EP4389681A1 - Erkennung von lastanomalien - Google Patents

Erkennung von lastanomalien Download PDF

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Publication number
EP4389681A1
EP4389681A1 EP23214096.2A EP23214096A EP4389681A1 EP 4389681 A1 EP4389681 A1 EP 4389681A1 EP 23214096 A EP23214096 A EP 23214096A EP 4389681 A1 EP4389681 A1 EP 4389681A1
Authority
EP
European Patent Office
Prior art keywords
load
control unit
forklift truck
target load
touchscreen
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
EP23214096.2A
Other languages
English (en)
French (fr)
Inventor
Tommaso PESSO
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Toyota Material Handling Manufacturing Italy SpA
Original Assignee
Toyota Material Handling Manufacturing Italy SpA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Toyota Material Handling Manufacturing Italy SpA filed Critical Toyota Material Handling Manufacturing Italy SpA
Publication of EP4389681A1 publication Critical patent/EP4389681A1/de
Pending legal-status Critical Current

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Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66F—HOISTING, LIFTING, HAULING OR PUSHING, NOT OTHERWISE PROVIDED FOR, e.g. DEVICES WHICH APPLY A LIFTING OR PUSHING FORCE DIRECTLY TO THE SURFACE OF A LOAD
    • B66F9/00—Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes
    • B66F9/06—Devices for lifting or lowering bulky or heavy goods for loading or unloading purposes movable, with their loads, on wheels or the like, e.g. fork-lift trucks
    • B66F9/063—Automatically guided
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B66—HOISTING; LIFTING; HAULING
    • B66F—HOISTING, LIFTING, HAULING OR PUSHING, NOT OTHERWISE PROVIDED FOR, e.g. DEVICES WHICH APPLY A LIFTING OR PUSHING FORCE DIRECTLY TO THE SURFACE OF A LOAD
    • B66F17/00—Safety devices, e.g. for limiting or indicating lifting force
    • B66F17/003—Safety devices, e.g. for limiting or indicating lifting force for fork-lift trucks

