Automated guided vehicle system

Abstract

Provided is a novel automated guided vehicle system for transporting a heavy object to a destination on the premise of traveling on a specified travel route. An unmanned transport system (100) that travels on a specified virtual activity route (210) and transports a heavy object (53) toward a specified destination is provided with: an unmanned transport vehicle (300) that travels in an unmanned manner on the basis of a control signal; one or more cameras (10) that capture images of the site (50) on which the automated guided vehicle (300) travels from above the site (50) and generate still images or moving images; and a driving control means (20) that generates, on the basis of the still image or the moving image, a control signal for controlling the automated guided vehicle (300) to travel on the virtual movement route (210). A driving control device (20) is provided with: a detection unit (21) that detects an automated guided vehicle (300) on the basis of a still image or a moving image; a position ascertaining unit (22) that ascertains the position of the automated guided vehicle (300) in the site (50) by using the detection result of the detection unit (21), without relying on a sensor mounted on the automated guided vehicle (300); and a control unit (24) that generates a control signal on the basis of the position of the automated guided vehicle (300) grasped by the position grasping unit (22).

Description

[0001] Cross-references between related applications

[0002] This application claims the benefit of patent application No. 2023-7710 filed in Japan on January 20, 2023, the contents of which are incorporated herein by reference. Technical Field

[0003] The present invention relates to an unmanned transport system (ie, an automatic guided vehicle system) that travels along a designated moving route and transports heavy objects toward a designated destination. Background Art

[0004] Automated guided vehicles (AGVs) have traditionally been used to transport heavy objects within designated areas, such as factories and warehouses. In these systems, the route (or path, or even route) that the AGV should travel within the area is specified by indicator tape. The AGV detects and follows these indicator tapes, staying on the designated route and transporting the objects to their destination within the area.

[0005] In a venue, there is a situation where the destination needs to be changed. In this case, the activity route also needs to be changed. However, when the activity route is changed, the sign strips installed on the venue need to be reinstalled, which is a heavy burden.

[0006] In particular, when an automated guided vehicle is a forklift that transports heavy objects placed on pallets along with the pallets, changes in pallet size cause changes in the spacing between the objects, leading to deviations in the destinations. Consequently, such changes often require frequent changes in destinations. Consequently, the burden of resetting the movement route, such as the indicator tape, is significant each time the pallet size is changed.

[0007] It should be noted that some autonomous guided vehicles do not follow designated routes, but instead use sensors to understand their surroundings (such as obstacles) and autonomously drive themselves toward their destination. However, in busy areas such as factories and warehouses, it is extremely dangerous if automated guided vehicles carrying heavy loads are allowed to freely roam freely. Summary of the Invention

[0008] The object of the present invention is to provide a novel unmanned transport system for transporting heavy objects to a destination on the premise of traveling on a designated activity route.

[0009] An unmanned transport system according to one embodiment of the present invention is an unmanned transport system for transporting heavy objects to a specified destination by traveling on a specified virtual activity route, and is provided with: an unmanned transport vehicle that travels in an unmanned manner according to a control signal; one or more cameras that photograph the site on which the unmanned transport vehicle is traveling from above the site and generate a still image or a dynamic image; and a driving control mechanism that generates the control signal for controlling the unmanned transport vehicle to travel on the said virtual activity route based on the still image or the dynamic image, the driving control mechanism comprising: a detection unit that detects the unmanned transport vehicle based on the still image or the dynamic image; a position grasping unit that uses the detection result of the detection unit to grasp the position of the unmanned transport vehicle in the said site without relying on sensors mounted on the unmanned transport vehicle; and a control unit that generates the control signal based on the position of the unmanned transport vehicle grasped by the position grasping unit.

[0010] In the above-mentioned unmanned transport system, the unmanned transport vehicle may be a forklift vehicle that lifts the heavy object placed on a pallet together with the pallet and transports the heavy object.

[0011] In the above-mentioned unmanned transport system, the site may be indoors, and the one or more cameras may be installed on a ceiling or a wall to shoot the site from above.

[0012] In the above-mentioned unmanned transport system, the site may be outdoors, and the one or more cameras may be installed on a building located outdoors to shoot the site from above.

[0013] In the above-mentioned unmanned guided vehicle system, the driving control mechanism may further include a direction grasping unit that grasps the direction of the unmanned guided vehicle based on the still image or the moving image, and the control unit may generate the control signal based on the direction grasped by the direction grasping unit.

[0014] In the above-mentioned unmanned transport system, the unmanned transport vehicle can perform autonomous driving to load or unload the heavy objects at the destination.

[0015] In the above-mentioned unmanned transport system, the detection unit of the driving control mechanism may further detect obstacles based on the still image or the dynamic image, and the control unit of the driving control mechanism may further generate the control signal based on the detection result of the detection unit.

[0016] In the above-mentioned unmanned guided vehicle system, the unmanned guided vehicle may further include an operating unit for a user to operate to start traveling on the activity route, and the control unit of the driving control mechanism may start generating the control signal in response to the operation of the operating unit.

[0017] In the above-mentioned unmanned transport system, there may also be a plurality of unmanned transport vehicles, each of which is assigned the destination and the imaginary activity route. The detection unit of the driving control mechanism can detect the plurality of unmanned transport vehicles based on the still image or the dynamic image, the position grasping unit of the driving control mechanism can grasp the respective positions of the plurality of unmanned transport vehicles in the site, and the control unit of the driving control mechanism can 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.

