304 can be constructed based on the positional relationship information 302_3 between the 3D point cloud model 303 and at least one physical device.

[0130] According to embodiments of this disclosure, operation S210 may include the following operations.

[0131] Based on the terminal detection signal, auxiliary information is determined, wherein the auxiliary information includes at least one of the following: first auxiliary position information and second auxiliary position information. The first position information is determined based on the auxiliary information.

[0132] According to embodiments of this disclosure, the object location detection instruction may further include a terminal detection signal.

[0133] According to embodiments of this disclosure, after receiving an object location detection command, auxiliary information can be determined based on the terminal detection signal in the object location detection command. The auxiliary information may refer to information used to determine the location of the detection terminal. The auxiliary information includes at least one of the following: first auxiliary location information and second auxiliary location information.

[0134] For example, if the auxiliary information includes first auxiliary location information, the first location information can be determined based on the first auxiliary location information. Alternatively, if the auxiliary information includes second auxiliary location information, the first location information can be determined based on the second auxiliary location information. Alternatively, if the auxiliary information includes both first and second auxiliary location information, the first location information can be determined based on both the first and second auxiliary location information.

[0135] According to embodiments of this disclosure, since the first location information is determined based on auxiliary information, which includes at least one of first auxiliary location information and second auxiliary location information, the accuracy of the first location information is improved by utilizing the auxiliary information to determine the first location information.

[0136] According to embodiments of this disclosure, when the auxiliary information includes first auxiliary location information, determining the first location information based on the auxiliary information may include the following operations.

[0137] The first location information is determined based on IoT positioning information.

[0138] According to embodiments of this disclosure, the first auxiliary location information may include IoT location information.

[0139] According to embodiments of this disclosure, the detection terminal may have a second RFID tag. IoT location information may be obtained based on the second RFID tag. The second RFID tag of the detection terminal may include one of the following: a Bluetooth-based RFID tag, a WiFi-based RFID tag, a UWB-based RFID tag, a ZigBee-based RFID tag, and an RFID-based RFID tag.

[0140] Figure 4A The illustration shows an example diagram of a method for obtaining first location information in response to detecting an object location detection command from a detection terminal, according to an embodiment of the present disclosure.

[0141] like Figure 4A As shown, in 400A, in response to detecting an object location detection command 401 from a detection terminal, the object location detection command 401 may include a terminal detection signal 401_1. Auxiliary information 402 can be determined based on the terminal detection signal 401_1. If the auxiliary information 402 includes first auxiliary location information 402_1, the first auxiliary location information 402_1 may include IoT positioning information 403, and first location information 404 can be determined based on the IoT positioning information 403.

[0142] According to embodiments of this disclosure, when the auxiliary information further includes second auxiliary location information, determining the first location information based on IoT positioning information may include the following operations.

[0143] The first location information is determined based on IoT location information and regional location information.

[0144] According to embodiments of this disclosure, the second auxiliary location information may include regional location information.

[0145] According to embodiments of this disclosure, mobile shelving units in a warehouse may have column labels. Area location information may be obtained from the column labels. Column labels may include at least one of the following: RFID-based column labels and QR code-based column labels.

[0146] According to embodiments of this disclosure, when the auxiliary information includes both first auxiliary location information and second auxiliary location information, coordinate mapping and correction can be performed on the IoT positioning information based on the regional positioning information. For example, coordinate mapping can be understood as defining the coordinate range of the column in the virtual warehouse. The area where the shelf column can be palletized is the aisle, so the coordinate range is a long strip of coordinates. When the IoT positioning information is outside the long strip of coordinates, the k-Nearest Neighbor (kNN) classification algorithm can be used to map the IoT positioning information to the nearest coordinate point within the long strip of coordinates.

[0147] According to embodiments of this disclosure, offset correction can be understood as obtaining indoor coordinates through IoT positioning information and mapping them to virtual warehouse coordinates, correcting the data during the mapping process. Offset correction may refer to ensuring that the coordinates of the detection terminal are located in aisle or passageway areas. The offset correction mode may be to shift the coordinates to the area where the detection terminal is located at the nearest distance. Alternatively, supplementary offset correction can be performed based on area positioning information.

[0148] According to embodiments of this disclosure, when indoor IoT technology for positioning is not available, the auxiliary information may include only second auxiliary location information. In this case, the first location information can be determined based on the regional positioning information.

[0149] Figure 4B The illustration shows an example diagram of a method for obtaining first location information in response to detecting an object location detection command from a detection terminal, according to another embodiment of the present disclosure.

[0150] like Figure 4B As shown, in 400B, in response to detecting an object location detection command 405 from a detection terminal, the object location detection command 405 may include a terminal detection signal 405_1. Auxiliary information 406 can be determined based on the terminal detection signal 405_1. If the auxiliary information 406 includes first auxiliary location information 406_1 and second auxiliary location information 406_2, the first auxiliary location information 406_1 may include IoT positioning information 407, and the second auxiliary location information 406_2 may include area positioning information 408. First location information 409 can be determined based on the IoT positioning information 407 and the area positioning information 408.

