JP7683708B2 - Function imparting device, function imparting method, and function imparting program - Google Patents

Description

The present disclosure relates to a function-imparting device, a function-imparting method, and a function-imparting program.

Advances in ICT (Information and Communications Technology) have made "digital twins" possible. Digital twins can link the real world with cyberspace and have been attracting attention in recent years.

A digital twin is a digital object that accurately represents a real-world object in cyberspace. Examples of real-world objects include production machines in a factory, aircraft engines, and automobiles. A digital twin maps the shape, condition, or function of such objects in cyberspace.

Digital twins make it possible to conduct simulations in cyberspace. For example, simulations can analyze the current state of an object, predict the future, and evaluate possibilities.

ICT-related technologies are easily utilized in cyberspace. For this reason, the application of digital twins to ICT can provide benefits such as intelligent control of real-world objects, which can be fed back to real-world objects.

As more and more real-world objects are turned into digital twins, it is expected that digital twins will lead to increased demand for simulations in cyberspace. For example, there is a high possibility of increased demand for solutions such as interacting with heterogeneous and diverse digital twins across industry boundaries, cross-industry collaboration through the combination of heterogeneous and diverse digital twins, and large-scale simulations.

Interactions between digital twins are calculated by digitizing the inherent functions of their physical twins (i.e., real objects), such as the "cutting" function of a knife or the "writing" function of a pen.

Machine learning models such as neural networks are used to estimate the functionality of the physical twin. The machine learning models use images, point clouds and 3D meshes of the physical twin as input. From this input, the machine learning models estimate the functionality of the physical twin. The estimated functionality is assigned to the corresponding digital twin as natural language labels.

“NEDO Project Research Results and Model Database Function Recognition (1) Function Recognition Based on Machine Learning” [online], [searched September 3, 2021], Internet <http://isl.sist.chukyo-u.ac.jp/archives/nedopro/kinou-1/> “3D Shape Segmentation with Projective Convolutional Networks” [online], [Retrieved September 3, 2021], Internet: <https://people.cs.umass.edu/~kalo/papers/shapepfcn/ShapePFCN.pdf>

However, with the above prior art, it can be difficult to automatically create digital objects that implement functions.

For example, in the prior art mentioned above, only functional labels are assigned to the digital twin; that is, the functions themselves are not digitized.

Therefore, the present disclosure proposes a function-imparting device, a function-imparting method, and a function-imparting program that can automatically create digital objects with implemented functions.

In one aspect of the present disclosure, a function-imparting device includes an acquisition unit that acquires a digital object generated by digitizing a physical object and data indicating a function of the digital object, and an imparting unit that acquires a program that digitally reproduces the function of the digital object from a predetermined storage device and imparts the acquired program to the digital object.

A function-imparting device according to one or more embodiments of the present disclosure can automatically create digital objects that implement functions.

FIG. 1 shows an example of the creation of a digital twin with inferred functionality. Figure 2 shows an example of function implementation in a digital twin. FIG. 3 is a block diagram of an example environment for implementing functionality in digital objects. FIG. 4 shows an overview of the functional implementation according to the present disclosure. FIG. 5 is a block diagram of an example of the configuration of a function implementation system according to the present disclosure. FIG. 6 shows an example of the flow of data in a function implementation system according to the present disclosure. FIG. 7 shows an example of functionality according to the present disclosure. FIG. 8 is a flow chart illustrating an example process for creating a functionally implemented digital object. FIG. 9 shows an example of the hardware configuration of a computer.

Several embodiments are described in detail below with reference to the drawings. However, the present invention is not limited to these several embodiments. The several features of the various embodiments can be combined in various ways, provided that these several features are not mutually contradictory. The same elements are indicated by the same reference numerals, and duplicated descriptions are omitted.

1. Introduction
In digital twin technology, digital twins can be generated with functional labels that indicate the functions of the digital twins. The functional labels allow developers to identify uses for the digital twins. For example, the functional labels are determined by machine learning models such as neural nets.

Figure 1 shows generation 10, which is an example of the generation of a digital twin with an estimated function. In generation 10, a real object is first digitized and a digital twin is generated. Then, the function of the digital twin is estimated and a functional label is assigned to the digital twin. The functional label is a natural language label. In the example of Figure 1, the digital twin is a saw digital twin and the functional label indicates the function of cutting.

