Automated Transport System

Abstract

To provide an unmanned conveying system capable of suppressing the reduction of an operation rate of an unmanned conveying vehicle whose traveling is interrupted by an obstacle.SOLUTION: An unmanned conveying system 1 includes: an unmanned conveying vehicle 10 that conveys a cargo A; an obstacle sensor 20 that detects an obstacle B which interrupts traveling of the unmanned conveying vehicle 10; multiple kinds of unmanned machines 2 configured to be able to lift up an object; and an obstacle addressing device 60 that selects, from among the multiple kinds of unmanned machines 2, an obstacle addressing machine (e.g., an unmanned clamp lift 30, an unmanned forklift 40 or a drone 50) that eliminates the obstacle B based on a detection result of the obstacle B by the obstacle sensor 20. The obstacle addressing machine selected from the multiple kinds of unmanned machines 2 lifts up the obstacle B, and moves the obstacle B to a location that does not interrupt the traveling of the unmanned conveying vehicle 10.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to an unmanned transport system equipped with an obstacle handling device. [Background technology]

[0002] Generally, an unmanned guided vehicle such as an unmanned forklift that travels on a road surface to transport cargo has an obstacle sensor that detects obstacles on the road surface that impede its travel, and is configured to stop traveling when an obstacle is detected (see, for example, Patent Document 1). In addition, generally, the unmanned guided vehicle is configured to notify a person of the stoppage of the unmanned guided vehicle due to an obstacle, and the unmanned guided vehicle is configured to resume traveling when a person who recognizes that the unmanned guided vehicle has stopped removes the obstacle.

[0003] However, if there is a delay in humans removing the obstacle, it will take a long time for the automated guided vehicle to stop moving and then resume moving again, which will reduce the operating rate of the automated guided vehicle. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2007-269452 A Summary of the Invention [Problem to be solved by the invention]

[0005] The present invention has been made in consideration of the above circumstances, and an object of the present invention is to provide an automatic guided vehicle system that can suppress a decrease in the operating rate of an automatic guided vehicle whose travel is hindered by an obstacle. [Means for solving the problem]

[0006] In order to solve the above problems, the unmanned transport system of the present invention comprises an unmanned transport vehicle that travels on a road surface to transport luggage, an obstacle sensor that detects obstacles on the road surface that impede the travel of the unmanned transport vehicle, multiple types of unmanned vehicles configured to be capable of lifting objects, and an obstacle dealing device that selects an obstacle dealing machine from the multiple types of unmanned vehicles that is capable of lifting the obstacle based on the detection result of the obstacle by the obstacle sensor, and is characterized in that the obstacle dealing machine selected from the multiple types of unmanned vehicles lifts the obstacle and evacuates the obstacle to a location that does not impede the travel of the unmanned transport vehicle.

[0007] In addition, it is preferable that the system further includes a storage device that stores a learning model generated by machine learning using data related to the shape of the object and data related to the drone capable of lifting the object as training data, and the obstacle dealing device selects the obstacle dealing machine based on the data related to the shape of the obstacle included in the obstacle detection result and the learning model.

[0008] It is also preferable that the multiple types of unmanned aerial vehicles include an unmanned clamp lift that clamps and lifts an object horizontally.

[0009] It is also preferable that the multiple types of unmanned vehicles include an unmanned forklift that inserts forks into objects to lift them up.

[0010] It is also preferable that the multiple types of unmanned aerial vehicles include a drone that flies while holding an object. Effect of the Invention

[0011] According to the present invention, it is possible to provide an automatic guided vehicle system that can remove obstacles without relying on humans and can suppress a decrease in the operating rate of the automatic guided vehicle. [Brief description of the drawings]

[0012] [Figure 1] 1 is a schematic configuration diagram of an automated guided vehicle system according to an embodiment of the present invention; [Diagram 2] 13 is a flowchart showing an obstacle removal process according to the embodiment. [Diagram 3] 13(A) to 13(C) are schematic diagrams showing the process of an unmanned clamp lift lifting an obstacle. [Figure 4] 13(A) to 13(C) are schematic diagrams showing a process in which an unmanned forklift lifts an obstacle. [Diagram 5] (A) to (C) are schematic diagrams showing the process of a drone lifting an obstacle. [Figure 6] 13 is a flowchart showing an obstacle removing process according to a modified example. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] An automated guided vehicle system 1 according to an embodiment of the present invention will be described with reference to FIGS. As shown in FIG. 1, the unmanned transport system 1 includes an unmanned transport vehicle 10, an obstacle sensor 20, multiple types of unmanned vehicles 2 (an unmanned clamp lift 30, an unmanned forklift 40, and a drone 50), an obstacle handling device 60, and a memory device 70.