Definitions

  • the present disclosure relates to a forklift truck.
  • the present disclosure relates to a forklift truck capable of recognizing an anomaly of a load to be picked up.
  • a forklift truck including a mast and lifting element that is mounted on the mast so as to be slidable along the mast, wherein the lifting element is configured to lift a load.
  • a forklift truck can be used in a ware storage, at an industrial site and the like.
  • a forklift truck with an assisted driving function in which a certain task usually performed by a user of the forklift truck is at least partially automated.
  • This type of forklift trucks can be configured to semiautomatically perform an operation, such as a driving operation and a loading operation for picking up a load from a shelf.
  • an anomalous load may comprise a ware and a movable load support, wherein the movable load support is damaged. There is, therefore, the danger that the movable load support may break when the anomalous load is picked up which may result in the anomalous load falling down from the lifting element of the forklift truck.
  • the user may specify a target load that is a load to be picked up automatically by the forklift truck. In case the user fails to realize that the load is anomalous there may be a danger of causing damage to the target load, the user, the shelf or the forklift truck.
  • the present disclosure proposes a forklift truck including: material handling means for lifting a load, an optical sensor for acquiring image information representing an image of an environment, the environment including one or more loads, a control unit communicably coupled to the optical sensor to receive the image information, a touchscreen communicably coupled to the control unit and configured to display the image of the environment under the control of the control unit, the touchscreen being further configured to acquire from a user a load selection input relating to a target load out of the one or more loads represented in the image displayed by the touchscreen; wherein the control unit is configured to provide, based on the image information acquired by the optical sensor and based on the load selection input, an anomaly notification relating to an anomaly level of spatial characteristics of the target load, wherein the anomaly notification indicates a danger in case of picking up the target load using the material handling means.
  • the proposed forklift truck is capable of recognizing an anomaly of a load to be picked up and notify the user accordingly. Thus, the user may easily identify whether or not a load is anomalous. In this manner, the forklift truck that can safely perform material handling operations and, in particular, loading operations.
  • Fig. 1 shows a side view of a forklift truck 1 according to an embodiment of the present disclosure.
  • the forklift truck includes material handling means 2 for lifting a load 3.
  • the material handling means 2 may be mounted on a mast 4 so as to be slidable along the mast 4.
  • the load 3 may comprise a movable load support 31 and a ware 32.
  • the ware 32 may comprise one or more items.
  • the movable load support 31 is a pallet on which two barrels as the ware 32 are placed.
  • the material handling means 2 may be adapted to match the load 3.
  • the material handling means 2 may be a fork adapted to slide under an upper supporting surface of the pallet in order to lift the load 3.
  • a load 3 comprising a barrel that is not placed on any pallet may be picked up using a barrel clamp as the material handling means 2.
  • a load comprising a roll of sheet metal may be picked up using a boom attachment as the material handling means 2.
  • a load comprising bag of material may be picked up using a hook attachment as the material handling means 2.
  • the forklift truck 1 may further include an optical sensor 5 for acquiring image information representing an image of an environment, the environment including one or more loads 3.
  • the optical sensor 5 may be mounted on a roof of the forklift truck 1 or on an upper portion of the mast 4.
  • the optical sensors 5 may be a camera configured to capture a photo or video of the environment as the image information.
  • the environment may be a ware storage, an industrial site and the like.
  • Fig. 2 shows an example for an environment including one or more loads.
  • the environment comprises shelves on which loads are stored, wherein the shelves comprise a top row R1, middle row R2 and bottom row R2.
  • the shelves are further divided into a first column C1, second column C2, third column C3 and fourth column C4.
  • the load placed in compartment R1-C2 comprises a large barrel.
  • the load placed in compartment R1-C4 comprises a roll of sheet metal.
  • the load placed in compartment R2-C1 comprises a large box on a pallet.
  • the load placed in compartment R2-C3 comprises two small barrels on a pallet.
  • the load placed in compartment R3-C1 comprises three small boxes on a pallet.
  • the load placed in compartment R3-C3 comprises a bag of material with a tap on top.
  • the load placed in compartment R3-C4 comprises a foil-wrapped stack of material on a pallet.
  • the forklift truck 1 further includes a control unit 6 communicably coupled to the optical sensor 5 to receive the image information.
  • the control unit 6 may comprise a processor (e.g. a CPU) configured to control the one or more operations of the forklift truck 1.
  • the control unit 6 may further comprise a working memory (e.g. a random-access memory) and a storage for storing a computer program having computer-readable instructions which, when executed by the processor, cause the processor to perform an operation of the forklift truck 1, in particular any of the operations performed by the control unit 6 as described in the present disclosure.
  • control unit 6 may acquire image information from the optical sensor 5 and/or instruct the optical sensor 5 to perform an operation such as increasing/decreasing a zoom level, changing an angle in which the optical sensor 5 is facing, changing a field-of-view, and the like.
  • the control unit 6 may be further configured to control the operation of the material handling means 2 and of the mast 4 under the control of a user and/or in an automated/semi-automated manner.
  • the control unit 6 may control one or more actuators (not shown) for controlling the movement of the material handling means, e.g. the tilting of the mast 4, the lifting height of the material handling means 2 and the like.
  • the control unit 6 may be further configured to control the operation of a drive motor and/or of a steering mechanism and/or a braking system of the forklift truck 1 under the control of a user and/or in an automated/semi-automated manner.
  • the control unit 6 may be configured to perform an autonomous and/or assisted driving function of the forklift truck 1.
  • the control unit 6 may be configured to perform an autonomous and/or assisted material handling function of the forklift truck 1, such as a load picking up operation or an offloading operation.
  • the forklift truck 1 further includes a touchscreen 7 communicably coupled to the control unit 6 and configured to display the image of the environment under the control of the control unit 6.
  • the touchscreen 7 is further configured to acquire from a user (not shown) a load selection input relating to a target load out of the one or more loads represented in the image displayed by the touchscreen 7.
  • the user may sit in the forklift truck 1 and specify a load selection input the target load by referring to the image displayed by the touchscreen 7.
  • the user may do so using input means of a user interface of the forklift truck 1.
  • the touchscreen may be mounted in the cabin of the forklift truck, e.g. on the armrest of a user seat.
  • Fig. 3A shows an example of an image of the environment displayed on the touchscreen 7.