[0018] The above-mentioned unmanned guided vehicle system may include a plurality of cameras having different fields of view, and the position grasping unit may grasp the position of the unmanned guided vehicle in the site by integrating a plurality of still images or moving images generated by the plurality of cameras.

[0019] In the above-mentioned unmanned guided vehicle system, the detection unit may detect the unmanned guided vehicle using a neural network.

[0020] In the above-mentioned unmanned guided vehicle system, the upper surface of the unmanned guided vehicle may have a predetermined mark, and the detection unit may detect the unmanned guided vehicle by detecting the predetermined mark.

[0021] In the above-mentioned unmanned guided vehicle system, the driving control mechanism may store a map of the site defining the activity route, and the position grasping unit may grasp the position of the unmanned guided vehicle by mapping the unmanned guided vehicle detected by the detection unit onto the map.

[0022] The above-mentioned unmanned guided vehicle system may include a predetermined mark at a predetermined position in the site, the detection unit may detect the predetermined mark, and the position grasping unit may grasp the position of the unmanned guided vehicle based on the predetermined mark detected by the detection unit.

[0023] In the above-mentioned unmanned transport system, the detection unit of the driving control mechanism may further detect the heavy object being transported by the unmanned transport vehicle.

[0024] In the above-mentioned unmanned guided vehicle system, the unmanned guided vehicle may include: an onboard detection unit for detecting surrounding obstacles; and an emergency stop processing unit for performing an emergency stop process on the unmanned guided vehicle based on the detection of the obstacle by the onboard detection unit.

[0025] The above-mentioned unmanned guided vehicle system may further include a derailment determination mechanism, which determines whether the unmanned guided vehicle has deviated from the active route. When the derailment determination mechanism determines that the unmanned guided vehicle has deviated from the active route, the driving control mechanism generates the control signal to stop the unmanned guided vehicle or return the unmanned guided vehicle to the active route.

[0026] In the above-mentioned unmanned guided vehicle system, the derailment determination mechanism may include: an on-board camera mounted on the unmanned guided vehicle, which captures the surroundings of the unmanned guided vehicle and generates a still image or a moving image; and a determination unit which determines whether the unmanned guided vehicle has deviated from the active route based on the still image or the moving image generated by the on-board camera.

[0027] In the above-mentioned unmanned guided vehicle system, the derailment determination mechanism may include: a receiver that receives a positioning signal; and a determination unit that determines whether the unmanned guided vehicle has deviated from the moving path based on the positioning signal received by the receiver. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 1 is a top view showing a site to which the unmanned transport system according to an embodiment of the present invention is applied;

[0029] Figure 2 is a side view of a site to which the unmanned transport system according to an embodiment of the present invention is applied;

[0030] Figure 3 1 is a perspective view showing an unmanned guided vehicle in an unmanned guided vehicle system according to an embodiment of the present invention;

[0031] Figure 4 This is a block diagram showing the structure of an unmanned transport system according to an embodiment of the present invention;

[0032] Figure 5A This is a diagram showing an example of a change in an activity route according to an embodiment of the present invention;

[0033] Figure 5B This is a diagram showing an example of a change in an activity route according to an embodiment of the present invention;

[0034] Figure 6 It is a side view showing another example of a site to which the unmanned transport system according to the embodiment of the present invention is applied. DETAILED DESCRIPTION

[0035] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. It should be noted that the embodiments described below are merely examples of embodiments of the present invention and do not limit the present invention to the specific structures described below. When implementing the present invention, specific structures corresponding to the embodiments may be appropriately adopted.

[0036] Figure 1 1 is a plan view showing a site to which the unmanned transport system according to an embodiment of the present invention is applied. Figure 2 This is a side view of a site where the unmanned transport system according to an embodiment of the present invention is used. The site 50 to which the unmanned transport system (i.e., automated guided vehicle system) according to this embodiment is applied can be considered to be a factory, warehouse, or the like. In this embodiment, the unmanned transport vehicle (i.e., automated guided vehicle, AGV) 300 is a forklift vehicle that lifts and transports a heavy object 53 placed on a pallet 54 along with the pallet 54.

[0037] An automated guided vehicle 300 travels along a designated virtual route within a site 50, transporting heavy objects toward a designated destination. For example, the site 50 may contain manufacturing equipment 52, and workers 400 may be walking. These manufacturing equipment 52 and workers 400 may become obstacles as the automated guided vehicle 300 navigates the site 50. Furthermore, heavy objects 53 and pallets 54 placed within the site 50 may also become obstacles. If multiple automated guided vehicles 300 are operating within the site 50, other automated guided vehicles 300 may also become obstacles.

[0038] A site 50 is located inside a building (indoors), and multiple overhead cameras 10 are mounted on the ceiling 55. Each of the multiple overhead cameras 10 captures the site 50 from above. It should be noted that the overhead cameras 10 can be installed high up on a building wall, pillar, pole, or other structure. Furthermore, multiple markers 51 are placed within the site 50 at locations visible from the overhead cameras 10.