[0151] According to embodiments of this disclosure, operation S230 may include the following operations.

[0152] Based on the first preset mapping relationship and object identification information, the target detection object identification information is determined. Based on the target detection object identification information, the target location information corresponding to the target detection object identification information is determined. The target location information is then determined as the second location information.

[0153] According to embodiments of this disclosure, the first preset mapping relationship may include a first preset key-value relationship corresponding to at least one preset detection object. The first preset key-value relationship may include preset detection object identification information and preset location information corresponding to the preset detection object identification information.

[0154] According to embodiments of this disclosure, preset detection object identification information can be used to identify preset detection objects. For example, the preset detection object identification information can refer to a box identifier or object identifier for storing objects. Preset location information can be used to characterize the intended storage location of the preset detection object. For example, the preset location information can refer to an object storage address code assigned to a warehouse or shelf.

[0155] According to embodiments of this disclosure, a first similarity can be calculated between object identification information and preset detection object identification information of at least one first preset key-value relationship. In response to a first similarity greater than a first preset threshold, it can be determined that the preset detection object identification information and object identification information in the first preset key-value relationship corresponding to the first similarity match. The preset detection object identification information can be determined as the target detection object identification information. The preset location information corresponding to the target detection object identification information can be determined as the target location information. The target location information can be determined as the second location information. The first preset threshold can be set according to actual business needs and is not limited here. For example, the first preset threshold can be set to 0.95.

[0156] According to embodiments of this disclosure, similarity can be used to characterize the degree of similarity between object identification information and preset detection object identification information. The relationship between the similarity value and the degree of similarity can be configured according to actual business needs and is not limited herein. For example, a higher similarity value indicates a greater degree of similarity between the object identification information and the preset detection object identification information. Conversely, a lower similarity value indicates a lower degree of similarity between the object identification information and the preset detection object identification information. Alternatively, a lower similarity value indicates a greater degree of similarity between the object identification information and the preset detection object identification information. Conversely, a higher similarity value indicates a lower degree of similarity between the object identification information and the preset detection object identification information.

[0157] According to embodiments of this disclosure, the similarity can be configured according to actual business needs, and is not limited thereto. For example, the similarity can include at least one of the following: methods based on literal similarity, methods based on text similarity, and methods based on entity similarity. Methods based on literal similarity can include at least one of the following: edit distance, Dice coefficient, and Jaccard similarity. Methods based on text similarity can include at least one of the following: cosine similarity, relative entropy, KL (Kullback-Leibler, KL) divergence, and probabilistic model similarity.

[0158] According to the embodiments of this disclosure, since the second location information is determined based on the target location information, the target location information is determined based on the target detection object identification information, and the target detection object identification information is determined based on the first preset mapping relationship and the object identification information, the efficiency and accuracy of determining the second location information are improved.

[0159] Figure 5 The illustration shows an example diagram of a method for obtaining second location information in response to receiving a target detection signal from an object to be detected, according to an embodiment of the present disclosure.

[0160] like Figure 5 As shown, in 500, the first preset mapping relationship 501 may include a first preset key-value relationship corresponding to at least one preset detection object. At least one first preset key-value relationship may include first preset key-value relationship 501_1, first preset key-value relationship 501_2, ..., first preset key-value relationship 501_n, ..., first preset key-value relationship 501_N.

[0161] The first preset key-value relationship 501_1 may include preset detection object identification information 501_11 and preset position information 501_12 corresponding to the preset detection object identification information 501_11. The first preset key-value relationship 501_2 may include preset detection object identification information 501_21 and preset position information 501_22 corresponding to the preset detection object identification information 501_21. And so on, preset detection object identification information 501_n1 and preset position information 501_n2 corresponding to the preset detection object identification information 501_n1. And so on, preset detection object identification information 501_N1 and preset position information 501_N2 corresponding to the preset detection object identification information 501_N1.

[0162] The target detection object identification information 503 can be determined based on the preset detection object identification information 501_11, preset detection object identification information 501_21, ..., preset detection object identification information 501_n1, ..., preset detection object identification information 501_N1 and object identification information 502.

[0163] After obtaining the target detection object identification information 503, the target location information 504 corresponding to the target detection object identification information 503 can be determined based on the target detection object identification information 503. The target location information 504 can be determined as the second location information 505.

[0164] According to embodiments of this disclosure, operation S220 may include the following operations.

[0165] Based on the first location information, a first detection positioning point is determined. Based on the preset distance information, a detection radius is determined. Based on the first detection positioning point and the detection radius, a first detection plane range is determined. Based on preset coefficients and the first detection plane range, a sphere shape range is determined, wherein the sphere shape range is represented by a three-dimensional coordinate system.

[0166] According to embodiments of this disclosure, the first detection range may include a spherical shape range.

