KR20210128579A - Pallet moving robot and method for moving pallet using the same - Google Patents

Abstract

In a logistics transport robot and a logistics transport method using the same, the logistics transport robot includes a sensor unit, a processing unit, an output unit, and a driving unit. The sensor unit includes a 3D lidar for measuring the surrounding yard, containers and pallets, and a stereoscopic camera for photographing in close proximity to the pallet. The processing unit includes a mapping unit that maps the positions of the structure of the yard, the container and the pallet based on the measurement information of the 3D lidar, and a learning unit that specifies the pallet based on the photographing information of the stereoscopic camera. The output unit outputs a path to the pallet based on the mapping result and the specified pallet information. The driving unit automatically drives the logistics transport robot along the output path. An object of the present invention is to provide the logistics transport robot that can reduce the time for loading and unloading as well as saving labor costs by performing loading or unloading by unmanned driving of pallets in containers.

Description

Logistics transport robot and logistics transport method using the same

The present invention relates to a logistics transport robot and a logistics transport method using the same, and more particularly, to a logistics transport robot capable of performing loading or unloading by unmanned driving of a pallet in a container and a logistics transport method using the same.

1 is a schematic diagram illustrating a state in which the logistics transfer device 2 according to the prior art loads or unloads a pallet (not shown) into the container 1 .

In the case of loading or unloading pallets using such a conventional logistics transport robot, a separate transport device 3 for moving the pallet within the container 1 as well as a driver driving the logistics transport robot is required. An operator was needed to do this.

Accordingly, there is a problem that not only increases the cost due to the employment of the driver or operator, but also increases the up-and-down time due to the inexperience of the driver or the operator.

Accordingly, various systems have been developed for automatically performing vertical loading and unloading of logistics to such containers, and Korean Patent Laid-Open No. 10-2019-0066990 discloses a technology related to an automatic pallet loading and unloading device.

However, the disclosed technology is merely a technology for transferring a pallet to the inside of a container or taking it out to the outside using a transfer module, and a technology related to unmanned driving or unmanned operation of a logistics transport robot that actually loads and unloads pallets into a container has not yet been developed.

Republic of Korea Patent Registration No. 10-2019-0066990

Accordingly, the technical problem of the present invention was conceived in this regard, and the object of the present invention is to perform loading or unloading by unmanned driving of pallets in containers, thereby reducing the time of loading and unloading as well as saving labor costs. will provide

In addition, another object of the present invention is to provide a logistics transport method using the logistics transport robot.

Logistics transport robot according to an embodiment for realizing the object of the present invention includes a sensor unit, a processing unit, an output unit and a driving unit. The sensor unit includes a 3D lidar for measuring the surrounding yard, containers and pallets, and a stereoscopic camera for photographing in close proximity to the pallet. The processing unit includes a mapping unit that maps the structure of the yard, the positions of the container and the pallet based on the measurement information of the 3D rider, and a learning unit that specifies the pallet based on the shooting information of the stereoscopic camera . The output unit outputs a path to the pallet based on the mapping result and the specified pallet information. The driving unit automatically drives the logistics transfer robot along the output path.

In an embodiment, the sensor unit may further include a collision sensor for detecting a collision between the logistics transport robot and the container, and a gap sensor for sensing a distance between the logistics transport robot and a side surface of the container. .

In one embodiment, the gap sensor is provided on the side frame of the logistics transport robot, and when the pallet is loaded and unloaded on the container, it is possible to sense a gap between the logistics transport robot and the side of the container.

In an embodiment, the mapping unit may map the 3D lidar's measurement information using simultaneous localization and mapping (SLAM).

In an embodiment, the processing unit may further include a database for storing information on the pre-fabricated pallets.

In an embodiment, the learning unit may specify a pallet corresponding to the captured pallet from among the pallets stored in the database by performing deep learning based on the shooting information of the stereoscopic camera.

In one embodiment, the output unit calculates a path close to the pallet based on the mapping result, and up to the specified pallet for pickup of the specified pallet based on the coordinate value of the specified pallet. It may include a path calculating unit for additionally calculating the path.

In an embodiment, the coordinate values may include corner coordinates of the front part of the pallet, and corner coordinates of each of the openings formed in the front part of the pallet.

In an embodiment, the output unit may include an output unit for outputting a mapping result of the mapping unit and a path calculation result of the path calculating unit.