[0039] Each of the plurality of overhead cameras 10 is arranged so that the areas of the scene 50 that can be photographed partially overlap (see Figure 2 ), thereby, the imaging areas of the multiple overhead cameras 10 cover the entire site 50. It should be noted that the entire site 50 does not necessarily need to be captured; the site 50 may include portions not captured by any overhead camera 10. In other words, within the site 50, areas where the automated guided vehicles 300 are not planned to travel may not be within the imaging range of any overhead camera 10.

[0040] The automated guided vehicle 300 loads at the loading location and unloads at the destination, using the loading location as its starting point to transport the heavy object 53 to the destination. After completing the transport, the automated guided vehicle 300 returns to the loading location without the heavy object 53 for the next transport. At this point, the automated guided vehicle 300 moves (returns) with the unloading location as its starting point and the loading location as its destination. In the unmanned transport system of this embodiment, this transport of the heavy object 53 and the return of the automated guided vehicle 300 are performed in an unmanned manner.

[0041] A hypothetical movement route 210 is set up at the site 50. Please note that this movement route 210 is a hypothetical route, not a physical route set up at the site 50. In conventional automated guided vehicle systems where a physical movement route (hereinafter referred to as a "physical movement route") is set up at the site 50, the automated guided vehicle 300 can travel to its destination along the physical movement route by detecting the physical movement route and traveling without deviating from it.

[0042] However, in conventional automated guided vehicle systems, changing the route of the automated guided vehicle 300 requires changing the physical movement path, which is a significant operational burden. Therefore, in the automated guided vehicle system 100 of this embodiment, a virtual movement path 210 is set rather than a physical movement path, and the automated guided vehicle 300 is controlled so that it can travel along this virtual movement path 210.

[0043] Figure 3 1 is a perspective view showing an unmanned guided vehicle in an unmanned guided vehicle system according to an embodiment of the present invention. Figure 3 As shown, the front end of the automated guided vehicle 300 is equipped with a fork 330 that can move up and down. In addition, the automated guided vehicle 300 is equipped with an onboard camera 310 that can capture the front in order to capture the surroundings of the automated guided vehicle 300. In addition, a mark 350 is provided on the upper surface of the automated guided vehicle 300.

[0044] Furthermore, the automated guided vehicle 300 is provided with individual identification information, and this identification information is indicated as an identification information mark 370 on the upper surface of the automated guided vehicle 300 so that it can be captured by the overhead camera 10 above. Figure 1 In the example, two automated guided vehicles 300 are assigned identification information "1" and "2," respectively, and identification information marks 370 indicating this identification information are indicated on the top surface of the automated guided vehicles 300. It should be noted that the identification information marks 370 may be codes (e.g., barcodes, QR codes, etc.) generated by encoding the identification information.

[0045] Figure 4: is a block diagram showing the structure of an unmanned transport system according to an embodiment of the present invention. Figure 4 As shown, the unmanned guided vehicle system 100 of this embodiment includes multiple bird's-eye view cameras 10, a driving control device 20, and an unmanned guided vehicle 300. Each of the multiple bird's-eye view cameras 10 is connected to the driving control device 20 via a wired cable. The bird's-eye view cameras 10 capture the site 50 from above, where the unmanned guided vehicle 300 is traveling, and generate a dynamic image. The bird's-eye view cameras 10 transmit the generated dynamic image streams to the driving control device 20 in real time, and the driving control device 20 receives the dynamic image streams from the multiple bird's-eye view cameras 10.

[0046] It should be noted that the bird's-eye view camera 10 can be wirelessly connected to the driving control device 20 to wirelessly transmit and receive dynamic image streams. Furthermore, the bird's-eye view camera 10 can continuously capture still images and generate a series of still images, which are then transmitted to the driving control device 20 in real time. Each of the multiple bird's-eye view cameras 10 is assigned unique identification information. The driving control device 20 uses the identification information of the bird's-eye view camera 10 to determine which still image or dynamic image is being captured.

[0047] The driving control device 20 generates a control signal for controlling the automated guided vehicle 300 to travel along the virtual activity route 210 based on the still image or moving image transmitted from the bird's-eye view camera 10, and transmits the control signal to the automated guided vehicle 300. The driving control device 20 may be located within or outside the site 50, or may be located in the cloud and communicate with the bird's-eye view camera 10 and the automated guided vehicle 300 via the Internet. Furthermore, the driving control device 20 may be located in the bird's-eye view camera 10 or the automated guided vehicle 300. As such, the driving control device 20 may be located anywhere as long as it can transmit data (moving image streams, still images, control signals, etc.) between the bird's-eye view camera 10 and the automated guided vehicle 300.

[0048] The driving control device 20 includes a detection unit 21, a position grasping unit 22, a direction grasping unit 23, a control unit 24, and a storage unit 25. The detection unit 21 detects the automated guided vehicle 300 based on a still image or a 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 automated guided vehicle 300 based on each of the still images or moving images acquired by these plurality of overhead cameras 10.

[0049] The detection unit 21 inputs a still image or a moving image into the learned neural network, thereby detecting the automated guided vehicle 300 based on the still image or the moving image. Note that, if the driving control device 20 acquires moving images from the overhead camera 10, the detection unit 21 can extract frame images from the moving image at predetermined intervals and detect the automated guided vehicle 300 based on these frame images (still images).

