WO2020039817A1 - Dispositif d'aide à l'opération de chargement de chariot élévateur à fourche - Google Patents

Dispositif d'aide à l'opération de chargement de chariot élévateur à fourche Download PDF

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Publication number
WO2020039817A1
WO2020039817A1 PCT/JP2019/028728 JP2019028728W WO2020039817A1 WO 2020039817 A1 WO2020039817 A1 WO 2020039817A1 JP 2019028728 W JP2019028728 W JP 2019028728W WO 2020039817 A1 WO2020039817 A1 WO 2020039817A1
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WO
WIPO (PCT)
Prior art keywords
forklift
unit
cargo handling
pallet
fork
Prior art date
Application number
PCT/JP2019/028728
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English (en)
Japanese (ja)
Inventor
岡本浩伸
比嘉孝治
Original Assignee
株式会社豊田自動織機
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Application filed by 株式会社豊田自動織機 filed Critical 株式会社豊田自動織機
Publication of WO2020039817A1 publication Critical patent/WO2020039817A1/fr

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    • 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
    • B66F9/075—Constructional features or details
    • B66F9/20—Means for actuating or controlling masts, platforms, or forks
    • B66F9/24—Electrical devices or systems

Definitions

  • the present invention relates to a cargo handling support device for a forklift.
  • the periphery of the traveling vehicle body at the target position is photographed, the position of the object on the image data is predicted, and a search range of a predetermined range including the predicted position of the object is determined.
  • Feature points of the image data calculate the feature amounts of the extracted matching candidate points, and match the feature amounts of the matching candidate points with the model data to recognize the position of the object on the image data.
  • the object recognition device disclosed in Patent Document 2 detects a feature point in a three-dimensional image including an object, calculates a feature amount at each point, and determines a feature point and a specific geometric condition for the feature point.
  • a group of matching candidate points for pattern matching is defined as interpolation points that satisfy the conditions, and object recognition is performed by comparing similarities with model data based on the feature amounts of the matching candidate points included in each group. I have to.
  • the pallet position information is required, so that it can be applied only to the autonomous vehicle.
  • the technique of Patent Document 2 is used to recognize a pallet from a camera image, erroneous detection may occur during two-dimensional image processing.
  • the method of finding a part that seems to be a pallet in a two-dimensional image before recognizing the image in the three-dimensional image and recognizing the part in a three-dimensional image may cause erroneous detection during two-dimensional image processing.
  • An object of the present invention is to provide a forklift cargo handling work support device capable of detecting a pallet with high accuracy.
  • a forklift cargo handling work support device for solving the above-described problems is a forklift cargo handling work support device for supporting a cargo handling work of a forklift.
  • the forklift cargo handling work support device further includes a fork target height calculating unit that calculates a fork target height based on the position of the pallet recognized by the image recognition unit.
  • the cargo handling work support device for a forklift further includes a notifying unit for notifying the fork target height calculated by the fork target height calculating unit.
  • the cargo handling work support device for a forklift further includes an automatic control unit that automatically controls the forklift based on the position of the pallet recognized by the image recognition unit.
  • the forklift cargo handling support device is used for a forklift remote operation system, wherein the forklift remote operation system includes the forklift and a remote operation device, and the forklift is mounted on a machine base.
  • the remote control device includes a cargo handling device and has a vehicle communication unit, and the remote control device has an operation device communication unit that performs wireless communication with the vehicle communication unit, and remotely controls traveling of the forklift and cargo handling by the cargo handling device. It is preferred to be used.
  • a pallet can be detected with high accuracy.
  • FIG. 2 is a block diagram showing an electric configuration of a forklift remote control system.
  • FIG. 2 is a block diagram showing an electrical configuration of a part of the remote control device.
  • action The figure which shows the display screen for demonstrating an effect
  • FIG. 3 is a schematic plan view for explaining a positional relationship between a forklift and a pallet at a work place.
  • FIG. 3 is a schematic side view for explaining a positional relationship between a forklift and a pallet at a work place.
