WO2021203784A1 - 图像选取方法、自行走设备及计算机存储介质 - Google Patents

图像选取方法、自行走设备及计算机存储介质 Download PDF

Info

Publication number
WO2021203784A1
WO2021203784A1 PCT/CN2021/070301 CN2021070301W WO2021203784A1 WO 2021203784 A1 WO2021203784 A1 WO 2021203784A1 CN 2021070301 W CN2021070301 W CN 2021070301W WO 2021203784 A1 WO2021203784 A1 WO 2021203784A1
Authority
WO
WIPO (PCT)
Prior art keywords
image
scoring
parameter
identifiable
obstacle
Prior art date
Application number
PCT/CN2021/070301
Other languages
English (en)
French (fr)
Inventor
王逸星
吴震
谢濠键
张磊
Original Assignee
北京石头世纪科技股份有限公司
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 北京石头世纪科技股份有限公司 filed Critical 北京石头世纪科技股份有限公司
Priority to EP21784600.5A priority Critical patent/EP4134773A4/en
Priority to US17/995,730 priority patent/US11880967B2/en
Publication of WO2021203784A1 publication Critical patent/WO2021203784A1/zh

Links

Images

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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
    • A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
    • A47L11/4011—Regulation of the cleaning machine by electric means; Control systems and remote control systems therefor
    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
    • G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
    • G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
    • 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
    • G05D1/02—Control of position or course in two dimensions
    • G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
    • G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
    • 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
    • G05D1/20—Control system inputs
    • G05D1/24—Arrangements for determining position or orientation
    • G05D1/247—Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons
    • G05D1/249—Arrangements for determining position or orientation using signals provided by artificial sources external to the vehicle, e.g. navigation beacons from positioning sensors located off-board the vehicle, e.g. from cameras
    • 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
    • G05D1/60—Intended control result
    • G05D1/617—Safety or protection, e.g. defining protection zones around obstacles or avoiding hazards
    • G05D1/622—Obstacle avoidance
    • G05D1/628—Obstacle avoidance following the obstacle profile, e.g. a wall or undulated terrain
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • A—HUMAN NECESSITIES
    • A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
    • A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
    • A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
    • A47L2201/04—Automatic control of the travelling movement; Automatic obstacle detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30168—Image quality inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30248—Vehicle exterior or interior
    • G06T2207/30252—Vehicle exterior; Vicinity of vehicle
    • G06T2207/30261—Obstacle

