Method and apparatus for operating control of device, storage medium and electronic device

Abstract

This application provides a method and apparatus for controlling the operation of a device, a storage medium, and an electronic device. The method includes: acquiring an image of a target ground image by using an image acquisition component on a cleaning device; performing object recognition on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned, wherein the object parameters of the set of target objects include object categories and aggregation parameters of the target objects, the aggregation parameters of the set of target objects representing the degree of aggregation of the set of target objects in the area to be cleaned; determining target operating parameters of the cleaning device based on the object categories and aggregation parameters of the set of target objects; and controlling the cleaning device to clean the set of target objects according to the target operating parameters. This application solves the problem of low cleaning efficiency caused by incomplete cleaning in related technologies.

Description

[Technical Field]

[0001] This application relates to the field of smart homes, and more specifically, to a method and apparatus for controlling the operation of a device, a storage medium, and an electronic device. [Background Technology]

[0002] Currently, in the process of controlling cleaning equipment to perform area cleaning, the area to be cleaned is usually cleaned according to the set operating parameters. However, using the above-mentioned equipment operation control method, since the actual conditions of different areas are not exactly the same, cleaning the area according to the set operating parameters is prone to incomplete cleaning, resulting in the need for multiple cleanings and low cleaning efficiency.

[0003] It is evident that the operation and control methods of the equipment in the relevant technologies suffer from low cleaning efficiency due to the tendency for incomplete cleaning. [Summary of the Invention]

[0004] The purpose of this application is to provide a method and apparatus for controlling the operation of a device, a storage medium and an electronic device, so as to at least solve the problem of low cleaning efficiency caused by incomplete cleaning in the operation control methods of related technologies.

[0005] The purpose of this application is to achieve the following technical solution:

[0006] According to one aspect of the embodiments of this application, a method for controlling the operation of a device is provided, comprising: acquiring an image of a target ground image by means of an image acquisition component on a cleaning device; performing object recognition on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned, wherein the object parameters of the set of target objects include object categories and aggregation parameters of the set of target objects, the aggregation parameters of the set of target objects being used to represent the degree of aggregation of the set of target objects in the area to be cleaned; determining target operating parameters of the cleaning device based on the object categories and aggregation parameters of the set of target objects; and controlling the cleaning device to clean the set of target objects according to the target operating parameters.

[0007] In one exemplary embodiment, the step of acquiring an image of the area to be cleaned through the image acquisition component on the cleaning device to obtain a target ground image includes: activating a supplementary lighting component on the cleaning device, wherein the activated supplementary lighting component is used to provide supplementary lighting to the area to be cleaned; and acquiring an image of the area to be cleaned through the image acquisition component to obtain the target ground image.

[0008] In an exemplary embodiment, the step of performing object recognition on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned includes: recognizing the object shadow of each candidate object in a set of candidate objects contained in the target ground image to obtain the object size of each candidate object; filtering the set of target objects from the set of candidate objects according to the object size of each candidate object to obtain object parameters of the set of target objects, wherein the object size of each target object in the set of target objects is less than or equal to a first size threshold.

[0009] In an exemplary embodiment, identifying the object shadow of each candidate object in a set of candidate objects contained in the target ground image to obtain the object size of each candidate object includes: determining the shadow area of ​​the object shadow of each candidate object in the target ground image to obtain the shadow area of ​​each candidate object; and converting the shadow area of ​​each candidate object into the object size of each candidate object according to the projection angle of each candidate object.

[0010] In an exemplary embodiment, the step of filtering a group of target objects from a group of candidate objects according to the object size of each candidate object to obtain the object parameters of the group of target objects includes: determining candidate objects in the group of candidate objects whose object size is less than or equal to a second size threshold as first target objects, wherein the first target objects belong to the group of target objects; determining the object parameters of the first target objects according to the degree of aggregation of the first target objects in the area to be cleaned, wherein the object category of the first target objects is set to a preset category; identifying the object categories of other candidate objects in the group of candidate objects besides the first target objects to obtain the object categories of the other candidate objects; determining candidate objects in the other candidate objects whose object categories belong to the category to be cleaned as second target objects, wherein the second target objects belong to the group of target objects; and determining the object parameters of the second target objects according to the object category of the second target objects and the degree of aggregation of the second target objects in the area to be cleaned.

[0011] In an exemplary embodiment, determining the target operating parameters of the cleaning device based on the object category of the set of target objects and the aggregation parameters of the set of target objects includes: when the set of target objects includes multiple target objects, determining the operating parameters corresponding to each target object based on the object category of each target object and the aggregation parameters of each target object; and performing a fusion operation on the operating parameters corresponding to each target object to obtain the target operating parameters of the cleaning device.

[0012] In one exemplary embodiment, the object parameters of the set of target objects further include: location information for indicating the object position of the set of target objects; before controlling the cleaning device to clean the set of target objects according to the target operating parameters, the method further includes: controlling the cleaning device to move towards the object position of the set of target objects until the distance between the cleaning component of the cleaning device and the set of target objects is less than or equal to a target distance threshold.

[0013] According to another aspect of the embodiments of this application, an operation control device for an equipment is also provided, comprising: an acquisition unit, configured to acquire images of a target ground image by means of an image acquisition component on the cleaning equipment; an identification unit, configured to perform object identification on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned, wherein the object parameters of the set of target objects include object categories and aggregation parameters of the set of target objects, and the aggregation parameters of the set of target objects are used to represent the degree of aggregation of the set of target objects in the area to be cleaned; a determination unit, configured to determine target operating parameters of the cleaning equipment based on the object categories and aggregation parameters of the set of target objects; and a first control unit, configured to control the cleaning equipment to clean the set of target objects according to the target operating parameters.

[0014] In one exemplary embodiment, the acquisition unit includes: a startup module for activating a supplementary lighting component on the cleaning device, wherein the activated supplementary lighting component is used to provide supplementary lighting to the area to be cleaned; and an acquisition module for acquiring an image of the area to be cleaned through the image acquisition component to obtain the target ground image.

[0015] In an exemplary embodiment, the identification unit includes: an identification module, configured to identify the object shadow of each candidate object in a set of candidate objects contained in the target ground image, and obtain the object size of each candidate object; and a filtering module, configured to filter the set of target objects from the set of candidate objects according to the object size of each candidate object, and obtain the object parameters of the set of target objects, wherein the object size of each target object in the set of target objects is less than or equal to a first size threshold.

