WO2025079128A1 - 情報処理装置、制御方法、及び制御プログラム - Google Patents

情報処理装置、制御方法、及び制御プログラム Download PDF

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Publication number
WO2025079128A1
WO2025079128A1 PCT/JP2023/036679 JP2023036679W WO2025079128A1 WO 2025079128 A1 WO2025079128 A1 WO 2025079128A1 JP 2023036679 W JP2023036679 W JP 2023036679W WO 2025079128 A1 WO2025079128 A1 WO 2025079128A1
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WO
WIPO (PCT)
Prior art keywords
robot device
information processing
processing device
image
control unit
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
PCT/JP2023/036679
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English (en)
French (fr)
Japanese (ja)
Inventor
政人 土屋
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.)
Mitsubishi Electric Corp
Original Assignee
Mitsubishi Electric Corp
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 Mitsubishi Electric Corp filed Critical Mitsubishi Electric Corp
Priority to JP2024513420A priority Critical patent/JPWO2025079128A1/ja
Priority to PCT/JP2023/036679 priority patent/WO2025079128A1/ja
Publication of WO2025079128A1 publication Critical patent/WO2025079128A1/ja
Anticipated expiration legal-status Critical
Pending legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/40—Control within particular dimensions
    • G05D1/43—Control of position or course in two dimensions [2D]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/40—Control within particular dimensions
    • G05D1/46—Control of position or course in three dimensions [3D]

Definitions

  • the processor 101 controls the entire information processing device 100.
  • the processor 101 is a CPU (Central Processing Unit), an FPGA (Field Programmable Gate Array), or the like.
  • the processor 101 may be a multiprocessor.
  • the information processing device 100 may also have a processing circuit.
  • the volatile memory device 102 is the main memory device of the information processing device 100.
  • the volatile memory device 102 is a RAM (Random Access Memory).
  • the non-volatile memory device 103 is an auxiliary memory device of the information processing device 100.
  • the non-volatile memory device 103 is a HDD (Hard Disk Drive) or an SSD (Solid State Drive).
  • the information processing device 100 includes a storage unit 110, an acquisition unit 120, and a control unit .
  • the storage unit 110 may be realized as a storage area secured in the volatile storage device 102 or the non-volatile storage device 103 .
  • a part or all of the acquisition unit 120 and the control unit 130 may be realized by a processing circuit.
  • a part or all of the acquisition unit 120 and the control unit 130 may be realized as a module of a program executed by the processor 101.
  • the program executed by the processor 101 is also called a control program.
  • the control program is recorded on a recording medium.
  • the storage unit 110 stores map information, the current position of the robot device 200, the remaining battery charge of the robot device 200, information indicating the status of the robot device 200, etc. For example, the status of the robot device 200 may be stopped, moving, or being monitored.
  • the acquisition unit 120 acquires information indicating that a target has been detected. For example, the acquisition unit 120 acquires the information from the robot device 200.
  • the acquisition unit 120 may acquire the information from the robot device 200 via an external device.
  • the external device is a cloud server. The external device is omitted from the diagram.
  • the control unit 130 controls the robot device 200 to repeatedly capture images of the target.
  • the control unit 130 transmits an instruction to the robot device 200 to repeatedly capture images of the target.
  • the robot device 200 repeatedly captures images of the target.
  • the robot device 200 may transmit a large amount of rare data to the information processing device 100, or may transmit a large amount of rare data to the terminal device 300. In this way, the information processing device 100 can cause the robot device 200 to collect a large amount of rare data.
  • the target is a suspicious object.
  • 4 is a flowchart showing an example of processing executed by the information processing device.
  • the robot device 200 is performing surveillance. It is assumed that the robot device 200 detects a suspicious object. Then, the robot device 200 transmits information indicating that a suspicious object has been detected.
  • Step S11 The acquisition unit 120 acquires information indicating that a suspicious object has been detected.
  • Step S12 The control unit 130 controls the robot device 200 to repeatedly capture images while moving around the suspicious object.
  • the control unit 130 transmits an instruction to the robot device 200 to repeatedly capture images while moving around the suspicious object.
  • the control unit 130 may also use map information to generate route information for moving around the suspicious object.
  • the control unit 130 may transmit the instruction and the route information to the robot device 200.
  • the robot device 200 repeats capturing images while moving around the suspicious object based on the instruction. Thus, many images of the suspicious object are collected.
  • FIG. 5 is a flowchart showing an example of processing executed by the information processing device of the first modified example.
  • the robot device 200 is performing surveillance. It is assumed that the robot device 200 has detected a suspicious person. For example, the robot device 200 captures an image of a person behaving suspiciously, and detects the suspicious person using the captured image and a trained model. Also, for example, the robot device 200 detects the suspicious person using the image and image recognition technology. Furthermore, for example, when the robot device 200 detects a person speaking loudly, it detects the person as a suspicious person. Then, the robot device 200 transmits information indicating that a suspicious person has been detected.
  • Step S21 The acquisition unit 120 acquires information indicating that a suspicious individual has been detected.
  • Step S22 The control unit 130 controls the robot device 200 to repeatedly capture images while tracking the suspicious individual. In detail, the control unit 130 transmits an instruction to the robot device 200 to repeatedly capture images while tracking the suspicious individual. As a result, the robot device 200 repeatedly captures images while tracking the suspicious individual. Thus, many images of the suspicious individual are collected.
  • FIG. 6 is a flowchart showing an example of processing executed by the information processing device of the second modified example.
  • the robot device 200 is performing monitoring. It is assumed that the robot device 200 detects a location where aging deterioration is occurring. For example, when the robot device 200 detects a crack in a building, it takes an image of the location where the crack exists, inputs the image obtained by taking the image into the trained model, and when the trained model outputs information indicating that aging deterioration is occurring, detects the location as a location where aging deterioration is occurring.
  • the robot device 200 may detect the location where aging deterioration is occurring using the image and image recognition technology. Then, the robot device 200 transmits information indicating that a location where aging deterioration is occurring has been detected.
  • Step S31 The acquisition unit 120 acquires information indicating that a portion in which aging deterioration has occurred has been detected.
  • Step S32 The control unit 130 controls the robot device 200 to periodically capture images of the areas where aging deterioration is occurring. In detail, the control unit 130 transmits an instruction to the robot device 200 to periodically capture images of the areas where aging deterioration is occurring. As a result, the robot device 200 periodically captures images of the areas where aging deterioration is occurring. Thus, many images of the areas where aging deterioration is occurring are collected.
  • the control unit 130 may transmit an instruction to the robot device 200 to capture the image using any of the following methods: a method using an RGB-D camera, a method using an RGB camera and a depth sensor, and a method of capturing images of the location from various angles.
  • a method using an RGB-D camera a method using an RGB camera and a depth sensor
  • a method of capturing images of the location from various angles.
  • the control unit 130 can generate three-dimensional information of the location using the image.
  • the control unit 130 may output the three-dimensional information of the location.
  • the control unit 130 outputs the three-dimensional information of the location to the terminal device 300. This allows the user to recognize the location in three dimensions.
  • FIG. 7 is a flowchart showing an example of processing executed by the information processing device of the third modified example.
  • the robot device 200 is performing monitoring. It is assumed that the robot device 200 detects a site where danger is occurring. For example, after an earthquake occurs, the robot device 200 captures an image of a bridge, inputs the captured image into the trained model, and when the trained model outputs information indicating that the bridge is in a state where it is about to collapse, it detects the site where the bridge exists as a site where danger is occurring. In addition, the robot device 200 may detect the site where danger is occurring using an image recognition technology. Then, the robot device 200 transmits information indicating that the site where danger is occurring has been detected.
  • Step S41 The acquisition unit 120 acquires information indicating that a scene in which a danger has occurred has been detected.
  • Step S42 The control unit 130 controls the robot device 200 to periodically capture an image of the site where a danger is occurring. In detail, the control unit 130 transmits an instruction to the robot device 200 to periodically capture an image of the site where a danger is occurring. As a result, the robot device 200 periodically captures an image of the site where a danger is occurring. Thus, many images of the site where a danger is occurring are collected.
  • the control unit 130 may transmit an instruction to the robot device 200 to capture the image using any of the following methods: a method using an RGB-D camera, a method using an RGB camera and a depth sensor, and a method of capturing images of the site from various angles.
  • a method using an RGB-D camera a method using an RGB camera and a depth sensor
  • a method of capturing images of the site from various angles.
  • the control unit 130 can generate three-dimensional information of the site using the image.
  • the control unit 130 may output the three-dimensional information of the site.
  • the control unit 130 outputs the three-dimensional information of the site to the terminal device 300. This allows the user to recognize the site in three dimensions.

