KR102177289B1 - Simulating method of 3D moedels in factory using drones - Google Patents

Abstract

The present invention relates to a three-dimensional factory model describing method using a drone. The method includes: (a) a step wherein at least one drone (100) collects boundary data of a factory through early flight; (b) a step wherein a control part (200) determines a factory space by determining the boundary of the factory through analysis on the boundary data, and divides the determined factory space in accordance with a predetermined method; (c) a step wherein the at least one drone (100) is placed in each divided factory space and collects exploration data including size, shape, and position of an object through primary flight; (d) a step wherein the control part (200) determines the size, shape, and position of the object by analyzing the exploration data; (e) a step wherein the at least one drone (100) is placed in each divided factory space to collect precise data including images of each object through secondary flight flying over each object one by one; (f) a step wherein the control part (f) individually describes three-dimensional models of each object by using the precise data and the exploration data; and (g) a step wherein the control part (200) describes a three-dimensional factory model by connecting the individually described three-dimensional models of each object through a predetermined method. Therefore, the present invention is capable of preventing drones from being unnecessarily placed by placing drones considering the size of a factory.

Description

Simulating method of 3D moedels in factory using drones

The present invention relates to a method for describing a 3D model of a factory using a drone. Specifically, it relates to a method for the control unit to describe a 3D model of each object using the exploration data and precision data generated by the drone flying over the industrial site and, based on this, to describe the 3D model of the factory.

In order to understand and predict a large factory at a glance, you need a virtual factory that can describe the same factory. The virtual factory consists of 3D models, which are necessary to increase the consistency and intuition between the real factory and the virtual factory.

There was a problem in that the diffusion of simulation was limited due to the large demands of manpower, time, and resources in the way that humans directly perform programming, interviews, and data research to obtain 3D models.

For example, Korean Patent Publication No. 10-2014-0087533 relates to a simulation system, and more specifically, to a manufacturing facility simulation system. A virtual factory capable of implementing a continuous process can be built by modeling an actual facility as each virtual facility, and combining each virtual facility, but it has to be modeled by direct programming, so there is a big problem in manpower, time, and resources.

For example, Korean Patent Document No. 10-1873289 relates to a 3D simulation and monitoring system and method for manufacturing process management of an offshore plant, the step of mapping with 3D design data, the processor being the update data And storing the 3D design data in an integrated database, and the processor describing a 3D simulation model based on the 3D design data and the updated data. However, since the model must be directly programmed and modeled, manpower and time , There is a big problem with resources, etc.

(Patent Document 1) Korean Patent Publication No. 10-2014-0087533

(Patent Document 2) Korean Patent Document No. 10-1873289

The present invention was devised to solve the above problems.

Specifically, it is for 3D modeling in the factory by minimizing the time and cost required for 3D modeling.

This is to easily create images and data necessary for 3D modeling using a drone.

This is to minimize errors in the manufacturing process of 3D modeling.

An embodiment of the present invention for solving the above problems,

It is a method of simulating a 3D model of a factory by using a drone that can collect boundary data, exploration data, and precision data that includes a photographing device and a sensor, and (a) one or more drones 100 are initially Collecting the boundary data of the factory by flying; (b) The control unit 200 analyzes the boundary data to determine the boundary of the factory to determine the factory space, and divides the determined factory space according to a predetermined method. (C) collecting search data including the size, shape, and location of the object by placing the at least one drone 100 in each of the divided factory spaces and making a primary flight; (d) the control unit (200) analyzing the search data to determine the size, shape, and position of the object; (e) the one or more drones 100 are disposed in each of the divided factory spaces, and each object is Collecting precision data including an image of each object by performing a second flight flying one by one; (f) The control unit 200 uses the search data and the precision data to describe each 3D model of each object. step; And (g) describing the factory 3D model by connecting the 3D models of the objects depicted by the control unit 200 in a predetermined manner; including, in step (g), (g1) the control unit ( 200) arranging the 3D models to be connected to each other for each object that is the search data determined in step (c); And (g2) describing, by the control unit 200, the 3D model of the factory using the result of the step (g1). It relates to a method of depicting a 3D model of a factory using a drone including.