Definitions

  • the present disclosure relates to image processing technology, and in particular to an image selection method, self-propelled device and computer-readable storage medium.
  • a sensor is installed in front of the sweeper to detect obstacles. If it hits a wall or other obstacles, it will turn on its own to avoid obstacles. However, the current sweeper cannot intuitively view the obstacles to be avoided, let alone identify what the obstacles to be avoided are, and the user experience is poor.
  • an image selection method using a self-propelled device.
  • the method includes: in the process of traveling, image acquisition of the surrounding environment; when the acquired image contains identifiable obstacles, the image is scored according to the scoring rule, and the score value of the score is used to indicate all the obstacles.
  • the method further includes: after the image is scored according to the scoring rule, at least the image with the highest score among all the images containing the identifiable obstacle is saved.
  • the method further includes: storing at least identification information that can uniquely identify the image with the highest score.
  • the scoring the image according to the scoring rule specifically includes: scoring the image using one or more of the following scoring parameters: the first scoring parameter: indicates when the image is collected , The angular velocity of the self-propelled device; the second scoring parameter: indicates the distance between the self-propelled device and the identifiable obstacle when the image is collected; the third scoring parameter: indicates the identifiable The size of the area occupied by the obstacle on the image; the fourth scoring parameter: indicates the position of the identifiable obstacle on the image; the fifth scoring parameter: indicates whether the supplementary light is used when the image is collected light.
  • the first scoring parameter indicates when the image is collected , The angular velocity of the self-propelled device
  • the second scoring parameter indicates the distance between the self-propelled device and the identifiable obstacle when the image is collected
  • the third scoring parameter indicates the identifiable The size of the area occupied by the obstacle on the image
  • the fourth scoring parameter indicates the position of the identifiable obstacle on the image
  • the fifth scoring parameter indicates whether the supplementary light is used when the image is collected light.
  • At least two of the first scoring parameter, the second scoring parameter, the third scoring parameter, the fourth scoring parameter, and the fifth scoring parameter are used.
  • the parameter values of the at least two scoring parameters are weighted according to a preset weight value to obtain the scoring value of the image.
  • a parameter value with a large absolute value of the angular velocity is greater than or equal to a parameter value with a small absolute value of the angular velocity; or, for the second scoring parameter, the distance value is within a certain range
  • the parameter value is greater than or equal to the parameter value of other distance values; or, for the third scoring parameter, the parameter value that the identifiable obstacle occupies a large area on the image is greater than or equal to the parameter value that occupies a small area; or
  • the fill light is not used
  • the parameter value at time is greater than or equal to the parameter value at the time of using the fill light.
  • a self-propelled device includes: an image acquisition device, which is used to collect images of the surrounding environment during the traveling of the equipment; Scoring, the score of the score is used to indicate the imaging quality of the identifiable obstacle in the image; the display control device is used to view the image of the identifiable obstacle when a request is received After the command, the image containing the identifiable obstacle with the highest score is selected as the image to be displayed.
  • the device further includes: a storage device for storing at least the scoring value of all images containing the identifiable obstacle after the image is scored according to the scoring rule by the scoring device The highest image.
  • the storage device is also used to store at least identification information that can uniquely identify the image with the highest score.
  • the scoring device is specifically configured to use one or more of the following scoring parameters to score the image: the first scoring parameter: indicates that the self-propelled device's performance when the image is collected Angular velocity; the second scoring parameter: indicates the distance between the self-propelled device and the identifiable obstacle when the image is collected; the third scoring parameter: indicates that the identifiable obstacle is on the image The size of the occupied area; the fourth scoring parameter: indicates the position of the identifiable obstacle on the image; the fifth scoring parameter: indicates whether the fill light is used when the image is collected.
  • the first scoring parameter indicates that the self-propelled device's performance when the image is collected Angular velocity
  • the second scoring parameter indicates the distance between the self-propelled device and the identifiable obstacle when the image is collected
  • the third scoring parameter indicates that the identifiable obstacle is on the image The size of the occupied area
  • the fourth scoring parameter indicates the position of the identifiable obstacle on the image
  • the fifth scoring parameter indicates whether the fill light is used when the image is collected.
  • the scoring device is specifically configured to use the first scoring parameter, the second scoring parameter, the third scoring parameter, the fourth scoring parameter, and the fifth scoring parameter.
  • the parameter values of the at least two scoring parameters are weighted according to a preset weight value to obtain the scoring value of the image.
  • a computer-readable storage medium including a set of computer-executable instructions, when the instructions are executed, they are used to execute any of the above-mentioned image selection methods.
  • a self-propelled device including a processor and a memory.
  • the memory stores computer program instructions that can be executed by the processor. When the instruction is executed by the processor, it is used to execute any of the above-mentioned image selection methods.
  • FIG. 1 shows a schematic diagram of the implementation process of an image selection method according to an embodiment of the present disclosure
  • Fig. 2 shows a schematic diagram of the composition structure of a cleaning machine in an embodiment of the present disclosure.
  • Fig. 1 shows a schematic diagram of an implementation process of an image selection method according to an embodiment of the present disclosure.
  • the image selection method of the embodiment of the present disclosure is applied to a self-propelled device.
  • the method includes: operation 101, in the process of traveling, image acquisition of the surrounding environment through the image acquisition device; operation 102, such as judging the captured image If it contains identifiable obstacles, the image is scored according to the scoring rules; operation 103, after receiving a command to view the image of a certain identifiable obstacle, include all the images with the highest score. The image of the identifiable obstacle is selected as the image to be displayed.
  • the self-propelled equipment may be a sweeping machine, or a cleaning machine for cleaning glass windows waiting to be cleaned.
  • the image capture device may be a camera arranged in front of the sweeper. Specifically, taking a sweeper as an example, during the traveling of the sweeper, an image of the surrounding environment is collected through a camera.
  • operation 102 it is first determined whether the captured image contains identifiable obstacles, and if it is determined that the captured image contains identifiable obstacles, the image is scored according to the scoring rule. Wherein, the value of the score is used to indicate the imaging quality of the identifiable obstacle in the image;
  • operation 102 scoring the image according to the scoring rule specifically includes: scoring the image using any one or any combination of the following scoring parameters: Parameter a: When the image is collected, the self-propelled device Angular velocity; parameter b: the distance between the self-propelled device and the identifiable obstacle when the image is collected; parameter c: the size of the area occupied by the identifiable obstacle on the image; parameter d: The position of the identifiable obstacle on the image; parameter e: whether the fill light is on when the image is collected.