[0167] According to embodiments of this disclosure, after obtaining the first position information, a first detection positioning point can be determined based on the first position information. A detection radius can be determined based on preset distance information. After determining the first detection positioning point and the detection radius, the first detection positioning point can be defined as the center of a first circle, and the detection radius can be defined as the radius of a first circle. A first detection plane range can be determined based on the first center and the first radius. After obtaining the first detection plane range, the sphere shape range can be determined based on a first preset coefficient and the first detection plane range.

[0168] According to embodiments of this disclosure, alternatively, after determining the first detection positioning point and the detection radius, the first detection positioning point can be determined as the center of a second circle, and the detection radius can be determined as the radius of a second circle. The sphere's shape range can then be directly determined based on a second preset coefficient, the second center of the second circle, and the second radius of the second circle. The first preset coefficient and the second preset coefficient can be configured according to actual business needs and are not limited herein. For example, the first preset coefficient and the second preset coefficient may be the same or different.

[0169] According to the embodiments of this disclosure, since the sphere shape range is determined based on a preset coefficient, a first detection positioning point, and a detection radius, the first detection positioning point is determined based on first position information, and the detection radius is determined based on preset distance information, the sphere shape range can be used to characterize the candidate range where the object to be detected is located, thereby improving the accuracy of the sphere shape range and thus improving the efficiency and accuracy of object position detection.

[0170] Figure 6A The illustration shows an example diagram of a method for determining a first detection range based on first location information and preset distance information according to an embodiment of the present disclosure.

[0171] like Figure 6A As shown, in 600A, in response to detecting an object position detection command 601 from the detection terminal, first position information 602 can be acquired. The object position detection command 601 may include preset distance information 601_1.

[0172] After obtaining the first location information 602, the first detection positioning point 603 can be determined based on the first location information 602. The detection radius 604 can be determined based on the preset distance information 601_1.

[0173] After obtaining the first detection positioning point 603 and the detection radius 604, the first detection plane range 605 can be determined based on the first detection positioning point 603 and the detection radius 604.

[0174] After obtaining the first detection plane range 605, the sphere shape range 607 can be determined according to the preset coefficient 606 and the first detection plane range 605.

[0175] According to embodiments of this disclosure, operation S240 may include the following operations.

[0176] Based on the target detection signal, the detection angle range is determined. Based on the detection angle range, the hemispherical shape range is determined within the first detection range, wherein the hemispherical shape range is characterized by a three-dimensional coordinate system.

[0177] According to embodiments of this disclosure, the second detection range may include a hemispherical shape range.

[0178] According to embodiments of this disclosure, after obtaining the target detection signal, a detection angle range can be determined based on the target detection signal. After obtaining the detection angle range, a first detection range can be filtered based on the detection angle range to determine a hemispherical shape range within the first detection range. The hemispherical shape range can be configured according to actual business needs and is not limited herein. For example, the hemispherical shape range can be within 180 degrees.

[0179] According to embodiments of this disclosure, since the hemispherical shape range is determined within a first detection range based on the detection angle range, and the detection angle range is determined based on the target detection signal, the hemispherical shape range can be used to characterize the range in which the object to be detected is located, thereby improving the accuracy of the hemispherical shape range and thus improving the efficiency and accuracy of object position detection.

[0180] Figure 6B The illustration shows an example schematic diagram of a method for determining a second detection range based on a target detection signal and a first detection range according to an embodiment of the present disclosure.

[0181] like Figure 6B As shown, in 600B, in response to receiving a target detection signal 608 from the object to be detected, a detection angle range 609 can be determined based on the target detection signal 608. After obtaining the detection angle range 609, a hemispherical shape range 611 can be determined within a first detection range 610 based on the detection angle range 609.

[0182] According to embodiments of this disclosure, operation S250 may include the following operations.

[0183] Based on the second detection range, environmental object identification information is determined. Based on the second preset mapping relationship and the environmental object identification information, target environmental object identification information is determined. Based on the target environmental object identification information, target signal attenuation information corresponding to the target environmental object identification information is determined. The second detection range is adjusted based on the target signal attenuation information to obtain the adjusted second detection range.

[0184] According to embodiments of this disclosure, the second preset mapping relationship may include a second preset key-value relationship corresponding to at least one preset environment object. The second preset key-value relationship may include preset environment object identification information and preset signal attenuation information corresponding to the preset environment object identification information.

[0185] According to embodiments of this disclosure, preset environmental object identification information can be used to identify the materials of different environmental objects. Preset signal attenuation information can be used to characterize the signal attenuation values ​​of different environmental objects. The second preset key value relationship can include preset penetration conditions corresponding to the preset environmental object identification information. The preset penetration conditions can be used to characterize whether an environmental object can be penetrated. For example, liquids and metal back panels cannot be penetrated, while shelves, boxes, and walls can be penetrated.