In one embodiment, the logistics transport robot, a body portion, a side frame extending to the side of the body portion, a loading portion extending to the front end of the body portion to pick up a pallet, and vertical extending in the upper direction from the front end of the body portion Including a frame, the 3D rider is provided on the upper portion of the vertical frame, the stereoscopic camera may be provided at the front end of the body portion.

In the logistics transport method according to an embodiment for realizing another object of the present invention, the structure of the yard, the position of the container and the pallet are mapped based on the information measured by the 3D lidar. The logistics transfer robot moves to approach the pallet. The adjacent pallet is photographed with a stereoscopic camera. Based on the shooting information, the learning unit specifies the pallet. A path for picking up the pallet is calculated based on the mapping result and the specific pallet information. The logistics transport robot is automatically driven along the path to pick up the pallet and load it up and down.

In one embodiment, in the step of loading and unloading the pallet, based on the sensing result of the gap sensor, the pallet may be vertically loaded while maintaining a gap between the logistics transfer robot and the side of the container.

In an embodiment, in the step of specifying the pallet, learning may be performed based on the photographing information of the adjacent pallet, and the pallet corresponding to the photographed pallet may be specified from a database in which information of pre-fabricated pallets is stored. .

In one embodiment, in the step of calculating the path, a path to the specified pallet for pickup of the specified pallet may be calculated based on the coordinate value of the specified pallet.

According to the embodiments of the present invention, the conventional logistics transfer robot that manually manipulates the operator to perform vertical loading and unloading of pallets is automatically driven based on the sensing result to perform vertical loading and unloading of pallets, which is required for vertical loading and unloading of logistics It is possible to reduce the time it takes and save labor costs, and build an unmanned logistics transport system.

In this case, the overall map is derived by SLAM mapping based on the information measured by the 3D rider, but it is difficult to derive the path for detailed pallet up and down using only SLAM mapping. Since the movement path is calculated from the information of

In particular, since there are various types of pallets, it is difficult to specify the size or exact position only with information photographed with a camera. By specifying the same pallet as the pallet, the shape, size and structure of the corresponding pallet can be derived.

Furthermore, for the pallet specified as described above, by accurately deriving the position of the opening for pickup based on the coordinates of the side and the corner of the opening, the logistics transport robot can automatically pick up the pallet accurately.

On the other hand, even if the pick-up of the pallet is correct, a collision with the container may occur when the actual pallet is vertically loaded. By inducing the pallet to be loaded and unloaded while maintaining a constant distance between the side of the container and the logistics transfer robot, it is possible to perform vertical loading and unloading of the pallet in parallel along the extension direction of the side of the container.

1 is a schematic diagram showing a vertical state of a pallet using a logistics transfer device according to the prior art.
Figure 2 is a perspective view showing a logistics transfer robot according to an embodiment of the present invention.
3 is a block diagram illustrating the logistics transfer robot of FIG. 2 .
4 is a flowchart illustrating a logistics transport method using the logistics transport robot of FIG. 2 .
Figure 5 is an image of the yard map in the step of mapping with the 3D lidar of Figure 4, and Figure 6 is the 3D mapping of the yard structure, the position of the container and the pallet in the mapping step with the 3D lidar of Figure 4 An image representing the result.
7 is an image showing the result of photographing the pallet with the stereoscopic camera of FIG.
FIG. 8 is an image showing the result of extracting the coordinate values of the specified pallet of FIG. 4 .
9 is an example of an output image used in the step of vertical loading along the edge of the container of FIG. 4 .

Since the present invention may have various changes and may have various forms, embodiments will be described in detail in the text. However, this is not intended to limit the present invention to the specific disclosed form, it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention. In describing each figure, like reference numerals have been used for like elements. Terms such as first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms.

The above terms are used only for the purpose of distinguishing one component from another. The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise.

In the present application, terms such as "comprises" or "consisting of" are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification is present, but one or more other features It is to be understood that it does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

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

Figure 2 is a perspective view showing a logistics transfer robot according to an embodiment of the present invention. 3 is a block diagram illustrating the logistics transfer robot of FIG. 2 . 4 is a flowchart illustrating a logistics transport method using the logistics transport robot of FIG. 2 . FIG. 5 is an image of the yard mapping in the 3D lidar mapping step of FIG. 4, and FIG. 6 is a 3D mapping of the yard structure, container and pallet positions in the 3D lidar mapping step of FIG. An image representing the result. 7 is an image showing the result of photographing the pallet with the stereoscopic camera of FIG. 8 is an image showing the result of extracting the coordinate values of the specified pallet of FIG. 9 is an example of an output image used in the step of vertical loading along the edge of the container of FIG. 4 .