[0016] In an exemplary embodiment, the identification module includes: a first determining submodule, configured to determine the shadow area of ​​the object shadow of each candidate object in the target ground image, thereby obtaining the shadow area of ​​each candidate object; and a conversion submodule, configured to convert the shadow area of ​​each candidate object into the object size of each candidate object according to the projection angle of each candidate object.

[0017] In an exemplary embodiment, the filtering module includes: a second determining submodule, configured to determine candidate objects whose object size is less than or equal to a second size threshold from the set of candidate objects as first target objects, wherein the first target objects belong to the set of target objects; a third determining submodule, configured to determine object parameters of the first target objects based on the degree of aggregation of the first target objects in the area to be cleaned, wherein the object category of the first target objects is set to a preset category; an identification submodule, configured to identify the object categories of other candidate objects in the set of candidate objects besides the first target objects, to obtain the object categories of the other candidate objects; a fourth determining submodule, configured to determine candidate objects whose object category belongs to the category to be cleaned from the other candidate objects as second target objects, wherein the second target objects belong to the set of target objects; and a fifth determining submodule, configured to determine object parameters of the second object based on the object category of the second target object and the degree of aggregation of the second target objects in the area to be cleaned.

[0018] In one exemplary embodiment, the determining unit includes: a determining module, configured to determine, when the set of target objects includes multiple target objects, an operating parameter corresponding to each target object based on the object category of each target object and the aggregation parameter of each target object; and an execution module, configured to perform a fusion operation on the operating parameters corresponding to each target object to obtain the target operating parameters of the cleaning device.

[0019] In one exemplary embodiment, the object parameters of the set of target objects further include: location information for indicating the object position of the set of target objects; the device further includes: a second control unit, configured to control the cleaning device to move towards the object position of the set of target objects before the cleaning device is controlled to clean the set of target objects according to the target operating parameters, until the distance between the cleaning component of the cleaning device and the set of target objects is less than or equal to a target distance threshold.

[0020] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, and the computer program is configured to execute the operation control method of the above-described device when it is run.

[0021] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the device operation control method through the computer program.

[0022] In this embodiment, the operating parameters of the cleaning equipment are set by considering the object categories and aggregation levels of a set of target objects. The image acquisition component on the cleaning equipment acquires images of the area to be cleaned, obtaining a target ground image. Object recognition is performed on the target ground image to obtain object parameters for a set of target objects to be cleaned within the area. These object parameters include object categories and aggregation parameters, representing the aggregation level of the target objects in the area to be cleaned. Based on the object categories and aggregation parameters, target operating parameters for the cleaning equipment are determined. The cleaning equipment is then controlled to clean the set of target objects according to these target operating parameters. Since the operating parameters are determined based on the object categories and aggregation levels of the objects to be cleaned, the operating parameters can be flexibly adjusted to suit the current objects to be cleaned, ensuring complete cleaning and improving the integrity of the area cleaning. This achieves the technical effect of improving area cleaning efficiency, thereby solving the problem of low cleaning efficiency caused by incomplete cleaning in related technologies. [Attached Image Description]

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0024] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a schematic diagram of the hardware environment of an optional device operation control method according to an embodiment of this application;

[0026] Figure 2This is a flowchart illustrating an optional device operation control method according to an embodiment of this application;

[0027] Figure 3 This is an optional mapping representation according to an embodiment of this application;

[0028] Figure 4 This is a flowchart illustrating another optional device operation control method according to an embodiment of this application;

[0029] Figure 5 This is a structural block diagram of an optional device operation control apparatus according to an embodiment of this application;

[0030] Figure 6 This is a structural block diagram of an optional electronic device according to an embodiment of this application.

Detailed Implementation Methods

[0031] The present application will be described in detail below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specified, the embodiments and features described in the embodiments of the present application can be combined with each other.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0033] According to one aspect of the embodiments of this application, a method for controlling the operation of a device is provided. Optionally, in this embodiment, the above-described method for controlling the operation of a device can be applied to, for example... Figure 1 The hardware environment shown consists of cleaning equipment 102, base station 104, and cloud platform 106. For example... Figure 1 As shown, the cleaning device 102 can be connected to the base station 104 and / or the cloud platform 106 (e.g., a voice cloud platform) via a network to enable interaction between the cleaning device 102 and the base station 104 and / or the cloud platform 106.

[0034] The aforementioned networks may include, but are not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network (WAN), metropolitan area network (MAN), local area network (LAN). The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth, infrared. The network used by the cleaning device 102 to communicate with the base station 104 and / or the cloud platform 106 may be the same as or different from the network used by the base station 104 to communicate with the cloud platform 106. The cleaning device 102 may include, but is not limited to: a sweeper, a floor scrubber, etc.

[0035] The device operation control method of this application embodiment can be executed by the cleaning device 102, the base station 104, or the cloud platform 106 individually, or by at least two of the cleaning device 102, the base station 104, and the cloud platform 106 together. The device operation control method of this application embodiment can also be executed by a client installed on the cleaning device 102 or the base station 104.

[0036] Taking the cleaning equipment 102 as an example to illustrate the equipment operation control method in this embodiment, Figure 2 This is a flowchart illustrating an optional device operation control method according to an embodiment of this application, as shown below. Figure 2 As shown, the process of this method may include the following steps:

[0037] Step S202: The image acquisition component on the cleaning equipment acquires images of the area to be cleaned to obtain a target ground image.

[0038] The device operation control method in this embodiment can be applied to scenarios where the operating status of cleaning equipment is controlled. The cleaning equipment can be a device with area cleaning function (e.g., sweeping, washing, etc.), such as a robot with area cleaning function. The robot can include, but is not limited to, one of the following: a sweeping robot (i.e., a sweeping machine), a floor scrubbing robot (i.e., a floor scrubbing machine), or a robot that integrates washing and mopping.

[0039] In related technologies, cleaning equipment typically operates according to fixed parameters during area cleaning. However, the required operating parameters for effectively cleaning an area vary depending on the objects to be cleaned. If fixed operating parameters are consistently used for cleaning dust, the cleaning equipment may fail to clean certain types of objects effectively, while incurring significant resource waste when cleaning other types.

