Unmanned conveyance system

Abstract

To provide an unmanned conveyance system for a vehicle to convey a heavy object to a destination on the premise that the vehicle will run on a specified traffic line.SOLUTION: An unmanned conveyance system for conveying a heavy object to a destination on a specified virtual traffic line comprises: an unmanned conveyance vehicle running unmanned according to a control signal; one or more cameras for taking pictures of a field in which the unmanned conveyance vehicle runs from above the field to generate a static image or a dynamic image; and operation control means for generating a control signal to control the unmanned conveyance vehicle so as to run on the virtual traffic line on the basis of the static image or the dynamic image. The operation control means comprises: a detection unit for detecting the unmanned conveyance vehicle based on the static image or the dynamic image; a position determining unit for determining the position of the unmanned conveyance vehicle in the field regardless of a sensor boarded on the unmanned conveyance vehicle using the detection result of the detection unit; and a control unit for generating the control signal on the basis of the position of the unmanned conveyance vehicle determined by the position determining unit.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present invention relates to an unmanned transport system (i.e., an automatic guidance system) that travels on a designated traffic line toward a designated destination to transport heavy objects.

Background Art

[0002] Conventionally, in a predetermined field such as a factory or a warehouse, an unmanned transport vehicle (i.e., an automatic guided vehicle, AGV) has been used to transport heavy objects. In a conventional unmanned transport system, a traffic line (or a path or route) on which the unmanned transport vehicle should travel in the field is designated by a tape or the like. The unmanned transport vehicle travels along the tape while detecting the tape, and thus travels on the designated traffic line to transport the heavy object to a destination in the field.

Summary of the Invention

Problems to be Solved by the Invention

[0003] In the field, it may be necessary to change the destination. In this case, the traffic line also needs to be changed. However, when changing the traffic line, it is necessary to reinstall the tape installed on the field, and the burden is large.

[0004] In particular, when the unmanned transport vehicle is a forklift that transports a heavy object placed on a pallet together with the pallet, the size of the pallet is changed, so the interval between the heavy objects to be stored is changed, resulting in a deviation in the destination, and such destination changes are frequently made. Therefore, the burden of reinstalling the tape or the like serving as the traffic line every time the size of the pallet is changed becomes extremely large.

[0005] Note that there are also automated guided vehicles that perform autonomous driving and drive towards a destination while grasping the surrounding environment (such as obstacles) by sensing, rather than driving on a designated route. However, in a field where people also come and go, such as a factory or a warehouse, it would be dangerous if an automated guided vehicle carrying heavy loads could freely drive on a route.

[0006] Therefore, an object of the present invention is to provide a novel automated guided system for transporting heavy loads towards a destination on the premise of driving on a designated route.

Means for Solving the Problems

[0007] An automated guided system according to an aspect of the present invention is an automated guided system that travels on a designated virtual route towards a designated destination and transports heavy loads, including an automated guided vehicle that travels unmanned according to a control signal, one or more cameras that photograph the field on which the automated guided vehicle travels from above the field to generate a still image or a moving image, and driving control means for generating the control signal for controlling the automated guided vehicle to travel on the virtual route based on the still image or the moving image. The driving control means includes a detection unit for detecting the automated guided vehicle from the still image or the moving image, a position grasping unit for grasping the position of the automated guided vehicle in the field without relying on a sensor mounted on the automated guided vehicle using the result of detection by the detection unit, and a control unit for generating the control signal based on the position of the automated guided vehicle grasped by the position grasping unit.

[0008] In the above-described automated guided system, the automated guided vehicle may be a forklift truck that lifts and transports the heavy load placed on a pallet together with the pallet.

[0009] In the above-described automated guided system, the field may be indoors, and the one or more cameras may be attached to the ceiling or a wall to photograph the field from above.

[0010] In the above-described unmanned transport system, the field may be outdoors, and the one or more cameras may be attached to a structure installed outdoors to photograph the field from above.

[0011] In the above-described unmanned transport system, the operation control means may further include an orientation grasping unit that grasps the orientation of the unmanned transport vehicle based on the still image or moving image, and the control unit may generate the control signal based on the orientation grasped by the orientation grasping unit.

[0012] In the above-described unmanned transport system, the unmanned transport vehicle may perform autonomous operation for loading or unloading the heavy object at the destination.

[0013] In the above-described unmanned transport system, the detection unit of the operation control means may further detect an obstacle from the still image or moving image, and the control unit of the operation control means may further generate the control signal based on the result of the detection by the detection unit.

[0014] In the above-described unmanned transport system, the unmanned transport vehicle may be provided with an operation unit for a user to perform an operation to start traveling on the traffic line, and the control unit of the operation control means may start generating the control signal in response to the operation on the operation unit.

[0015] In the above-described unmanned transport system, there may be provided a plurality of the unmanned transport vehicles in which the destination and the virtual traffic line are respectively specified. The detection unit of the operation control means may detect a plurality of the unmanned transport vehicles from the still image or moving image. The position grasping unit of the operation control means may grasp the respective positions of the plurality of unmanned transport vehicles in the field. The control unit of the operation control means may generate the control signal for each of the plurality of unmanned transport vehicles based on the plurality of positions grasped by the position grasping unit.

[0016] The above unmanned transport system may include a plurality of the cameras with different fields of view, and the position determination unit may determine the position of the unmanned transport vehicle in the field by integrating a plurality of still images or moving images generated by the plurality of cameras.