However, in generation 10, functional labels are merely assigned to specific parts of the digital twin. In other words, the functions of the digital twin themselves are not reproduced digitally.

Figure 2 shows function implementation 20, which is an example of function implementation in a digital twin. As shown in Figure 2, a saw digital twin that has a cutting function implemented can cut a tree digital twin. In function implementation 20, a developer creates a digital twin that implements functions according to the labels assigned to the digital twin.

However, manually creating a digital twin with implemented functions every time an object is turned into a digital twin is costly. Developers can create a digital twin with implemented functions every time a digital twin is created. In the real world, an unspecified number of objects are turned into digital twins. For this reason, manually implementing functions increases the cost of creating digital twins.

To solve the above problems, a function implementation system according to one or more embodiments of the present disclosure implements one or more functions as described below.

[2. Environment for implementing functions]
First, an environment for implementing the functions according to the present disclosure will be described with reference to FIG.

3 is a block diagram of an environment 1, which is an example of an environment for implementing functions in digital objects. As shown in FIG. 3, the environment 1 includes a function implementation system 100, a network 200, and a user device 300.

The function implementation system 100 is a system that performs one or more function implementations. The function implementation system 100 is an example of a function-imparting device. The one or more function implementations include a process of imparting a function to a digital object. An example of a digital object is a digital twin. An overview of the function implementation related to the present disclosure is described in the next section.

The function implementation system 100 includes one or more data processing devices, such as one or more servers. An example of the configuration of the function implementation system 100 is described in Section 4.

The network 200 is, for example, a network such as a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, etc. The network 200 connects the function implementation system 100 and the user device 300.

The user device 300 is a data processing device such as a client device. The user of the user device 300 is, for example, a person who wants to create a digital twin with functions implemented. The user sends an image of a real object to the function implementation system 100. The user then receives a digital twin corresponding to the real object from the function implementation system 100. In this digital twin, the function of the object is also reproduced.

[3. Overview of function implementation]
Next, an overview of the implementation of functions according to the present disclosure will be described with reference to Fig. 4. Note that this overview is not intended to limit the present invention or the embodiments described in the following sections.

Figure 4 shows an overview 30 of function implementation according to the present disclosure. The overview 30 includes five steps. The function implementation system 100 automatically generates a digital twin that reproduces the original functions of the physical twin without human intervention.

In step S1, the function implementation system 100 digitizes the saw 31 and generates a saw digital twin 32.

In step S2, the function implementation system 100 estimates the function of the saw digital twin 32 and assigns a label indicating the estimated function to the saw digital twin 32. As a result, the function implementation system 100 generates a saw digital twin 33 with a function label 34. The function label 34 indicates the function of cutting.

In step S3, the function implementation system 100 sends the function label 34 as a query to the function database 35.

The function database 35 manages function programs that have been created by developers. A function program is a program for digitally reproducing a function. In the function database 35, function labels are keys and function programs are values.

In step S4, the function implementation system 100 retrieves a function program 36 corresponding to the function label 34 from the function database 35. The function program 36 is a disconnection script.

In step S5, the function implementation system 100 assigns the function program 36 to the saw digital twin 33. As a result, the function implementation system 100 generates a saw digital twin 37 that implements the function of cutting.

As described above, the function implementation system 100 uses the label obtained by estimating the function of the digital twin as a query to obtain a function program. Then, the function implementation system 100 assigns the obtained function program to the digital twin. The function programs are stored in a function database. The function implementation system 100 can reuse function programs that were created in the past. Therefore, the function implementation system 100 can reduce the implementation cost of creating a digital twin in which even the functions are digitized.

[4. Details of the function implementation system]
Next, the function implementation system 100 will be described in detail with reference to FIGS.

Figure 5 is a block diagram of a function implementation system 100, which is an example of the configuration of a function implementation system according to the present disclosure. As shown in Figure 5, the function implementation system 100 includes a communication unit 110, a control unit 120, and a memory unit 130. The function implementation system 100 may include an input unit (e.g., a keyboard, a mouse) that accepts input from an administrator of the function implementation system 100. The function implementation system 100 may also include an output unit (e.g., a liquid crystal display, an organic EL (Electro Luminescence) display) that displays information to the administrator of the function implementation system 100.

4-1. Communication Unit 110
The communication unit 110 is implemented by, for example, a network interface card (NIC). The communication unit 110 is connected to the network 200 by wire or wirelessly. The communication unit 110 can transmit and receive information to and from the user device 300 via the network 200.