Landscapes

  • Engineering & Computer Science (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
  • Manipulator (AREA)
PCT/JP2023/036679 2023-10-10 2023-10-10 情報処理装置、制御方法、及び制御プログラム Pending WO2025079128A1 (ja)

Priority Applications (2)

Application Number Priority Date Filing Date Title
JP2024513420A JPWO2025079128A1 (https=) 2023-10-10 2023-10-10
PCT/JP2023/036679 WO2025079128A1 (ja) 2023-10-10 2023-10-10 情報処理装置、制御方法、及び制御プログラム

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/JP2023/036679 WO2025079128A1 (ja) 2023-10-10 2023-10-10 情報処理装置、制御方法、及び制御プログラム

Publications (1)

Publication Number Publication Date
WO2025079128A1 true WO2025079128A1 (ja) 2025-04-17

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WO (1) WO2025079128A1 (https=)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2014119901A (ja) * 2012-12-14 2014-06-30 Secom Co Ltd 自律移動ロボット
JP2016206876A (ja) * 2015-04-21 2016-12-08 Cyberdyne株式会社 自律移動体の走行経路教示システムおよび走行経路教示方法
WO2017065103A1 (ja) * 2015-10-16 2017-04-20 株式会社プロドローン 小型無人飛行機の制御方法
JP2020006793A (ja) * 2018-07-06 2020-01-16 パナソニックＩｐマネジメント株式会社 収音機能付き無人航空機
WO2020246085A1 (ja) * 2019-06-03 2020-12-10 株式会社イクシス 点検支援システム
JP2022149017A (ja) * 2021-03-25 2022-10-06 株式会社フジタ 無人移動体

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2014119901A (ja) * 2012-12-14 2014-06-30 Secom Co Ltd 自律移動ロボット
JP2016206876A (ja) * 2015-04-21 2016-12-08 Cyberdyne株式会社 自律移動体の走行経路教示システムおよび走行経路教示方法
WO2017065103A1 (ja) * 2015-10-16 2017-04-20 株式会社プロドローン 小型無人飛行機の制御方法
JP2020006793A (ja) * 2018-07-06 2020-01-16 パナソニックＩｐマネジメント株式会社 収音機能付き無人航空機
WO2020246085A1 (ja) * 2019-06-03 2020-12-10 株式会社イクシス 点検支援システム
JP2022149017A (ja) * 2021-03-25 2022-10-06 株式会社フジタ 無人移動体

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