[0186] According to embodiments of this disclosure, the environmental objects and directions involved in the signal path can be calculated by a virtual warehouse. The preset signal attenuation information may include at least one of the following: first preset signal attenuation information and second preset signal attenuation information. For example, for paper boxes, the preset penetration condition is penetrable; the first preset signal attenuation information may include a first preset attenuation value, and the second preset signal attenuation information may include a first adjusted attenuation value. Alternatively, for mobile shelving units with metal back panels, the preset penetration condition is impermeable; the first preset signal attenuation information may include a second preset attenuation value, and the second preset signal attenuation information may include a second adjusted attenuation value.

[0187] According to embodiments of this disclosure, a second similarity can be calculated between environmental object identification information and preset environmental object identification information of at least one second preset key-value relationship. In response to a second similarity greater than a second preset threshold, it can be determined that the preset environmental object identification information and the environmental object identification information in the second preset key-value relationship corresponding to the second similarity match. The preset environmental object identification information can be determined as the target environmental object identification information. The preset signal attenuation information corresponding to the target environmental object identification information can be determined as the target signal attenuation information. The second detection range can be adjusted according to the target signal attenuation information to obtain an adjusted second detection range. The second preset threshold can be set according to actual business needs and is not limited here. For example, the second preset threshold can be uniformly set to 0.95.

[0188] According to the embodiments of this disclosure, since the adjusted second detection range is obtained by adjusting the second detection range based on the target signal attenuation information, the target signal attenuation information is determined based on the target environmental object identification information, and the target environmental object identification information is determined based on the second preset mapping relationship and the environmental object identification information, the accuracy of determining the adjusted second detection range is improved.

[0189] According to embodiments of this disclosure, operation S250 may further include the following operations.

[0190] If the adjusted second detection range includes the second position information, determine the object position detection result indicating that the position detection has passed. If the adjusted second detection range does not include the second position information, determine the object position detection result indicating that the position detection has failed. If the second position information is located at the critical position of the adjusted second detection range, determine the object position detection result indicating that the position detection has failed.

[0191] According to embodiments of this disclosure, a virtual warehouse can be linked with a physical warehouse via Internet of Things (IoT) technology, so that the latest status of the physical warehouse, such as the movement of shelves, can be synchronously implemented in the virtual warehouse. Critical positions can be used to characterize the boundary area of ​​the second detection range. Critical positions can be used to avoid errors caused by directional errors of the detection terminal, preset distance information errors, and environmental object occlusion, thereby avoiding false alarms that could cause problems for business operations.

[0192] According to embodiments of this disclosure, when the adjusted second detection range includes the second location information, it can be considered a reasonable case of multiple scans by the detection terminal. In this case, the object location detection result indicating successful location detection can be determined. When the adjusted second detection range does not include the second location information, it can be considered an abnormal case of misplaced object. In this case, the object location detection result indicating failed location detection can be determined. For example, if the detection radius of the second detection range is 3 meters and the second location information is 15 meters, in this case, the item can be determined to be misplaced.

[0193] Figure 7 The illustration shows an example schematic diagram of an object location detection process according to an embodiment of the present disclosure.

[0194] like Figure 7 As shown, in step 700, in response to detecting an object location detection command 701 from a detection terminal, first location information 702 can be acquired. The object location detection command 701 may include preset distance information 701_1. After acquiring the first location information 702, a first detection range 703 can be determined based on the first location information 702 and the preset distance information 701_1.

[0195] In response to receiving a target detection signal 704 from the object to be detected, second position information 705 can be obtained. A second detection range 706 can be determined based on the target detection signal 704 and the first detection range 703.

[0196] After obtaining the second detection range 706, environmental object identification information 708 can be determined based on the second detection range 706. Target environmental object identification information 709 can be determined based on the second preset mapping relationship 707 and the environmental object identification information 708. Target signal attenuation information 710 corresponding to the target environmental object identification information 709 can be determined based on the target environmental object identification information 709. The second detection range 706 can be adjusted based on the target signal attenuation information 710 to obtain the adjusted second detection range 711. After obtaining the second detection range 711, operation S710 can be executed.

[0197] In operation S710, is the second position information located at the critical position of the adjusted second detection range? If yes, then the object position detection result 712, representing the position detection failure, can be determined. If not, then operation S720 can be executed.

[0198] In operation S720, does the adjusted second detection range include the second position information? If not, then the position detection result 712, representing the object whose position detection failed, can be determined. If yes, then the position detection result 713, representing the object whose position detection passed, can be determined.

[0199] According to embodiments of this disclosure, the object location detection method 200 may further include the following operations.

[0200] Using a digital twin model, the first location information, the second location information, the second detection range, and the object location detection results are displayed. The digital twin model corresponds to the physical warehouse where the object to be detected is located.

[0201] According to embodiments of this disclosure, after obtaining the object location detection result, a visualization tagging component can be used to display the first location information, the second location information, the second detection range, and the object location detection result in a digital twin model.

[0202] According to embodiments of this disclosure, the first location information can be used to characterize the location of the detection terminal. The second location information can be used to characterize a preset location of the object to be detected. The second detection range can be used to characterize the range in which the actual location of the object to be detected is located.

[0203] Figure 8A The illustration shows an example schematic diagram of an object location detection method according to an embodiment of the present disclosure.