4-2. Control Unit 120
The control unit 120 is a controller. The control unit 120 uses a random access memory (RAM) as a working area and is implemented by one or more processors (e.g., a central processing unit (CPU), a micro processing unit (MPU)) that execute various programs stored in a storage device of the function implementation system 100. The control unit 120 may also be implemented by an integrated circuit such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), or a general purpose graphic processing unit (GPGPU).

5, the control unit 120 includes a function management unit 121, a function storage unit 122, an image receiving unit 123, a 3D mesh generation unit 124, a function estimation unit 125, a material estimation unit 126, a function provision unit 127, a DT management unit 128, and a function deficiency confirmation unit 129. One or more processors of the function implementation system 100 can implement each control unit by executing instructions stored in one or more memories of the function implementation system 100. The data processing performed by each control unit is an example, and each control unit (e.g., the function provision unit 127) may perform data processing described in relation to other control units (e.g., the function estimation unit 125).

[4-3. Storage unit 130]
The storage unit 130 is implemented by, for example, a semiconductor memory element such as a RAM or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG.

[4-4. Functions of each control unit]
In this subsection, the function of each of the above-mentioned control units will be described with reference to Figures 6 and 7. Also, the function of the function database 131 will be described in relation to the function management unit 121.

Figure 6 shows flow 40, which is an example of data flow in the function implementation system according to the present disclosure. As shown in Figure 6, data for creating a digital twin with functions is exchanged between function management unit 121, function storage unit 122, image receiving unit 123, 3D mesh generation unit 124, function estimation unit 125, material estimation unit 126, function assignment unit 127, DT management unit 128 and function deficiency confirmation unit 129.

[4-4-1. Function management department 121]
The function management unit 121 manages various programs in which functions are implemented. These various programs are, for example, programs that digitally reproduce the functions of a digital twin. These various programs are created by digitizing the functions of a physical twin.

The function management unit 121 is implemented as a database management system. For example, the function management unit 121 can search and rewrite a database according to a query. In the example of Figures 5 and 6, this database is the function database 131.

The input (i.e., query) of the function management unit 121 is a natural language label that describes the function or material of an object. The output of the function management unit 121 is a program in which the function is implemented.

The function management unit 121 uses labels representing functions and materials as keys. The function management unit 121 also uses programs as values. Therefore, the function management unit 121 manages programs in which functions are implemented in a KVS (Key-Value Store). When a query arrives, the function management unit 121 searches for and returns a program with a key that matches the query.

In this specification, a program in which a function is implemented is called a function program. Examples of function programs include a script for reproducing antenna feedback and a script for automatically setting the friction coefficient.

4-4-2. Function Storage Unit 122
The function storage unit 122 stores various function programs in the function database 131. The function storage unit 122 is an example of a storage unit. As described above, a function program is a program in which a function is implemented.

The function storage unit 122 receives a function program from a developer. The function storage unit 122 also receives a label indicating a function to be reproduced by the function program from the developer. In this specification, the label indicating a function is called a function label.

The function storage unit 122 associates the function program with a corresponding function label. The function storage unit 122 then stores the function program associated with the function label in the function database 131.

When a developer develops a new function program that does not exist in the function database 131, the developer sends the new program to the function storage unit 122. The function storage unit 122 adds the new program to the function database 131. The function storage unit 122 may accept access from general users. In this way, the function storage unit 122 may collect a wide range of function programs.

4-4-3. Image Receiving Unit 123
The image receiving unit 123 receives an image of a real object from the user device 300. The image receiving unit 123 can store the image in the storage unit 130.

The image of the real object is, for example, a photograph. The image receiving unit 123 can receive multiple images for generating a three-dimensional model of the object.

3D Mesh Generation Unit 124
The 3D mesh generating unit 124 generates a digital object by digitizing the shape of the object depicted in the image. For example, the 3D mesh generating unit 124 generates a 3D mesh from a point cloud obtained by measuring the surface of the object with a three-dimensional laser scanner. Alternatively, the 3D mesh generating unit 124 may create a 3D mesh from a plurality of photos received by the image receiving unit 123 without using a three-dimensional laser scanner. The 3D mesh generating unit 124 is an example of a generating unit. The 3D mesh generating unit 124 can acquire a plurality of images, a point cloud, and a 3D mesh generated in the past from the storage unit 130. In addition, the 3D mesh generating unit 124 can store the generated digital object in the storage unit 130.