  • the forklift operation support device is used for a forklift remote operation system.
  • the forklift remote control system 10 includes a forklift 20 and a remote control device 40 used to remotely control the traveling of the forklift 20 and the loading and unloading work by the loading and unloading device.
  • the forklift 20 is arranged in a work place.
  • the remote control device 40 is arranged in an operation room. Then, the forklift 20 at the work place can be remotely controlled from the operation room using the remote control device 40.
  • shelves 50 are installed in the workplace.
  • the pallets 51 to 58 and the load W can be arranged in two stages. That is, the load W is arranged on the pallet 51 in the lower stage, and the load W is arranged on the pallet 52 in the upper stage.
  • the load W is placed on the pallet 53 in the lower stage next to it, and the load W is placed on the pallet 54 in the upper stage.
  • the load W is placed on the pallet 55 in the lower stage next to it, and the load W is placed on the pallet 56 in the upper stage.
  • the load W is placed on the pallet 57 in the lower stage next to it, and the load W is placed on the pallet 58 in the upper stage. From this state, the operator remotely operates the forklift 20 to pick up luggage.
  • a pallet hole (fork insertion hole) 60 is formed in each of the pallets 51 to 58, and a fork is inserted into the pallet hole 60.
  • the forklift 20 is provided with wheels 22 before and after a machine base 21.
  • the machine base 21 is provided with a cargo handling device 23.
  • the cargo handling device 23 can stack or unload cargo.
  • the cargo handling device 23 includes a mast 24, a bracket 25, and a fork 26.
  • a fork 26 is provided on the mast 24 via a bracket 25 so as to be vertically movable.
  • the forklift 20 of the present embodiment is configured so that a driver can sit and operate it, an unmanned forklift having no driver's seat may be used.
  • the forklift 20 may be, for example, an engine type equipped with an engine, an EV type equipped with a power storage device and an electric motor, or an FCV type equipped with a fuel cell and an electric motor. It may be.
  • the forklift 20 may be, for example, an HV type having an engine, a power storage device, and an electric motor.
  • the forklift 20 includes a wireless unit 30 as a vehicle communication unit, a control unit 31, a video signal processing unit 32, a camera 33, and an actuator unit.
  • the camera 33 is mounted on the forklift 20 and captures an image of the front of the forklift 20. Specifically, as shown in FIG. 2, the camera 33 is embedded at the tip of the fork 26 and captures an image of the front of the fork 26. Note that the camera 33 is attached to one of the left and right forks 26.
  • 3 includes a traveling actuator and a cargo handling actuator, and the cargo handling actuator includes a tilt actuator and a lifting / lowering actuator.
  • the wheels 22 are rotated and steered by the traveling actuator.
  • the remote operation device 40 includes a wireless unit 41 as an operation device communication unit, a control unit 42, an operation unit 43, a display unit (monitor) 44, and a video signal processing unit 45.
  • a wireless unit 41 as an operation device communication unit
  • a control unit 42 controls the operation unit 43
  • an operation unit 43 controls the operation unit 43
  • a video signal processing unit 45 As an operation method in the operation unit 43, a touch panel method, a mouse method, a joystick method, or the like is used.
  • the wireless unit 41 can perform wireless communication with the wireless unit 30 of the forklift 20. That is, the wireless unit 30 of the forklift 20 and the wireless unit 41 of the remote control device 40 can wirelessly communicate with each other.
  • the control unit 42 sends the operation content to the forklift 20 via the wireless unit 41.
  • the operation content from the remote control device 40 is received by the wireless unit 30 and the control unit 31 drives the actuator unit 34 to perform a desired operation.
  • an image captured by the camera 33 is sent by the control unit 31 to the remote control device 40 via the video signal processing unit 32 and the wireless unit 30.
  • a camera image from the forklift 20 is received by the wireless unit 41 and displayed on the display unit 44 via the video signal processing unit 45 by the control unit 42. That is, the display unit 44 provided in the remote control device 40 is for displaying an image captured by the camera 33, and has a screen 44a (see FIG. 5). The operator operates while viewing the image captured by the camera 33 on the display unit 44.
  • the forklift remote control system 10 has a function of automatically controlling the forklift 20.
  • a loading operation can be performed using this automatic control function. Specifically, as shown in FIG. 7, the forklift 20 is automatically adjusted in position and the fork 26 is inserted into the pallet hole 60 from a state in which the pallets 51 to 58 selected by the operator are directly opposed as shown in FIG. And the fork 26 inserted into the pallet hole 60 can be lifted by automatic control.