  • Parameter a When the image is collected, the self-propelled device Angular velocity
  • parameter b the distance between the self-propelled device and the identifiable obstacle when the image is collected
  • parameter c the size of the area occupied by the identifiable obstacle on the image
  • parameter d The position of the identifiable obstacle on the image
  • parameter e whether the fill light is on when the image is collected.
  • the size of the area occupied by the identifiable obstacle on the image can be determined in the form of an area rectangle, that is, the size of the area rectangle occupied by the identifiable obstacle on the image can be determined. size.
  • the position of the identifiable obstacle on the image can be determined by determining the distance between the matrix of the area occupied by the identifiable obstacle and the edge of the image.
  • the parameter values of the scoring parameters may be weighted according to a preset weight value to obtain the scoring value of the image.
  • Moderate, not close or far is best; or, for the parameter c, the parameter value of the large area occupied by the identifiable obstacle on the image is greater than or equal to the parameter value of the small area, and the obstacle can be identified
  • the size of the area rectangle on the image, the larger the better; or, for the parameter d, the closer the position of the identifiable obstacle on the image is to the image center, the larger the value of the parameter d, that is, the area rectangle and the collected The distance between the edge of the image of, the farther the better; or, for the parameter e, the parameter value when the fill light state is off is greater than or equal to the parameter value when the fill light state is on, that is, the fill light is not turned on Better.
  • the weights can be in the order of eabcd from high to low.
  • the self-propelled device After operation 102, the self-propelled device automatically saves images containing identifiable obstacles.
  • the image containing the identifiable obstacle with the highest score can be selected as the image to be displayed in the subsequent operation 103, at least the image containing the identifiable obstacle needs to be saved during the automatic saving process. The image with the highest score among all the images in.
  • the self-propelled device when the self-propelled device saves the image, it can assign an identification information that can uniquely identify the image for each image; and store the identification information and the image correspondingly, so that in the subsequent image viewing, by carrying in the viewing instruction
  • the method of identifying information quickly displays the corresponding image.
  • the image with the highest score can be directly assigned to the image containing the identifiable obstacle.
  • the image of the recognized obstacle is selected as the image to be displayed.
  • the present disclosure uses self-propelled equipment, such as an image acquisition device set on a sweeper, to collect images and identify obstacle images, and then use scoring rules to score the obstacle images, and when receiving a viewing instruction, the highest score is selected
  • the obstacle image is determined as the image to be displayed, so that the sweeper can intuitively view the obstacle to be avoided, and since the obstacle image to be displayed has the highest score (the best imaging quality), it can be used by the user to identify the avoided obstacle. What exactly is the obstacle, so as to effectively improve the user experience.
  • embodiments of the present disclosure further provide a computer-readable storage medium that stores a program, and when the program is executed by a processor, the The processor performs at least the following operation steps: operation 101, during the traveling process, image acquisition of the surrounding environment through the image acquisition device; operation 102, if it is determined that the captured image contains identifiable obstacles, it is based on the score The image is scored according to the rules; operation 103, after receiving a command to view the image of a certain identifiable obstacle, the image containing the identifiable obstacle with the highest score is selected as the image to be displayed .
  • embodiments of the present disclosure also provide a self-propelled device, as shown in FIG. Image acquisition; scoring device 202, if it is determined that the collected image contains identifiable obstacles, then the image is scored according to the scoring rule, and the score of the score is used to indicate the identifiable obstacle
  • the imaging quality of the obstacle in the image; the display control device 203 is configured to, after receiving a command requesting to view the image of an identifiable obstacle, include the identifiable obstacle with the highest score
  • the image of is selected as the image to be displayed.
  • the device 20 further includes: a storage device for storing at least the highest score among all images containing the identifiable obstacle after the image is scored according to the scoring rule by the scoring device Image.
  • the scoring device 202 is specifically configured to use any one or any combination of the following scoring parameters to score the image: parameter a, the angular velocity of the self-propelled device when the image is collected; parameter b: the distance between the self-propelled device and the identifiable obstacle when the image is collected; parameter c: the size of the area occupied by the identifiable obstacle on the image; parameter d: the identifiable obstacle Identify the position of the obstacle on the image; parameter e: whether the fill light is on when the image is collected.
  • the scoring device 202 is specifically used to weight the value of the scoring parameter according to a preset weight value when there are more than two scoring parameters to obtain the score of the image.
  • the parameter value with a large absolute value of the angular velocity is greater than or equal to the parameter value with a small absolute value of the angular velocity; or, for the parameter b, the parameter value with a distance value within a certain range is greater than or equal to The parameter values of other distance values; or, for the parameter c, the parameter value of the large area occupied by the identifiable obstacle on the image is greater than or equal to the parameter value of the small occupied area; or, for the parameter d,
  • the disclosed device and method may be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the units is only a logical function division, and there may be other divisions in actual implementation, such as: multiple units or components can be combined, or It can be integrated into another system, or some features can be ignored or not implemented.
  • the coupling, or direct coupling, or communication connection between the components shown or discussed may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms. of.
  • the units described above as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • the functional units in the embodiments of the present disclosure can be all integrated into one processing unit, or each unit can be individually used as a unit, or two or more units can be integrated into one unit;
  • the unit can be implemented in the form of hardware, or in the form of hardware plus software functional units.
  • the foregoing program can be stored in a computer readable storage medium.
  • the execution includes The steps of the foregoing method embodiment; and the foregoing storage medium includes: various media that can store program codes, such as a mobile storage device, a read only memory (Read Only Memory, ROM), a magnetic disk, or an optical disk.
  • ROM Read Only Memory
  • the aforementioned integrated unit of the present disclosure is implemented in the form of a software function module and sold or used as an independent product, it may also be stored in a computer readable storage medium.
  • the computer software product is stored in a storage medium and includes several instructions for A computer device (which may be a personal computer, a server, or a network device, etc.) executes all or part of the methods described in the various embodiments of the present disclosure.
  • the aforementioned storage media include: removable storage devices, ROMs, magnetic disks, or optical disks and other media that can store program codes.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Remote Sensing (AREA)
  • Automation & Control Theory (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Electromagnetism (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Quality & Reliability (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
  • Image Processing (AREA)