The 3D mesh generator 124 generates a 3D mesh model of a real object based on the images and point clouds. The generated 3D mesh model is an example of a digital twin.

4-4-5. Function Estimation Unit 125
The function estimation unit 125 estimates the function of an object depicted in the original image based on the image of the real object received by the image receiving unit 123 and the shape of a digital object (e.g., a digital twin) generated by the 3D mesh generating unit 124. The function estimation unit 125 is an example of an estimation unit. The function estimation unit 125 can acquire an image depicting an object or a digital object from the storage unit 130. In addition, the function estimation unit 125 can store data indicating the estimated function in the storage unit 130 as a function label.

The input of the function estimation unit 125 is data such as an image, a point cloud, or a 3D mesh. The function estimation unit 125 can also use tag information attached to such data as input. For example, the tag information indicates the name of the photographed object.

The output of the function estimation unit 125 is functional part information and natural language labels that represent the functions. The functional part information indicates the parts that have a function. As an example, the functional part information of a saw digital twin may indicate the range that corresponds to the blade. The function estimation unit 125 can estimate the function on a part-by-part basis.

The function estimation unit 125 can estimate the function of an object using a machine learning model. An instance of training data is a range that represents a function within data such as an image, a point cloud, or a 3D mesh. A label of training data is a natural language label of the function corresponding to this range. The function estimation unit 125 can train a machine learning model based on the training data. The function estimation unit 125 can output an estimated function by inputting data such as an image, a point cloud, or a 3D mesh into the trained model.

[4-4-6. Material estimation unit 126]
The material estimation unit 126 acquires an image depicting an object from the storage unit 130. Then, the material estimation unit 126 estimates the material of the object based on the acquired image. The material estimation unit 126 can store a material label indicating the estimated material in the storage unit 130.

4-4-7. Function providing unit 127
The function imparting unit 127 acquires a digital object and a functional label of the digital object from the storage unit 130. This is an example of an acquisition unit of the function imparting unit 127. In addition, the function imparting unit 127 can acquire functional part information of the digital object and a material label of the digital object from the storage unit 130.

The function imparting unit 127 obtains a function program corresponding to the function indicated by the function label from the function database 131. As described above, a function program is a program in which a function is implemented (for example, a program that digitally reproduces the function of a saw to cut an object). The function imparting unit 127 then imparts the obtained function program to a digital object. The function imparting unit 127 is an example of an imparting unit. The function imparting unit 127 can store the digital object to which the function program has been imparted in the memory unit 130 as a digital object implementing a function.

Figure 7 shows function assignment 50, which is an example of function assignment according to the present disclosure. In function assignment 50, the input of the function assignment unit 127 is functional part information, a function label (i.e., a natural language label representing the function), and a digital twin (e.g., a 3D mesh). The output of the function assignment unit 127 is a digital twin with the function.

In the example of FIG. 7, the function imparting unit 127 first acquires the digital twin 51 along with functional part information and a functional label. The digital twin 51 is a saw digital twin. The functional part information indicates the range that corresponds to the blade. The functional label indicates the function of cutting.

Next, the function granting unit 127 sends a function label to the function management unit 121. This function label is sent as a query. The function management unit 121 searches the function database 131 for a function program associated with the key corresponding to the query. In the example of FIG. 7, a disconnection script is searched for. The function management unit 121 sends the disconnection script to the function granting unit 127. In this way, the function granting unit 127 can obtain a function program corresponding to the function of the digital object from the function database 131.

Next, the function imparting unit 127 imparts a functional program to the digital object based on the functional part information. In the example of Figure 7, a cutting script is imparted to the blade part of the saw digital twin.

[4-4-8. DT management department 128]
Returning to Fig. 6, the DT management unit 128 manages digital objects. For example, the DT management unit 128 manages various digital twins (DTs). The various digital twins include normal digital twins that do not implement the functions of a physical twin.

The DT management unit 128 can acquire the digital twin in which the function is implemented from the storage unit 130. The DT management unit 128 can then provide the acquired digital twin to the user device 300.

The DT management unit 128 can receive various digital twins from the developer. The DT management unit 128 can store the various received digital twins in the memory unit 130.