  • the video signal processing unit 45 can detect a pallet selected from a plurality of pallets 51 to 58 by performing image recognition processing on an image captured by the camera 33.
  • the video signal processing unit 45 of the remote control device 40 has an image recognition unit 45a and a fork target height calculation unit 45b. Further, the control unit 42 of the remote operation device 40 has an automatic control unit 42a.
  • the operation unit 43 has a detection area designation unit 43a.
  • the detection area specifying unit 43a includes a mouse, a keyboard, and the like.
  • the detection area specifying unit 43a is for specifying an area Rd (see FIG. 6) in which the pallets 51 to 58 are to be recognized in the entire image captured by the camera 33 that captures the front of the forklift 20.
  • the region designation information is sent from the detection region designation unit 43a to the video signal processing unit 45.
  • the image recognizing unit 45a can recognize the positions of the pallets 51 to 58 in the region Rd specified by the detection region specifying unit 43a.
  • the fork target height calculator 45b calculates the fork target height Hg (see FIG. 8) based on the positions of the pallets 51 to 58 recognized by the image recognizer 45a.
  • the automatic control unit 42a automatically controls the forklift 20 based on the positions of the pallets 51 to 58 recognized by the image recognition unit 45a.
  • the video signal processing unit 45 receives image data and sends the image data to the display unit 44.
  • the recognition result (relative height information) is sent to the control unit 42.
  • the automatic control unit 42a instructs the forklift operation amount to the forklift side in response to an instruction to start fork height automatic adjustment from the operation unit 43.
  • the forklift 20 is located at a position distant from the shelf 50 (pallets 51 to 58). From this state, the forklift 20 travels so as to approach the shelf 50 (pallets 51 to 58). Further, the forklift 20 is directly opposed to the pallets 51 to 58 as shown in FIG. In this state, the left and right forks 26 of the forklift 20 are separated from the left and right pallet holes 60 of the pallets 51 to 58 by a predetermined distance. By moving the left and right forks 26 forward, the left and right forks 26 are inserted into the left and right pallet holes 60.
  • an image captured by the camera 33 is displayed on the display unit 44.
  • an image captured by the camera 33 is displayed as shown in FIG.
  • the operator specifies an area (Rd) including the specific pallet 52 in the image captured by the camera 33 using a cursor or the like.
  • a rectangular area Rd is designated by four designated points P1, P2, P3, and P4, and the designated rectangular area Rd includes the pallet 52.
  • the region Rd in which the pallets 51 to 58 are to be recognized in the entire image captured by the camera 33 is specified.
  • the image recognition unit 45a performs image recognition of the position of the pallet 52 in the specified area Rd. Therefore, the pallet 52 can be detected with high accuracy.
  • pallet recognition using a laser requires laser-related parts, which affects the cost.
  • the pallets 51 to 58 can be recognized from the camera image, there is a cost advantage compared to the case where a laser is used. It is difficult to adjust the height of the pallet hole 60 and the height of the fork 26 by adjusting the height of the fork 26 based on the camera image, which may burden the operator. Therefore, the pallets 51 to 58 are detected from the image information, and the fork height adjustment is supported by using the recognized position information of the pallets 51 to 58.
  • the shapes of the pallets 51 to 58 are formed by straight lines, the amount of characteristics is small in terms of shape, it is difficult to detect the pallets from the entire image, and it is difficult to make a difference in the amount of characteristics with racks and columns in the environment. . That is, the pallets 51 to 58 are formed of straight lines, have few edges, and have a small amount of features. Therefore, as shown by the area P100 in FIG. 2, it is difficult to recognize the division between the pallets, and it is difficult to make a difference in the feature amount from other areas.
  • the detection accuracy of the pallet 52 is improved by specifying a rough detection area (Rd) including the pallet 52 as a target on the image.
  • a region (Rd) from which features are extracted comparison targets are narrowed down.
  • the false recognition rate decreases.
  • the mounting position of the camera 33 is a camera position where the positional relationship between the fork 26 and the pallets 51 to 58 can be understood. Specifically, it is the tip of the fork, which operates in conjunction with the fork 26, and sets the camera position where the fork 26 and the pallets 51 to 58 are simultaneously projected.