In addition, in the step (c), the search data further includes an object connection method, which is a method in which objects are connected to each other in a serial method 311 or a parallel method 312, and in step (d), the control unit It is preferable that the step 200 is a step of determining the size, shape and position of the object, and a connection method of the object using the search data.

In addition, in step (g), (g3) the control unit 200 uses the precision data to determine the type of the object as a first object 301 that is assembled by entering a product, and a first object that is disassembled by entering the product. The step of determining any one of the second object 302 and the third object 303 processed by entering the product; further comprising, in the step (g1), the control unit 200 determines that the step (g3) It is preferable that it is a step of arranging each depicted 3D model to be connected to each other as the type of object and the connection method of the object.

In addition, in the step (g), (g4) the control unit 200 analyzes the type of the object determined in step (g3) and the connection method of the object using the precision data, Comparing with the factory 3D model; (g5) determining, by the control unit 200, the type of the object of the depicted factory 3D model and a connection method of the objects that are different from the actual factory model in step (g4); (g6) the control unit 200 re-collecting one or more of the types of objects that differ from the actual factory model, the object connection method, and describing the corrected 3D model; And (g7) arranging, by the control unit 200, the modified 3D model to be connected to the depicted factory 3D model.

In addition, in step (g8), it is preferable that the control unit 200 further comprises a step of removing the type of the object having the difference from the actual factory model and the connection method of the object from the depicted factory 3D model.

In addition, the step (b) is preferably a step of dividing the factory space into the same area by the number of the drones 100 by the control unit 200.

In addition, in step (e), it is preferable that the secondary flight is to rotate one object by 360 degrees, then move to another object, and then fly in a manner of rotating the other object by 360 degrees.

The method according to the invention,

By deploying drones in consideration of the size of the factory, unnecessary drone deployment can be prevented.

It is possible to easily create data and images necessary for 3D modeling by using ultrasonic waves, infrared rays and image capturing that the drones fly and irradiate in 3D.

Drones can generate exploration data and precision data for objects in the factory and convert them into a 3D model based on 3 dimensions.

The control unit can describe the virtual model in such a way that the 3D frame of the object is overlaid on the image of each object.

Errors in the manufacturing process of 3D modeling can be minimized, including the process of comparing the depicted 3D model with the actual factory model.

1 is a diagram illustrating a method of depicting a 3D model according to the present invention.
2 is a diagram showing a process of generating boundary data by flying a drone.
3 is a diagram illustrating a process of generating search data by flying a drone.
4 is a diagram illustrating a process of generating search data by flying a drone.
5 is a diagram showing an object according to the present invention.
6 is a diagram showing a 3D model of a depicted virtual factory according to the present invention.

"Drone" refers to an object that can move while flying in the X, Y, and Z axes, and is not limited to a specific product.

"Factory" refers to a space where a workbench, equipment, conveyor belt, etc. are located and products are manufactured, and is not limited to any specific factory, and the present invention can be applied to all industrial sites including factories.

"Object" refers to a machine or device in which a process is performed, including all worktables, facilities, and conveyor belts, and a number of processes such as assembly, processing, disassembly, and chemical processes can be performed. It is not limited.

The “control unit” refers to a device, program, or central server capable of processing and calculating a plurality of data such as boundary data, search data, and precision data collected by the drone 100.

Hereinafter, the present invention will be described in more detail with reference to the drawings.

1. A step in which one or more drones 100 initially fly to collect factory boundary data

1 is a diagram illustrating depicting a 3D model of a factory through the following process.

In order to describe the 3D model of the factory, the drone 100 must be placed in the factory, and at this time, the number of drones 100 to be deployed in the factory becomes a problem.

The number of drones 100 may be determined in consideration of the area of the factory. According to the size of the factory, the number of drones 100 required to form a 3D model in the factory may be different. In addition, as the number of drones 100 increases, the speed of depicting the 3D model per the same factory area increases, and the number of drones 100 may be determined in consideration of this. In consideration of factors required to describe the 3D model in the factory in addition to the factory area and the speed of description, the number of drones 100 may be preset to one or more.