[0050] Since a predetermined mark 350 is provided on the upper surface of the AGV 300, the detection unit 21 can use the mark 350 as a clue to detect the AGV 300 from a still image or a moving image. In other words, the detection unit 21 can detect the mark 350 provided on the AGV 300 as the AGV 300.

[0051] The detection unit 21 also detects the identification information mark 370 of the automated guided vehicle 300. Figure 1 As shown in the example of , when the identification information is represented by characters (including numbers), the detection unit 21 identifies the identification information of the detected automated guided vehicle 300 by performing character recognition on the detected identification information mark 370. Alternatively, when the identification information is represented by code information, the detection unit 21 decodes the detected identification information mark 370 to identify the identification information of the detected automated guided vehicle 300. Furthermore, the mark 350 may also serve as the identification information mark 370.

[0052] The position grasping unit 22 uses the detection results from the detection unit 21 to grasp the position of the AGV 300 within the site 50. It should be noted that although the AGV 300 is equipped with an onboard camera 310, the position grasping unit 22 does not rely on the onboard camera 310 or other onboard sensors mounted on the AGV 300. Instead, the position grasping unit 22 grasps the position of the AGV 300 within the site 50 based on detection results from still or moving images captured by the overhead camera 10.

[0053] The storage unit 25 stores a map of the site 50. This map defines the route that the automated guided vehicle 300 should travel. The position grasping unit 22 grasps the position of the automated guided vehicle 300 by mapping the automated guided vehicle 300 detected by the detection unit 21 onto this map. For this mapping, a predetermined marker 51 is placed at a predetermined location in the site 50 and captured by the overhead camera 10. The detection unit 21 detects the marker 51, and the position grasping unit 22 grasps the position of the automated guided vehicle 300 based on the marker 51 detected by the detection unit 21.

[0054] In addition, the position grasping unit 22 can integrate still images or moving images of multiple different areas obtained from multiple overhead cameras 10 based on the identification information of the overhead cameras 10, thereby generating a still image or moving image of the entire site 50, and use such an integrated image to grasp the position of the unmanned guided vehicle 300 in the site 50.

[0055] The orientation grasping unit 23 grasps the orientation of the automated guided vehicle 300 based on a still image or a moving image. The orientation grasping unit 23 inputs the still image or the moving image into a learned neural network, thereby detecting the orientation of the automated guided vehicle 300 based on the still image or the moving image. Furthermore, the orientation grasping unit 23 can grasp the orientation of the automated guided vehicle 300 by grasping the orientation of the marker 350 of the automated guided vehicle 300 detected by the detection unit 21.

[0056] The control unit 24 generates control signals for controlling the movement of the AGV 300 based on the position of the AGV 300 as determined by the position determination unit 22 and the orientation of the AGV 300 as determined by the orientation determination unit 23. Specifically, the control unit 24 generates control signals, including instructions to advance, stop, and steer, based on the position and orientation of the AGV 300, to cause the AGV 300 to travel toward the destination along the active route 210 defined on the map. The generated control signals are transmitted to the corresponding AGV 300 in real time.

[0057] The automated guided vehicle 300 receives control signals from the driving control device 20 and drives according to the control signals. The automated guided vehicle 300 includes a driving control unit 301, an elevator control unit 302, an onboard detection unit 303, an emergency stop processing unit 304, a determination unit 305, an autonomous driving processing unit 306, an operation unit 307, a driving drive unit 308, an elevator drive unit 309, an onboard camera 310, and a receiver 311.

[0058] The travel drive unit 308 includes a power source, a power transmission mechanism, a steering mechanism, a speed change mechanism, a brake mechanism, and wheels for driving the automated guided vehicle 300. The lift drive unit 309 includes a power source, a power transmission mechanism, and an auxiliary locking mechanism for securing the forks 330 in a predetermined position. The travel drive unit 308 is driven under the control of the travel control unit 301. The lift drive unit 309 is driven under the control of the lift control unit 302.

[0059] The travel control unit 301 drives the travel drive unit 308 in response to a control signal received from the driving control device 20, thereby controlling the automated guided vehicle 300 to travel along the set virtual movement route 210. In the unmanned guided vehicle system 100 of this embodiment, the travel control unit 301 and the travel drive unit 308 are all that are required for the automated guided vehicle 300 to travel along the virtual movement route 210. Other components (e.g., the onboard detection unit 303 and the onboard camera 310) are additional components.

[0060] The onboard detection unit 303 is used to bring the AGV 300 to an emergency stop. The onboard detection unit 303 may be, for example, an infrared sensor or LiDAR (laser radar). If an obstacle is ahead of the AGV 300, the onboard detection unit 303 detects the obstacle. Alternatively, the onboard detection unit 303 can also detect obstacles in all directions around the AGV 300, not just ahead of it.

[0061] If the onboard detection unit 303 detects an obstacle, the emergency stop processing unit 304 executes an emergency stop process for the automated guided vehicle 300. Specifically, the emergency stop processing unit 304 controls the travel drive unit 308 to stop generating power from the power source and apply the brakes as an emergency stop. At this time, if the vehicle were to brake suddenly, there is a risk that the pallet 54 would fall off the forks 330 and the load 53 would be detached from the automated guided vehicle 300. Therefore, the braking force is applied at a level that does not cause such an accident.