[0040] For example, when the object to be cleaned is something that is relatively easy to clean, such as dust, only a small amount of operating parameters are needed to clean the area; when the object to be cleaned is something that is difficult to clean, such as something with larger particles or something sticky, a larger amount of operating parameters are needed to clean the area.

[0041] In this embodiment, during the area cleaning process, the cleaning equipment can first determine the object category and degree of aggregation of the objects to be cleaned, determine the operating parameters of the cleaning equipment based on the determined object category and degree of aggregation, and control the cleaning equipment to clean the objects to be cleaned according to the determined operating parameters. This can ensure that the operating parameters of the cleaning equipment are suitable for the current objects to be cleaned, thereby saving resources and improving the cleaning efficiency of the cleaning equipment.

[0042] For the current area to be cleaned, while the cleaning equipment is cleaning the area, it can acquire images of the area to be cleaned through its image acquisition component to obtain a target ground image. The image acquisition device can be a camera, a video camera (e.g., a macro camera), or other components with image acquisition capabilities; this embodiment does not limit the specific device used.

[0043] For example, a robot vacuum cleaner can use a macro camera to acquire images of the ground (an example of the target ground image mentioned above).

[0044] Optionally, to better acquire images of the area to be cleaned, multiple image acquisition components can be installed on the cleaning equipment. Multiple ground images can be obtained by acquiring images of the area to be cleaned through some or all of these components. The target ground image can be multiple ground images, or it can be a single ground image obtained by processing multiple ground images. The aforementioned processing of multiple ground images can be either stitching together multiple ground images or performing feature fusion on multiple ground images; this embodiment does not limit the specific method used.

[0045] Multiple image acquisition components can be set in different locations on the cleaning device, or they can be set in the same location on the cleaning device. For example, an image acquisition component can be set on the bottom surface of the robot vacuum cleaner to acquire images of the bottom area to be cleaned, or an image acquisition component can be set in front of the robot vacuum cleaner to acquire images of the front area to be cleaned. This embodiment does not limit this.

[0046] In this embodiment, when the image acquisition component acquires images of the area to be cleaned, it can acquire multiple images of the area to be cleaned to obtain multiple ground images. Similarly, the target ground image can be multiple ground images, or it can be a single ground image obtained by processing multiple ground images.

[0047] Step S204: Perform object recognition on the target ground image to obtain object parameters of a set of target objects to be cleaned in the area to be cleaned. The object parameters of the set of target objects include object categories and aggregation parameters of the target objects. The aggregation parameters of the set of target objects are used to represent the degree of aggregation of the set of target objects in the area to be cleaned.

[0048] In this embodiment, after obtaining the target ground image, the cleaning device can perform object recognition on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned. Here, the set of target objects can be dirt particles within the area to be cleaned. The object parameters of the set of target objects may include: object categories of the set of target objects, aggregation parameters of the set of target objects, and may also include other parameters of the set of target objects, such as object location. The aggregation parameters of the set of target objects are used to represent the degree of aggregation of the set of target objects in the area to be cleaned.

[0049] Optionally, the process of object recognition in the target ground image can be as follows: first, object recognition is performed on the target ground image to determine the object location and object category of each target object in a set of target objects included in the target ground image; then, based on the object location and object category of each target object, a set of object parameters of the target objects are determined.

[0050] The method for determining the location of each target object can be as follows: first, determine the location of each target object in the target ground image; then, based on the transformation relationship between the target ground image and the area to be cleaned, determine the location of the target object within the area to be cleaned. The method for determining the object category of each target object can be as follows: extract the object features of each target object; and then, based on these features, determine the object category of each target object.

[0051] When determining the object parameters of a set of target objects, the object category with the highest number of objects among all target objects in the set can be identified as the object category of the set of target objects. Alternatively, all corresponding object categories within the set of target objects can be identified as the object category of the set of target objects. In this case, the set of target objects can have one or more object categories. When determining the aggregation parameters of a set of target objects, the distribution of the set of target objects in the area to be cleaned can be determined based on the object location of each target object (this can be represented by density or other parameters). Based on the distribution of the set of target objects in the area to be cleaned, the aggregation parameters of the set of target objects can be determined.

[0052] Optionally, the aggregation parameters of a set of target objects can be determined based on the brightness of the objects corresponding to the locations of the target objects in the target ground image. The lower the brightness of the objects corresponding to the locations of the target objects, the higher the aggregation parameters of the set of target objects (i.e., the higher the degree of aggregation of the set of target objects in the area to be cleaned).

[0053] Step S206: Determine the target operating parameters of the cleaning equipment based on the object categories of a set of target objects and the aggregation parameters of a set of target objects.

[0054] In this embodiment, after determining a set of object categories and a set of aggregation parameters for the target objects, the cleaning device can determine its target operating parameters based on these parameters. For example, after determining that the object to be cleaned is cat litter and its aggregation parameters, the robotic vacuum cleaner can determine the operating parameters used to clean the cat litter based on these parameters.

[0055] Optionally, the cleaning equipment may store a mapping table of target operating parameters corresponding to different aggregation parameters under different object categories. The process of determining the target operating parameters of the cleaning equipment described above can be: based on the object category and aggregation parameters of a set of target objects, the corresponding operating parameters are found in the mapping table to obtain the target operating parameters. The target operating parameters may include the operating parameters of multiple equipment components on the cleaning equipment, including the operating parameters of liquid storage components (e.g., water tanks), the operating parameters of cleaning components (e.g., roller brushes, mops, etc.), the operating parameters of motors (e.g., negative pressure generators), and the operating parameters of other components, which are not limited in this embodiment.

[0056] For example, such as Figure 3 As shown, after the robot vacuum cleaner determines that the object category of a set of objects to be cleaned is A and the aggregation parameter is B, it can look up the running parameters (i.e., running parameters C) corresponding to the object category A and aggregation parameter B in the mapping table.

[0057] Step S208: Control the cleaning equipment to clean a group of target objects according to the target operating parameters.

[0058] After determining the target operating parameters, the cleaning equipment can be controlled to clean a set of target objects according to these parameters. For example, the cleaning equipment can adjust the operating state of its cleaning components according to the target operating parameters, so that the cleaning components clean the set of target objects at a speed corresponding to the object category and aggregation parameters. For instance, the mop of a robotic vacuum cleaner can be controlled to clean a set of objects to be cleaned according to the determined operating parameters C.