[0204] like Figure 8A As shown, the virtual warehouse has 3 columns. The first column includes 5 rows of shelves, the second column includes 2 rows of shelves, and the third column includes 4 rows of shelves.

[0205] In 800A, in response to detecting an object position detection command from a detection terminal, first position information 801 can be acquired. A first detection range can be determined based on the first position information 801 and the preset distance information in the object position detection command.

[0206] In response to receiving a target detection signal from the object to be detected, second location information 802 can be acquired. A second detection range, i.e., the shelf area encompassed by the dashed line k to the dashed line l, can be determined based on the target detection signal and the first detection range. The second detection range can be used to characterize the actual location information 803 of the object to be detected.

[0207] If the second detection range (i.e., the shelf range included by the dashed line k to the dashed line l) does not include the second location information 802, the object location detection result 804 representing the location detection failure can be determined.

[0208] In this case, a digital twin model can be used to display the first location information 801, the second location information 802, the second detection range (i.e., the shelf range included by the dashed line k to the dashed line l), and the object location detection result 804.

[0209] Figure 8BThe illustration shows an example schematic diagram of an object location detection method according to another embodiment of the present disclosure.

[0210] like Figure 8B As shown, the virtual warehouse has 3 columns. The first column includes 5 rows of shelves, the second column includes 2 rows of shelves, and the third column includes 4 rows of shelves.

[0211] In 800B, in response to detecting an object position detection command from a detection terminal, first position information 805 can be acquired. A first detection range can be determined based on the first position information 805 and the preset distance information in the object position detection command.

[0212] In response to receiving a target detection signal from the object to be detected, second location information 806 can be acquired. A second detection range, i.e., the shelf area encompassed by the dashed line p to the dashed line q, can be determined based on the target detection signal and the first detection range. The second detection range can be used to characterize the actual location information 807 of the object to be detected.

[0213] If the second detection range (i.e., the shelf range included by the dashed line p to the dashed line q) includes the second location information 806, the object location detection result 808 representing the location detection passing can be determined.

[0214] In this case, a digital twin model can be used to display the first location information 805, the second location information 806, the second detection range (i.e., the shelf range included by the dashed line p to the dashed line q) and the object location detection result 808.

[0215] The above are merely exemplary embodiments, but are not limited thereto. Other object location detection methods known in the art may also be included, as long as they can improve the efficiency and accuracy of object location detection.

[0216] Figure 9 A block diagram of an object position detection apparatus according to an embodiment of the present disclosure is shown schematically.

[0217] like Figure 9 As shown, the object position detection device 900 may include a first acquisition module 910, a first determination module 920, a second acquisition module 930, a second determination module 940, and a third determination module 950.

[0218] The first acquisition module 910 is used to acquire first location information in response to detecting an object location detection command from a detection terminal, wherein the object location detection command includes preset distance information, and the first location information corresponds to the detection terminal.

[0219] The first determining module 920 is used to determine the first detection range based on the first position information and the preset distance information.

[0220] The second acquisition module 930 is used to acquire second location information in response to receiving a target detection signal from the object to be detected, wherein the target detection signal includes object identification information of the object to be detected, and the second location information is associated with the object identification information.

[0221] The second determining module 940 is used to determine a second detection range based on the target detection signal and the first detection range, wherein the second detection range belongs to the first detection range.

[0222] The third determining module 950 is used to determine the object position detection result corresponding to the object to be detected based on the second position information and the second detection range.

[0223] According to embodiments of this disclosure, the first detection range includes a spherical shape range.

[0224] According to embodiments of this disclosure, the first determining module 920 may include a first determining submodule, a second determining submodule, a third determining submodule, and a fourth determining submodule.

[0225] The first determination submodule is used to determine the first detection positioning point based on the first position information.

[0226] The second determining submodule is used to determine the detection radius based on preset distance information.

[0227] The third determining submodule is used to determine the range of the first detection plane based on the first detection positioning point and the detection radius.

[0228] The fourth determination submodule is used to determine the sphere shape range based on preset coefficients and the range of the first detection plane, wherein the sphere shape range is characterized by a three-dimensional coordinate system.

[0229] According to embodiments of this disclosure, the second acquisition module 930 may include a fifth determination submodule, a sixth determination submodule, and a seventh determination submodule.

[0230] The fifth determination submodule is used to determine the target detection object identification information based on the first preset mapping relationship and the object identification information.

[0231] The sixth determination submodule is used to determine the target location information corresponding to the target detection object identification information based on the target detection object identification information.

[0232] The seventh determination submodule is used to determine the target location information as the second location information.

[0233] According to embodiments of this disclosure, the first preset mapping relationship includes a first preset key-value relationship corresponding to at least one preset detection object, and the first preset key-value relationship includes preset detection object identification information and preset location information corresponding to the preset detection object identification information.

[0234] According to embodiments of this disclosure, the second detection range includes a hemispherical shape range.

[0235] According to embodiments of this disclosure, the second determining module 940 may include an eighth determining submodule and a ninth determining submodule.