  • the environment comprises a first arrangement of shelves on the left-hand side and a second arrangements of shelves on the right-hand side.
  • the forklift truck 1 may enter the space between the first and second arrangement of shelves to access the loads stored therein.
  • the target load 71 is located in the first arrangement of shelves.
  • the control unit 6 may be configured to control the touchscreen 7 so that, when the user touches a target load 71 on the touchscreen 7, a contour is displayed around the selected target load 71.
  • the control unit 6 may be configured to control the touchscreen 7 so that, in response to the user touching a target load 71 on the touchscreen 7, a contour is displayed around the selected target load 71.
  • Fig. 3B shows the image according to the example of Fig. 3A and further comprises a load selection input 72 by the user.
  • the contour indicating the load selection input 72 may have the shape of a rectangular bounding box around the target load 71 displayed on the touchscreen 7.
  • the contour indicating the load selection input 72 may be displayed in a first color (as indicated by the dotted line in Fig. 3B ).
  • the first color may be the color yellow.
  • the control unit 6 is further configured to provide, based on the image information acquired by the optical sensor 5 and based on the load selection input 72, an anomaly notification 73 relating to an anomaly level of spatial characteristics of the target load 71, wherein the anomaly notification 73 indicates a danger in case of picking up the target load 71 using the material handling means 2.
  • the anomaly level of spatial characteristics will be described later with reference to Figs. 4A to 4D .
  • the forklift truck 1 is capable of recognizing an anomaly of the target load to be picked up and can notify the user accordingly.
  • the user may easily identify whether or not a load is anomalous.
  • the user may assess the danger of picking up the target load and take appropriate actions.
  • the forklift truck 1 can safely perform loading operations. Since the anomaly notification is provided based on the load selection input 72, the anomaly notification can be confined (i.e. only refer) to the target load as identified by the user by means of the load selection input; this achieves an improved and clearer notification for the user.
  • the anomaly notification 73 may comprise visual and/or audible alerts to indicate that the target load 71 specified by the user is not safe for picking up.
  • the control unit 6 may be configured to cause the touchscreen 7 to output the anomaly notification 73 to the user. In this manner, the user gazing at the touchscreen 7, after having performed the load selection input 72, may be able to immediately recognize that there is a danger in case of picking up the target load 71.
  • the control unit 6 may be configured to cause the touchscreen 7 to output the anomaly notification 73 under the form of a contour surrounding the target load 71 for which an anomaly has been determined.
  • Fig. 3C shows the image according to the example of Fig. 3A and further comprises an anomaly notification 73.
  • the contour indicating the anomaly notification 73 may have the shape of a rectangular bounding box around the target load 71 displayed on the touchscreen 7.
  • the contour indicating the anomaly notification 73 may be displayed in a second color (as indicated by the double line in Fig. 3C ).
  • control unit 6 may be configured to control the touchscreen 7 so that a contour is displayed around the selected target load in a first color.
  • the contour may be provided, for example, as yellow rectangular bounding box around the target load 71.
  • the control unit 6 may be configured to control the touchscreen 7 so that a contour is displayed around the selected target load 71 in a second color different from the first color.
  • the second color may be the color red.
  • the color of the rectangular bounding box indicating the load selection input 72 by the user may change the first color to the second color, e.g. from yellow to red.
  • the anomaly notification 73 may provide an easy to understand and intuitive alert to the user that there is a danger in case of picking up the target load 71.
  • the control unit 6 may further be configured to provide a safety notification 74 based on the image information acquired by the optical sensor 5 and based on the load selection input 72, the safety notification 74 indicating that the target load 71 can be picked up using the material handling means 2 without danger.
  • the user gazing at the touchscreen 7, after having performed the load selection input 72 may be able to immediately recognize that there is no danger in case of picking up the target load 71.
  • Fig. 3D shows the image according to the example of Fig. 3A and further comprises a safety notification 74.
  • the contour indicating the safety notification 74 may have the shape of a rectangular bounding box around the target load 71 displayed on the touchscreen 7.
  • the contour indicating the anomaly notification 73 may be displayed in a third color (as indicated by the solid line in Fig. 3D ).
  • the safety notification 74 may be provided instead of an anomaly notification 73 in case there is no danger in picking up the target load 71.
  • the control unit 6 may be configured to determine, based on the image information acquired by the optical sensor 5 and based on the load selection input 71, whether the anomaly notification 73 should be provided or not. In case it is determined that no anomaly notification 73 should be provided, the control unit 6 may be configured to provide the safety notification 74. The determination on whether the anomaly notification should be provided or not can be performed based on an analysis of only a part of the image information relating to the target load, based on the load selection input, thus making the determination more efficient.
  • control unit 6 may be configured to control the touchscreen 7 so that a contour is displayed around the selected target load 71 in a second color
  • control unit 6 may be configured to cause the touchscreen 7 to output the safety notification 74 under the form of a contour surrounding the target load 71 in a third color (as indicated by the solid line in Fig. 3D ) that is different from the second color.
  • the third color may be the color green.
  • the color of the rectangular bounding box indicating the load selection input 72 by the user may change the first color to the third color, e.g. from yellow to green.
  • the safety notification 74 may provide an easy to understand and intuitive alert to the user that there is no danger in case of picking up the target load 71.
  • the load selection input 71, the anomaly notification 73 and the safety notification 74 may be provided on the touchscreen display 7 is a manner different from a contour in shape of a rectangular bounding box around the target load 71.
  • the contour may be determined based on image processing using semantic segmentation in order for the contour to closely skirt the target load 71 as displayed on the touchscreen 7.
  • the whole target load 71 as displayed on the touchscreen 7 may be highlighted by toning it in one of the first, second or third color according to the description above.
  • the anomaly level of spatial characteristics of the target load 71 may relate to any one of the following, any combination of the following or all of the following: a position of the ware 32 on the movable load support 31; a spatial deformation of the movable load support 31 with respect to an expected shape of the movable load support 31; a shape of the ware 32; an orientation of the ware 32 on the movable load support 31; a position of the center of gravity of the ware 32 with respect to the movable load support 31.