[0062] It should be noted that obstacles can also be detected by the driving control device 20, and the control unit 24 can generate a control signal based on the presence of the obstacle. In this case, the detection unit 21 detects the obstacle based on a still image or a moving image obtained by the overhead camera 10. The control unit 24 also generates a control signal based on the obstacle detection result of the detection unit 21.

[0063] In this case, in this embodiment, the AGV 300 is not controlled to deviate from the set moving path 210 and avoid obstacles. Instead, if an obstacle prevents it from traveling along the moving path 210, the AGV 300 is stopped immediately. Since the AGV 300 in this embodiment is a transport vehicle that carries heavy objects 53, it is undesirable from a safety perspective for the AGV 300 to deviate from the pre-set moving path 210 and travel in an arbitrary space. In this case, to notify the surrounding area of ​​the AGV 300 that the AGV 300 is unable to advance along the moving path 210 due to an obstacle, the AGV 300 may activate an alarm (not shown) and sound an alarm.

[0064] As described above, in the unmanned guided vehicle system 100 of this embodiment, the movement of the unmanned guided vehicle 300 is controlled based on still images or moving images obtained by the overhead camera 10, so that the unmanned guided vehicle 300 can travel along the set virtual activity route 210. If there is an obstacle in the path of the unmanned guided vehicle 300, the unmanned guided vehicle 300 automatically detects the obstacle and performs an emergency stop.

[0065] Furthermore, even if the AGV 300 is in an emergency stop state, the AGV 300 can be restarted if the control unit 24 recognizes that the event that caused the AGV 300 to reach the emergency stop state has been resolved. Conventionally, if the AGV 300 relies on manual operation to manually determine that the event that caused the AGV 300 to reach the emergency stop state has been resolved, the reliability of resuming travel from the emergency stop state is extremely low. It should be noted that the control unit 24 may recognize that the event that caused the AGV 300 to reach the emergency stop state has been resolved based on the AGV 300's onboard detection unit 303 or onboard camera 310 no longer detecting an obstacle, or may recognize that the event that caused the AGV 300 to reach the emergency stop state has been resolved based on a still image or moving image from the overhead camera 10.

[0066] As described above, it is assumed that the automated guided vehicle 300 is always traveling or stopped on the active route 210 under normal circumstances. However, it is also assumed that the automated guided vehicle 300 may derail (or become derailed) from the active route 210 for some reason. Therefore, the automated guided vehicle system 100 of this embodiment has a function for detecting derailment of the automated guided vehicle 300.

[0067] The control unit 24 determines whether the position determined by the position determination unit 22 has deviated from the active route 210 defined by the map stored in the storage unit 25. If the control unit 24 determines that the position has deviated from the active route 210, the control unit 24 generates a control signal to stop the automated guided vehicle 300 and return the automated guided vehicle 300 to the active route 210.

[0068] As described above, the driving control device 20 can determine the position of the AGV 300 based on the still or moving images from the overhead camera 10 and thereby determine derailment. However, the driving control device 20 may also include a derailment determination system that does not utilize the still or moving images from the overhead camera 10, in addition to determining the position of the AGV 300 based on the still or moving images from the overhead camera 10. Alternatively, the driving control device 20 may include a derailment determination system that does not utilize the still or moving images from the overhead camera 10, instead of determining the position of the AGV 300 based on the still or moving images from the overhead camera 10. In this case, the control unit 24 also generates a control signal to stop the AGV 300 and return it to the active route 210 in response to the derailment determination system determining that the AGV 300 has deviated from the active route 210.

[0069] The first derailment determination system comprises an onboard camera 310 and a determination unit 305. The onboard camera 310 is mounted on the AGV 300 and captures the area around the AGV 300, generating still or moving images. The determination unit 305 determines whether the AGV 300 has deviated from the active route 210 based on the still or moving images generated by the onboard camera 310. Specifically, the determination unit 305 determines whether the AGV 300 has derailed by determining whether the image captured by the onboard camera 310 is the image that would be captured if the AGV 300 were located on the active route 210.

[0070] The second derailment determination system is composed of a receiver 311 and a determination unit 305. Receiver 311 receives a positioning signal transmitted into site 50. The positioning signal is generated within site 50. Various conventional indoor positioning technologies have been proposed and employed, and any conventional indoor positioning technology can be employed as the second derailment determination system.

[0071] For example, receiver 311 can receive WiFi (wireless network communication technology) waves as positioning signals. In this case, site 50 is equipped with multiple base stations that transmit WiFi waves. Receiver 311 receives WiFi waves from these multiple base stations. Determination unit 305 determines the position of automated guided vehicle 300 based on the differences in the strength of the WiFi waves received by receiver 311 from the multiple base stations. Determination unit 305 then determines whether automated guided vehicle 300 has deviated from route 210 as defined on the map by mapping the position onto the map defining route 210.

[0072] Furthermore, for example, the receiver 311 can receive positioning signals from beacons installed within the site 50. In this case, multiple beacons are installed within the site 50. The determination unit 305 determines the position of the automated guided vehicle 300 within the site 50 based on the strength of the positioning signals received from each of the multiple beacons, and determines whether the automated guided vehicle 300 has deviated from the route 210 defined on the map by mapping the position onto the map defining the route 210.

[0073] The derailment determination system can use any other conventional positioning technology, such as positioning using magnetic sensors, positioning using IMES (Indoor MEssaging System) based on the same principle as GPS (Global Positioning System), positioning using PDR (Pedestrian Dead Reckoning), positioning using visible light, and positioning using ultrasonic waves, to determine derailment.