Hereinafter, the logistics transfer robot according to the present embodiment and the logistics transfer method using the logistics transfer robot will be described at the same time for convenience of description.

First, referring to FIGS. 2 and 3 , the logistics transport robot 10 according to this embodiment is an autonomous driving robot that picks up pallets and loads them up and down in containers, the sensor unit 100, the processing unit 200, It includes an output unit 300 , a control unit 400 , and a robot unit 500 , wherein the sensor unit 100 includes a 3D lidar 110 , a stereoscopic camera 120 , a collision sensor 130 , and a gap sensor 140 . ), and the processing unit 200 includes a mapping unit 210 , a learning unit 220 and a database 230 , and the output unit 300 includes an output unit 310 and a path calculating unit 320 . Including, the control unit 400 includes a driving unit 410 and a display unit 420, the robot unit 500 includes a body unit 510, a manual operation unit 520, a side frame 530, vertical It includes a frame 540 and a loading unit 550 .

In particular, the robot part 500 forms the outer shape of the logistics transfer robot 10 , and the body part 510 corresponds to the center of the robot part 500 , and the manual operation part 520 is an emergency It is a part operated by the user when the situation or manual operation of the logistics transfer robot 10 is required.

In addition, the side frame 530 is formed along the side surface of the body portion 510 , and the gap sensor 140 to be described later is provided on the side frame 530 .

The loading part 550 is extended in a pair toward the front of the body part 510, and the loading part 550 has a pair of protrusions inserted into a pair of openings of the pallet, respectively, to lift the pallet. will be picked up

In this case, the stereoscopic camera 120 is positioned on the front of the body 510 to photograph the pallet positioned on the front.

The vertical frame 540 extends upward from the front of the body 510 , and the loading unit 550 moves in the vertical direction along the vertical frame 540 .

On the other hand, the 3D rider 110 is located on the upper portion of the vertical frame 540, as well as the front, it is possible to measure the periphery to the side or rear.

The driving unit 410 may be located at various positions, but may be located at the front end of the side frame 530 as shown in FIG. 2 . In addition, the collision sensor 130 is positioned on the upper surface of the driving unit 410 , and it is possible to monitor in real time whether or not the collision sensor 130 collides with a surrounding structure around the side surface of the robot unit 500 .

More specifically, referring to FIGS. 2, 3 and 4 , in the logistics transport method using the logistics transport robot 10 , first, the 3D lidar (Lidar) 110 of the logistics transport robot 10 The surrounding yard, container, and pallet 600 are measured, and the mapping unit 210 maps the structure of the yard, the position of the container and the pallet based on the measured information (step S10) .

The 3D lidar is to measure the distance, shape, structure, etc. of the surrounding object based on the change in time, intensity, frequency, etc. of the scattered or reflected laser by emitting a laser, and the like, through which the logistics transport It is possible to measure the distance, shape, structure, etc. to a specific structure in the vicinity of which the robot 10 is located.

That is, through the 3D lidar 110, the logistics transfer robot 10 is located, the structure of the yard, the position or structure of the container, and the position or structure of the pallet is measured.

The measured result is provided to the mapping unit 210, and the mapping unit 210 performs navigation on the structure and location of the surrounding yard as shown in FIG. 5 based on the measured result. In addition to deriving information, as shown in FIG. 6 , it may be derived by mapping a 3D map.

In this case, the mapping unit 210 performs mapping by, for example, simultaneous localization and mapping (SLAM), and as shown in FIGS. 5 and 6 , the structure of the yard, the container and the pallet. It can be derived by visualizing or imaging a location, etc.

Meanwhile, the mapping image derived in this way may be output to the outside through the output unit 310 .

However, the visualization results of the structure of the yard, the container and the pallet position derived through the 3D rider 110 and the mapping unit 210 in this way are limited in deriving the accurate position of the pallet relatively. there is

On the other hand, after deriving the mapping image as described above, referring to FIGS. 2, 3 and 4 , based on the result of the mapping image, the logistics transfer robot 10 moves to be close to the pallet 600 . do (step S20).

That is, the driving unit 410 moves the logistics transport robot 10 to be close to the pallet 600, and in this case, the structure of the yard around the logistics transport robot 10 derived through the mapping image, Information such as the location of containers and pallets is used.