[0014] The automated guided vehicle 10 is a moving body that travels on a road surface R and transports a load A. In this embodiment, the automated guided vehicle 10 is an unmanned forklift equipped with a fork 11. The unmanned forklift is a forklift that can move without being operated by an operator, and includes a manned / unmanned forklift that operates in an unmanned mode.

[0015] The obstacle sensor 20 detects an obstacle B on the road surface R that impedes the travel of the automated guided vehicle 10 by detecting an object present around the automated guided vehicle 10 or on the travel path of the automated guided vehicle 10. The obstacle sensor 20 detects, for example, the size, shape, position, etc. of the obstacle B, and outputs the detection result. In this embodiment, the obstacle sensor 20 is provided in the automated guided vehicle 10.

[0016] Each of the multiple types of unmanned aerial vehicles 2 is a mobile body configured to be autonomously mobile and capable of lifting an object. In this embodiment, the multiple types of unmanned aerial vehicles 2 include an unmanned clamp lift 30, an unmanned forklift 40, and a drone 50. The unmanned clamp lift 30 is a cargo handling vehicle equipped with a pair of left and right liftable clamps 31, and lifts an object by clamping it with the clamps 31 from a horizontal direction. The unmanned forklift 40 is a cargo handling vehicle equipped with a pair of left and right liftable forks 41, and inserts the forks 41 into an object to lift it. The drone 50 is an unmanned airplane equipped with a holding mechanism 51 that holds an object, and flies while holding the object with the holding mechanism 51.

[0017] The obstacle handling device 60 is a computer configured to be able to communicate directly or indirectly with the automated guided vehicle 10, the obstacle sensor 20, the automated clamp lift 30, the automated forklift 40, and the drone 50. In this embodiment, the obstacle handling device 60 is provided in the automated guided vehicle 10. The obstacle handling device 60 selects an obstacle handling machine (hereinafter referred to as a "handling machine 2A") capable of lifting the obstacle B from among multiple types of unmanned vehicles 2 based on the detection result of the obstacle B by the obstacle sensor 20. Specifically, in this embodiment, the obstacle handling device 60 estimates an unmanned vehicle capable of appropriately lifting the obstacle B based on data related to the shape of the obstacle B included in the detection result of the obstacle B and a learning model stored in the storage device 70, and selects the unmanned vehicle as the handling machine 2A.

[0018] In addition, if an obstacle avoidance route exists that allows the unmanned guided vehicle 10 to avoid obstacle B, it is preferable that the obstacle handling device 60 selects the obstacle avoidance route and that the unmanned guided vehicle 10 travels along the obstacle avoidance route until obstacle B is removed.

[0019] The storage device 70 stores a learning model for selecting the countermeasure vehicle 2A. In this embodiment, the storage device 70 is provided in the obstacle countermeasure device 60. The learning model stored in the storage device 70 is a model generated by machine learning using data related to the shape of an object and data related to a drone capable of appropriately lifting the object as teacher data.

[0020] The photographing device 80 recognizes the obstacle B by photographing the obstacle B. By photographing the obstacle B with the photographing device 80, the shape and dimensions of the obstacle B can be recognized, and the optimum location for holding the obstacle B, the fork insertion port, etc. can be recognized. In this embodiment, the photographing device 80 is provided in each of the multiple types of unmanned aerial vehicles 2.

[0021] Next, an obstacle removal process when an obstacle B is detected by the obstacle sensor 20 will be described with reference to Figures 2 to 5. Figures 3 to 5 show the state when the coping machine 2A lifts up the obstacle B and moves it.

[0022] First, the obstacle handling device 60 acquires data relating to the form of the obstacle B (specifically, the shape and dimensions of the obstacle B) included in the detection result of the obstacle B from the obstacle sensor 20 (step S1).

[0023] Next, the obstacle dealing device 60 selects a countermeasure unit 2A capable of appropriately lifting the obstacle B from among a plurality of types of unmanned vehicles 2 based on the data related to the shape of the obstacle acquired in step S1 and the learning model stored in the storage device 70 (step S2). In step S2, for example, when the obstacle B is small in size, a drone 50 is selected as the countermeasure unit 2A, when the obstacle B has a fork insertion port (not shown), an unmanned forklift 40 is selected as the countermeasure unit 2A, and when the obstacle B is other than those, an unmanned clamp lift 30 is selected as the countermeasure unit 2A.