  • the area specification (Rd) is specified by the operator on the image on the image display monitor, and the specification is performed using an input device such as a mouse or a keyboard. Judge the specified range (Rd) from the input information.
  • the image recognition unit 45a performs pallet detection by focusing on a specified region Rd (it is also possible in the vicinity).
  • the image recognition unit 45a calculates a distance dp (see FIG. 8) from the detected size of the pallet 52 to the pallet 52.
  • the image recognition unit 45a grasps the relative height ⁇ H (see FIG. 8) between the fork 26 and the pallet 52 based on the calculated distance information (dp).
  • the size of the pallets 51 to 58 is defined for the method of grasping the relative height ⁇ H
  • the camera 33 is located directly opposite to the pallets 51 to 58 as shown in FIG.
  • the approximate distance is calculated from the pallet size (length of side, area, etc.). If the distance dp between the pallets 51 to 58 is known, the installation position of the camera 33 is known in advance (since it is the fork tip in this embodiment), so the relative height between the camera 33 and the pallet can be known.
  • the pallet height (Hg) is known from the position. Thus, the relative height ⁇ H between the fork 26 and the pallets 51 to 58 can be determined.
  • the image recognition unit 45a notifies the automatic control unit 42a of information on the relative height ⁇ H between the fork 26 and the pallets 51 to 58.
  • the automatic control unit 42a determines the lift operation amount from the relative height information and instructs the forklift 20 to be controlled. Thereby, the height of the fork 26 is adjusted to the same height as the pallet.
  • a fork target height calculator 45b for calculating the fork target height Hg based on the positions of the pallets 51 to 58 recognized by the image recognizer 45a is further provided. Therefore, the fork target height can be obtained.
  • An automatic control unit 42a for automatically controlling the forklift 20 based on the position of the pallet 52 recognized by the image recognition unit 45a is further provided. Therefore, the forklift 20 can be automatically controlled based on the recognized position of the pallet 52.
  • the forklift cargo handling work support device is used for the forklift remote operation system 10, and the forklift remote operation system 10 includes the forklift 20 and the remote operation device 40.
  • the platform 21 includes the cargo handling device 23 and a wireless unit 30 as a vehicle communication unit.
  • the remote operation device 40 includes a wireless unit 41 as an operation device communication unit that performs wireless communication with the wireless unit 30 as a vehicle communication unit. It is used to remotely control the traveling of the forklift 20 and the cargo handling by the cargo handling device 23. Therefore, when performing remote control, the pallet 52 can be detected with high accuracy.
  • the embodiment is not limited to the above, and may be embodied as follows, for example. ⁇ If the image display screen has a touch panel function, the area may be specified using the touch panel.
  • ⁇ O ⁇ Operation support may be display of the relative height ⁇ H on the image instead of automatic adjustment. That is, when displaying the lift height which is the height of the fork on the display unit 44 as the notification unit, the relative height ⁇ H is displayed, and the operator adjusts the height of the fork by the relative height ⁇ H. You may.
  • the fork target height Hg is notified by displaying the fork target height Hg calculated by the fork target height calculator 45b. That is, the fork target height Hg may be displayed as it is, or the relative height ⁇ H that is a difference from the current lift height may be displayed.
  • the display unit 44 may be further provided as a notification unit for notifying the fork target height Hg calculated by the fork target height calculation unit 45b.
  • the horizontal direction may be adjusted. That is, as shown in FIG. 7, when the place to be directly opposed to the pallet is shifted in the horizontal direction, the guide may be guided in the horizontal direction.
  • the image recognition unit 45a and the automatic control unit 42a may be integrated.
  • the process performed by the control unit 42 of the remote control device 40 may be performed by the control unit 31 of the forklift 20.
  • the camera is provided at the tip of the fork, but is not limited to this. For example, it may be provided on the bracket 25. In short, the camera only needs to capture an image in front of the forklift.
  • the forklift operation support device is used in a forklift remote operation system, but is not limited to this.
  • it may be used for a manned forklift. That is, the present invention may be applied to, for example, a manned forklift equipped with a camera and a display unit, instead of including an unmanned forklift equipped with a camera and a remote control device having a display unit.