[0074] As described above, in the automated guided vehicle system 100 of this embodiment, the automated guided vehicle 300 can be controlled to travel on the virtual active route 210 in principle, and even if it derails for some reason, the derailment can be detected and the travel of the automated guided vehicle 300 can be controlled so as to return to the active route 210.

[0075] When the automated guided vehicle 300 is transporting a heavy object 53, the heavy object 53 is loaded onto the automated guided vehicle 300 at the departure location and unloaded from the automated guided vehicle 300 at the destination. Furthermore, when the automated guided vehicle 300 is returned from the unloading location to the loading location, the heavy object 53 is unloaded from the automated guided vehicle 300 at the departure location and loaded onto the automated guided vehicle 300 at the destination.

[0076] The loading and unloading of cargo at the departure and destination points can be performed autonomously by the automated guided vehicle 300. The autonomous driving processing unit 306 of the automated guided vehicle 300 performs autonomous driving to load and unload the heavy object 53 at the departure and destination points. Therefore, upon returning to the departure point, the autonomous driving processing unit 306 analyzes the image from the onboard camera 310 and detects the heavy object 53 to be loaded. Based on the detected heavy object 53, the autonomous driving processing unit 306 controls the travel drive unit 308 and the lift drive unit 309 to perform loading.

[0077] Furthermore, when the autonomous driving processing unit 306 reaches the destination during transport driving, it analyzes images from the vehicle-mounted camera 310 and detects the location where the cargo should be unloaded. Based on the detected location, the autonomous driving processing unit 306 controls the travel drive unit 308 and the lift drive unit 309 to unload the cargo.

[0078] The automated guided vehicle 300 includes an operating unit 307, which is used by a user to initiate travel on the active route 210. When the user operates the operating unit 307 to initiate travel, an operation signal is transmitted from the automated guided vehicle 300 to the driving control device 20. Upon receiving this operation signal, the control unit 24 begins generating a control signal. As described above, the control unit 24 can initiate travel control in response to this operation signal, regardless of whether loading or unloading is being performed by autonomous driving or manually. The operating unit 307 can be a terminal independent of the automated guided vehicle 300, such as a tablet terminal. Furthermore, when loading or unloading is being performed by autonomous driving, travel can be automatically initiated after loading or unloading is completed, without responding to an operation signal from the operating unit 307.

[0079] As described above, the site 50 is equipped with multiple automated guided vehicles 300, each assigned a different destination and route. The driving control device 20 controls the multiple automated guided vehicles 300 simultaneously. Therefore, the detection unit 21 detects the multiple automated guided vehicles 300 based on still or moving images from the overhead camera 10. Furthermore, the position grasping unit 22 grasps the positions of the multiple automated guided vehicles 300 in the site 50. Furthermore, the control unit 24 generates control signals for each of the multiple automated guided vehicles 300 based on the multiple positions grasped by the position grasping unit 22.

[0080] Therefore, multiple AGVs 300 can be controlled simultaneously in a single site 50. Furthermore, by treating other AGVs 300 as obstacles, when another AGV 300 is ahead of a particular AGV 300, the other AGV 300 can be detected as an obstacle, causing the particular AGV 300 to come to an emergency stop. Consequently, the virtual movement routes 210 set for multiple AGVs 300 can be set to intersect with each other.

[0081] Furthermore, in the above-described embodiment, when simultaneously controlling multiple automated guided vehicles 300, identification information marks 370 are provided on the top surfaces of the automated guided vehicles 300. The driving control device 20 detects the identification information marks 370 based on still or moving images from the overhead camera 10, thereby determining the position of each automated guided vehicle 300 and generating a control signal for each automated guided vehicle 300. In other words, the identification information marks 370 are utilized to individually control each automated guided vehicle 300. Alternatively, the automated guided vehicles 300 may be configured without the identification information marks 370.

[0082] In this case, the AGV 300 transmits the onboard camera image from the onboard camera 310 to the driving control device 20. The control unit 24 of the driving control device 20 analyzes the onboard camera image to identify the location of the AGV 300 from which the image originates. This allows the driving control device 20 to identify the AGV 300 detected by the image from the bird's-eye view camera 10 and the AGV 300 that transmitted the onboard camera image as the same AGV 300. This allows the driving control device 20 to transmit control signals to each AGV 300 detected by the image from the bird's-eye view camera 10.

[0083] It should be noted that the detection unit 21 can not only detect the AGV 300 based on still or moving images, but can also detect the load being carried by the AGV 300. This makes it possible to confirm whether the AGV 300 is carrying the load 53, that is, whether it is in the process of carrying the load or returning it, and whether the load 53 being carried has fallen from the AGV 300.

[0084] As described above, the automated guided vehicle system 100 of this embodiment uses the bird's-eye view camera 10 to monitor the position of the automated guided vehicle 300 and controls the movement of the automated guided vehicle 300 by comparing it with a map. This allows the automated guided vehicle 300 to travel from its departure point to its destination along a virtual route 210, rather than a physical route. This is particularly advantageous when a route change is necessary. This is because the route change does not require physical movement within the site 50; it can simply be made on the map. Next, the process of changing a route will be described.