[0059] Optionally, when the cleaning equipment is controlled to clean a group of target objects according to the target operating parameters, the cleaning equipment can first move to the object position of the group of target objects in the area to be cleaned, and then control the cleaning equipment to clean the group of target objects according to the target operating parameters, so as to achieve personalized cleaning of the group of target objects (i.e., directional cleaning of the group of target objects).

[0060] Through steps S202 to S208, the image acquisition component on the cleaning equipment acquires images of the area to be cleaned, obtaining a target ground image. Object recognition is performed on the target ground image to obtain object parameters for a set of target objects to be cleaned within the area. These object parameters include object categories and aggregation parameters, which represent the degree of aggregation of the target objects in the area to be cleaned. Based on the object categories and aggregation parameters, target operating parameters for the cleaning equipment are determined. The cleaning equipment is then controlled to clean the target objects according to these target operating parameters. This solves the problem of low cleaning efficiency caused by incomplete cleaning in related technologies, thus improving the efficiency of area cleaning.

[0061] In one exemplary embodiment, an image acquisition component on a cleaning device acquires an image of the area to be cleaned to obtain a target ground image, including:

[0062] S11, activate the supplementary lighting component on the cleaning equipment, wherein the activated supplementary lighting component is used to provide supplementary lighting to the area to be cleaned;

[0063] S12: The image acquisition component acquires images of the area to be cleaned to obtain a target ground image.

[0064] In this embodiment, in order to improve the image quality of the ground image, when it is necessary to acquire images of the area to be cleaned, the area to be cleaned can be illuminated first, and then the image acquisition component can be used to acquire images of the area to be cleaned to obtain the target ground image. With the help of illumination, the clarity of the acquired ground image can be improved, thereby improving the accuracy of object recognition.

[0065] Optionally, supplemental lighting for the area to be cleaned can be achieved by activating a supplemental lighting component on the cleaning equipment. Once activated, the supplemental lighting component can be used to illuminate the area to be cleaned. During the image acquisition process of the area to be cleaned by the image acquisition component, the supplemental lighting component can remain on. The aforementioned supplemental lighting component can be a supplemental light installed on the cleaning equipment, or other supplemental lighting components installed on the cleaning equipment; this embodiment does not limit this. The supplemental lighting component can use white light, yellow light, or other colors of light to illuminate the area to be cleaned; this embodiment does not limit this either.

[0066] Optionally, to avoid wasting resources, after the image acquisition component acquires an image of the area to be cleaned and obtains the target ground image, the supplementary lighting component can be turned off to stop supplementary lighting on the area to be cleaned.

[0067] It should be noted that, in order to better supplement the lighting of the area to be cleaned, the supplementary lighting component can be an angle-adjustable supplementary lighting component to supplement the lighting of the area to be cleaned from different directions. During the process of supplementing the lighting of the area to be cleaned by the above-mentioned supplementary lighting component, the cleaning equipment can record the supplementary lighting angle of the supplementary lighting component. That is, the angle information of the supplementary lighting component when the target ground image was acquired can be attached to the target ground image.

[0068] For example, after adjusting the angle of the supplementary light, the robot vacuum can turn on the supplementary light to illuminate the area to be cleaned, and take pictures of the area to be cleaned using the camera on the robot vacuum to obtain a ground image.

[0069] In this embodiment, after supplementing the area to be cleaned with supplemental lighting by the supplemental lighting component, the image quality of the collected ground image can be improved, thereby increasing the accuracy of object recognition.

[0070] In one exemplary embodiment, object recognition is performed on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned, including:

[0071] S21, Identify the object shadow of each candidate object in a set of candidate objects contained in the target ground image, and obtain the object size of each candidate object;

[0072] S22, according to the object size of each candidate object, select a set of target objects from a set of candidate objects to obtain a set of target object object parameters, wherein the object size of each target object in the set of target objects is less than or equal to the first size threshold.

[0073] The target ground image may contain a set of candidate objects. This set of candidate objects can be all objects on the area to be cleaned, and may or may not be objects to be cleaned. To identify the candidate objects in the target ground image, object size can be identified based on object shadows, and the target objects to be cleaned can be selected based on the object size of the candidate objects.

[0074] In this embodiment, after obtaining the target ground image, the cleaning device can identify the object shadow of each candidate object in a set of candidate objects contained in the target ground image to obtain the object size of each candidate object. When identifying the object size of the candidate objects, the cleaning device can first determine the size of the object shadow of each candidate object, and then determine the object size of each candidate object based on the size of the object shadow.

[0075] The size of the object shadow of a candidate object can be the area, perimeter, or diameter of the object shadow; this embodiment does not limit this. For example, for a candidate object, if the conversion ratio between the size of the object shadow and the object size is D, and the size of the object shadow is determined to be E, then the object size E / D can be determined.

[0076] In this embodiment, after determining the object size of each candidate object, the cleaning device can filter out a set of target objects from a set of candidate objects according to the object size of each candidate object, thus obtaining a set of object parameters for the target objects. For some larger objects that are not suitable for cleaning by the cleaning device, a first size threshold can be set, that is, the maximum size of the object to be cleaned, and the object size of each filtered target object is less than or equal to the first size threshold.

[0077] For example, if the first size threshold is set to 20mm (this is just an example; the actual size threshold can be set according to actual needs), and the sizes of a set of candidate objects F1, F2, and F3 are 17mm, 18mm, and 24mm respectively, the robot vacuum cleaner can identify candidate objects F1 and F2 as objects to be cleaned, while excluding F3 and not treating it as an object to be cleaned.

[0078] It should be noted that, considering that when the object shadow is not obvious enough, it may not be possible to accurately identify the object shadow, that is, it may be impossible to determine whether it is the shadow of a candidate object. Therefore, the target ground image can be sharpened first to highlight the object shadow of each candidate object in the target ground image, thereby facilitating the identification of the object shadow of each candidate object.

[0079] In this embodiment, the object size of candidate objects in the ground image is determined by the object shadow, and then the objects to be cleaned are selected according to the object size of the candidate objects. This simplifies the process of determining the objects to be cleaned and improves the efficiency of area cleaning.