[0017] In the above unmanned transport system, the detection unit may detect the unmanned transport vehicle using a neural network.

[0018] In the above unmanned transport system, the unmanned transport vehicle may have a predetermined mark on its upper surface, and the detection unit may detect the unmanned transport vehicle by detecting the predetermined mark.

[0019] In the above unmanned transport system, the driving control means may store a map of the field in which the traffic line is defined, and the position determination unit may determine the position of the unmanned transport vehicle by mapping the unmanned transport vehicle detected by the detection unit on the map.

[0020] The above unmanned transport system may have a predetermined mark at a predetermined position in the field, the detection unit may detect the predetermined mark, and the position determination unit may determine the position of the unmanned transport vehicle based on the predetermined mark detected by the detection unit.

[0021] In the above unmanned transport system, the detection unit of the driving control means may further detect the heavy object being transported by the unmanned transport vehicle.

[0022] In the above unmanned transport system, the unmanned transport vehicle may include an in-vehicle detection unit for detecting surrounding obstacles and an emergency stop processing unit for performing emergency stop processing of the unmanned transport vehicle based on the detection of the obstacles by the in-vehicle detection unit.

[0023] The above unmanned transportation system may further include a derailment determination means for determining whether the unmanned transport vehicle has deviated from the traffic line. When the derailment determination means determines that the unmanned transport vehicle has deviated from the traffic line, the operation control means may generate the control signal so as to stop the unmanned transport vehicle or return the unmanned transport vehicle to the traffic line.

[0024] In the above unmanned transportation system, the derailment determination means may include an in-vehicle camera mounted on the unmanned transport vehicle for photographing the periphery of the unmanned transport vehicle to generate a still image or a moving image, and a determination unit for determining whether the unmanned transport vehicle has deviated from the traffic line based on the still image or the moving image generated by the in-vehicle camera.

[0025] In the above unmanned transportation system, the derailment determination means may include a receiver for receiving a positioning signal, and a determination unit for determining whether the unmanned transport vehicle has deviated from the traffic line based on the positioning signal received by the receiver.

Brief Description of the Drawings

[0026]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5A

Figure 5B

Figure 6

Best Mode for Carrying Out the Invention

[0027] Hereinafter, embodiments of the present invention will be described with reference to the drawings. Note that the embodiments described below are merely examples of implementing the present invention, and the present invention is not limited to the specific configurations described below. In implementing the present invention, specific configurations according to the embodiments may be appropriately adopted.

[0028] FIG. 1 is a plan view showing a field to which the unmanned transport system according to an embodiment of the present invention is applied, and FIG. 2 is a side view of the field to which the unmanned transport system according to an embodiment of the present invention is applied. As the field 50 to which the unmanned transport system (i.e., the automatic guidance system) according to the present embodiment is applied, factories, warehouses, etc. are assumed. In the present embodiment, the unmanned transport vehicle (i.e., the automatic guided vehicle, AGV) 300 is a forklift vehicle that lifts and transports the heavy object 53 placed on the pallet 54 together with the pallet 54.

[0029] The unmanned transport vehicle 300 travels on a designated virtual traffic line toward a designated destination within the field 50 to transport the heavy object. In the field 50, for example, manufacturing equipment 52 is installed, and sometimes workers 400 are walking. These manufacturing equipment 52 and workers 400 can be obstacles when the unmanned transport vehicle 300 travels within the field 50. Also, the heavy objects 53 and pallets 54 placed within the field 50 are also obstacles, and when a plurality of unmanned transport vehicles 300 travel within the field 50, other unmanned transport vehicles 300 can also be obstacles.

[0030] The field 50 is inside a building (indoors), and a plurality of overhead cameras 10 are attached to the ceiling 55. The plurality of overhead cameras 10 each photograph the field 50 from above. Note that the overhead cameras 10 may be installed at high places such as the walls, pillars, and poles of the building. Also, a plurality of marks 51 are provided in the field 50 at positions visible from the overhead cameras 10.

[0031] Each of the plurality of overhead cameras 10 has a part of the area of the shootable field 50 overlapping (see Fig. 2), whereby the shooting areas of the plurality of overhead cameras 10 cover the entire field 50. Note that it is not necessary to always shoot the entire field 50, and the field 50 may include a partial area that is not shot by any of the overhead cameras 10. That is, in the field 50, an area where the unmanned transport vehicle 300 is not scheduled to travel does not have to be included in the shooting range of any of the overhead cameras 10.

[0032] The unmanned transport vehicle 300 loads at the loading position and unloads at the destination, thereby transporting the heavy object 53 from the loading position as the starting point to the destination. After the transport is completed, the unmanned transport vehicle 300 returns to the loading position without carrying the heavy object 53 for the next transport. At this time, the unmanned transport vehicle 300 moves (returns) with the unloading position as the starting point and the loading position as the destination. In the unmanned transport system of the present embodiment, the transport of such a heavy object 53 and the running for the return of the unmanned transport vehicle 300 are performed unmanned.

[0033] A virtual traffic line 210 is set in the field 50. Note that this traffic line 210 is virtual and is not provided as a physical entity in the field 50. In the case of a conventional unmanned transport system in which a traffic line as a physical entity (hereinafter referred to as a physical traffic line) is provided in the field 50, the unmanned transport vehicle 300 can travel along the physical traffic line to the destination by detecting the physical traffic line and running so as not to deviate from the physical traffic line.