[0085] Figure 5A as well as Figure 5B : is a diagram showing an example of a change in an activity route according to an embodiment of the present invention. Figure 5A In the example, the smaller pallet 54 (heavy object 53) is the transport object. Figure 5B In the example, the larger pallet 54 (heavy object 53) is the transport object, and therefore, at the destination, when the heavy objects 53 are arranged for storage, the distances between adjacent heavy objects 53, that is, the distances between the movement routes 210 of adjacent heavy objects toward the storage place (destination) are different from each other. Figure 5A In the example of FIG. 1 , the distance between the activity routes 210a toward the destination, ie, the storage location, is short. Figure 5B In the example of FIG, the distance between the activity routes 210b toward the destination, ie, the storage location, is longer.

[0086] In the state where the heavy object 53 is transported in such a site 50 or even a heavy object 53, if the size of the pallet 54 (heavy object 53) changes, the distance between the moving paths 210 also needs to be changed. For example, if the size of the pallet 54 (heavy object 53) becomes larger, the distance between the moving paths 210 also needs to be increased, such as from Figure 5A The activity route 210a shown is changed to Figure 5B Even in such a case, according to this embodiment, since both the activity route 210a and the activity route 210b are not physically set in the actual site 50 but are defined on the map stored in the storage unit 25, they can be easily changed.

[0087] Figure 6 This is a side view showing another example of a location where the unmanned transport system according to an embodiment of the present invention can be used. While the above embodiment describes an example where the location 50 is located inside a building and the bird's-eye view camera 10 is mounted on the ceiling 55, the unmanned transport system 100 according to this embodiment can also be used outdoors. However, in this case, since there is no ceiling, the bird's-eye view camera 10 is installed at a high point on a tall structure, such as a pole 56 or an outer wall of the building, to capture the location 50.

[0088] (Variation)

[0089] The control unit 24 can control the speed of the automated guided vehicle 300 based on the still or moving images from the overhead camera 10. The detection unit 21 detects the automated guided vehicle 300 to be controlled and obstacles (including workers 400, manufacturing equipment 52, stored heavy objects 53, other automated guided vehicles 300, etc.) based on the still or moving images from the overhead camera 10. If there are no obstacles within a specified range around the automated guided vehicle 300 to be controlled, the control unit 24 generates a control signal to increase the driving speed. Alternatively, since the automated guided vehicle 300 is traveling on the active route 210, the control unit 24 can determine whether there are any obstacles within a specified range along the active route 210 from the automated guided vehicle 300.

[0090] In this way, by ensuring the safety of the area surrounding the automated guided vehicle 300 and increasing its speed, the transport operation cycle can be shortened. This can effectively improve production efficiency in factories. It should be noted that speed control can be implemented, for example, so that the automated guided vehicle 300 travels at a lower speed when moving forward with the forks 330 in front, and travels at a higher speed when moving backward toward the side opposite the forks 330.

[0091] As described above, even when speed control is performed to vary depending on the presence of obstacles, control based on still or moving images from the bird's-eye view camera 10 is effective. Specifically, when sensors mounted on the automated guided vehicle 300 (such as onboard cameras and LiDAR) are used to detect obstacles and verify safety, there are cases where obstacles cannot be detected due to blind spots. Furthermore, there are cases where distant obstacles cannot be detected, making safety impossible. Therefore, by utilizing the bird's-eye view camera 10, it is possible to set a required range around the automated guided vehicle 300 and verify the presence of obstacles within that range.

[0092] Furthermore, regardless of whether there are obstacles around the AGV 300, a speed can be set for each section of the route defined on the map. Based on the position of the AGV 300, a control signal corresponding to the speed set on the map can be generated. For example, a faster speed can be set in sections that do not intersect the routes 210 of other AGVs 300, while a slower speed can be set in sections that intersect the routes 210 of other AGVs 300 or cross areas where workers 400 travel.

[0093] It should be noted that the aforementioned driving control device 20 can be implemented by a computer, and the detection unit 21, position detection unit 22, orientation detection unit 23, and control unit 24 can be functions implemented by a processor executing one or more driving control programs of this embodiment. Furthermore, the driving control unit 301, elevator control unit 302, emergency stop processing unit 304, determination unit 305, and autonomous driving processing unit 306 of the unmanned guided vehicle 300 can be functions implemented by a processor executing one or more unmanned transport programs of this embodiment. Furthermore, the driving control unit 301, elevator control unit 302, emergency stop processing unit 304, determination unit 305, and autonomous driving processing unit 306 do not necessarily need to be located on the unmanned guided vehicle 300; they can be located on, for example, a cloud-based service provider, enabling communication between the unmanned guided vehicle 300 and the service provider.

[0094] In the above embodiment, the automated guided vehicle 300 is a forklift, but the automated guided vehicle 300 is not limited thereto and may be, for example, a truck or even a flatbed type transporter. In this case, loading and unloading can be performed by the operator 400.