[0080] In one exemplary embodiment, identifying the object shadow of each candidate object from a set of candidate objects contained in the target ground image to obtain the object size of each candidate object includes:

[0081] S31, determine the shadow area of ​​each candidate object in the target ground image, and obtain the shadow area of ​​each candidate object;

[0082] S32, based on the projection angle of each candidate object, convert the shadow area of ​​each candidate object into the object size of each candidate object.

[0083] The shadow area of ​​a candidate object is positively correlated with its size; that is, the larger the size of the candidate object, the larger its shadow area. In addition to its size, the shadow area is also related to its projection angle; the shadow area is smaller when the projection angle is vertical than when it is tilted.

[0084] In this embodiment, the object size of each candidate object can be determined based on the shadow area and projection angle of each candidate object. The cleaning equipment can first determine the shadow area of ​​each candidate object in the target ground image to obtain the shadow area of ​​each candidate object; then, based on the projection angle of each candidate object, the shadow area of ​​each candidate object is converted into the object size of each candidate object.

[0085] The projection angle of each candidate object can be determined based on the lighting angle of the supplementary lighting component or the shooting angle of the candidate object by the image acquisition component; this embodiment does not limit this. The process of converting the shadow area of ​​each candidate object into the object size of each candidate object can be: the quotient of the shadow area (e.g., s) and the cosine of the projection angle of the candidate object (e.g., α) is determined as the object size of the candidate object (i.e., s / tanα).

[0086] This embodiment improves the accuracy of object size determination by determining the size of candidate objects based on the projection angle and shadow area.

[0087] In one exemplary embodiment, a set of target objects is selected from a set of candidate objects according to the object size of each candidate object, resulting in a set of object parameters for the target objects, including:

[0088] S41, the candidate objects whose object size is less than or equal to the second size threshold in a group of candidate objects are determined as the first target objects, wherein the first target objects belong to a group of target objects;

[0089] S42, based on the degree of aggregation of the first target object in the area to be cleaned, determine the object parameters of the first target object, wherein the object category of the first target object is set to a preset category;

[0090] S43, Identify the object categories of other candidate objects in a set of candidate objects besides the first target object, and obtain the object categories of other candidate objects;

[0091] S44, among other candidate objects, the candidate objects whose object category belongs to the category to be cleaned are identified as the second target objects, wherein the second target objects belong to a group of target objects;

[0092] S45, determine the object parameters of the second target object based on the object category of the second target object and the degree of aggregation of the second target object in the area to be cleaned.

[0093] In this embodiment, when filtering objects to be cleaned according to the object size of each candidate object, all candidate objects with an object size less than or equal to the second size threshold can be identified as objects to be cleaned, without needing to identify the object category of each candidate object separately. Instead, their object category can be directly determined as a preset category (or it can be left unset and directly identified as objects to be cleaned). The cleaning device can identify candidate objects with an object size less than or equal to the second size threshold from a group of candidate objects as the first target object, and the first target object belongs to a group of target objects.

[0094] For example, if the second size threshold is 10mm (this is just an example; the actual size threshold can be set according to actual needs), the robot vacuum cleaner can identify objects smaller than 10mm as objects to be cleaned.

[0095] After determining the first target object, the cleaning device can determine the object parameters of the first target object based on the degree of aggregation of the first target object in the area to be cleaned. Here, the aggregation parameters of the first target object can be determined in the same or similar way as in the previous embodiments. The first target object can be directly set to a preset category, which can be the category to be cleaned. This embodiment does not limit this.

[0096] For a set of candidate objects other than the primary target object, the cleaning device can identify the object category of the other candidate objects to determine their object category. For example, for candidate objects with a size greater than 10mm and less than 20mm, the robot vacuum cleaner can identify the object category of these candidate objects to determine whether their object category matches the category to be cleaned.

[0097] After determining the object categories of other candidate objects, the cleaning device can identify those candidate objects whose object categories belong to the category to be cleaned as the second target objects. These second target objects belong to a set of target objects. Here, the category to be cleaned can be a preset category of objects that need cleaning. For example, if the object category of another candidate object is identified as cat litter, then that other candidate object is determined to be an object to be cleaned; if the object category of another candidate object is identified as small toys, then that other candidate object is determined not to be an object to be cleaned.

[0098] In this embodiment, after determining the second target object, the cleaning device can determine the object parameters of the second target object based on the object category of the second target object and the degree of aggregation of the second target object in the area to be cleaned. Here, the aggregation parameters of the second target object can be determined in the same or similar way as in the previous embodiment, and the object category of the second target object is the object category identified above.

[0099] This embodiment uses different methods to determine the object parameters of the object to be cleaned based on the different object sizes, which can improve the accuracy of determining the object parameters of the object to be cleaned.

[0100] In one exemplary embodiment, determining the target operating parameters of the cleaning equipment based on a set of object categories of target objects and a set of aggregation parameters of target objects includes:

[0101] S51, when a set of target objects contains multiple target objects, determine the running parameters corresponding to each target object based on the object category of each target object and the aggregation parameters of each target object;

[0102] S52, perform a fusion operation on the operating parameters corresponding to each target object to obtain the target operating parameters of the cleaning equipment.

[0103] In this embodiment, the object category of a set of target objects can be one or more. If the set of target objects consists of multiple target objects, the cleaning device can determine the operating parameters corresponding to each target object based on the object category and aggregation parameters of each target object. The process of determining the operating parameters corresponding to each target object is similar to the method of determining the target operating parameters in the previous embodiments, and will not be described in detail here.

[0104] For example, when a set of target objects contains two object categories, G and H, the running parameter I1 corresponding to the object to be cleaned can be determined based on the object category of the object G and the aggregation parameter of the object G; and the running parameter I2 corresponding to the object to be cleaned can be determined based on the object category of the object H and the aggregation parameter of the object H.

[0105] In this embodiment, after determining the operating parameters corresponding to each target object, the cleaning device can perform a fusion operation on the operating parameters corresponding to each target object to obtain the target operating parameters of the cleaning device. For example, the cleaning device can fuse operating parameter I1 and operating parameter I2 to obtain the final operating parameters (i.e., the aforementioned target operating parameters).

[0106] Optionally, the method for performing the fusion operation on the running parameters corresponding to each target object can be: performing a superposition operation on the parameter values ​​of the same running parameters among the running parameters corresponding to each target object, and using the superimposed parameter value as the parameter value of the same running parameter; or selecting the maximum value among the parameter values ​​of the same running parameters as the parameter value of the same running parameter; and storing all kinds of running parameters in the target running parameters among the running parameters corresponding to each target object, which is not limited in this embodiment.

