Data processing method and apparatus for robot inspection

Abstract

This application discloses a data processing method and apparatus for robot inspection. The method includes: acquiring data to be processed, which is data collected by the robot during the execution of a first inspection task; performing target detection processing on the data to be processed based on visual routes to obtain temporary inspection task target data; performing inspection task generation processing on the temporary inspection task target data to obtain second inspection task data; the robot executes the second inspection task based on the second inspection task data, and after executing the second inspection task, the robot continues to execute the first inspection task. By performing target detection based on visual routes on the data collected by the robot during the inspection process, temporary inspection tasks are generated for the inspection targets detected during the first inspection, and the robot executes the temporary inspection tasks before continuing to execute the first inspection. This achieves automatic detection of inspection targets within the park and execution of inspection tasks, improving the autonomy of robot inspection.

Description

Technical Field

[0001] This application relates to the field of robotics, and more specifically, to a data processing method and apparatus for robot inspection. Background Technology

[0002] With the continuous development of robotics technology, robots are widely used in various fields. In some industrial scenarios, such as industrial parks and factories, robots are used to monitor industrial production safety. Traditional manual inspection methods suffer from high labor intensity, low efficiency, and inconsistent inspection quality. Robots are increasingly being used in industrial parks, factories, and other industrial settings to perform inspection tasks.

[0003] In existing technologies, robot inspection is mainly based on pre-fixed inspection patterns, and the robot relies primarily on manually set inspection tasks during inspection. The inventors discovered that while robots perform inspections by determining the inspection location and planning their path, they struggle to effectively inspect dynamic targets within a park.

[0004] Therefore, this application is made in response to the aforementioned problems with robotic inspection. Summary of the Invention

[0005] The main objective of this application is to provide a data processing method and apparatus for robot inspection, in order to solve the aforementioned problems pointed out in the prior art.

[0006] To achieve the above objectives, the first aspect of this application proposes a data processing method for robot inspection, comprising:

[0007] Acquire data to be processed, wherein the data to be processed is data collected during the robot's execution of the first inspection task;

[0008] The data to be processed is subjected to target detection processing based on visual route to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent temporary inspection targets detected based on visual route.

[0009] The temporary inspection task target data is processed to generate inspection tasks, resulting in second inspection task data.

[0010] The robot performs the second inspection task based on the second inspection task data. After performing the second inspection task, the robot continues to perform the first inspection task.

[0011] Furthermore, the data to be processed is subjected to target detection processing based on visual routes to obtain temporary inspection task target data, including:

[0012] The data to be processed is identified to obtain video frame image data, wherein the video frame image data is video frame image data collected to represent the current running position of the robot;

[0013] The video frame image data is subjected to image extraction processing based on visual route features to obtain visual route feature image data, wherein the visual route feature data is image data used to represent the visual route features;

[0014] The visual route feature image data is subjected to target detection processing based on preset interest targets to obtain the temporary inspection task target data, wherein the temporary inspection task target data is data used to represent the preset interest targets present in the visual route feature image data.

[0015] Furthermore, the video frame image data is subjected to image extraction processing based on visual route features to obtain visual route feature image data, including:

[0016] The video frame image data is subjected to image filtering processing based on visual route to obtain visual route image data, wherein the visual route image data is data used to represent the video frame image corresponding to the visual route direction;

[0017] The visual route image data is processed by image extraction based on the first visual route feature to obtain the first visual route feature image data, wherein the first visual route feature image data is used to represent the image data corresponding to the first visual route feature;

[0018] The visual route image data is subjected to image extraction processing based on the second visual route features to obtain second visual route feature image data, wherein the second visual route feature image data is used to represent image data corresponding to the second visual route features;

[0019] The visual route feature image data is obtained based on the first visual route feature image data and the second visual route feature image data.

[0020] Furthermore, the temporary inspection task target data is processed to generate inspection tasks, resulting in second inspection task data including:

[0021] The temporary inspection task target data is processed by inspection path planning to obtain temporary inspection path data;

[0022] Match the inspection execution feature data corresponding to the temporary inspection task target data in the preset inspection database to obtain the inspection execution feature data.

[0023] The second inspection task data is generated based on the temporary inspection path data and the inspection execution characteristic data.

[0024] Furthermore, the temporary inspection task target data is processed by inspection path planning to obtain temporary inspection path data, including:

[0025] The execution point data is obtained by filtering the target data of the temporary inspection task. The execution point data is the point data used to represent the inspection task corresponding to the temporary inspection target.

[0026] Acquire running point data, wherein the running point data is position data used to represent the current running point of the robot;

[0027] The temporary inspection path data is obtained by performing path planning processing based on a preset global map on the running point data and the execution point data.

[0028] Furthermore, the temporary inspection task target data is processed to generate inspection tasks, resulting in second inspection task data including:

[0029] The temporary inspection task target data is identified and processed to obtain first temporary inspection task target data and second temporary inspection task target data, wherein the first temporary inspection task target data is data used to represent the first temporary inspection target, and the second temporary inspection task target data is data used to represent the second temporary inspection target.