4-4-9. Functionality Deficiency Check Unit 129
When the function of the digital object is an active function that affects other physical objects, the function deficiency confirmation unit 129 acquires other digital objects generated by digitizing this other physical object from the storage unit 130. The other digital objects are included in various digital twins managed by the DT management unit 128. Then, the function deficiency confirmation unit 129 identifies the function of the other digital object as a passive function that is affected by the digital object.

A digital object's functionality may require a target digital object. In this case, the functionality of the target digital object is identified as a functionality that the digital object is missing.

As an example, the input to the function deficiency confirmation unit 129 is a function label indicating the function of a digital object (e.g., a natural language label expressing the function). On the other hand, the output of the function deficiency confirmation unit 129 is function deficiency information such as a digital twin with a missing function, a function label indicating the function that is missing in the digital twin, and functional part information corresponding to the function label.

For example, if a new function added to a digital twin affects other objects, the function deficiency confirmation unit 129 analyzes the space in which the physical twin corresponding to this digital twin exists. As an example, the function deficiency confirmation unit 129 acquires an image depicting the physical twin from the memory unit 130. Then, the function deficiency confirmation unit 129 determines whether other objects are included in the acquired image.

If another object is included in the acquired image, the function deficiency confirmation unit 129 identifies the other object as an object that is affected by the physical twin. Then, the function deficiency confirmation unit 129 acquires another digital twin corresponding to the identified other object from the storage unit 130.

The obtained functions of the other digital twins are identified as functions that are affected by the digital twin. The function deficiency confirmation unit 129 sends the above function deficiency information to the function assignment unit 127 according to the digital twin and the other digital twins and the functional labels of these digital twins. The function assignment unit 127 can assign functional programs corresponding to passive functions to the other digital twins.

For example, assume that a paper cup has been digitally twinned, and a knife with the function of "cutting" has been digitally twinned. In this example, the function deficiency confirmation unit 129 sends the paper cup digital twin and a functional label indicating "cut" to the function assignment unit 127. The function assignment unit 127 can assign a functional label indicating "cut" to the paper cup digital twin.

[5. Utilizing function implementation]
This section describes the use of the functional implementations according to the present disclosure.

The function implementation system 100 can add various function scripts to the digital twin. For example, the function implementation system 100 can automatically generate a digital twin of a knife that can "cut" other objects in a virtual space from an image of a knife.

The function implementation system 100 can impart a script for reproducing antenna FB (Feedback) to the digital twin. For example, the function implementation system 100 automatically generates an egg digital twin from an image of an egg in which the strength of the force returning to the tactile glove changes before and after the egg cracks. The function implementation system 100 can obtain a function program whose key is a material attribute and whose value is tactile feedback from the function database 131. By imparting such a function program to the egg digital twin, the function implementation system 100 can automatically impart the antenna FB function to the egg digital twin.

The function implementation system 100 can automatically set the friction coefficient. For example, an administrator of the function implementation system 100 measures the friction coefficient for each material in advance. The measured friction coefficient is stored in the function database 131. The function implementation system 100 can automatically set the friction coefficient in the digital twin (e.g., 3D mesh) based on the material label.

6. Function implementation flow chart
Next, a flowchart of an example of function implementation according to the present disclosure will be described with reference to Fig. 8. The example of function implementation includes a process for creating a digital object in which a function is implemented. The process for creating a digital object in which a function is implemented is performed by, for example, the function implementation system 100 of Fig. 3.

Figure 8 is a flowchart showing process P100, which is an example of a process for creating a digital object with implemented functionality.

As shown in FIG. 8, first, the function storage unit 122 of the function implementation system 100 receives various function programs from a developer (step S101).

Next, the function storage unit 122 stores the various function programs in the function database 131 of the function implementation system 100 (step S102).

Next, the image receiving unit 123 of the function implementation system 100 receives an image of the object from the user (step S103).

Next, the 3D mesh generation unit 124 of the function implementation system 100 generates a digital twin of the object from the received image (step S104).

Next, the function estimation unit 125 of the function implementation system 100 estimates the function of the generated digital twin based on the shape of the generated digital twin (step S105).

Next, the function granting unit 127 of the function implementation system 100 retrieves a function program corresponding to the estimated function from the function database 131 (step S106).

Next, the function assignment unit 127 assigns the acquired function program to the generated digital twin (step S107).