  • the anomaly level of spatial characteristics of the target load 71 is further described with reference to the examples illustrated in Figs. 4A to 4D , wherein the movable load support 31 is provided by a pallet.
  • Fig 4A shows an example of a load 3 in which the ware 32 is positioned close to an edge of the movable load support 31.
  • the center of gravity of the ware 32 is positioned close to the edge of the movable load support 31.
  • the position of the ware 31 and the center of gravity of the ware 32 with respect to the movable load support 31 each indicate an anomaly as the ware 32 may fall off the movable load support 31 in case the load 3 is picked up.
  • Fig 4B shows an example of a load 3 in which the movable load support 31 has a spatial deformation 311.
  • the one of the planks constituting the movable load support 31 has a spatial deformation 311 in the form of a crack.
  • the spatial deformation 311 of the movable load supports 31 indicates an anomaly as the movable load supports 31 may break apart in case the load 3 is picked up.
  • Fig. 4C shows an example of a load 3 in which the ware 32 comprising three stacked boxes has an unstable shape.
  • the three stacked boxes exhibit a misalignment with respect to the direction of stacking.
  • the shape of the ware 32 indicates an anomaly as the three stacked boxes may collapse in case the load 3 is picked up.
  • Fig. 4D shows an example of a load 3 in which the ware 32 comprising two rolls of metal sheet has an unstable orientation.
  • the two rolls of metal sheet lie on their respective longitudinal side.
  • the orientation of the ware 32 indicates an anomaly as the two rolls of metal sheet may roll off the movable load support 31 in case the load 3 is picked up.
  • the control unit 6 may be configured to determine, based on the image information acquired by the optical sensor 5, whether a restriction to a material handling operation relating to the target load should be imposed or whether a material handling operation relating to the target load should be prohibited.
  • the restriction can include any one of following, any combination of the following or all of the following: a maximum speed of movement of a lifting element of the material handling means 2, a maximum speed or acceleration of the forklift truck 1, a maximum tilt angle of a mast of the material handling means 2, a maximum steering angle of the forklift truck, a maximum lifting height of a lifting element of the forklift truck 1, a maximum number operations in a combined maneuver by the material handling means 2.
  • any combined maneuver by the material handling means can be prevented.
  • the acceleration of the lifted load may be reduced and/or the balancing of the lifted load may be improved.
  • the restrictions to the operations by the control unit can improve the safety not only at time of picking up the load, but also in a subsequent phase in which the loaded forklift truck is driven.
  • a maneuver by the material handling means 2 is an operation of the material handling means 2 that causes a movement of a load handled by the material handling means 2 with respect to a frame of the forklift truck 1, e.g. a frame onto which the mast 4 is mounted in a tiltable fashion.
  • a maneuver by the material handling means 2 is the lifting of a load (e.g. by lifting a fork along the mast 4), the tilting of a load (e.g. by tilting the mast 4) or the like.
  • the maximal vertical acceleration of the lifted load may be reduced.
  • the maximal longitudinal acceleration of the lifted load may be reduced, where "longitudinal” refers to the orientation of the forklift truck 1.
  • the maximal lateral acceleration of the lifted load may be reduced, where "lateral” refers to the orientation of the forklift truck 1.
  • the lifted load is subjected the fewer simultaneous movements caused by a movement of the material handling means 2 and/or of the mast 4 with respect to a frame of the forklift truck 1, whereby the acceleration of the lifted load may be reduced and/or the balancing of the lifted load may be improved.
  • the control unit 6 may prohibit the combined maneuver in which a fork of the material handling means vertically lifts and simultaneously horizontally translates the load lifted by the fork.
  • the control unit 6 may be configured to determine the anomaly level of spatial characteristics of the target load 71 based on the image information acquired by the optical sensor 5 by using a trained neural network.
  • the trained neural network may comprise a model trained using training data.
  • the training data may comprise of a plurality of images of loads, wherein each of the plurality of images of loads is labelled to indicate a danger in case of picking up the load.
  • the training data may be historic data in which each of the plurality of images of loads is associated with accident information indicating the presence or absence of an accident that occurred when the load was picked up.
  • the neural network may identify spatial characteristics of the load to determine the anomaly level thereof.
  • An anomaly notification 73 may be provided in case the anomaly level is equal or greater than a predetermined threshold.
  • a safety notification 74 may be provided in case the anomaly level is less than the predetermined threshold.
  • the predetermined threshold may be determined based on a desired level of safety of operating the forklift truck.
  • the control unit 6 may be distributed and include local processing means 61 mounted on-bord of the forklift truck 1 and remote processing means 62 located in a remote processing device 8, wherein the forklift truck 1 includes transceiver means 9 for establishing a communication between the local processing means and the remote processing means 62. In this manner, the processing of image information may be performed by the remote processing device 8.
  • the remote processing device 8 may perform the processing of image information for each of a plurality of forklift trucks.
  • the control unit 6 may further be configured to transmit via the transceiver means 9 accident information, wherein the accident information indicates whether or not an accident has occurred when the target load 71 is picked up.
  • the accident information may be determined automatically using the optical sensor 5. Alternatively, the accident information may be provided by input from the user.
  • Fig. 5 shows schematic view of the distributed control unit 6 including the local processing means 61 mounted on-bord of the forklift truck 1 and the remote processing means 62 located in the remote processing device 8.
  • the remote processing device 8 may be coupled to a database 10.
  • the database 10 may be used to store information received from each of the plurality of forklift trucks.
  • the database 10 may be included in the remote processing device 8 or may be located on an external server or the like.
  • the remote processing device 8 may be configured to store image information received from a forklift truck 1 in a database 10.
  • the remote processing device 8 may further be configured to store accident information received from the forklift truck 1 in association with the image information in the database 10. In this manner, the remote processing means 62 may continuously expand the training data to improve the efficiency of the trained neural network.
  • control unit 6 may further be configured to determine whether to provide either an anomaly notification 73 or a safety notification 74, or whether to impose a restriction to a material handling operation, or whether to prohibit the material handling operation based on the determined anomaly level of spatial characteristics of the target load.
  • control unit 6 may further be configured to determine the kind and/or the amount of the restriction to the material handling operation based on the determined anomaly level. In this manner, the handling of the lifted load can be fine-tuned to the anomaly level.