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  • Engineering & Computer Science (AREA)
  • Transportation (AREA)
  • Structural Engineering (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Civil Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Geology (AREA)
  • Mechanical Engineering (AREA)
  • Forklifts And Lifting Vehicles (AREA)

Abstract

La présente invention comprend : une caméra (33) montée sur un chariot élévateur à fourche, la caméra capturant une image vers l'avant du chariot élévateur à fourche; une unité de désignation de région de détection (43a) pour désigner une région dans laquelle une palette doit être reconnue à partir de l'intérieur de la totalité de l'image capturée par la caméra; et une unité de reconnaissance d'image (45a) qui effectue une reconnaissance d'image à la position de la palette dans la région désignée.
PCT/JP2019/028728 2018-08-24 2019-07-23 Dispositif d'aide à l'opération de chargement de chariot élévateur à fourche WO2020039817A1 (fr)

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JP2018157339A JP2020029361A (ja) 2018-08-24 2018-08-24 フォークリフト用荷役作業支援装置
JP2018-157339 2018-08-24

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021195195A (ja) * 2020-06-10 2021-12-27 三菱ロジスネクスト株式会社 フォークリフト、フォークリフトの制御方法、及びプログラム
WO2022199644A1 (fr) * 2021-03-26 2022-09-29 未来机器人（深圳）有限公司 Dispositif de reconnaissance d'inclinaison d'empilement de palettes

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102598941B1 (ko) * 2021-07-19 2023-11-07 (주)러셀로보틱스 자율 주행 지게차의 포킹 높이 제어 방법 및 서버
JP7347910B2 (ja) 2021-09-10 2023-09-20 三菱ロジスネクスト株式会社 荷役車両の遠隔操作システム

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JP2013218571A (ja) * 2012-04-10 2013-10-24 Toyota Motor Corp 画像認識装置および運転支援装置
JP2018072945A (ja) * 2016-10-25 2018-05-10 株式会社豊田自動織機 産業車両用遠隔操作システム、遠隔操作装置、産業車両用遠隔操作プログラム及び産業車両

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US5812395A (en) * 1994-11-16 1998-09-22 Masciangelo; Stefano Vision based forklift control system for autonomous pallet loading
JP2002241094A (ja) * 2001-02-16 2002-08-28 Toyota Industries Corp 産業車両におけるカメラ昇降装置
JP2003155199A (ja) * 2001-11-19 2003-05-27 Toyota Industries Corp 産業車両の音声報知装置及び産業車両
JP2009061795A (ja) * 2007-09-04 2009-03-26 Fujitsu Ten Ltd 駐車支援制御装置
JP2010205121A (ja) * 2009-03-05 2010-09-16 Sony Ericsson Mobile Communications Ab 情報処理装置および携帯端末
KR20110027460A (ko) * 2009-09-10 2011-03-16 부산대학교 산학협력단 모노 비전 기반의 팔레트 위치 및 자세 측정 방법
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JP2013218571A (ja) * 2012-04-10 2013-10-24 Toyota Motor Corp 画像認識装置および運転支援装置
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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2021195195A (ja) * 2020-06-10 2021-12-27 三菱ロジスネクスト株式会社 フォークリフト、フォークリフトの制御方法、及びプログラム
JP7132976B2 (ja) 2020-06-10 2022-09-07 三菱ロジスネクスト株式会社 フォークリフト、フォークリフトの制御方法、及びプログラム
WO2022199644A1 (fr) * 2021-03-26 2022-09-29 未来机器人（深圳）有限公司 Dispositif de reconnaissance d'inclinaison d'empilement de palettes

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