[0034] However, in such a conventional unmanned transport system, when trying to change the running route of the unmanned transport vehicle 300, it is necessary to change the physical traffic line, and the work burden is large. Therefore, in the unmanned transport system 100 of the present embodiment, without using a physical traffic line, a virtual traffic line 210 is set, and the unmanned transport vehicle 300 is controlled so that the unmanned transport vehicle 300 can run on this virtual traffic line 210.

[0035] Figure 3 is a perspective view showing an automated guided vehicle in the automated material handling system according to an embodiment of the present invention. As shown in Figure 3, the automated guided vehicle 300 is provided with a fork 330 that can move up and down at its tip. In addition, an in-vehicle camera 310 capable of photographing the front is attached to the automated guided vehicle 300 in order to photograph the surroundings of the automated guided vehicle 300. Further, a mark 350 is provided on the upper surface of the automated guided vehicle 300.

[0036] In addition, individual identification information is given to the automated guided vehicle 300, and the identification information is displayed on the upper surface of the automated guided vehicle 300 as an identification information notation 370 so that it can be photographed by the overhead camera 10 above. In the example of Figure 1, the two automated guided vehicles 300 are given identification information of "1" and "2" respectively, and the identification information notations 370 representing these identification information are displayed on the upper surface of the automated guided vehicle 300. Note that the identification information notation 370 may be a code (for example, a barcode, a two-dimensional code, etc.) generated by encoding the identification information.

[0037] Figure 4 is a block diagram showing the configuration of the automated material handling system according to an embodiment of the present invention. As shown in Figure 4, the automated material handling system 100 of the present embodiment includes a plurality of overhead cameras 10, an operation control device 20, and automated guided vehicles 300. The plurality of overhead cameras 10 are each connected to the operation control device 20 by a wired cable. The overhead camera 10 photographs the field 50 in which the automated guided vehicle 300 travels from above the field 50 and generates a moving image. The overhead camera 10 transmits the generated moving image stream to the operation control device 20 in real time, and the operation control device 20 receives the moving image stream from the plurality of overhead cameras 10.

[0038] Note that the overhead camera 10 may be wirelessly connected to the driving control device 20 to wirelessly transmit and receive a moving image stream. Further, the overhead camera 10 may continuously perform still photography to generate consecutive still images and transmit the generated still images to the driving control device 20 in real time. Unique identification information is assigned to each of the plurality of overhead cameras 10. The driving control device 20 identifies whether the still image or moving image is from which overhead camera 10 using the identification information of the overhead camera 10.

[0039] Based on the still image or moving image sent from the overhead camera 10, the driving control device 20 generates a control signal for controlling the unmanned transport vehicle 300 to travel on the virtual traffic line 210 and transmits it to the unmanned transport vehicle 300. The driving control device 20 may be provided inside or outside the field 50, or may be provided on the cloud and communicate with the overhead camera 10 and the unmanned transport vehicle 300 via the Internet. Further, the driving control device 20 may be provided in the overhead camera 10 or the unmanned transport vehicle 300. Thus, the driving control device 20 may be arranged anywhere as long as it can transmit data (such as a moving image stream, a still image, a control signal, etc.) between the overhead camera 10 and the unmanned transport vehicle 300.

[0040] The driving control device 20 includes a detection unit 21, a position grasping unit 22, an orientation grasping unit 23, a control unit 24, and a storage unit 25. The detection unit 21 detects the unmanned transport vehicle 300 from the still image or moving image. Since the driving control device 20 acquires still images or moving images from a plurality of overhead cameras 10, the detection unit 21 detects the unmanned transport vehicle 300 from each of the still images or moving images obtained from those plurality of overhead cameras 10.

[0041] The detection unit 21 detects the unmanned carrier vehicle 300 from a still image or a moving image by inputting the still image or the moving image into a learned neural network. When the operation control device 20 acquires a moving image from the overhead camera 10, the detection unit 21 may extract frame images at predetermined intervals from the moving image and detect the unmanned carrier vehicle 300 from those frame images (still images).

[0042] Since a predetermined mark 350 is provided on the upper surface of the unmanned carrier vehicle 300, the detection unit 21 may detect the unmanned carrier vehicle 300 from the still image or the moving image using this mark 350 as a clue. That is, the detection unit 21 may detect the mark 350 provided on the unmanned carrier vehicle 300 as the unmanned carrier vehicle 300.

[0043] The detection unit 21 further detects the identification information notation 370 of the unmanned carrier vehicle 300. As shown in the example of FIG. 1, when the identification information is represented by characters (including numbers), the detection unit 21 performs character recognition on the detected identification information notation 370 to specify the identification information of the detected unmanned carrier vehicle 300. When the identification information is represented as code information, the detection unit 21 decodes the detected identification information notation 370 to specify the identification information of the detected unmanned carrier vehicle 300. Also, the mark 350 may also serve as the identification information notation 370.

[0044] The position grasping unit 22 grasps the position of the unmanned carrier vehicle 300 in the field 50 using the result of the detection by the detection unit 21. Although the unmanned carrier vehicle 300 is equipped with an in-vehicle camera 310, the position grasping unit 22 does not rely on the in-vehicle camera 310 or other in-vehicle sensors mounted on the unmanned carrier vehicle 300, but based on the detection result from the still image or the moving image captured by the overhead camera 10, grasps the position of the unmanned carrier vehicle 300 within the field 50.