[0107] In this embodiment, by performing a fusion operation on the operating parameters corresponding to each object to be cleaned, the operating parameters of the cleaning equipment can be obtained, which can improve the accuracy of the determination of operating parameters and improve the efficiency of area cleaning.

[0108] In one exemplary embodiment, the object parameters of a set of target objects further include: location information indicating the object positions of the set of target objects, wherein the object positions of the set of target objects are the object positions of the set of target objects within the area to be cleaned. Here, the object positions of the set of target objects can be a region or the location of the center point of the region; this embodiment does not limit this.

[0109] Correspondingly, before controlling the cleaning equipment to clean a group of target objects according to the target operating parameters, the above method further includes:

[0110] S61, control the cleaning equipment to move towards the object position of a group of target objects until the distance between the cleaning part of the cleaning equipment and the group of target objects is less than or equal to the target distance threshold.

[0111] In this embodiment, to better clean a group of target objects, the cleaning device can first move towards the object locations of the group of target objects until the distance between the cleaning component of the cleaning device and the group of target objects is less than or equal to a target distance threshold. For example, a robotic vacuum cleaner can be controlled to move near the object locations of a group of objects to be cleaned, so that the cleaning component of the robotic vacuum cleaner can better clean the group of objects to be cleaned.

[0112] Optionally, if a distance sensor is provided on the cleaning equipment, the cleaning equipment can determine the distance between the cleaning component of the cleaning equipment and a group of target objects through the distance sensor. If a distance sensor is not provided on the cleaning equipment, the cleaning equipment can determine the distance between the cleaning component of the cleaning equipment and a group of target objects through an image acquisition component. This embodiment does not limit this.

[0113] In this embodiment, by first controlling the cleaning equipment to move near the object to be cleaned, and then cleaning the object, targeted cleaning of the object can be achieved, thereby improving the efficiency of area cleaning.

[0114] The operation control method of the device in the embodiments of this application will be explained below with reference to optional examples. In this optional example, the cleaning device is a sweeper, the target object is microparticles (i.e., dirt particles), and the above-mentioned supplementary lighting component is a supplementary light.

[0115] This optional example provides a scheme for identifying ground impurities, combined with Figure 4 As shown, the flow of the device operation control method in this optional example may include the following steps:

[0116] Step S402: Use a fill light to illuminate the near-ground area and use a macro camera to acquire a ground image.

[0117] The near-ground area can be 2-3 cm above the ground. After illuminating the near-ground area with a fill light, a camera can be used to capture an image of the ground.

[0118] Step S404: Determine the particle size by projecting the ground particles, perform preliminary classification based on particle size, and identify and locate the corresponding particles.

[0119] Particle size is determined by projecting it onto the ground, and a preliminary classification is performed based on particle size. Smaller particles can be directly identified as particles to be cleaned, while larger particles are first identified in terms of their type, and if they are classified as such, they are then identified as particles to be cleaned. The particles to be cleaned can also be located to pinpoint their positions.

[0120] Step S406: Automatically adjust the suction power and water volume of the sweeper according to the degree and type of particle aggregation, and use the adjusted sweeper to clean the particles to be cleaned. For example, after adjusting the suction power and water volume of the sweeper, the sweeper can be controlled to move to the location of the particles for precise cleaning.

[0121] This optional example allows you to distinguish the types of particulate matter on the ground and use different cleaning methods for different types of particulate matter, which can more effectively clean the ground while meeting personalized cleaning needs.

[0122] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0123] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM (Read-Only Memory) / RAM (Random Access Memory), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0124] According to another aspect of the embodiments of this application, an operation control device for implementing the operation control method of the above-described device is also provided. Figure 5 This is a structural block diagram of an optional device operation control apparatus according to an embodiment of this application, such as... Figure 5 As shown, the device may include:

[0125] The acquisition unit 502 is used to acquire images of the area to be cleaned through the image acquisition component on the cleaning equipment to obtain a target ground image;

[0126] The identification unit 504 is connected to the acquisition unit 502 and is used to perform object identification on the target ground image to obtain object parameters of a set of target objects to be cleaned in the area to be cleaned. The object parameters of the set of target objects include the object categories of the set of target objects and the aggregation parameters of the set of target objects. The aggregation parameters of the set of target objects are used to represent the degree of aggregation of the set of target objects in the area to be cleaned.

[0127] The determining unit 506, connected to the identifying unit 504, is used to determine the target operating parameters of the cleaning equipment based on the object categories of a set of target objects and the aggregation parameters of a set of target objects.

[0128] The first control unit 508, connected to the determining unit 506, is used to control the cleaning equipment to clean a group of target objects according to the target operating parameters.

[0129] It should be noted that the acquisition unit 502 in this embodiment can be used to execute the above step S202, the identification unit 504 in this embodiment can be used to execute the above step S204, the determination unit 506 in this embodiment can be used to execute the above step S206, and the first control unit 508 in this embodiment can be used to execute the above step S208.

[0130] Through the aforementioned modules, the image acquisition component on the cleaning equipment acquires images of the area to be cleaned, obtaining a target ground image. Object recognition is then performed on the target ground image to obtain object parameters for a set of target objects to be cleaned within the area. These object parameters include object categories and aggregation parameters, which represent the degree of aggregation of the target objects in the area to be cleaned. Based on the object categories and aggregation parameters, target operating parameters for the cleaning equipment are determined. The cleaning equipment is then controlled to clean the target objects according to these target operating parameters. This solves the problem of low cleaning efficiency caused by incomplete cleaning in related technologies, thus improving the efficiency of area cleaning.

[0131] In one exemplary embodiment, the acquisition unit 502 includes:

[0132] The start-up module is used to activate the supplemental lighting component on the cleaning equipment. Once activated, the supplemental lighting component provides supplemental lighting to the area to be cleaned.

[0133] The acquisition module is used to acquire images of the area to be cleaned through the image acquisition component, thereby obtaining a target ground image.

[0134] In one exemplary embodiment, the identification unit 504 includes:

[0135] The recognition module is used to identify the object shadow of each candidate object in a set of candidate objects contained in the target ground image, and to obtain the object size of each candidate object;

[0136] The filtering module is used to filter a set of target objects from a set of candidate objects according to the object size of each candidate object, and obtain the object parameters of a set of target objects, wherein the object size of each target object in the set of target objects is less than or equal to a first size threshold.