7. Effects
As described above, the function implementation system 100 can automate the implementation for digitally reproducing the functions of an object. As a result, the function implementation system 100 can reduce the cost of creating a digital twin to which functions are assigned. Furthermore, the function implementation system 100 can automatically assign to the digital twin functions that cannot be reproduced by applying attribute information of the digital twin to a commercially available physics calculation engine.

[8. Other]
A portion of a process described as being performed automatically may be performed manually. Alternatively, all or a portion of a process described as being performed manually may be performed automatically in a known manner. Furthermore, information including the procedure, specific names, various data, and parameters of the processes shown in this specification and drawings may be changed arbitrarily unless otherwise specified. For example, various information shown in each drawing is not limited to the illustrated information.

The components of the illustrated systems and devices conceptually represent the functions of the systems and devices. The components are not necessarily physically configured as shown in the drawings. In other words, the specific form of the distributed or integrated systems and devices is not limited to the form of the systems and devices shown in the drawings. All or part of the systems and devices may be functionally or physically distributed or integrated depending on various loads and usage conditions.

9. Hardware Configuration
9 is a diagram showing an example of a hardware configuration of a computer 1000. The systems and methods described in this specification are implemented by, for example, the computer 1000 shown in FIG.

Figure 9 shows an example of a computer in which a function implementation system 100 is implemented by executing a program. The computer 1000 has, for example, a memory 1010 and a CPU 1020. The computer 1000 also has a hard disk drive interface 1030, a disk drive interface 1040, a serial port interface 1050, a video adapter 1060, and a network interface 1070. Each of these components is connected by a bus 1080.

The memory 1010 includes a ROM (Read Only Memory) 1011 and a RAM 1012. The ROM 1011 stores a boot program such as a BIOS (Basic Input Output System). The hard disk drive interface 1030 is connected to a hard disk drive 1090. The disk drive interface 1040 is connected to a disk drive 1100. A removable storage medium such as a magnetic disk or optical disk is inserted into the disk drive 1100. The serial port interface 1050 is connected to a mouse 1110 and a keyboard 1120, for example. The video adapter 1060 is connected to a display 1130, for example.

The hard disk drive 1090 stores, for example, an OS 1091, an application program 1092, a program module 1093, and program data 1094. That is, a program that defines each process of the function implementation system 100 is implemented as a program module 1093 in which code executable by the computer 1000 is written. The program module 1093 is stored, for example, in the hard disk drive 1090. For example, a program module 1093 for executing a process similar to the functional configuration in the function implementation system 100 is stored in the hard disk drive 1090. The hard disk drive 1090 may be replaced by an SSD (Solid State Drive).

The hard disk drive 1090 can store a function-enabling program for implementing the function. The function-enabling program can also be created as a program product. When executed, the program product performs one or more methods, such as those described above.

In addition, the setting data used in the processing of the above-described embodiment is stored as program data 1094, for example, in memory 1010 or hard disk drive 1090. Then, the CPU 1020 reads out the program module 1093 or program data 1094 stored in memory 1010 or hard disk drive 1090 into RAM 1012 as necessary and executes it.

Note that the program module 1093 and the program data 1094 are not limited to being stored in the hard disk drive 1090, but may be stored in, for example, a removable storage medium and read by the CPU 1020 via the disk drive 1100 or the like. Alternatively, the program module 1093 and the program data 1094 may be stored in another computer connected via a network (LAN, WAN, etc.). The program module 1093 and the program data 1094 may then be read by the CPU 1020 from the other computer via the network interface 1070.

10. Summary of the embodiment
As described above, the function implementation system 100 according to the present disclosure includes the function imparting unit 127. In at least one embodiment, the function imparting unit 127 acquires a digital object generated by digitizing a physical object and data indicating a function of the digital object. Then, the function imparting unit 127 acquires a program that digitally reproduces the function of the digital object from the function database 131, and imparts the acquired program to the digital object.

As described above, the function implementation system 100 according to the present disclosure includes a function storage unit 122. In at least one embodiment, the function storage unit 122 receives one or more programs that digitally reproduce a function of an object, and stores the one or more programs in the function database 131. In some embodiments, the function granting unit 127 acquires a program that digitally reproduces a function of a digital object from among the one or more programs stored in the function database 131.