At least one drone 100 generates boundary data of each factory. Boundary data refers to the total perimeter and area within the factory, and is generated based on the inner wall that forms the perimeter of the factory.

In order to collect boundary data, one or more drones 100 are spread radially from the center of the factory, and start initial flight. When each drone 100 is spread radially and moves in different directions and is located at a certain distance from the inner wall, each drone 100 can move along different inner walls while moving in the same direction along the inner wall. . Each of the drones 100 may generate boundary data for a perimeter and an area directly moved along an inner wall, respectively. At this time, depending on the shape of the factory, each drone 100 may move the same perimeter and area, but is not limited thereto.

For example, Figures 2(a) and (b) show that the number of drones 100 is two. The two drones 100 form an angle of 180 degrees to each other and start flying in different directions, then move in the same direction along the inner wall of the factory, and can move the perimeter and area of the inner wall of the factory at different locations. . Each drone 100 may move along the inner wall of the factory to generate boundary data for each. That is, each drone 100 generates boundary data corresponding to the perimeter and half of the area of the factory, respectively.

In addition, for example, Figures 2(c) and (d) show that the number of drones 100 is three. The three drones 100 form an angle of 120 degrees to each other and start flying in different directions. Each drone 100 generates boundary data corresponding to a third of the perimeter and area of the factory, respectively.

In this case, a real-time position sensor and a distance measurement sensor may be attached to the drone 100. The drone 100 may generate boundary data on the perimeter and area of the factory by irradiating ultrasonic waves and lasers while flying over the inner wall of the factory.

Each of the drones 100 may transmit each generated boundary data to the control unit 200, and the control unit 200 may receive the respective boundary data generated by the drone 100.

2. The step of dividing the factory space by analyzing the boundary data by the control unit 200

The controller 200 may determine the area and perimeter of the entire factory by synthesizing each boundary data transmitted from each of the drones 100.

The control unit 200 may divide the factory space by analyzing the boundary data. In this case, the control unit 200 may divide the factory space according to the number of drones 100. For example, when the number of drones 100 is three, the control unit 200 may divide the factory space into three. The control unit 200 may divide the space into an equal area per drone 100 according to the number of drones 100, but is not limited thereto.

For example, the control unit 200 may not arrange the factory space in the same area according to the arrangement of objects located in the factory. When one object is separated into different spaces and is searched by each drone 100, a separate procedure may be required, such as synthesizing each of the 3D models depicted thereafter. Thus, in this case, the space can be divided so that one object is not separated.

In addition, for example, when the number of objects located in a corresponding area or the object is made of a plurality of parts, the speed of describing the 3D model may increase for each space. In this case, the area of the space allocated to the drone 100 flying the space can be divided into a small amount.

3. At least one drone 100 is disposed in each divided factory space, and the first flight is performed to collect search data / the control unit 200 analyzes the search data

The drone 100 is disposed in each divided space to make a primary flight. The drone 100 flies and collects search data on the size, shape, and location of objects located in each space.

At this time, the primary flight means flying while moving a number of objects.

The exploration data is data for generating a 3D model along with the precision data thereafter, so that the approximate size and shape of the object to be 3D modeled can be identified.

The controller 200 may determine where the object is located using the search data, and then place the drone 100 in consideration of this for precise photographing. In addition, the control unit 200 may perform a task of generating a dummy of objects using the search data, but is not limited thereto, and the control unit 200 may generate a dummy of objects through precision data to be described later. have.

3 is a diagram showing that one or more drones 100 are arranged for each divided space to perform primary flight. In FIG. 3(a), two drones 100 move up and down, left and right, and FIG. 3(b) is a diagram showing three drones 100 move up and down, left and right.

4 is a diagram illustrating that the drone 100 searches for each object while moving.