Abstract

一种图像选取方法、自行走设备及计算机可读存储介质。首先在自行走设备行进过程中，通过图像采集装置对周围环境进行图像采集（101）；之后在所采集的图像中含有可识别的障碍物时，根据评分规则对所述图像进行评分，评分的分值高低用于表示可识别的障碍物在图像中的成像质量（102）；最后在收到请求查看可识别的障碍物的图像的命令后，将评分分值最高的包含可识别的障碍物的图像选为待显示图像（103）。

Description

图像选取方法、自行走设备及计算机存储介质
相关申请的交叉引用
本申请要求2020年4月9日提交的中国专利申请号202010275969.5的优先权，该中国专利申请以其整体通过引用并入本文。
技术领域
本公开涉及图像处理技术，尤其涉及一种图像选取方法、自行走设备及计算机可读存储介质。
背景技术
随着产品智能化的不断创新，与白色家电一样，扫地机(即扫地机器人)也由初级智能向着更高程度的智能化发展，以逐步取代人工清洁。
一般地，扫地机的前方有设置感应器，可侦测障碍物，如碰到墙壁或其他障碍物，会自行转弯，以躲避障碍物。然而，目前扫地机无法直观地查看所躲避的障碍物，更无法识别所躲避的障碍物到底是什么，用户体验差。
发明内容
根据本公开第一方面，提供了一种图像选取方法，应用自行走设备。该方法包括：在行进过程中，对周围环境进行图像采集；当所采集的图像中含有可识别的障碍物时，根据评分规则对所述图像进行评分，所述评分的分值高低用于表示所述可识别的障碍物在所述图像中的成像质量；在收到请求查看所述可识别的障碍物的图像的命令后，将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
根据本公开一实施方式，所述方法还包括：在根据评分规则对所述图像进行评分之后，至少保存含有所述可识别的障碍物的所有图像中评分分值最高的图像。
根据本公开一实施方式，所述方法还包括：至少保存可唯一标识所述评 分分值最高的图像的标识信息。
根据本公开一实施方式，所述根据评分规则对所述图像进行评分，具体包括：采用如下评分参数中的一个或多个对所述图像进行评分：第一评分参数：表示采集所述图像时，所述自行走设备的角速度；第二评分参数：表示采集所述图像时，所述自行走设备与所述可识别的障碍物之间的距离；第三评分参数：表示所述可识别的障碍物在所述图像上所占据面积的大小；第四评分参数：表示所述可识别的障碍物在所述图像上的位置；第五评分参数：表示采集所述图像时是否有使用补光灯。
根据本公开一实施方式，在采用所述第一评分参数、所述第二评分参数、所述第三评分参数、所述第四评分参数和所述第五评分参数中的至少两个评分参数对所述图像进行评分时，按照预设的权重值对所述至少两个评分参数的参数值进行加权，得到所述图像的评分分值。
根据本公开一实施方式，针对所述第一评分参数，角速度绝对值大的参数值大于等于角速度绝对值小的参数值；或，针对所述第二评分参数，距离值在一定范围之内的参数值大于等于其他距离值的参数值；或，针对所述第三评分参数，所述可识别的障碍物在所述图像上所占据面积大的参数值大于等于占据面积小的参数值；或，针对所述第四评分参数，所述可识别的障碍物在所述图像上的位置越接近图像中心，参数值越大；或，针对所述第五评分参数，未使用所述补光灯时的参数值大于等于使用所述补光灯时的参数值。
根据本公开第二方面，还提供了一种自行走设备。所述设备包括：图像采集装置，用于在设备行进过程中，对周围环境进行图像采集；评分装置，用于在所采集的图像中含有可识别的障碍物时，根据评分规则对所述图像进行评分，所述评分的分值高低用于表示所述可识别的障碍物在所述图像中的成像质量；显示控制装置，用于在收到请求查看所述可识别的障碍物的图像的命令后，将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
根据本公开一实施方式，所述设备还包括：存储装置，用于在通过评分装置根据评分规则对所述图像进行评分之后，至少保存含有所述可识别的障碍物的所有图像中评分分值最高的图像。
根据本公开一实施方式，所述存储装置，还用于至少保存可唯一标识所 述评分分值最高的图像的标识信息。
根据本公开一实施方式，所述评分装置，具体用于采用如下评分参数中的一个或多个对所述图像进行评分：第一评分参数：表示采集所述图像时，所述自行走设备的角速度；第二评分参数：表示采集所述图像时，所述自行走设备与所述可识别的障碍物之间的距离；第三评分参数：表示所述可识别的障碍物在所述图像上所占据面积的大小；第四评分参数：表示所述可识别的障碍物在所述图像上的位置；第五评分参数：表示采集所述图像时是否有使用补光灯。
根据本公开一实施方式，所述评分装置，具体用于在采用所述第一评分参数、所述第二评分参数、所述第三评分参数、所述第四评分参数和所述第五评分参数中的至少两个评分参数对所述图像进行评分时，按照预设的权重值对所述至少两个评分参数的参数值进行加权，得到所述图像的评分分值。
根据本公开第三方面，又提供一种计算机可读存储介质，所述存储介质包括一组计算机可执行指令，当所述指令被执行时用于执行上述任一图像选取方法。
根据本公开第四方面，又提供一种自行走设备，包括处理器和存储器。所述存储器存储有能够被所述处理器执行的计算机程序指令。当所述指令被所述处理器执行时用于执行上述任一图像选取方法。