In some embodiments, the function storage unit 122 associates one or more programs that digitally reproduce a function of an object with one or more labels that respectively indicate one or more functions reproduced by the one or more programs, and stores the one or more programs associated with the one or more labels in the function database 131. In some embodiments, the function assignment unit 127 identifies a label that corresponds to the function of the digital object from among one or more labels stored in the function database 131, and assigns the program associated with the identified label to the digital object.

As described above, the function implementation system 100 according to the present disclosure includes a 3D mesh generator 124. In at least one embodiment, the 3D mesh generator 124 generates a digital object corresponding to an object depicted in an image by digitizing the shape of the object depicted in the image. In some embodiments, the function imparting unit 127 acquires the digital object generated by the 3D mesh generator 124 as a digital object generated by digitizing a physical object.

As described above, the function implementation system 100 according to the present disclosure includes a function estimation unit 125. In at least one embodiment, the function estimation unit 125 estimates a function of an object depicted in an image based on the shape of the digital object generated by the 3D mesh generation unit 124. In some embodiments, the function assignment unit 127 acquires data indicating the function estimated by the function estimation unit 125 as data indicating the function of the digital object.

As described above, the function implementation system 100 according to the present disclosure includes a function deficiency confirmation unit 129. In at least one embodiment, when the function of a digital object is a function that affects another physical object, another digital object generated by digitizing the other physical object is obtained, and the function of the other digital object is identified as a function that is affected by the digital object.

Various embodiments have been described in detail herein with reference to the drawings, but these are merely examples and are not intended to limit the present invention to these embodiments. The features described herein can be realized in a variety of ways, including various modifications and improvements based on the knowledge of those skilled in the art.

In addition, the above-mentioned "module (-er suffix, -or suffix)" can be read as a unit, a means, a circuit, etc. For example, a communication module, a control module, and a storage module can be read as a communication unit, a control unit, and a storage unit, respectively.

REFERENCE SIGNS LIST 1 Environment 100 Function implementation system 110 Communication unit 120 Control unit 121 Function management unit 122 Function storage unit 123 Image receiving unit 124 3D mesh generating unit 125 Function estimation unit 126 Material estimation unit 127 Function provision unit 128 DT management unit 129 Function deficiency confirmation unit 130 Storage unit 131 Function database 200 Network 300 User device

Claims (6)

a receiving unit for receiving one or more programs for digitally reproducing a function of an object, the one or more programs having been previously created and applied to one or more digital objects generated by digitizing one or more physical objects;
an associating unit that associates the one or more programs with one or more labels that respectively indicate one or more functions reproduced by the one or more programs;
a storage unit configured to store the one or more programs associated with the one or more labels in a predetermined storage device;
an acquisition unit that acquires a new digital object generated by digitizing a new physical object and data indicative of a function of the new digital object;
an identification unit that identifies a label corresponding to a function of the new digital object from among the one or more labels stored in the predetermined storage device;
and an assigning unit that assigns a program associated with the identified label to the new digital object. A generating unit is further provided for generating a digital object corresponding to an object depicted in an image by digitizing a shape of the object depicted in the image,
The function imparting device according to claim 1 , wherein the acquisition unit acquires the digital object generated by the generation unit as the new digital object generated by digitizing a new physical object. An estimation unit that estimates a function of the object depicted in the image based on a shape of the new digital object generated by the generation unit,
The function imparting device according to claim 2 , wherein the acquisition unit acquires data indicating the function estimated by the estimation unit as the data indicating the function of the new digital object. The function-granting device of any one of claims 1 to 3, further comprising an identification unit that, when the function of the new digital object is a function that affects another physical object, acquires another digital object generated by digitizing the other physical object, and identifies the function of the other digital object as a function that is influenced by the new digital object. 1. A computer-implemented method for providing functionality, comprising:
a receiving unit for receiving one or more programs for digitally reproducing a function of an object, the one or more programs having been previously created and applied to one or more digital objects generated by digitizing one or more physical objects;
an associating step of associating said one or more programs with one or more labels, each of said labels indicating one or more functions reproduced by said one or more programs;
a storing step of storing the one or more programs associated with the one or more labels in a predetermined storage device;
acquiring a new digital object generated by digitizing a new physical object and data indicative of a function of said new digital object;
an identification unit that identifies a label corresponding to a function of the new digital object from among the one or more labels stored in the predetermined storage device;
and an assigning step of assigning a program associated with the identified label to the new digital object. A function-imparting program for causing a computer to function as the function-imparting device according to any one of claims 1 to 4 .

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