However, as described above, the surrounding information derived from the mapping image includes insufficient information for the logistics transfer robot 10 to accurately pick up the pallet 600, so in this embodiment the procedure to follow Through this, information for accurate pickup is additionally obtained.

That is, referring to FIGS. 2, 3 and 4 , in a state where the logistics transport robot 10 is close to the pallet 600 , the stereoscopic camera 120 takes a three-dimensional image of the pallet 600 . do (step S30).

An example of the three-dimensional image of the pallet 600 photographed in this way is shown in FIG. 7 .

The logistics transfer robot 10 is to pick up the pallet 600 through the loading unit 550, for accurate pickup, as shown in FIG. 7 , the stereoscopic camera 120 is the pallet 600 ) to obtain a three-dimensional image of the front part 610 .

In this case, since the obtained image is a three-dimensional image of the front part 610 , an image of a pair of openings 620 formed in the front part 610 is also included.

Thereafter, referring to FIGS. 2, 3 and 4 , the learning unit 220 performs learning based on the photographing information photographed by the stereoscopic camera 120 to determine what kind of the photographed pallet 600 is. It is specified whether the pallet has a type, structure, shape, etc. (step S40).

In the case of a three-dimensional image taken by the actual three-dimensional camera 120, information about the shape or structure of the front part 610 and the opening 620 of the pallet 600 is included, but the precise Acquiring information such as the size, the exact distance from the logistics transfer robot 10 to the pallet 600 is limited.

Accordingly, through this step (step S40), by accurately specifying what kind of pallet the photographed pallet 600 is, the size of the pallet 600, the exact distance to the pallet 600, etc. , it is possible to accurately derive all information about the pallet 600 .

In the present embodiment, in order to specify the pallet 600, the learning unit 220 performs learning through so-called deep learning.

That is, in a state in which information on all types of pallets that have been pre-fabricated are stored in the database 230 , the learning unit 220 based on the photographed image of the pallet 600 , the database 230 . ), the same pallet as the photographed pallet 600 is selected from among the stored pallets by learning based on the information on the stored pallets, and finally the photographed pallet 600 corresponds to a certain pallet specify a.

In this case, since the learning unit 220 performs deep learning learning, it is possible to select and specify the same pallet as the photographed pallet 600 relatively quickly. An example of the pallet 600 thus specified is as shown in FIG. 8 .

In this way, when the learning unit 220 specifies the pallet, the next step is performed after fetching an image and related information for the pallet.

That is, referring to FIGS. 2, 3 and 4 , the path calculating unit 320 extracts the exact position of the pallet 600 based on the coordinate value of the specified pallet 600 (step S50). .

Since the specific pallet 600 in the learning unit 220 can obtain an image having an accurate shape and structure from the database 230, as illustrated in FIG. 8 , the path calculating unit 320 is the specific An exact position of the pallet 600 is extracted using the image of the pallet 600 .

In this case, since information such as the size of the specified pallet 600 and the length of each structure is also stored in the database 230, the path calculating unit 320 is positioned to the pallet 600 based on the information. can be extracted.

For example, the path calculating unit 320, from the image of the specified pallet 600, the outermost four corners 1, 2, 11, 12 of the front portion 610, and the front portion It is possible to obtain the coordinate values of the four corners 3 to 6 and 7 to 10 of each of the pair of openings formed in the 610, and the coordinate values obtained in this way and the actual value of the specified pallet 600 Based on the size and length information, it is possible to obtain distance and direction information from the logistics transport robot 10 to the specified pallet 600 .

In this case, it can be precisely called the distance and direction information from the loading part 550 of the logistics transfer robot 10 to the opening 620 of the pallet 600 .

On the other hand, as described above, accurate information such as the size and length of the pallet 600 can be acquired, and since the size of the container 700 is generally determined, when the pallet 600 is loaded, the container 700 ), it is possible to obtain information on the total number of pallets 600 that can be loaded, as well as information on the number of pallets 600 that can be stacked up to one layer.

Similarly, even when the pallet 600 is unloaded, information on the total number of pallets currently loaded in the container 700 and the number of pallets loaded on one floor may be acquired.

Thus, in the up-and-down step to be described later, one pallet is exemplified up and down, but when two or more pallets are up-and-down, it can be easily performed with the same procedure by additionally considering the loading information of the pallet.

Thereafter, referring to FIGS. 2, 3 and 4 , the path calculating unit 320 is based on the distance and direction information, the path from the logistics transfer robot 10 to the pallet 600, that is, the It is possible to calculate a path for picking up the pallet 600 (step S60).