需要理解的是，本公开的教导并不需要实现上面所述的全部有益效果，而是特定的技术方案可以实现特定的技术效果，并且本公开的其他实施方式还能够实现上面未提到的有益效果。
附图说明
通过参考附图阅读下文的详细描述，本公开示例性实施方式的上述以及其他目的、特征和优点将变得易于理解。在附图中，以示例性而非限制性的方式示出了本公开的若干实施方式。
在附图中，相同或对应的标号表示相同或对应的部分。
图1示出了本公开实施例图像选取方法的实现流程示意图；
图2示出了本公开实施例清洁机的组成结构示意图。
具体实施方式
下面将参考若干示例性实施方式来描述本公开的原理和精神。应当理解，给出这些实施方式仅仅是为使本领域技术人员能够更好地理解进而实现本公开，而并非以任何方式限制本公开的范围。相反，提供这些实施方式是为使本公开更加透彻和完整，并能够将本公开的范围完整地传达给本领域的技术人员。
下面结合附图和具体实施例对本公开的技术方案进一步详细阐述。
图1示出了本公开实施例图像选取方法的实现流程示意图。
参考图1，本公开实施例图像选取方法，应用于自行走设备，该方法包括：操作101，在行进过程中，通过图像采集装置对周围环境进行图像采集；操作102，如判断出所采集的图像中含有可识别的障碍物，则根据评分规则对所述图像进行评分；操作103，在收到请求查看某一所述可识别的障碍物的图像的命令后，将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
其中，自行走设备可以是扫地机，还可以是用于清洁玻璃窗等待清洁对象的清洁机等。
在操作101，图像采集装置可以是设置在扫地机前方的摄像头。具体地，以扫地机为例，在扫地机行进过程中，通过摄像头对周围环境进行图像采集。
在操作102，首先判断所采集的图像中是否含有可识别的障碍物，若判断出所所采集的图像中含有可识别的障碍物，则根据评分规则对所述图像进行评分。其中，评分的分值高低用于表示所述可识别的障碍物在所述图像中的成像质量；
这里，操作102根据评分规则对所述图像进行评分，具体包括：采用如下评分参数中的任意一个或任意组合对所述图像进行评分：参数a：采集所述图像时，所述自行走设备的角速度；参数b：采集所述图像时，自行走设备与所述可识别的障碍物之间的距离；参数c：所述可识别障碍物在所述图像上所占据面积的大小；参数d：所述可识别障碍物在所述图像上的位置；参数e：采集所述图像时补光灯是否处于开启状态。
这里，为了方便确定参考c的分值，可以以区域矩形的方式来确定可识别障碍物在所述图像上所占据面积的大小，即确定可识别障碍物在所述图像 上所占据区域矩形的大小。同上参数c的确认，为了方便确定参考d的分值，可以通过确定可识别障碍物所占据区域矩阵距离图像边缘的距离，来确定可识别障碍物在图像上的位置。
在一可实施方式中，当以上评分参数a～e中有两个以上时，可以按照预设的权重值对所述评分参数的参数值进行加权，得到所述图像的评分分值。
具体地，在对上述及评分参数进行参数值确定时，针对不同的参数采用不同的评分规则：针对所述参数a，角速度绝对值大的参数值大于等于角速度绝对值小的参数值，即角速度绝对值越小越好；或，针对所述参数b，距离值在一定范围之内的参数值大于等于其他距离值的参数值，即自行走设备与可识别的障碍物之间的距离，距离适中，不近不远最好；或，针对所述参数c，所述可识别障碍物在所述图像上所占据面积大的参数值大于等于占据面积小的参数值，即可识别障碍物在图像上区域矩形的大小，越大越好；或，针对所述参数d，所述可识别障碍物在所述图像上的位置越接近图像中心，参数d的值越大，即区域矩形与所采集的图像边缘的距离，越远越好；或，针对所述参数e，所述补光灯状态为关闭时的参数值大于等于补光灯状态为开启时的参数值，即补光灯未打开比较好。
在一应用实例中，对于以上a～e评分参数而言，权重从高到底可以依次为eabcd的顺序。
在操作102之后，自行走设备会自动保存含有可识别的障碍物的图像。为了保证能够在后续操作103中能够将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像，故在自动保存的过程中，至少需要保存含有所述可识别的障碍物的所有图像中评分分值最高的图像。
这里，自行走设备在进行图像保存时，可以为每个图像分配一个可唯一标识该图像的标识信息；并且将该标识信息和图像对应存储，从而在后续图像查看时，通过在查看指令中携带标识信息的方式，快速地将对应图像加以显示。
在操作103，由于已对包含可识别的障碍物的图像进行了评分，故在收到请求查看某一可识别的障碍物的图像的命令后，可以直接将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
如此，本公开通过自行走设备，如扫地机上设置的图像采集装置进行图像采集并识别障碍物图像，之后利用评分规则对障碍物图像进行评分的方式，并在接收到查看指令时将评分最高的障碍物图像确定为待显示图像，使得扫地机可以直观地查看所躲避的障碍物，而且由于待显示的障碍物图像评分最高(成像质量最好)，故可供用户很好地识别所躲避的障碍物到底是什么，从而有效提升用户体验。