[0137] In one exemplary embodiment, the identification module includes:

[0138] The first determining submodule is used to determine the shadow area of ​​each candidate object in the target ground image, and obtain the shadow area of ​​each candidate object;

[0139] The transformation submodule is used to convert the shadow area of ​​each candidate object into the object size of each candidate object based on the projection angle of each candidate object.

[0140] In one exemplary embodiment, the filtering module includes:

[0141] The second determining submodule is used to determine the candidate objects whose object size is less than or equal to the second size threshold from a set of candidate objects as the first target object, wherein the first target object belongs to a set of target objects;

[0142] The third determining submodule is used to determine the object parameters of the first target object based on the degree of aggregation of the first target object in the area to be cleaned, wherein the object category of the first target object is set to a preset category;

[0143] The identification submodule is used to identify the object category of other candidate objects in a set of candidate objects besides the first target object, and obtain the object category of other candidate objects;

[0144] The fourth determination submodule is used to determine the candidate objects whose object category belongs to the category to be cleaned from other candidate objects as the second target objects, wherein the second target objects belong to a group of target objects;

[0145] The fifth determination submodule is used to determine the object parameters of the second target object based on the object category of the second target object and the degree of aggregation of the second target object in the area to be cleaned.

[0146] In one exemplary embodiment, the determining unit 506 includes:

[0147] The determination module is used to determine the running parameters corresponding to each target object when a set of target objects contains multiple target objects, based on the object category and aggregation parameters of each target object.

[0148] The execution module is used to perform a fusion operation on the operating parameters corresponding to each target object to obtain the target operating parameters of the cleaning equipment.

[0149] In one exemplary embodiment, the object parameters of a set of target objects further include: location information for indicating the object positions of the set of target objects; the above-described apparatus further includes:

[0150] The second control unit is used to control the cleaning equipment to move towards the object position of the group of target objects before controlling the cleaning equipment to clean the group of target objects according to the target operating parameters, until the distance between the cleaning part of the cleaning equipment and the group of target objects is less than or equal to the target distance threshold.

[0151] It should be noted that the examples and application scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the content disclosed in the above embodiments. It should also be noted that the above modules, as part of a device, can operate in environments such as... Figure 1 The hardware environment shown can be implemented through software or hardware, and the hardware environment includes the network environment.

[0152] According to another aspect of the embodiments of this application, a storage medium is also provided. Optionally, in this embodiment, the storage medium can be used to execute program code for the operation control method of any of the devices described in the embodiments of this application.

[0153] Optionally, in this embodiment, the storage medium may be located on at least one of the network devices in the network shown in the above embodiment.

[0154] Optionally, in this embodiment, the storage medium is configured to store program code for performing the following steps:

[0155] S1, the image acquisition component on the cleaning equipment acquires an image of the area to be cleaned, thus obtaining a target ground image;

[0156] S2, perform object recognition on the target ground image to obtain a set of object parameters of a set of target objects to be cleaned in the area to be cleaned. The set of object parameters of a set of target objects includes a set of object categories and a set of clustering parameters of target objects. The set of clustering parameters of target objects is used to represent the degree of clustering of a set of target objects in the area to be cleaned.

[0157] S3, determine the target operating parameters of the cleaning equipment based on the object categories of a set of target objects and the aggregation parameters of a set of target objects;

[0158] S4 controls the cleaning equipment to clean a group of target objects according to the target operating parameters.

[0159] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated in this embodiment.

[0160] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, ROMs, RAMs, portable hard drives, magnetic disks, or optical disks.

[0161] According to another aspect of the embodiments of this application, an electronic device for implementing the operation control method of the above-described device is also provided. The electronic device may be a server, a terminal, or a combination thereof.

[0162] Figure 6 This is a structural block diagram of an optional electronic device according to an embodiment of this application, such as... Figure 6 As shown, it includes a processor 602, a communication interface 604, a memory 606, and a communication bus 608. The processor 602, communication interface 604, and memory 606 communicate with each other via the communication bus 608.

[0163] Memory 606 is used to store computer programs;

[0164] When processor 602 executes a computer program stored in memory 606, it performs the following steps:

[0165] S1, the image acquisition component on the cleaning equipment acquires an image of the area to be cleaned, thus obtaining a target ground image;

[0166] S2, perform object recognition on the target ground image to obtain a set of object parameters of a set of target objects to be cleaned in the area to be cleaned. The set of object parameters of a set of target objects includes a set of object categories and a set of clustering parameters of target objects. The set of clustering parameters of target objects is used to represent the degree of clustering of a set of target objects in the area to be cleaned.

[0167] S3, determine the target operating parameters of the cleaning equipment based on the object categories of a set of target objects and the aggregation parameters of a set of target objects;

[0168] S4 controls the cleaning equipment to clean a group of target objects according to the target operating parameters.

[0169] Optionally, in this embodiment, the communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, Figure 6 The symbol is represented by a single thick line, but this does not indicate that there is only one bus or one type of bus. The communication interface is used for communication between the aforementioned electronic device and other devices.

[0170] The aforementioned memory may include RAM, or non-volatile memory, such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0171] As an example, the memory 606 described above may include, but is not limited to, the acquisition unit 502, the identification unit 504, the determination unit 506, and the first control unit 508 from the control device of the aforementioned device. Furthermore, it may include, but is not limited to, other module units from the control device of the aforementioned device, which will not be elaborated upon in this example.

[0172] The processors mentioned above can be general-purpose processors, including but not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; they can also be DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0173] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments, and will not be repeated here.

[0174] Those skilled in the art will understand that Figure 6 The structure shown is for illustrative purposes only. The device implementing the above-described operation control method can be a terminal device, such as a smartphone (e.g., Android phone, iOS phone), tablet computer, handheld computer, mobile internet device (MID), PAD, etc. Figure 6 This does not limit the structure of the aforementioned electronic device. For example, the electronic device may also include components that are more... Figure 6 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 6 The different configurations shown.

[0175] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, ROM, RAM, disk or optical disk, etc.

[0176] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0177] If the integrated units in the above embodiments are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause one or more computer devices (which may be personal computers, servers, or network devices, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application.

[0178] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0179] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0180] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the solution provided in this embodiment, depending on actual needs.