[0045] The memory unit 25 stores the map of the field 50. In this map, the route along which the automated guided vehicle 300 should travel is defined. The position determination unit 22 determines the position of the automated guided vehicle 300 by mapping the automated guided vehicle 300 detected by the detection unit 21 on this map. For this mapping, a predetermined mark 51 is provided at a predetermined position in the field 50 and is photographed by the overhead camera 10. The detection unit 21 detects the mark 51, and the position determination unit 22 determines the position of the automated guided vehicle 300 based on the mark 51 detected by the detection unit 21.

[0046] Further, the position determination unit 22 may generate a still image or a moving image of the entire field 50 by integrating still images or moving images of a plurality of different regions acquired from a plurality of overhead cameras 10 according to the identification information of the overhead cameras 10, and determine the position of the automated guided vehicle 300 in the field 50 using such an integrated image.

[0047] The orientation determination unit 23 determines the orientation of the automated guided vehicle 300 based on the still image or the moving image. The orientation determination unit 23 may detect the orientation of the automated guided vehicle 300 from the still image or the moving image by inputting the still image or the moving image into a learned neural network. Further, the orientation determination unit 23 may determine the orientation of the automated guided vehicle 300 by determining the orientation of the mark 350 of the automated guided vehicle 300 detected by the detection unit 21.

[0048] The control unit 24 generates a control signal for controlling the travel of the automated guided vehicle 300 based on the position of the automated guided vehicle 300 determined by the position determination unit 22 and the orientation of the automated guided vehicle 300 determined by the orientation determination unit 23. Specifically, the control unit 24 generates a control signal including instructions for forward movement, stop, and steering so that the automated guided vehicle 300 travels toward the destination on the route 210 defined in the map based on the position and orientation of the automated guided vehicle 300. The generated control signal is transmitted to the corresponding automated guided vehicle 300 in real time.

[0049] The automated guided vehicle 300 receives a control signal from the operation control device 20 and travels according to this control signal. The automated guided vehicle 300 includes a travel control unit 301, a lift control unit 302, an in-vehicle detection unit 303, an emergency stop processing unit 304, a determination unit 305, an autonomous driving processing unit 306, an operation unit 307, a travel drive unit 308, a lift drive unit 309, an in-vehicle camera 310, and a receiver 311.

[0050] The travel drive unit 308 includes a power source, a power transmission mechanism, a steering mechanism, a transmission mechanism, a braking mechanism, wheels, etc. for driving the automated guided vehicle 300. The lift drive unit 309 includes a drive source for moving the fork 330 up and down, a power transmission mechanism, a sub-lock mechanism for fixing the fork 330 at a predetermined position, etc. The travel drive unit 308 is driven according to the control by the travel control unit 301. The lift drive unit 309 is driven according to the control by the lift control unit 302.

[0051] The travel control unit 301 drives the travel drive unit 308 according to the control signal received from the operation control device 20, and thereby performs control for the automated guided vehicle 300 to travel on the set virtual route 210. In the automated guided vehicle system 100 of the present embodiment, for the automated guided vehicle 300 to travel along the virtual route 210, all that is necessary are this travel control unit 301 and the travel drive unit 308, and other components (for example, the in-vehicle detection unit 303 and the in-vehicle camera 310) are additional components.

[0052] The in-vehicle detection unit 303 is used for the emergency stop of the automated guided vehicle 300. The in-vehicle detection unit 303 may be, for example, an infrared sensor or LiDAR. The in-vehicle detection unit 303 detects that there is an obstacle in front of the automated guided vehicle 300 in the traveling direction. Alternatively, the in-vehicle detection unit 303 may detect that there is an obstacle not only in front of the traveling direction but also around the entire automated guided vehicle 300.

[0053] When the in-vehicle detection unit 303 detects an obstacle, the emergency stop processing unit 304 executes emergency stop processing for the automated guided vehicle 300. Specifically, as the emergency stop processing, the emergency stop processing unit 304 controls the traveling drive unit 308 to stop the generation of power from the power source and to apply braking. At this time, if sudden braking is performed, there is a possibility that the pallet 54 may come off the fork 330 and the heavy object 53 may detach from the automated guided vehicle 300. Therefore, braking is performed with a strength that does not cause such an accident.

[0054] Note that the obstacle may be detected by the driving control device 20, and a control signal may be generated by the control unit 24 in consideration of the presence of this obstacle. In this case, the detection unit 21 detects the obstacle from the still image or moving image obtained from the overhead camera 10. Then, the control unit 24 generates a control signal based on the result of the detection of the obstacle by the detection unit 21.

[0055] At this time, in the present embodiment, control is not performed such that the automated guided vehicle 300 deviates from the set travel route 210 to avoid an obstacle. If the automated guided vehicle 300 cannot travel on the travel route 210 due to an obstacle, the automated guided vehicle 300 is stopped on the spot. This is because, since the automated guided vehicle 300 of the present embodiment transports the heavy object 53, it is not desirable from the viewpoint of safety for the automated guided vehicle 300 to deviate from the preset travel route 210 and travel in an arbitrary space. At this time, in order to notify the surroundings of the automated guided vehicle 300 that the automated guided vehicle 300 cannot move forward on the travel route 210 due to an obstacle, the automated guided vehicle 300 may activate an alarm (not shown) to emit an alarm sound.