同理，基于上文所述图像选取方法，本公开实施例还提供一种计算机可读存储介质，所述计算机可读存储介质存储有程序，当所述程序被处理器执行时，使得所述处理器至少执行如下所述的操作步骤：操作101，在行进过程中，通过图像采集装置对周围环境进行图像采集；操作102，如判断出所采集的图像中含有可识别的障碍物，则根据评分规则对所述图像进行评分；操作103，在收到请求查看某一可识别的障碍物的图像的命令后，将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
进一步，基于如上文所述图像选取方法，本公开实施例还提供一种自行走设备，如图2所述，该设备20包括：图像采集装置201，用于在设备行进过程中，对周围环境进行图像采集；评分装置202，用于如判断出所采集的图像中含有可识别的障碍物，则根据评分规则对所述图像进行评分，所述评分的分值高低用于表示所述可识别的障碍物在所述图像中的成像质量；显示控制装置203，用于在收到请求查看某一可识别的障碍物的图像的命令后，将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
根据本公开一实施方式，设备20还包括：存储装置，用于在通过评分装置根据评分规则对所述图像进行评分之后，至少保存含有所述可识别的障碍物的所有图像中评分分值最高的图像。
根据本公开一实施方式，评分装置202，具体用于采用如下评分参数中的任意一个或任意组合对所述图像进行评分：参数a，采集所述图像时，所述自行走设备的角速度；参数b：采集所述图像时，自行走设备与所述可识别的障碍物之间的距离；参数c：所述可识别障碍物在所述图像上所占据面积的大小；参数d：所述可识别障碍物在所述图像上的位置；参数e：采集所述图像时补光灯是否处于开启状态。
根据本公开一实施方式，评分装置202，具体用于所述评分参数有两个 以上时，按照预设的权重值对所述评分参数的值进行加权，得到所述图像的分值。根据本公开一实施方式，针对所述参数a，角速度绝对值大的参数值大于等于角速度绝对值小的参数值；或，针对所述参数b，距离值在一定范围之内的参数值大于等于其他距离值的参数值；或，针对所述参数c，所述可识别障碍物在所述图像上所占据面积大的参数值大于等于占据面积小的参数值；或，针对所述参数d，所述可识别障碍物在所述图像上的位置越接近图像中心，参数d的值越大；或，针对所述参数e，所述补光灯状态为关闭时的参数值大于等于补光灯状态为开启时的参数值。
这里需要指出的是：以上对自行走设备实施例的描述，与前述图1所示的方法实施例的描述是类似的，具有同前述图1所示的方法实施例相似的有益效果，因此不做赘述。对于本公开自行走设备实施例中未披露的技术细节，请参照本公开前述图1所示的方法实施例的描述而理解，为节约篇幅，因此不再赘述。
需要说明的是，在本文中，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者装置不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者装置所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括该要素的过程、方法、物品或者装置中还存在另外的相同要素。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，如：多个单元或组件可以结合，或可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的各组成部分相互之间的耦合、或直接耦合、或通信连接可以是通过一些接口，设备或单元的间接耦合或通信连接，可以是电性的、机械的或其它形式的。
上述作为分离部件说明的单元可以是、或也可以不是物理上分开的，作为单元显示的部件可以是、或也可以不是物理单元；既可以位于一个地方，也可以分布到多个网络单元上；可以根据实际的需要选择其中的部分或全部单元来实现本实施例方案的目的。
另外，在本公开各实施例中的各功能单元可以全部集成在一个处理单元中，也可以是各单元分别单独作为一个单元，也可以两个或两个以上单元集成在一个单元中；上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：移动存储设备、只读存储器(Read Only Memory，ROM)、磁碟或者光盘等各种可以存储程序代码的介质。
或者，本公开上述集成的单元如果以软件功能模块的形式实现并作为独立的产品销售或使用时，也可以存储在一个计算机可读取存储介质中。基于这样的理解，本公开实施例的技术方案本质上或者说对现有技术做出贡献的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机、服务器、或者网络设备等)执行本公开各个实施例所述方法的全部或部分。而前述的存储介质包括：移动存储设备、ROM、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本公开的具体实施方式，但本公开的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本公开揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本公开的保护范围之内。因此，本公开的保护范围应以所述权利要求的保护范围为准。