[0236] The eighth determination submodule is used to determine the detection angle range based on the target detection signal. The ninth determination submodule is used to determine the hemispherical shape range within the first detection range based on the detection angle range, wherein the hemispherical shape range is characterized by a three-dimensional coordinate system.

[0237] According to embodiments of this disclosure, the object location detection instruction further includes a terminal detection signal.

[0238] According to embodiments of this disclosure, the first acquisition module 910 may include a tenth determination submodule and an eleventh determination submodule.

[0239] The tenth determining submodule is used to determine auxiliary information based on the terminal detection signal, wherein the auxiliary information includes at least one of the following: first auxiliary position information and second auxiliary position information.

[0240] The eleventh determination submodule is used to determine the first position information based on auxiliary information.

[0241] According to embodiments of this disclosure, the first auxiliary location information includes IoT location information.

[0242] According to embodiments of this disclosure, when the auxiliary information includes first auxiliary position information, the eleventh determining submodule may include a determining unit.

[0243] The determining unit is used to determine the first location information based on the IoT positioning information.

[0244] According to embodiments of this disclosure, the second auxiliary location information includes regional location information.

[0245] According to embodiments of this disclosure, when the auxiliary information further includes second auxiliary position information, the determining unit may include a determining subunit.

[0246] The determination sub-unit is used to determine the first location information based on IoT location information and regional location information.

[0247] According to embodiments of this disclosure, the third determining module 950 may include a twelfth determining submodule, a thirteenth determining submodule, a fourteenth determining submodule, and an adjustment submodule.

[0248] The twelfth determination submodule is used to determine the environmental object identification information based on the second detection range.

[0249] The thirteenth determination submodule is used to determine the target environment object identification information based on the second preset mapping relationship and the environment object identification information.

[0250] The fourteenth determination submodule is used to determine the target signal attenuation information corresponding to the target environment object identification information based on the target environment object identification information.

[0251] The adjustment submodule is used to adjust the second detection range according to the target signal attenuation information to obtain the adjusted second detection range.

[0252] According to embodiments of this disclosure, the second preset mapping relationship includes a second preset key-value relationship corresponding to at least one preset environment object. The second preset key-value relationship includes preset environment object identification information and preset signal attenuation information corresponding to the preset environment object identification information.

[0253] According to embodiments of this disclosure, the third determining module 950 may further include a fifteenth determining submodule, a sixteenth determining submodule, and a seventeenth determining submodule.

[0254] The fifteenth determination submodule is used to determine the object position detection result representing the position detection passing when the adjusted second detection range includes the second position information.

[0255] The sixteenth determination submodule is used to determine the object position detection result that represents the position detection failure when the adjusted second detection range does not include the second position information.

[0256] The seventeenth determination submodule is used to determine the object position detection result that represents the position detection failure when the second position information is at the critical position of the adjusted second detection range.

[0257] According to embodiments of this disclosure, the object location detection device 900 may further include a display module.

[0258] The display module uses a digital twin model to show the first location information, the second location information, the second detection range, and the object location detection results. The digital twin model corresponds to the physical warehouse where the object to be detected is located.

[0259] According to embodiments of this disclosure, a digital twin model can be constructed in the following manner.

[0260] Collect physical warehouse information corresponding to the physical warehouse, including warehouse structure information, equipment structure information of at least one physical device located inside the physical warehouse, and positional relationship information between the at least one physical device and each other.

[0261] Based on the warehouse structure information and the equipment structure information of at least one physical device, the physical warehouse is reconstructed in three dimensions to obtain a three-dimensional point cloud model.

[0262] A digital twin model is constructed based on the positional relationship information between the 3D point cloud model and at least one physical device.

[0263] Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure, or at least part of the functions of any one or more of them, can be implemented in one module. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be implemented by dividing them into multiple modules. Any one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as hardware circuitry, such as Field Programmable Gate Arrays (FPGAs), Programmable Logic Arrays (PLAs), Systems-on-Chip, Systems-on-Substrate, Systems-on-Package, Application-Specific Integrated Circuits (ASICs), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, one or more of the modules, submodules, units, and subunits according to embodiments of the present disclosure can be at least partially implemented as computer program modules, which, when run, can perform corresponding functions.

[0264] For example, any plurality of the first acquisition module 910, the first determination module 920, the second acquisition module 930, the second determination module 940, and the third determination module 950 can be combined into one module / unit / subunit, or any one of these modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functionality of one or more of these modules / units / subunits can be combined with at least part of the functionality of other modules / units / subunits and implemented in one module / unit / subunit. According to embodiments of this disclosure, at least one of the first acquisition module 910, the first determination module 920, the second acquisition module 930, the second determination module 940, and the third determination module 950 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging the circuitry, or implemented in software, hardware, or firmware, or in any suitable combination of any of these three implementation methods. Alternatively, at least one of the first acquisition module 910, the first determination module 920, the second acquisition module 930, the second determination module 940, and the third determination module 950 may be at least partially implemented as a computer program module, which can perform corresponding functions when the computer program module is run.