[0024] Next, the obstacle dealing device 60 transmits an obstacle removal command signal to the dealing machine 2A selected in step S2 to command the dealing machine 2A to remove the obstacle B (step S3). The obstacle removal command signal includes information related to the location of the obstacle B.

[0025] Next, the countermeasure unit 2A that receives the obstacle removal command signal moves autonomously based on information related to the location of obstacle B, moves to the location of obstacle B (step S4), recognizes obstacle B with the photographing device 80, lifts up obstacle B and moves (step S5).

[0026] Specifically, when the countermeasure machine 2A is an unmanned clamp lift 30, the unmanned clamp lift 30 holds the obstacle B with the clamp 31 (see FIG. 3(A)), raises the clamp 31 to lift the obstacle B (see FIG. 3(B)), and travels on the road surface R with the obstacle B lifted (see FIG. 3(C)). When the countermeasure machine 2A is an unmanned forklift 40, the unmanned forklift 40 inserts the fork 41 into the fork insertion port of the obstacle B (see FIG. 4(A)), raises the fork 41 to lift the obstacle B (see FIG. 4(B)), and travels on the road surface R with the obstacle B lifted (see FIG. 4(C)). When the countermeasure machine 2A is a drone 50, the drone 50 holds the obstacle B with the holding mechanism 51 (see FIG. 5(A)), rises to lift the obstacle B (see FIG. 5(B)), and flies on the road surface R (see FIG. 5(C)).

[0027] In this manner, the countermeasure machine 2A, which is any one of the unmanned clamp lift 30, the unmanned forklift 40, and the drone 50, lifts the obstacle B and evacuates the obstacle B to a place that does not interfere with the travel of the unmanned guided vehicle 10. The place where the obstacle B is evacuated is preferably a predetermined place.

[0028] The present embodiment provides the following effects. (1) The obstacle handling device 60 selects a handling machine 2A that removes the obstacle B from among multiple types of unmanned vehicles 2 (unmanned clamp lift 30, unmanned forklift 40, and drone 50) based on the detection result of the obstacle B by the obstacle sensor 20, and the handling machine 2A selected from the multiple types of unmanned vehicles 2 lifts the obstacle B and evacuates the obstacle B to a place that does not interfere with the travel of the unmanned transport vehicle 10. Therefore, since the obstacle B can be removed without relying on a person, the travel of the unmanned transport vehicle 10 can be quickly resumed, thereby suppressing a decrease in the operating rate of the unmanned transport vehicle 10. In addition, by selecting a handling machine 2A for evacuating the obstacle B from among multiple types of unmanned vehicles 2, the obstacle B can be evacuated using the unmanned vehicle 2 that is optimal for lifting the obstacle B.

[0029] (2) The obstacle dealing device 60 selects the dealing unit 2A based on data relating to the shape of obstacle B contained in the detection result of obstacle B and a learning model generated by machine learning. Therefore, by updating the learning model, the obstacle dealing device 60 can be configured to more appropriately select the dealing unit 2A that is optimal for lifting obstacle B.

[0030] (3) Since the multiple types of unmanned vehicles 2 include an unmanned clamp lift 30, when removing an obstacle B that does not have a fork insertion port, the obstacle B can be lifted and moved aside by the clamps 31 of the unmanned clamp lift 30.

[0031] (4) The multiple types of unmanned vehicles 2 include an unmanned forklift 40, so when removing an obstacle B having a fork insertion port, the obstacle B can be lifted up and removed by the forks 41 of the unmanned forklift 40.

[0032] (5) Since the multiple types of unmanned vehicles 2 include a drone 50, when removing a small-sized obstacle B, the obstacle B can be evacuated more quickly using the drone 50 than when the obstacle B is evacuated using the unmanned clamp lift 30.

[0033] The present invention is not limited to the above embodiment, and the above configurations can be modified. For example, the following modifications can be made, or the following modifications can be combined to make the present invention.

[0034] The obstacle handling device 60 may select the handling unit 2A without using a learning model, so long as it can select the handling unit 2A capable of appropriately lifting the obstacle B. The obstacle removal process according to this modification will be described with reference to Fig. 6. Note that the same steps as the obstacle removal process described in the above embodiment (i.e., steps S1, S4, S5) will not be described.