Claims (13)

  1. 一种图像选取方法，其特征在于，应用于自行走设备，所述方法包括：
    在行进过程中，通过图像采集装置对周围环境进行图像采集；
    当所采集的图像中含有可识别的障碍物时，根据评分规则对所述图像进行评分，所述评分的分值高低用于表示所述可识别的障碍物在所述图像中的成像质量；
    在收到请求查看所述可识别的障碍物的图像的命令后，将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
  2. 根据权利要求1所述的方法，其特征在于，所述方法还包括：在根据评分规则对所述图像进行评分之后，
    至少保存含有所述可识别的障碍物的所有图像中评分分值最高的图像。
  3. 根据权利要求2所述的方法，其特征在于，所述方法还包括：
    至少保存可唯一标识所述评分分值最高的图像的标识信息。
  4. 根据权利要求1所述的方法，其特征在于，
    根据评分规则对所述图像的评分，包括：采用如下评分参数中的一个或多个对所述图像进行评分：
    第一评分参数：表示采集所述图像时，所述自行走设备的角速度；
    第二评分参数：表示采集所述图像时，所述自行走设备与所述可识别的障碍物之间的距离；
    第三评分参数：表示所述可识别的障碍物在所述图像上所占据面积的大小；
    第四评分参数：表示所述可识别的障碍物在所述图像上的位置；
    第五评分参数：表示采集所述图像时是否有使用补光灯。
  5. 根据权利要求4所述的方法，还包括：
    在采用所述第一评分参数、所述第二评分参数、所述第三评分参数、所述第四评分参数和所述第五评分参数中的至少两个评分参数对所述图像进行评分时，按照预设的权重值对所述至少两个评分参数的参数值进行加权，得到所述图像的评分分值。
  6. 根据权利要求4或5所述的方法，其特征在于，
    针对所述第一评分参数，角速度绝对值大的参数值大于等于角速度绝对值小的参数值；或，
    针对所述第二评分参数，距离值在一定范围之内的参数值大于等于其他距离值的参数值；或，
    针对所述第三评分参数，所述可识别的障碍物在所述图像上所占据面积大的参数值大于等于占据面积小的参数值；或，
    针对所述第四评分参数，所述可识别的障碍物在所述图像上的位置越接近所述图像的中心，参数值越大；或，
    针对所述第五评分参数，未使用所述补光灯时的参数值大于等于使用所述补光灯时的参数值。
  7. 一种自行走设备，其特征在于，所述设备包括：
    图像采集装置，用于在设备行进过程中，对周围环境进行图像采集；
    评分装置，用于在所采集的图像中含有可识别的障碍物时，根据评分规则对所述图像进行评分，所述评分的分值高低用于表示所述可识别的障碍物在所述图像中的成像质量；
    显示控制装置，用于在收到请求查看所述可识别的障碍物的图像的命令后，将评分分值最高的包含所述可识别的障碍物的图像选为待显示图像。
  8. 根据权利要求7所述的设备，其特征在于，所述设备还包括：
    存储装置，用于在通过评分装置根据评分规则对所述图像进行评分之后，至少保存含有所述可识别的障碍物的所有图像中评分分值最高的图像。
  9. 根据权利要求8所述的设备，其特征在于，
    所述存储装置，还用于至少保存可唯一标识所述评分分值最高的图像的标识信息。
  10. 根据权利要求7所述的设备，其特征在于，
    所述评分装置，用于采用如下评分参数中的一个或多个对所述图像进行评分：第一评分参数：表示采集所述图像时，所述自行走设备的角速度；第二评分参数：表示采集所述图像时，所述自行走设备与所述可识别的障碍物之间的距离；第三评分参数：表示所述可识别的障碍物在所述图像上所占据面积的大小；第四评分参数：表示所述可识别的障碍物在所述图像上的位置；第五评分参数：表示采集所述图像时是否有使用补光灯。
  11. 根据权利要求10所述的设备，其特征在于，
    所述评分装置，用于在采用所述第一评分参数、所述第二评分参数、所述第三评分参数、所述第四评分参数和所述第五评分参数中的至少两个评分参数对所述图像进行评分时，按照预设的权重值对所述至少两个评分参数的参数值进行加权，得到所述图像的评分分值。
  12. 一种计算机可读存储介质，其特征在于，所述存储介质包括一组计算机可执行指令，当所述指令被执行时用于执行上述权利要求1至6任一项所述的图像选取方法。
  13. 一种自行走设备，包括处理器和存储器，所述存储器存储有能够被所述处理器执行的计算机程序指令，当所述指令被所述处理器执行时用于执行上述权利要求1至6任一项所述的图像选取方法。
PCT/CN2021/070301 2020-04-09 2021-01-05 图像选取方法、自行走设备及计算机存储介质 WO2021203784A1 (zh)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP21784600.5A EP4134773A4 (en) 2020-04-09 2021-01-05 IMAGE SELECTION METHOD, SELF-PROPELLED DEVICE, AND COMPUTER STORAGE MEDIUM
US17/995,730 US11880967B2 (en) 2020-04-09 2021-01-05 Image selection method, self-propelled apparatus, and computer storage medium

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202010275969.5A CN111538330B (zh) 2020-04-09 2020-04-09 一种图像选取方法、自行走设备及计算机存储介质
CN202010275969.5 2020-04-09

Publications (1)

Publication Number Publication Date
WO2021203784A1 true WO2021203784A1 (zh) 2021-10-14

Family

ID=71973578

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/070301 WO2021203784A1 (zh) 2020-04-09 2021-01-05 图像选取方法、自行走设备及计算机存储介质

Country Status (4)

Country Link
US (1) US11880967B2 (zh)
EP (1) EP4134773A4 (zh)
CN (1) CN111538330B (zh)
WO (1) WO2021203784A1 (zh)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111538330B (zh) * 2020-04-09 2022-03-04 北京石头世纪科技股份有限公司 一种图像选取方法、自行走设备及计算机存储介质

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107992086A (zh) * 2018-01-03 2018-05-04 广东工业大学 一种无人机避障方法及系统
US20180354132A1 (en) * 2017-06-09 2018-12-13 Lg Electronics Inc. Moving robot and control method thereof
CN109101862A (zh) * 2017-06-20 2018-12-28 中建空列（北京）科技有限公司 一种空中轨道车辆的障碍物检测方法、障碍物避让方法及其系统
CN110688913A (zh) * 2019-09-09 2020-01-14 苏州臻迪智能科技有限公司 一种基于智能设备的障碍物检测方法及装置
CN110895409A (zh) * 2018-08-23 2020-03-20 珠海格力电器股份有限公司 避让障碍物的控制方法
CN111538330A (zh) * 2020-04-09 2020-08-14 北京石头世纪科技股份有限公司 一种图像选取方法、自行走设备及计算机存储介质