In this case, the output unit 310 may output a path for pickup of the pallet 600 to the outside.

Thereafter, referring to FIGS. 2, 3 and 4 , the logistics transfer robot 10 is driven by the driving unit 410 so that the loading unit 550 moves the pallet 600 along the calculated path. is picked up (step S70).

Thereafter, the picked-up pallet 600 is loaded into the container 700 or loaded to the outside of the container 700 (step S80 ).

In this case, the step of picking up the pallet (step S70) and the step of loading and unloading into the container (step S80) will be described below separately from the step of loading and unloading.

First, in the case of carrying out the loading of the pallet 600, the loading unit 550 picks up the pallet 600 located in the yard, and then the mapping unit 210 shows the mapping result. Based on the included location information of the container 700 , the picked-up pallet 600 is moved to the container 700 .

At this time, in order to load the pallet 600 into the container 700 , it is important to maintain the pallet 600 so as not to collide with the side surface 710 of the container 700 .

Accordingly, in this embodiment, as described above, the gap between the side frame 530 of the logistics transport robot 10 and the side 710 of the container 700 is constant through the gap sensor 140 . It is sensed in real time whether or not it is maintained, and based on this, the loading is performed in a state in which the interval between the pallet 600 and the side 710 of the container 700 is maintained at a constant (preset value).

On the other hand, auxiliary, the collision sensor 130 senses whether the front and side surfaces of the logistics transport robot 10 collide with the side 710 of the container 700 in real time, and the possibility of collision is high. , information is provided to the driving unit 410 as well as informing the outside through the display unit 420 and the like, so that collision avoidance driving is possible.

Meanwhile, as an example of the result mapped through the mapping unit 210 in FIG. 9 , an image of the container 700 and the state of the pallet 600 loaded in the container 700 is illustrated.

Accordingly, when unloading the pallet 600 , as shown in FIG. 9 , based on the location information of the container 700 included in the mapping result through the mapping unit 210 , the logistics transport The robot 10 moves to the container 700 .

Thereafter, the loading unit 550 picks up the pallet 600 located inside the container 700 and performs unloading.

At this time, in order to unload the pallet 600 from the container 700 , it is important to keep the pallet 600 so as not to collide with the side surface 710 of the container 700 , as in the case of the container 700 . .

Accordingly, in this embodiment, as described above, the gap between the side frame 530 of the logistics transport robot 10 and the side 710 of the container 700 is constant through the gap sensor 140 . It is sensed in real time whether or not it is maintained, and unloading is performed in a state where the interval between the pallet 600 and the side surface 710 of the container 700 is maintained at a constant (preset value) based on this.

Thereafter, the unloaded pallet 600 is transferred to an area corresponding to the transfer destination of the pallet 600 among the surrounding yards based on the mapping result of the mapping unit 210 again.

Even in this unloading procedure, auxiliary, the collision sensor 130 senses whether the front and side surfaces of the logistics transport robot 10 collide with the side 710 of the container 700 in real time, and the possibility of collision When this is high, the display unit 420 not only informs the outside, but also provides information to the driving unit 410 to enable collision avoidance driving.

As described above, after loading or unloading of one pallet is performed, when additional pallets perform loading or unloading, as described above, the size of the container is fixed, and the size information of individual pallets is specific to the pallet. Since it is derived through, it is possible to easily obtain accurate location information for loading or unloading of two or more pallets, and through this, it is possible to easily perform automatic loading and unloading.

On the other hand, the display unit 420 is, for example, as shown in FIG. 2, is arranged adjacent to the manual operation unit 520, the driving state of the logistics transport robot 10, as well as the logistics transport method Results, etc. derived from each step can be displayed externally.

According to the embodiments of the present invention, the conventional logistics transfer robot that manually manipulates the operator to perform vertical loading and unloading of pallets is automatically driven based on the sensing result to perform vertical loading and unloading of pallets, which is required for vertical loading and unloading of logistics It is possible to reduce the time it takes and save labor costs, and build an unmanned logistics transport system.

In this case, the overall map is derived by SLAM mapping based on the information measured by the 3D rider, but it is difficult to derive the path for detailed pallet up and down using only SLAM mapping. Since the movement path is calculated from the information of

In particular, since there are various types of pallets, it is difficult to specify the size or exact position only with information photographed with a camera. By specifying the same pallet as the pallet, the shape, size and structure of the corresponding pallet can be derived.