[0056] As described above, in the automated guided vehicle system 100 of the present embodiment, by controlling the travel of the automated guided vehicle 300 based on the still image or moving image obtained by the overhead camera 10, the automated guided vehicle 300 can travel on the set virtual travel route 210. If there is an obstacle on the travel route of the automated guided vehicle 300, the automated guided vehicle 300 itself detects this and performs an emergency stop.

[0057] Also, even if the automated guided vehicle 300 is in an emergency stop state, when the control unit 24 recognizes that the event that caused the automated guided vehicle 300 to enter the emergency stop state has been resolved, the automated guided vehicle 300 may be made to travel again. Conventionally, when a person determines that the event that caused the automated guided vehicle 300 to enter the emergency stop state has been resolved and depends on manual operation to resume travel from the emergency stop state, the reliability is extremely low. Note that the control unit 24 may recognize that the event that caused the emergency stop state has been resolved when the in-vehicle detection unit 303 or in-vehicle camera 310 of the automated guided vehicle 300 no longer detects an obstacle, or alternatively, may recognize that the event that caused the emergency stop state has been resolved based on the still image or moving image of the overhead camera 10.

[0058] As described above, normally, the automated guided vehicle 300 is always on the traffic line 210 and is assumed to be traveling or stopped. However, it is also assumed that the automated guided vehicle 300 may deviate (go off track) from the traffic line 210 for some reason. Therefore, the unmanned transport system 100 of the present embodiment has a function for determining that the automated guided vehicle 300 has gone off track.

[0059] The control unit 24 determines whether the position grasped by the position grasping unit 22 is outside the traffic line 210 defined in the map stored in the storage unit 25. When the control unit 24 determines that it is outside the traffic line 210, it stops the automated guided vehicle 300 and generates a control signal to return the automated guided vehicle 300 to the traffic line 210.

[0060] In this way, the driving control device 20 may grasp the position of the automated guided vehicle 300 based on the still image or moving image of the overhead camera 10 and determine derailment. In addition to this, or instead of this, a derailment determination system that does not use the still image or moving image of the overhead camera 10 may be provided. Also in this case, when the control unit 24 determines that the automated guided vehicle 300 has deviated from the traffic line 210 by the derailment determination system, the control unit 24 stops the automated guided vehicle 300 and generates a control signal to return the automated guided vehicle 300 to the traffic line 210.

[0061] The first derailment determination system is composed of an in-vehicle camera 310 and a determination unit 305. The in-vehicle camera 310 is mounted on the automated guided vehicle 300, and captures the surroundings of the automated guided vehicle 300 to generate a still image or a moving image. The determination unit 305 determines whether the automated guided vehicle 300 has deviated from the traffic line 210 based on the still image or the moving image generated by the in-vehicle camera 310. Specifically, the determination unit 305 determines whether the automated guided vehicle 300 has derailed by determining whether the image of the in-vehicle camera 310 is an image that should be captured when the automated guided vehicle 300 is on the traffic line 210.

[0062] The second derailment determination system is composed of a receiver 311 and a determination unit 305. The receiver 311 receives a positioning signal propagating within the field 50. The positioning signal is generated within the field 50. As indoor positioning technologies, various conventional technologies have been proposed and adopted, and any conventional indoor positioning technology may be adopted as the second derailment determination system.

[0063] For example, the receiver 311 may be one that receives WiFi radio waves as the positioning signal. In this case, a plurality of base stations that transmit WiFi radio waves are installed in the field 50. The receiver 311 receives WiFi radio waves from these plurality of base stations, and the determination unit 305 grasps the position of the automated guided vehicle 300 from the difference in the intensities of the WiFi radio waves from the plurality of base stations received by the receiver 311, and maps it to the map where the traffic line 210 is defined, thereby determining whether the automated guided vehicle 300 has deviated from the traffic line 210 defined in the map.

[0064] Also, for example, the receiver 311 may be one that receives a positioning signal from a beacon installed within the field 50. In this case, a plurality of beacons are installed in the field 50. The determination unit 305 grasps the position of the automated guided vehicle 300 within the field 50 based on the intensities of the positioning signals received from the plurality of beacons respectively, and maps it to the map where the traffic line 210 is defined, thereby determining whether the automated guided vehicle 300 has deviated from the traffic line 210 defined in the map.

[0065] The derailment determination system may also perform positioning using any of the conventional positioning technologies such as positioning using a magnetic sensor, positioning using IMES (IndoorMEssaging System) based on the same principle as GPS, positioning using PDR (Pedestrian Dead Reckoning), positioning using visible light, and positioning using ultrasonic waves, and then determine derailment.

[0066] As described above, in the unmanned transport system 100 of the present embodiment, while the unmanned transport vehicle 300 is basically made to travel on the virtual traffic line 210, even if it derails for some reason, the derailment can be detected, and the travel of the unmanned transport vehicle 300 can be controlled to return to the traffic line 210.

[0067] When the unmanned transport vehicle 300 transports the heavy object 53, the heavy object 53 is loaded onto the unmanned transport vehicle 300 at the departure place, and the heavy object 53 is unloaded from the unmanned transport vehicle 300 at the destination. Also, when the unmanned transport vehicle 300 makes a return trip from the unloading place to the loading place, the heavy object 53 is unloaded from the unmanned transport vehicle 300 at the departure place, and the heavy object 53 is loaded onto the unmanned transport vehicle 300 at the destination.