The drone 100 may search for a location of an object using a real-time position sensor and a distance measurement sensor, search for a shape and size of the object, and generate search data. By irradiating ultrasonic waves and lasers, an empty space and a space in which the object is located can be distinguished, and the shape and size of the object can be searched by recognizing the distal vertices of the object, but is not limited thereto.

In this case, the distance measuring sensor may mean a sensor that generates ultrasonic waves that are generally used, but is not limited thereto. The drone 100 may generate search data by photographing an object.

The controller 200 may aggregate and collect search data for the size and shape of each object to which the products generated by each drone 100 are processed.

5 is a diagram for explaining a connection method of objects 301, 302, and 303, and is not limited to the illustrated object arrangement method and object type.

At this time, the type of object is the first object 301 that the product enters and is assembled, the second object 302 that the product enters and disassembles, the third object 303 that the product enters and processes, and between the objects. It includes a fourth object 304 that connects, that is, acts like a conveyor belt, but this is only an example of a process, and any process that can be performed in factories and industrial sites is not limited to the above type.

Each of the first object 301, the second object 302, and the third object 303 does not mean that they all go through the same process, but each process that can be included in the processes of assembling, disassembling and processing It can contain all, and products of different targets can enter. That is, even with the same third objects 303A, 303B, 303C, 303B, 303C, and 303F, the method of being assembled and the object being assembled may be different. For example, the third object 303A may perform a painting operation during the processing process, and the third object 303B may perform a heating operation during the processing process.

In addition, the drone 100 may further search for a connection method between objects. The connection method of the objects may include a serial method in which the number of objects does not change before and after the fourth object 304 is sequentially connected, and a parallel method in which the number of objects is changed before and after the fourth object 304 is connected. .

In Fig. 5(a), two third objects 303A and 303B are connected by the fourth object 304B, and the third object 303A is connected to the fourth object 304A before that. . All of the objects before and after the fourth object 304B are shown as one bar, which is a serial method 311.

In this case, the third objects 303A and 303B all refer to a processing process and may be in the same manner, but are not limited thereto, and may mean different processing processes as described above.

In FIG. 5(b), the second object 302 before the fourth object 304D is connected to the fourth object 304E and 304F after the fourth object 304D, and the parallel method 312 is shown.

In FIG. 5C, the fourth object 304I and 304J before the fourth object 304K and the first object 301 after the fourth object 304K are connected to each other in a parallel manner 312.

4. At least one drone 100 is arranged for each of the divided spaces to make a secondary flight, and collects precise data captured for each object / the control unit 200 describes each 3D model of the object

When the control unit 200 collects the search data, the drone 100 photographs an object included in the generated search data.

At this time, as described above, each of the drones 100 may divide the space into an equal area per drone 100 according to the number of drones 100, but the limitation is no.

For example, when the number of objects located in a corresponding area or an object is made of a large number of parts, the speed of describing the 3D model may increase for each space. In this case, the area of the space allocated to the drone 100 flying the space can be divided into a small amount.

The drone 100 precisely photographs an object and generates precise data.

Secondary flight refers to a method in which the drone 100 rotates one object 360 degrees and flies, then moves to another object and rotates 360 degrees when the drone 100 flies an object. The drone 100 may collect precision data for each object by rotating one object by 360 degrees and taking countless images of the object.

Fig. 6(a) shows depicting a 3D model from a captured image.

The control unit 200 may create a 3D model by using the precision data photographed and described by the drone 100 to overlay a 3D frame on each of the precision data.

In this case, the process of performing 3D modeling through an image is a well-known technique, and other detailed descriptions will be omitted.

5. The step of describing the factory 3D model by connecting the 3D model of the object depicted by the control unit 200 in a predetermined manner

The control unit 200 may arrange each object so that the depicted 3D models are connected to each other.

The control unit 200 may arrange 3D models each depicted so that all objects are connected to each other by using search data and precision data on the size, shape and position of the object and the connection method of the objects.

In this case, the control unit 200 may determine the type of object that is different from the actual factory model and the depicted factory 3D model, and a connection method of the objects.