Furthermore, for the pallet specified as described above, by accurately deriving the position of the opening for pickup based on the coordinates of the side and the corner of the opening, the logistics transport robot can automatically pick up the pallet accurately.

On the other hand, even if the pick-up of the pallet is correct, a collision with the container may occur when the actual pallet is vertically loaded. By inducing the pallet to be loaded and unloaded while maintaining a constant distance between the side of the container and the logistics transfer robot, it is possible to perform vertical loading and unloading of the pallet in parallel along the extension direction of the side of the container.

Although the above has been described with reference to the preferred embodiments of the present invention, those skilled in the art can variously modify and change the present invention without departing from the spirit and scope of the present invention as set forth in the following claims. You will understand that you can.

10: logistics transport robot 100: sensor unit
200: processing unit 300: output unit
400: control unit 500: robot unit
530: side frame 540: vertical frame

Claims (14)

A sensor unit including a 3D rider for measuring the surrounding yard, containers and pallets, and a stereoscopic camera for photographing close to the pallet;
a processing unit including a mapping unit for mapping the structure of the yard, positions of the container and the pallet based on the measurement information of the 3D rider, and a learning unit for specifying the pallet based on the shooting information of the stereoscopic camera;
an output unit for outputting a path to the pallet based on the mapping result and the specified pallet information; and
Logistics transport robot including a driving unit for automatically driving the logistics transport robot along the output path. According to claim 1, wherein the sensor unit,
a collision sensor for detecting a collision between the logistics transfer robot and the container; and
Logistics transport robot, characterized in that it further comprises a gap sensor for sensing the distance between the logistics transport robot and the side of the container. The method of claim 2, wherein the gap sensor,
It is provided on the side frame of the logistics transport robot,
When loading and unloading the pallet to the container, the logistics transport robot, characterized in that for sensing the distance between the side of the logistics transport robot and the container. According to claim 1, wherein the mapping unit,
Logistics transport robot, characterized in that the mapping by SLAM (simultaneous localization and mapping) based on the measurement information of the 3D lidar. According to claim 1, wherein the processing unit,
Logistics transport robot, characterized in that it further comprises a database for storing the information of the pre-fabricated pallets. The method of claim 5, wherein the learning unit,
Logistics transport robot, characterized in that by performing learning (deep learning) based on the photographing information of the stereoscopic camera, the pallet corresponding to the photographed pallet among the pallets stored in the database is specified. The method of claim 6, wherein the output unit,
A path calculating unit for calculating a path close to the pallet based on the mapping result and further calculating a path to the specified pallet for pickup of the specified pallet based on the coordinate value of the specified pallet Logistics transport robot, characterized in that. The method according to claim 7, wherein the coordinate value is
Logistics transport robot comprising the coordinates of the corners of the front part of the pallet, and the corner coordinates of each of the openings formed in the front part of the pallet. The method of claim 7, wherein the output unit,
Logistics transport robot comprising an output unit for outputting the mapping result of the mapping unit, and the path calculation result of the path calculating unit. According to claim 1,
The logistics transport robot includes a body part, a side frame extending on the side of the body part, a loading part extending on the front end of the body part to pick up pallets, and a vertical frame extending upward from the front end of the body part,
The 3D rider is provided on the upper part of the vertical frame,
The three-dimensional camera is a logistics transport robot, characterized in that provided at the front end of the body. mapping the structure of the yard, the positions of containers and pallets based on the information measured by the 3D lidar;
Moving the logistics transfer robot to approach the pallet;
photographing the adjacent pallet with a stereoscopic camera;
specifying the pallet by a learning unit based on the shooting information;
calculating a path for picking up the pallet based on the mapping result and the specific pallet information;
Logistics transport method comprising the step of automatically driving the logistics transport robot along the path to pick up the pallet and load it up and down. According to claim 11, In the step of loading and unloading the pallet,
Based on the sensing result of the gap sensor, the logistics transport method, characterized in that the pallet is vertically loaded while maintaining a gap between the logistics transport robot and the side of the container. According to claim 11, In the step of specifying the pallet,
Logistics transport method, characterized in that by performing learning based on the photographing information of the adjacent pallet, and specifying a pallet corresponding to the photographed pallet from a database in which information of the previously produced pallets is stored. The method of claim 13, wherein in the step of calculating the path,
Logistics transport method, characterized in that for calculating the path to the specified pallet for pickup of the specified pallet based on the coordinate value of the specified pallet.

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