[0068] The unmanned transport vehicle 300 may autonomously perform the loading and unloading at this departure place and destination. The autonomous driving processing unit 306 of the unmanned transport vehicle 300 performs autonomous driving for loading and unloading the heavy object 53 at the departure place or the destination. For this purpose, when the autonomous driving processing unit 306 arrives at the departure place by making a return trip, it analyzes the image of the in-vehicle camera 310 to detect the heavy object 53 to be loaded from the image. The autonomous driving processing unit 306 controls the travel drive unit 308 and the lift drive unit 309 according to the detected heavy object 53 to perform loading.

[0069] In addition, when the autonomous driving processing unit 306 arrives at the destination while performing the conveyance operation, it analyzes the image of the in-vehicle camera 310 to detect the position where unloading should be performed from the image. The autonomous driving processing unit 306 controls the traveling drive unit 308 and the lift drive unit 309 according to the detected position where unloading should be performed to perform unloading.

[0070] The driverless transport vehicle 300 is provided with an operation unit 307 for the user to operate in order to start traveling on the traffic line 210. When the user performs an operation to start traveling on the operation unit 307, an operation signal is transmitted from the driverless transport vehicle 300 to the operation control device 20. The control unit 24 that has received this operation signal starts generating a control signal. Even when loading and unloading are performed by autonomous driving as described above, or when loading and unloading are performed manually without autonomous driving, the control unit 24 may start traveling control according to this operation signal. The operation unit 307 may be a terminal independent of the driverless transport vehicle 300, for example, a tablet terminal. Also, when loading and unloading are performed by autonomous driving, it may be configured to automatically start traveling when loading or unloading is completed regardless of the operation signal of the operation unit 307.

[0071] As described above, a plurality of driverless transport vehicles 300 with different destinations and different traffic lines respectively specified are arranged in the field 50, and the operation control device 20 controls the plurality of driverless transport vehicles 300 simultaneously. For this purpose, the detection unit 21 detects the plurality of driverless transport vehicles 300 from the still image or moving image of the overhead camera 10. Also, the position grasping unit 22 grasps the respective positions of the plurality of driverless transport vehicles 300 in the field 50. Further, the control unit 24 generates control signals for each of the plurality of driverless transport vehicles 300 based on the plurality of positions grasped by the position grasping unit 22.

[0072] As a result, a plurality of automated guided vehicles 300 can be simultaneously controlled in one field 50. Also, by regarding other automated guided vehicles 300 as obstacles, when there is another automated guided vehicle 300 in front of the traveling direction of a certain automated guided vehicle 300, the other automated guided vehicle 300 may be detected as an obstacle and the certain automated guided vehicle 300 may be stopped urgently. Thereby, it becomes possible to set virtual traffic lines 210 set for the plurality of automated guided vehicles 300 so as to cross each other.

[0073] Also, in the above embodiment, when simultaneously controlling a plurality of automated guided vehicles 300, by providing the identification information notation 370 on the upper surface of the automated guided vehicle 300, the operation control device 20 detects the identification information notation 370 from the still image or moving image of the overhead camera 10, grasps the positions of the respective automated guided vehicles 300, and generates control signals for each of the automated guided vehicles 300. That is, the identification information notation 370 was used to control each automated guided vehicle 300 individually. Instead of this, the automated guided vehicle 300 may be configured not to have the identification information notation 370.

[0074] In this case, the automated guided vehicle 300 transmits the in-vehicle camera image of the in-vehicle camera 310 to the operation control device 20. The control unit 24 of the operation control device 20 analyzes this in-vehicle camera image to recognize from which position the image is of the automated guided vehicle 300. By doing so, the operation control device 20 can recognize that the automated guided vehicle 300 detected from the image of the overhead camera 10 and the automated guided vehicle 300 that has sent the in-vehicle camera image are the same automated guided vehicle 300. Then, the operation control device 20 can transmit the control signal for each of the automated guided vehicles 300 detected from the image of the overhead camera 10 to the corresponding automated guided vehicle 300.

[0075] Note that the above detection unit 21 may not only detect the unmanned carrier vehicle 300 from a still image or a moving image, but also detect the heavy object being carried by the unmanned carrier vehicle 300. According to this, it is possible to confirm whether the unmanned carrier vehicle 300 is carrying the heavy object 53, that is, whether it is in the process of transportation or in the process of returning, and whether the heavy object 53 being transported has fallen from the unmanned carrier vehicle 300.

[0076] As described above, according to the unmanned transportation system 100 of the present embodiment, the position of the unmanned carrier vehicle 300 is grasped using the overhead camera 10, and the travel of the unmanned carrier vehicle 300 is controlled in light of the map. Therefore, without using a physical traffic line, the unmanned carrier vehicle 300 can be made to travel from the starting point to the destination along the virtual traffic line 210. This is particularly beneficial when it is necessary to change the traffic line. When changing the traffic line, it is not necessary to physically change the traffic line in the field 50, because it is only necessary to change the traffic line on the map. Here, the situation of changing the traffic line will be described.