[0265] It should be noted that the object position detection device part in the embodiments of this disclosure corresponds to the object position detection method part in the embodiments of this disclosure. For a detailed description of the object position detection device part, please refer to the object position detection method part, which will not be repeated here.

[0266] Figure 10 A block diagram of an electronic device suitable for implementing an object position detection method according to an embodiment of the present disclosure is shown schematically. Figure 10 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0267] like Figure 10As shown, a computer electronic device 1000 according to an embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage portion 1009 into a random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or an associated chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0268] RAM 1003 stores various programs and data required for the operation of electronic device 1000. Processor 1001, ROM 1002, and RAM 1003 are interconnected via bus 1004. Processor 1001 performs various operations of the method flow according to embodiments of the present disclosure by executing programs in ROM 1002 and / or RAM 1003. It should be noted that the programs may also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 may also perform various operations of the method flow according to embodiments of the present disclosure by executing programs stored in said one or more memories.

[0269] According to embodiments of this disclosure, the electronic device 1000 may further include an input / output (I / O) interface 1005, which is also connected to a bus 1004. The electronic device 1000 may also include one or more of the following components connected to the I / O interface 1005: an input section 1006 including a keyboard, mouse, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I / O interface 1005 as needed. A removable medium 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 1010 as needed so that computer programs read from it can be installed into the storage section 1008 as needed.

[0270] According to embodiments of this disclosure, the method flow according to embodiments of this disclosure can be implemented as a computer software program. For example, embodiments of this disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for performing the methods shown in the flowchart. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1009, and / or installed from removable medium 1011. When the computer program is executed by processor 1001, it performs the functions defined in the system of embodiments of this disclosure. According to embodiments of this disclosure, the systems, devices, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0271] This disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or it may exist independently and not assembled into the device / apparatus / system. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0272] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium. Examples include, but are not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0273] For example, according to embodiments of this disclosure, a computer-readable storage medium may include the ROM 1002 and / or RAM 1003 described above and / or one or more memories other than ROM 1002 and RAM 1003.

[0274] Embodiments of this disclosure also include a computer program product comprising a computer program containing program code for performing the methods provided in the embodiments of this disclosure. When the computer program product is run on an electronic device, the program code is used to enable the electronic device to implement the object location detection method provided in the embodiments of this disclosure.

[0275] When the computer program is executed by the processor 901, it performs the functions defined in the system / apparatus of this disclosure embodiments. According to embodiments of this disclosure, the systems, apparatuses, modules, units, etc., described above can be implemented by computer program modules.

[0276] In one embodiment, the computer program may rely on a tangible storage medium such as an optical storage device or a magnetic storage device. In another embodiment, the computer program may also be transmitted and distributed in the form of signals over a network medium, and downloaded and installed via the communication section 909, and / or installed from a removable medium 911. The program code contained in the computer program can be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination thereof.

[0277] According to embodiments of this disclosure, program code for executing the computer programs provided in embodiments of this disclosure can be written in any combination of one or more programming languages. Specifically, these computational programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, languages ​​such as Java, C++, Python, "C", or similar programming languages. The program code can execute entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0278] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions. Those skilled in the art will understand that the features recited in the various embodiments and / or claims of this disclosure can be combined and / or combined in various ways, even if such combinations or combinations are not expressly described in this disclosure. In particular, the features described in the various embodiments and / or claims of this disclosure may be combined and / or combined in various ways without departing from the spirit and teachings of this disclosure. All such combinations and / or combinations fall within the scope of this disclosure.

[0279] The embodiments of this disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of this disclosure. Although various embodiments have been described above, this does not mean that the measures in the various embodiments cannot be used advantageously in combination. The scope of this disclosure is defined by the appended claims and their equivalents. Various substitutions and modifications can be made by those skilled in the art without departing from the scope of this disclosure, and all such substitutions and modifications should fall within the scope of this disclosure.

Claims

1. An object location detection method, comprising: In response to detecting an object location detection command from a detection terminal, first location information is acquired, wherein the object location detection command includes preset distance information, and the first location information corresponds to the detection terminal; Determining the sphere shape range based on the first location information and the preset distance information includes: determining a first detection positioning point based on the first location information; determining a detection radius based on the preset distance information; determining a first detection plane range based on the first detection positioning point and the detection radius; and determining the sphere shape range based on a preset coefficient and the first detection plane range, wherein the sphere shape range is represented by a three-dimensional coordinate system. In response to receiving a target detection signal from an object to be detected, second location information is obtained, wherein the target detection signal includes object identification information of the object to be detected, and the second location information is associated with the object identification information; Based on the target detection signal and the sphere shape range, a second detection range is determined, wherein the second detection range belongs to the sphere shape range; and Based on the second location information and the second detection range, the object location detection result corresponding to the object to be detected is determined.