[0035] 6, the obstacle dealing device 60 determines whether the obstacle B is small (whether it is within a predetermined dimensional range) based on the data acquired in step S1 (step S21). If the obstacle dealing device 60 determines that the obstacle B is not small (step S21: NO), it determines whether the obstacle B has a fork insertion port based on the data acquired in step S1 (step S22).

[0036] When the obstacle handling device 60 determines that the obstacle B is small (step S21: YES), it selects the drone 50 as the handling unit 2A (step S23). When the obstacle handling device 60 determines that the obstacle B has a fork insertion port (step S22: YES), it selects the unmanned forklift 40 as the handling unit 2A (step S24), and when the obstacle handling device 60 determines that the obstacle B does not have a fork insertion port (step S22: NO), it selects the unmanned clamp lift 30 as the handling unit 2A (step S25).

[0037] In step S3 of this modification, the obstacle dealing device 60 transmits an obstacle removal command signal to the dealing machine 2A selected in any one of steps S23 to S25. In this manner, it is also possible to select the dealing machine 2A corresponding to the obstacle B without using a learning model generated by machine learning.

[0038] The automated guided vehicle 10 does not have to be an unmanned forklift as long as it travels on the road surface R to transport cargo. In addition, the unmanned machine 2 may be configured as a moving body other than the unmanned clamp lift 30, the unmanned forklift 40, and the drone 50.

[0039] The obstacle sensor 20 does not have to be provided on the automated guided vehicle 10 as long as it can detect an obstacle B on the road surface R. For example, the obstacle sensor 20 can be provided at a predetermined point so as to detect an object present on the travel path of the automated guided vehicle 10.

[0040] The obstacle handling device 60 does not have to be provided in the unmanned guided vehicle 10 as long as the handling device 2A can be selected from a plurality of types of unmanned vehicles 2. For example, the obstacle handling device 60 can be provided in a management device (not shown) that remotely manages the unmanned guided vehicle 10.

[0041] If the countermeasure unit 2A is unable to lift and move the obstacle B in step S5, the countermeasure unit 2A may transmit an unremovable report signal to the obstacle countermeasure device 60 to report that the obstacle B cannot be removed, and the obstacle countermeasure device 60 may select an obstacle-free route based on receiving the unremovable report signal. In this case, the obstacle countermeasure device 60 may select an unmanned vehicle 2 of a different type from the countermeasure unit 2A that transmitted the unremovable report signal as a new countermeasure device 2A. Also, when the obstacle countermeasure device 60 receives the unremovable report signal, it may request a person to remove the obstacle B. [Explanation of symbols]

[0042] 1. Automated guided transport system 2 drone 10 Automated Guided Vehicle 11. Fork 20 Obstacle Sensor 30 Unmanned Clamp Lift (Unmanned Vehicle) 31 Clamp 40 Unmanned Forklift (Drone) 41 Fork 50 Drones 51 Retention mechanism 60 Obstacle handling device 70 Storage device 80 Imaging Equipment A. Luggage B Obstacle R Road surface

Claims

1. An automated guided vehicle that travels on roads to transport luggage; an obstacle sensor that detects an obstacle on the road surface that impedes travel of the automated guided vehicle; A plurality of types of unmanned aerial vehicles configured to be capable of lifting objects; an obstacle dealing device that selects an obstacle dealing machine capable of lifting the obstacle from among the plurality of types of unmanned vehicles based on a result of the detection of the obstacle by the obstacle sensor; The obstacle countermeasure machine selected from the plurality of types of unmanned vehicles lifts the obstacle and moves the obstacle away to a location where it does not interfere with the travel of the unmanned transport vehicle. The unmanned transport system is characterized by the above-mentioned.

2. The method further includes a storage device that stores a learning model generated by machine learning using data related to the shape of an object and data related to a drone capable of lifting the object as training data; The obstacle dealing device selects the obstacle dealing machine based on data related to the shape of the obstacle included in the obstacle detection result and the learning model.

2. The automated guided vehicle system according to claim 1 .

3. The multiple types of drones include an unmanned clamp lift that clamps and lifts objects horizontally.

3. The automated guided vehicle system according to claim 1 or 2.

4. The multiple types of drones include an unmanned forklift that inserts forks into objects to lift them up.

3. The automated guided vehicle system according to claim 1 or 2.

5. The multiple types of unmanned aerial vehicles include a drone that flies while holding an object.

3. The automated guided vehicle system according to claim 1 or 2.

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