[0077] FIGS. 5A and 5B are diagrams showing examples of changing the traffic line according to an embodiment of the present invention. In the example of FIG. 5A, a relatively small pallet 54 (heavy object 53) is the object to be transported, and in the example of FIG. 5B, a relatively large pallet 54 (heavy object 53) is the object to be transported. Therefore, when arranging and storing the heavy objects 53 at the destination, the distance between adjacent heavy objects 53, that is, the distance between the traffic lines 210 leading to the storage locations (destinations) of adjacent heavy objects, is different from each other. In the example of FIG. 5A, the distance between the traffic lines 210a leading to the storage location which is the destination is relatively short, and in the example of FIG. 5B, the distance between the traffic lines 210b leading to the storage location which is the destination is relatively long.

[0078] When the size of the pallet 54 (heavy object 53) is changed while the heavy object 53 is being transported in such a field 50 or with respect to the heavy object 53, it is necessary to change the distance between the flow lines 210. For example, when the size of the pallet 54 (heavy object 53) is increased, it is necessary to increase the distance between the flow lines 210, and it is necessary to change the flow lines from the flow line 210a shown in FIG. 5A to the flow line 210b shown in FIG. 5B. Even in such a case, according to the present embodiment, neither the flow line 210a nor the flow line 210b is physically provided in the actual field 50, but is defined on the map stored in the storage unit 25, so it can be easily changed.

[0079] FIG. 6 is a side view showing another example of a field to which the unmanned transport system according to the embodiment of the present invention is applied. In the above embodiment, an example in which the inside of a building is used as the field 50 and the overhead camera 10 is attached to the ceiling 55 has been described. However, the unmanned transport system 100 of the present embodiment can also be used outdoors. However, in this case, since there is no ceiling, the overhead camera 10 is installed at a high position of a tall structure such as a pole 56 or the outer wall of a building so as to photograph the field 50.

[0080] (Modification example) The control unit 24 may control the speed of the unmanned transport vehicle 300 based on a still image or a moving image of the overhead camera 10. The detection unit 21 detects obstacles (including the worker 400, the manufacturing facility 52, the stored heavy object 53, other unmanned transport vehicles 300, etc.) together with the unmanned transport vehicle 300 to be controlled from the still image or the moving image of the overhead camera 10. When there are no obstacles within a predetermined range around the unmanned transport vehicle 300 to be controlled, the control unit 24 generates a control signal so as to increase the traveling speed and travel. Alternatively, since the unmanned transport vehicle 300 travels on the flow line 210, the control unit 24 may determine the presence or absence of obstacles within a predetermined range along the flow line 210 from the unmanned transport vehicle 300.

[0081] In this way, by checking that the surroundings of the automated guided vehicle 300 are safe and increasing the speed of the automated guided vehicle 300, it is possible to shorten the cycle time of the conveyance operation. This is effective for improving production efficiency in a factory. Note that as for the speed control, for example, when the automated guided vehicle 300 moves forward with the fork 330 in front, it may be controlled to travel at a relatively low speed, and when it moves backward to the side opposite to the fork 330, it may be controlled to travel at a relatively high speed.

[0082] In this way, even when controlling to change the speed according to the presence or absence of surrounding obstacles, the control based on the still image or moving image of the overhead camera 10 is effective. That is, if an attempt is made to confirm safety by detecting surrounding obstacles with sensors (in-vehicle cameras, LiDAR, etc.) mounted on the automated guided vehicle 300, there may be cases where obstacles cannot be detected due to dead spots of the sensors, and there may also be cases where relatively distant obstacles cannot be detected, and safety cannot be ensured. Therefore, by using the overhead camera 10, it is possible to set a necessary range around the automated guided vehicle 300 and confirm whether there are any obstacles within that range.

[0083] Also, regardless of whether there are obstacles around the automated guided vehicle 300, speeds may be set for each section on the traffic lane defined on the map, and a control signal corresponding to the speed set on the map may be generated based on the position of the automated guided vehicle 300. For example, a relatively high speed may be set for sections that do not intersect with the traffic lane 210 of another automated guided vehicle 300, and a relatively low speed may be set for sections that intersect with the traffic lane 210 of another automated guided vehicle 300 or sections that cross the area where workers 400 come and go.

[0084] Incidentally, the above-described operation control device 20 may be implemented by a computer, and the detection unit 21, the position grasping unit 22, the orientation grasping unit 23, and the control unit 24 may be functions realized by a processor executing one or more operation control programs of the present embodiment. Further, the travel control unit 301, the lift control unit 302, the emergency stop processing unit 304, the determination unit 305, and the autonomous driving processing unit 306 of the automated guided vehicle 300 may be functions realized by a processor executing one or more automated guided programs of the present embodiment. Further, the travel control unit 301, the lift control unit 302, the emergency stop processing unit 304, the determination unit 305, and the autonomous driving processing unit 306 do not necessarily have to be provided in the automated guided vehicle 300. For example, they may be provided in a service provider on the cloud, and the automated guided vehicle 300 may communicate with the service provider.

[0085] In the above embodiment, the automated guided vehicle 300 was a forklift, but the automated guided vehicle 300 is not limited thereto. For example, it may be a wagon type or cart type transport vehicle. In this case, loading and unloading may be performed by the worker 400.