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  • Engineering & Computer Science (AREA)
  • Structural Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Geology (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Civil Engineering (AREA)
  • Forklifts And Lifting Vehicles (AREA)
EP23214096.2A 2022-12-22 2023-12-04 Erkennung von lastanomalien Pending EP4389681A1 (de)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
IT202200026451 2022-12-22

Publications (1)

Publication Number Publication Date
EP4389681A1 true EP4389681A1 (de) 2024-06-26

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3805888A1 (de) * 2018-05-24 2021-04-14 Kabushiki Kaisha Toyota Jidoshokki Fernbedienungssystem für gabelstapler
CA3111177A1 (en) * 2020-03-04 2021-09-04 Oshkosh Corporation Refuse can detection systems and methods
US20210276842A1 (en) * 2020-03-04 2021-09-09 Jungheinrich Aktiengesellschaft Warehouse inspection system
EP3960692A1 (de) * 2019-04-25 2022-03-02 Beijing Geekplus Technology Co., Ltd. Intelligentes gabelstapler- und behälterpositions- und haltungsabweichungsdetektionsverfahren
US20220078972A1 (en) * 2019-01-24 2022-03-17 Ceres Innovation, Llc Harvester with automated targeting capabilities
WO2022132239A1 (en) * 2020-12-16 2022-06-23 Motion2Ai Method, system and apparatus for managing warehouse by detecting damaged cargo

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP3805888A1 (de) * 2018-05-24 2021-04-14 Kabushiki Kaisha Toyota Jidoshokki Fernbedienungssystem für gabelstapler
US20220078972A1 (en) * 2019-01-24 2022-03-17 Ceres Innovation, Llc Harvester with automated targeting capabilities
EP3960692A1 (de) * 2019-04-25 2022-03-02 Beijing Geekplus Technology Co., Ltd. Intelligentes gabelstapler- und behälterpositions- und haltungsabweichungsdetektionsverfahren
CA3111177A1 (en) * 2020-03-04 2021-09-04 Oshkosh Corporation Refuse can detection systems and methods
US20210276842A1 (en) * 2020-03-04 2021-09-09 Jungheinrich Aktiengesellschaft Warehouse inspection system
WO2022132239A1 (en) * 2020-12-16 2022-06-23 Motion2Ai Method, system and apparatus for managing warehouse by detecting damaged cargo

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