Family Cites Families (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9675226B2 (en) * 2012-10-26 2017-06-13 Lg Electronics Inc. Robot cleaner system and control method of the same
CN103002152B (zh) * 2012-12-06 2015-09-09 广东欧珀移动通信有限公司 移动终端连续拍照方法及装置
CN103542873A (zh) * 2013-10-01 2014-01-29 刘文化 采集障碍空间情景(画面)信息的装置
CN106527423B (zh) * 2015-09-15 2020-01-21 小米科技有限责任公司 清洁机器人及其控制方法
CN107466477B (zh) * 2015-11-12 2021-08-10 松下电器（美国）知识产权公司 显示方法、计算机可读取记录介质以及显示装置
EP3422325A4 (en) * 2016-06-13 2019-04-24 SZ DJI Technology Co., Ltd. AIRCRAFT VEHICLE WITHOUT PILOT, DELIVERY SYSTEM, METHOD FOR CONTROLLING AERIAL VEHICLE WITHOUT DRIVER AND CONTROL PROGRAM FOR AERIAL VEHICLE WITHOUT PILOT
WO2018112707A1 (zh) * 2016-12-19 2018-06-28 深圳前海达闼云端智能科技有限公司 障碍物检测方法及装置
CN106791393B (zh) * 2016-12-20 2019-05-17 维沃移动通信有限公司 一种拍摄方法及移动终端
CN107625489A (zh) * 2017-08-25 2018-01-26 珠海格力电器股份有限公司 阻挡物信息的处理方法、装置、处理器及扫地机器人
CN108125622A (zh) * 2017-12-15 2018-06-08 珊口（上海）智能科技有限公司 控制方法、系统及所适用的清洁机器人
KR101886404B1 (ko) * 2018-01-11 2018-08-09 박민경 무인 비행체의 레이스 시스템 및 방법
US10769466B2 (en) * 2018-02-20 2020-09-08 International Business Machines Corporation Precision aware drone-based object mapping based on spatial pattern recognition
CN108833942A (zh) * 2018-06-28 2018-11-16 北京达佳互联信息技术有限公司 视频封面选取方法、装置、计算机设备及存储介质
JP6922969B2 (ja) * 2018-07-20 2021-08-18 ソニーグループ株式会社 移動体、制御方法、およびプログラム
CN109947109B (zh) * 2019-04-02 2022-06-21 北京石头创新科技有限公司 机器人工作区域地图构建方法、装置、机器人和介质
CN110784644B (zh) * 2019-08-26 2022-12-09 腾讯科技（深圳）有限公司 图像处理方法及装置

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20180354132A1 (en) * 2017-06-09 2018-12-13 Lg Electronics Inc. Moving robot and control method thereof
CN109101862A (zh) * 2017-06-20 2018-12-28 中建空列（北京）科技有限公司 一种空中轨道车辆的障碍物检测方法、障碍物避让方法及其系统
CN107992086A (zh) * 2018-01-03 2018-05-04 广东工业大学 一种无人机避障方法及系统
CN110895409A (zh) * 2018-08-23 2020-03-20 珠海格力电器股份有限公司 避让障碍物的控制方法
CN110688913A (zh) * 2019-09-09 2020-01-14 苏州臻迪智能科技有限公司 一种基于智能设备的障碍物检测方法及装置
CN111538330A (zh) * 2020-04-09 2020-08-14 北京石头世纪科技股份有限公司 一种图像选取方法、自行走设备及计算机存储介质

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See also references of EP4134773A4 *

Also Published As

Publication number Publication date
EP4134773A4 (en) 2024-03-20
CN111538330A (zh) 2020-08-14
CN111538330B (zh) 2022-03-04
US11880967B2 (en) 2024-01-23
US20230122704A1 (en) 2023-04-20
EP4134773A1 (en) 2023-02-15

Similar Documents

Publication Publication Date Title
TWI531929B (zh) 基於影像來識別觸控表面的目標接觸區域之技術
KR102539579B1 (ko) 정보의 표시 영역을 적응적으로 변경하기 위한 전자 장치 및 그의 동작 방법
CN111989537A (zh) 用于在无约束环境中检测人类视线和手势的系统和方法
EP3048605B1 (en) Information processing device, information processing method, and computer program
JP6958570B2 (ja) 表示制御装置、表示制御方法およびプログラム
JP2015521312A (ja) 視標追跡によるユーザ入力処理
US10936079B2 (en) Method and apparatus for interaction with virtual and real images
WO2021203784A1 (zh) 图像选取方法、自行走设备及计算机存储介质
US20210241467A1 (en) Electronic apparatus and controlling method thereof
CN108171116A (zh) 飞行器辅助避障方法、装置和辅助避障系统
WO2018179661A1 (ja) 情報処理装置、情報処理方法およびプログラム
CN110007832A (zh) 信息终端装置、信息处理系统以及存储有显示控制程序的计算机可读非暂时性的存储介质
CN111064896A (zh) 设备控制方法及电子设备
CN104904191A (zh) 移动装置与用于建立无线链路的方法
CN111176425A (zh) 多屏幕操作方法与使用此方法的电子系统
CN108509593A (zh) 一种显示方法及电子设备、存储介质
JP4979895B2 (ja) ディスプレイ制御装置、ディスプレイ制御方法、ディスプレイ制御プログラム、およびディスプレイ
WO2021203780A1 (zh) 图像查看方法、终端及清洁机
WO2019130729A1 (ja) 情報処理装置、情報処理方法および情報処理システム
KR102089063B1 (ko) Hmd를 이용한 로봇청소 시스템 및 그 제어 방법
TW202044007A (zh) 用於選擇在設備的顯示媒介上的交互物件的方法
TW201734715A (zh) 虛擬實境裝置及虛擬實境方法
US10372297B2 (en) Image control method and device
US11163379B2 (en) Illuminating an environment for localisation
JP2014225782A (ja) 情報処理装置、通信端末およびデータ取得方法

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21784600

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2021784600

Country of ref document: EP

Effective date: 20221109