[0095] Explanation of symbols:

[0096] 10 Overhead Camera

[0097] 20 Driving Controls

[0098] 21 Testing Department

[0099] 22 Position Control Unit

[0100] 23 Towards the control part

[0101] 24 Control Department

[0102] 25 Storage

[0103] 50 venues

[0104] 51 Mark

[0105] 52 Manufacturing Equipment

[0106] 53 Heavy Objects

[0107] 210 Activity Route

[0108] 300 Automated Guided Vehicles

[0109] 301 Driving Control Unit

[0110] 302 Elevator Control Department

[0111] 304 Emergency Stop Processing Department

[0112] 305 Judgment Department

[0113] 306 Autonomous Driving Processing Department

[0114] 307 Operation Department

[0115] 308 Travel Drive Unit

[0116] 309 Elevator Drive Unit

[0117] 310 Car Camera

[0118] 311 Receiver

[0119] 330 Fork

[0120] 350 mark

[0121] 370 Identification Information Sign

[0122] 400 operators.

Claims

1. An unmanned transport system that moves along a designated virtual movement route and transports heavy objects toward a designated destination, and comprises: An unmanned guided vehicle (AGV) that drives in an unmanned manner according to control signals; One or more cameras, which shoot the site where the automated guided vehicle is traveling from above the site and generate still images or dynamic images; as well as a driving control unit that generates the control signal for controlling the automated guided vehicle to travel along the imaginary activity route based on the still image or the dynamic image, The driving control mechanism comprises: a detection unit configured to detect the AGV based on the still image or the dynamic image; a position grasping unit that grasps the position of the AGV in the site using the detection result of the detection unit without relying on sensors mounted on the AGV; as well as A control unit generates the control signal based on the position of the automated guided vehicle grasped by the position grasping unit.

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

3. The unmanned transport system according to claim 1, wherein: The venue is indoors, The one or more cameras are installed on the ceiling or the wall to shoot the site from above.

4. The unmanned transport system according to claim 1, wherein: The venue is outdoors, The one or more cameras are mounted on a structure arranged outdoors to photograph the site from above.

5. The unmanned transport system according to claim 1, wherein: The driving control mechanism further includes a direction grasping unit for grasping the direction of the automated guided vehicle based on the still image or the moving image. The control unit also generates the control signal based on the orientation grasped by the orientation grasping unit.

6. The unmanned transport system according to claim 1, wherein: The unmanned guided vehicle performs autonomous driving to load or unload the heavy object at the destination.

7. The unmanned transport system according to claim 1, wherein: The detection unit of the driving control mechanism further detects obstacles based on the still image or the moving image. The control unit of the driving control mechanism further generates the control signal based on the detection result of the detection unit.

8. The unmanned transport system according to claim 1, wherein: The automated guided vehicle further includes an operating unit for a user to operate to start traveling on the activity route. The control portion of the driving control mechanism starts generating the control signal in response to the operation of the operation portion.

9. The unmanned transport system according to claim 1, wherein: The plurality of automated guided vehicles are provided, each of which is assigned the destination and the imaginary movement route. The detection unit of the driving control mechanism detects the plurality of automated guided vehicles based on the still image or the moving image. The position grasping unit of the driving control mechanism grasps the respective positions of the plurality of automated guided vehicles in the site. The control unit of the driving control mechanism generates the control signal for each of the plurality of automated guided vehicles based on the plurality of positions grasped by the position grasping unit.

10. The unmanned transport system according to claim 1, wherein: having a plurality of cameras with different fields of view, The position grasping unit grasps the position of the automated guided vehicle in the site by integrating a plurality of still images or moving images generated by the plurality of cameras.

11. The unmanned transport system according to claim 1, wherein: The detection unit detects the automated guided vehicle using a neural network.

12. The unmanned transport system according to claim 1, wherein: The upper surface of the automated guided vehicle has a prescribed mark. The detection unit detects the automated guided vehicle by detecting the predetermined mark.

13. The unmanned transport system according to claim 1, wherein: The driving control mechanism stores a map of the venue defining the active route, The position grasping unit grasps the position of the automated guided vehicle by mapping the automated guided vehicle detected by the detection unit on the map.

14. The unmanned transport system according to claim 1, wherein: The specified location of the site has a specified mark, The detection unit detects the predetermined mark, The position grasping unit grasps the position of the automated guided vehicle based on the predetermined mark detected by the detecting unit.

15. The unmanned transport system according to claim 1, wherein: The detection unit of the driving control mechanism further detects the heavy object being transported by the automated guided vehicle.

16. The unmanned transport system according to claim 1, wherein: The unmanned guided vehicle has: An onboard detection unit for detecting surrounding obstacles; and An emergency stop processing unit performs an emergency stop process on the automated guided vehicle based on the detection of the obstacle by the on-board detection unit.

17. The unmanned transport system according to claim 1, wherein: It also includes a derailment determination mechanism for determining whether the unmanned guided vehicle has deviated from the activity route. When the derailment determination unit determines that the automated guided vehicle has deviated from the active route, the driving control unit generates the control signal to stop the automated guided vehicle or return the automated guided vehicle to the active route.

18. The unmanned transport system according to claim 17, wherein: The derailment determination mechanism comprises: a vehicle-mounted camera mounted on the AGV to capture the surroundings of the AGV and generate still or moving images; and A determination unit determines whether the automated guided vehicle has deviated from the movement route based on the still image or the moving image generated by the vehicle-mounted camera.

19. The unmanned transport system according to claim 17, wherein: The derailment determination mechanism comprises: a receiver that receives a positioning signal; and A determination unit determines whether the automated guided vehicle has deviated from the movement route based on the positioning signal received by the receiver.

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