Explanation of Signs

[0086] 10 Overhead camera 20 Operation control device 21 Detection unit 22 Position grasping unit 23 Orientation grasping unit 24 Control unit 25 Storage unit 50 Field 51 Mark 52 Manufacturing facility 53 Heavy object 210 Traffic line 300 Automated guided vehicle 301 Travel control unit 302 Lift control unit 304 Emergency stop processing unit 305 Determination unit 306 Autonomous driving processing unit 307 Operation unit 308 Travel drive unit 309 Lift drive unit 310 On-vehicle camera 311 Receiver 330 Fork 350 Mark 370 Identification information notation 400 Operator

Claims

1. An unmanned transport system that transports heavy objects by traveling on a designated virtual route toward a designated destination, comprising: An unmanned transport vehicle that travels unmanned according to a control signal; One or more cameras that photograph a field on which the unmanned transport vehicle travels from above the field to generate a still image or a moving image; Operation control means for generating the control signal for controlling the unmanned transport vehicle to travel on the virtual route based on the still image or the moving image; Comprising; The operation control means includes: A detection unit that detects the unmanned transport vehicle from the still image or the moving image; A position grasping unit that grasps the position of the unmanned transport vehicle in the field without relying on a sensor mounted on the unmanned transport vehicle, using the result of detection by the detection unit; A control unit that generates the control signal based on the position of the unmanned transport vehicle grasped by the position grasping unit; An unmanned transport system comprising.

2. The unmanned transport system according to claim 1, wherein the unmanned transport vehicle is a forklift vehicle that lifts and transports the heavy object placed on the pallet together with the pallet.

3. The field is indoors, The unmanned transport system according to claim 1, wherein the one or more cameras are attached to the ceiling or a wall and photograph the field from above.

4. The field is outdoors, The unmanned transport system according to claim 1, wherein the one or more cameras are attached to a structure installed outdoors and photograph the field from above.

5. The operation control means further includes an orientation grasping unit that grasps the orientation of the unmanned transport vehicle based on the still image or the moving image, The unmanned transport system according to claim 1, wherein the control unit generates the control signal based also on the orientation grasped by the orientation grasping unit.

6. The unmanned transport system according to claim 1, wherein the unmanned transport vehicle performs autonomous operation for loading or unloading the heavy object at the destination.

7. The detection unit of the operation control means further detects an obstacle from the still image or the moving image, The unmanned transport system according to claim 1, wherein the control unit of the operation control means further generates the control signal based also on the result of the detection by the detection unit.

8. The unmanned transport vehicle is provided with an operation unit for a user to perform an operation to start traveling on the route. The control unit of the operation control means starts generating the control signal in response to the operation on the operation unit, the unmanned conveyance system according to claim 1.

9. Comprising a plurality of the unmanned carrier vehicles in which the destination and the virtual traffic line are respectively specified, The detection unit of the operation control means detects a plurality of the unmanned carrier vehicles from the still image or moving image, The position grasping unit of the operation control means grasps the respective positions of the plurality of unmanned carrier vehicles in the field, The control unit of the operation control means generates the control signal for each of the plurality of unmanned carrier vehicles based on the plurality of positions grasped by the position grasping unit, the unmanned conveyance system according to claim 1.

10. Comprising a plurality of cameras with different fields of view, The position grasping unit grasps the position of the unmanned carrier vehicle in the field by integrating a plurality of still images or moving images generated by the plurality of cameras, the unmanned conveyance system according to claim 1.

11. The detection unit detects the unmanned carrier vehicle using a neural network, the unmanned conveyance system according to claim 1.

12. The unmanned carrier vehicle has a predetermined mark on the upper surface, The detection unit detects the unmanned carrier vehicle by detecting the predetermined mark, the unmanned conveyance system according to claim 1.

13. The operation control means stores a map of the field in which the traffic line is defined, The position grasping unit grasps the position of the unmanned carrier vehicle by mapping the unmanned carrier vehicle detected by the detection unit on the map, the unmanned conveyance system according to claim 1.

14. Has a predetermined mark at a predetermined position in the field, The detection unit detects the predetermined mark, The position grasping unit grasps the position of the unmanned carrier vehicle based on the predetermined mark detected by the detection unit, the unmanned conveyance system according to claim 1.

15. The detection unit of the operation control means further detects the heavy object being carried by the unmanned carrier vehicle, the unmanned conveyance system according to claim 1.

16. The unmanned carrier vehicle, An in-vehicle detection unit for detecting surrounding obstacles, An emergency stop processing unit that performs emergency stop processing of the unmanned carrier vehicle based on the detection of the obstacles by the in-vehicle detection unit, Comprising the above, the unmanned conveyance system according to claim 1.

17. The unmanned transport vehicle further comprises a derailment determination means for determining whether the unmanned transport vehicle has deviated from the traffic line. The operation control means generates the control signal so as to stop the unmanned transport vehicle or return the unmanned transport vehicle to the traffic line when the derailment determination means determines that the unmanned transport vehicle has deviated from the traffic line. The unmanned transport system according to claim 1. **Claim 18** The derailment determination means An in-vehicle camera mounted on the unmanned transport vehicle, which photographs the periphery of the unmanned transport vehicle and generates a still image or a moving image; A determination unit that determines whether the unmanned transport vehicle has deviated from the traffic line based on the still image or the moving image generated by the in-vehicle camera. The unmanned transport system according to claim 17, comprising: **Claim 19** The derailment determination means A receiver that receives a positioning signal; A determination unit that determines whether the unmanned transport vehicle has deviated from the traffic line based on the positioning signal received by the receiver. The unmanned transport system according to claim 17, comprising:

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