The control unit 200 further comprises the step of re-collecting at least one of the described 3D model and the type of object that has the difference, and any one or more of the object connection method to describe the corrected 3D model, and comparing it with the actual factory model. I can. The control unit 200 may further include arranging the modified 3D model to be connected to the depicted factory 3D model, thereby describing a 3D model that matches the actual factory model.

Fig. 6(b) is a diagram showing a 3D model of a factory by arranging each depicted 3D model.

In the above, the present specification has been described with reference to the embodiments shown in the drawings so that those skilled in the art can easily understand and reproduce the present invention, but this is only exemplary, and those skilled in the art can use various modifications and equivalents from the embodiments of the present invention. It will be appreciated that embodiments are possible. Therefore, the scope of protection of the present invention should be determined by the claims.

100: drone
200: control unit
301: first object
302: second object
303, 303A, 303B, 303C, 303D, 303E, 303F: third object
304, 304A, 304B, 304C, 304D, 304E, 304F, 303G, 303H, 303I, 303J, 303K: fourth object
311: serial method
312: parallel method

Claims (7)

As a method of simulating a 3D model of a factory using a drone that includes an imaging device and a sensor and can collect boundary data, exploration data, and precision data,
(a) at least one drone 100 is initially flying to collect boundary data of the factory;
(b) determining the factory space by analyzing the boundary data and determining the boundary of the factory by the control unit 200, and dividing the determined factory space according to a predetermined method;
(c) collecting search data including the size, shape, and location of the object by first flying the one or more drones 100 respectively disposed in the divided factory spaces;
(d) determining, by the controller 200, the size, shape, and position of the object by analyzing the search data;
(e) the one or more drones 100 are disposed in each of the divided factory spaces to perform a secondary flight of flying each object one by one to collect precise data including images of each object;
(f) describing, by the control unit 200, a 3D model of each object using the search data and the precision data, respectively; And
(g) the control unit 200 connecting the 3D models of the objects each depicted in a predetermined manner to describe the factory 3D model; includes,
In step (g),
(g1) arranging the control unit 200 to connect each of the 3D models described in step (f) to each other; And
(g2) the control unit 200 depicting the factory 3D model using the result of the (g1) step; Including,
In step (c),
The search data further includes a connection method of objects, which is a method in which objects are connected to each other in a serial method 311 or a parallel method 312,
The step (d),
Determining, by the control unit 200, the size, shape and position of the object, and a connection method of the object, using the search data,
After the step (f) and before the step (g1),
The control unit 200 uses the precision data to determine the type of the object as a first object 301 that is assembled by entering the product, a second object 302 that is disassembled by entering the product, and The step of determining any one of the third objects 303; further includes,
The (g1) step,
Arranging, by the control unit 200, a type of the determined object and a connection method of the determined object, so that each of the 3D models described in step (f) are connected to each other; including,
A method of describing a 3D model of a factory using a drone.
delete delete The method of claim 1,
In step (g),
(g3) analyzing, by the control unit 200, the type of the determined object and the connection method of the object using the precision data, and comparing the actual factory model with the depicted factory 3D model;
(g4) determining, by the control unit 200, a type of an object of the depicted factory 3D model and a connection method of the objects that are different from the actual factory model in step (g3);
(g5) the control unit 200 re-collects one or more of the types of objects that have the difference from the actual factory model and the object connection method to describe the corrected 3D model; And
(g6) arranging, by the control unit 200, the modified 3D model to be connected to the depicted factory 3D model; including,
A method of describing a 3D model of a factory using a drone.
The method of claim 4,
In step (g),
(g7) further comprising the step of removing, by the control unit 200, the type of the object having the difference from the actual factory model and the connection method of the object from the depicted factory 3D model,
How to describe a 3D model of a factory using a drone.
The method of claim 1,
The step (b),
The control unit 200 is a step of dividing the factory space into the same area by the number of the drones 100,
How to describe a 3D model of a factory using a drone.
The method of claim 1,
In step (e),
The secondary flight is to fly in a manner of rotating one object 360 degrees and then moving to another object and rotating the other object 360 degrees,
How to describe a 3D model of a factory using a drone.

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