[0181] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0182] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for controlling the operation of equipment, characterized in that, include: The cleaning equipment acquires images of the area to be cleaned using its image acquisition components to obtain a target ground image. The cleaning equipment is equipped with a supplementary lighting component, which is an angle-adjustable supplementary lighting component to provide supplementary lighting to the area to be cleaned from different directions. During the process of the supplementary lighting component providing supplementary lighting to the area to be cleaned, the cleaning equipment records the supplementary lighting angle of the supplementary lighting component. Object recognition is performed on the target ground image to obtain object parameters of a set of target objects to be cleaned in the area to be cleaned. The object parameters of the set of target objects include the object category of the set of target objects and the aggregation parameter of the set of target objects. The aggregation parameter of the set of target objects is used to represent the degree of aggregation of the set of target objects in the area to be cleaned. The target operating parameters of the cleaning equipment are determined based on the object category of the set of target objects and the aggregation parameters of the set of target objects. The cleaning equipment is controlled to clean the group of target objects according to the target operating parameters. The step of performing object recognition on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned includes: The object shadow of each candidate object in a set of candidate objects contained in the target ground image is identified to obtain the object size of each candidate object; According to the object size of each candidate object, the target object is selected from the candidate object to obtain the object parameters of the target object, wherein the object size of each target object in the target object is less than or equal to the first size threshold. The step of identifying the object shadow of each candidate object in a set of candidate objects contained in the target ground image to obtain the object size of each candidate object includes: The shadow area of ​​each candidate object in the target ground image is determined to obtain the shadow area of ​​each candidate object; Based on the projection angle of each candidate object, the shadow area of ​​each candidate object is converted into the object size of each candidate object; The target ground image includes the angle information of the supplementary lighting component when the target ground image was acquired; the projection angle of each candidate object is determined according to the supplementary lighting angle of the supplementary lighting component; the process of converting the shadow area of ​​each candidate object into the object size of each candidate object is as follows: the quotient of the shadow area and the cosine of the projection angle of the candidate object is determined as the object size of the candidate object.

2. The method according to claim 1, characterized in that, The process of acquiring images of the area to be cleaned through the image acquisition component of the cleaning equipment to obtain a target ground image includes: The supplementary lighting component on the cleaning equipment is activated, wherein the activated supplementary lighting component is used to provide supplementary lighting to the area to be cleaned; The image acquisition component acquires images of the area to be cleaned, thereby obtaining the target ground image.

3. The method according to claim 1, characterized in that, The step of filtering the set of target objects from the set of candidate objects according to the object size of each candidate object, and obtaining the object parameters of the set of target objects, includes: Candidate objects whose size is less than or equal to the second size threshold in the group of candidate objects are identified as first target objects, wherein the first target objects belong to the group of target objects; Based on the degree of aggregation of the first target object in the area to be cleaned, the object parameters of the first target object are determined, wherein the object category of the first target object is set to a preset category; Identify the object categories of the other candidate objects in the set of candidate objects besides the first target object to obtain the object categories of the other candidate objects; Among the other candidate objects, those whose object category belongs to the category to be cleaned are identified as the second target object, wherein the second target object belongs to the group of target objects; The object parameters of the second target object are determined based on the object category of the second target object and the degree of aggregation of the second target object in the area to be cleaned.

4. The method according to claim 1, characterized in that, The step of determining the target operating parameters of the cleaning equipment based on the object category and aggregation parameters of the set of target objects includes: When the set of target objects contains multiple target objects, the running parameters corresponding to each target object are determined based on the object category of each target object and the aggregation parameter of each target object. A fusion operation is performed on the operating parameters corresponding to each target object to obtain the target operating parameters of the cleaning equipment.

5. The method according to any one of claims 1 to 4, characterized in that, The object parameters of the set of target objects further include: location information indicating the object positions of the set of target objects; before controlling the cleaning equipment to clean the set of target objects according to the target operating parameters, the method further includes: The cleaning device is controlled to move towards the object position of the group of target objects until the distance between the cleaning component of the cleaning device and the group of target objects is less than or equal to the target distance threshold.

6. An operation control device for equipment, characterized in that, include: The acquisition unit is used to acquire images of the area to be cleaned through the image acquisition component on the cleaning equipment to obtain a target ground image; wherein, the cleaning equipment is equipped with a supplementary lighting component, which is an angle-adjustable supplementary lighting component to provide supplementary lighting to the area to be cleaned from different directions; during the process of the supplementary lighting component providing supplementary lighting to the area to be cleaned, the cleaning equipment records the supplementary lighting angle of the supplementary lighting component. The identification unit is configured to perform object recognition on the target ground image to obtain object parameters of a set of target objects to be cleaned within the area to be cleaned. The object parameters of the set of target objects include the object category of the set of target objects and a clustering parameter of the set of target objects. The clustering parameter of the set of target objects represents the degree of clustering of the set of target objects within the area to be cleaned. The step of performing object recognition on the target ground image to obtain the object parameters of the set of target objects to be cleaned within the area to be cleaned includes: identifying the object shadow of each candidate object in a set of candidate objects contained in the target ground image to obtain the object size of each candidate object; and filtering the set of target objects from the set of candidate objects according to the object size of each candidate object to obtain the object parameters of the set of target objects. The object size of each target object is less than or equal to a first size threshold; wherein, the step of identifying the object shadow of each candidate object in a set of candidate objects contained in the target ground image to obtain the object size of each candidate object includes: determining the shadow area of ​​the object shadow of each candidate object in the target ground image to obtain the shadow area of ​​each candidate object; converting the shadow area of ​​each candidate object into the object size of each candidate object according to the projection angle of each candidate object; the target ground image is accompanied by the angle information of the supplementary lighting component when the target ground image is acquired; the projection angle of each candidate object is determined according to the supplementary lighting angle of the supplementary lighting component, and the process of converting the shadow area of ​​each candidate object into the object size of each candidate object is: determining the object size of the candidate object by the quotient of the shadow area and the cosine of the projection angle of the candidate object; The determining unit is configured to determine the target operating parameters of the cleaning equipment based on the object category of the set of target objects and the aggregation parameters of the set of target objects; The first control unit is used to control the cleaning equipment to clean the group of target objects according to the target operating parameters.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 5.

8. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 5 through the computer program.

Images