2. The method according to claim 1, wherein, The step of obtaining the second location information in response to receiving a target detection signal from the object to be detected includes: Based on the first preset mapping relationship and the object identification information, the target detection object identification information is determined; Based on the target detection object identification information, determine the target location information corresponding to the target detection object identification information; and The target location information is determined as the second location information; The first preset mapping relationship includes a first preset key-value relationship corresponding to at least one preset detection object. The first preset key-value relationship includes preset detection object identification information and preset location information corresponding to the preset detection object identification information.

3. The method according to claim 1, wherein, The second detection range includes the hemispherical shape range; The step of determining the second detection range based on the target detection signal and the sphere shape range includes: Based on the target detection signal, determine the detection angle range; and Based on the detection angle range, the hemispherical shape range is determined within the spherical shape range, wherein the hemispherical shape range is characterized by a three-dimensional coordinate system.

4. The method according to claim 1, wherein, The object location detection instruction also includes a terminal detection signal; Wherein, the step of obtaining the first location information in response to detecting an object location detection command from the detection terminal includes: Based on the terminal detection signal, auxiliary information is determined, wherein the auxiliary information includes at least one of the following: first auxiliary location information and second auxiliary location information; and The first location information is determined based on the auxiliary information.

5. The method according to claim 4, wherein, The first auxiliary location information includes IoT location information; Wherein, if the auxiliary information includes first auxiliary location information, determining the first location information based on the auxiliary information includes: The first location information is determined based on the IoT positioning information.

6. The method according to claim 5, wherein, The second auxiliary location information includes regional positioning information; Where the auxiliary information further includes second auxiliary location information, determining the first location information based on the IoT positioning information includes: The first location information is determined based on the IoT location information and the regional location information.

7. The method according to any one of claims 1 to 6, wherein, The step of determining the object location detection result corresponding to the object to be detected based on the second location information and the second detection range includes: Based on the second detection range, determine the environmental object identification information; Based on the second preset mapping relationship and the environmental object identification information, the target environmental object identification information is determined; Based on the target environment object identification information, determine the target signal attenuation information corresponding to the target environment object identification information; and The second detection range is adjusted according to the target signal attenuation information to obtain the adjusted second detection range; The second preset mapping relationship includes a second preset key-value relationship corresponding to at least one preset environment object. The second preset key-value relationship includes preset environment object identification information and preset signal attenuation information corresponding to the preset environment object identification information.

8. The method according to claim 7, further comprising: When the adjusted second detection range includes the second location information, the object location detection result representing the location detection is determined; If the adjusted second detection range does not include the second location information, determine the object location detection result that represents the location detection failure; as well as When the second location information is located at the critical position of the adjusted second detection range, the object location detection result representing the location detection failure is determined.

9. The method according to any one of claims 1 to 6, further comprising, after determining the object position detection result corresponding to the object to be detected based on the second position information and the second detection range: Using a digital twin model, the first location information, the second location information, the second detection range, and the object location detection result are displayed, wherein... The digital twin model corresponds to the physical warehouse where the object to be detected is located.

10. The method according to claim 9, wherein, The digital twin model was constructed in the following manner: Collect physical warehouse information corresponding to the physical warehouse, wherein the physical warehouse information includes warehouse structure information, equipment structure information of at least one physical device located inside the physical warehouse, and positional relationship information between the at least one physical device; Based on the warehouse structure information and the equipment structure information of each of the at least one physical device, the physical warehouse is reconstructed in three dimensions to obtain a three-dimensional point cloud model; and The digital twin model is constructed based on the positional relationship information between the three-dimensional point cloud model and the at least one physical device.

11. An object position detection device, comprising: The first acquisition module is configured to acquire first location information in response to detecting an object location detection command from a detection terminal, wherein the object location detection command includes preset distance information, and the first location information corresponds to the detection terminal; A first determining module is configured to determine the sphere shape range based on the first position information and the preset distance information, comprising: a first determining submodule, configured to determine a first detection positioning point based on the first position information; a second determining submodule, configured to determine a detection radius based on the preset distance information; a third determining submodule, configured to determine a first detection plane range based on the first detection positioning point and the detection radius; and a fourth determining submodule, configured to determine the sphere shape range based on a preset coefficient and the first detection plane range, wherein the sphere shape range is characterized by a three-dimensional coordinate system; The second acquisition module is used to acquire second location information in response to receiving a target detection signal from the object to be detected, wherein the target detection signal includes object identification information of the object to be detected, and the second location information is associated with the object identification information; The second determining module is configured to determine a second detection range based on the target detection signal and the sphere shape range, wherein the second detection range belongs to the sphere shape range; and The third determining module is used to determine the object position detection result corresponding to the object to be detected based on the second position information and the second detection range.

12. An electronic device, comprising: One or more processors; Memory, used to store one or more instructions. When the one or more instructions are executed by the one or more processors, the one or more processors cause the one or more processors to implement the method of any one of claims 1 to 10.

13. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 10.

14. A computer program product comprising computer-executable instructions, which, when executed, are used to implement the method of any one of claims 1 to 10.

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