[0030] In the preset inspection database, the inspection task features corresponding to the first temporary inspection task target data and the second temporary inspection task target data are matched respectively to obtain the first temporary inspection task feature data and the second temporary inspection task feature data.

[0031] The second inspection task data is generated based on the first temporary inspection task feature data and the second temporary inspection task feature data.

[0032] According to a second aspect of this application, a data processing device for robot inspection is proposed, comprising:

[0033] The data acquisition module is used to acquire data to be processed, wherein the data to be processed is data collected during the robot's execution of the first inspection task;

[0034] The target detection module is used to perform target detection processing on the data to be processed based on visual route to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent temporary inspection targets detected based on visual route.

[0035] The temporary inspection module is used to process the temporary inspection task target data to generate inspection tasks, thereby obtaining the second inspection task data.

[0036] The task execution module allows the robot to perform a second inspection task based on the second inspection task data. After performing the second inspection task, the robot continues to perform the first inspection task.

[0037] Furthermore, the target detection module includes:

[0038] The recognition module is used to recognize and process the data to be processed to obtain video frame image data, wherein the video frame image data is video frame image data collected to represent the current running position of the robot;

[0039] The image extraction module is used to perform image extraction processing based on visual route features on the video frame image data to obtain visual route feature image data, wherein the visual route feature data is image data used to represent the visual route features;

[0040] The task target detection module is used to perform target detection processing on the visual route feature image data based on preset interest targets to obtain the temporary inspection task target data, wherein the temporary inspection task target data is data used to represent the preset interest targets present in the visual route feature image data.

[0041] According to a third aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing the computer to perform the data processing method for robot inspection as described above.

[0042] According to a fourth aspect of this application, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform the aforementioned data processing method for robot inspection.

[0043] The technical solutions provided by the embodiments of this application may include the following beneficial effects:

[0044] In this application, data to be processed is acquired, wherein the data to be processed represents data collected by the robot during the execution of a first inspection task; target detection processing based on visual route is performed on the data to be processed to obtain temporary inspection task target data, wherein the temporary inspection task target data represents data of temporary inspection targets detected based on visual route; inspection task generation processing is performed on the temporary inspection task target data to obtain second inspection task data; the robot executes the second inspection task according to the second inspection task data, and after executing the second inspection task, the robot continues to execute the first inspection task. By performing target detection based on visual route on the data collected by the robot during the inspection process, and performing temporary inspection task generation processing on the inspection targets detected during the first inspection process, the robot executes the temporary inspection task and then continues to execute the first inspection task. This enables the detection and inspection of dynamically changing inspection targets within the park during the execution of inspection tasks. It realizes the automatic detection of inspection targets within the park and the execution of inspection tasks, improving the autonomy of robot inspection. Attached Figure Description

[0045] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application. In the drawings:

[0046] Figure 1 A flowchart of a data processing method for robot inspection provided in this application;

[0047] Figure 2 A flowchart of a data processing method for robot inspection provided in this application;

[0048] Figure 3 A flowchart of a data processing method for robot inspection provided in this application;

[0049] Figure 4 A schematic diagram of a data processing device for robot inspection provided in this application;

[0050] Figure 5 A schematic diagram of another data processing device for robot inspection provided in this application. Detailed Implementation

[0051] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0052] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0053] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0054] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in some cases to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0055] Furthermore, the terms "installation," "setup," "equipped with," "connection," "linked," and "socketing" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0056] In an optional embodiment of this application, a data processing method for robot inspection is proposed. Figure 1A flowchart of a data processing method for robot inspection provided in this application is shown below. Figure 1 As shown, the method includes the following steps:

[0057] S101: Obtain the data to be processed;

[0058] The data to be processed represents the data collected by the robot during the execution of the first inspection task. The first inspection task can be a daily inspection task or a routine inspection task. The first inspection task has a corresponding inspection route. The robot runs according to the inspection route of the first inspection task. While the robot is running according to the inspection route of the first inspection task, the robot collects environmental information in real time. The robot information collection equipment includes image acquisition equipment, ultrasonic acquisition equipment, etc. The robot uses image acquisition equipment to collect video frame images of the robot running according to the inspection route of the first inspection task in real time. Based on the collected video frame images, the robot identifies the inspection target so that the robot can generate and execute autonomous inspection tasks based on the identified inspection targets, thereby improving the degree of autonomy of robot inspection.

[0059] S102: Perform visual route-based target detection processing on the data to be processed to obtain temporary inspection task target data;

[0060] The temporary inspection task target data is used to represent the temporary inspection targets detected based on the visual route. The robot performs the first inspection task by running according to the inspection route. During the operation, the image acquisition device captures video frame images. The robot is set with a visual route, and it acquires images in the corresponding direction of the visual route. While running according to the inspection route, the robot can acquire images of the park according to the visual route, so as to detect the inspection targets based on the acquired images.

[0061] In an optional embodiment of this application, a data processing method for robot inspection is proposed. Figure 2 A flowchart of a data processing method for robot inspection provided in this application is shown below. Figure 2 As shown, the method includes the following steps:

[0062] S201: Perform recognition processing on the data to be processed to obtain video frame image data;

[0063] The video frame image data is the video frame image data collected to represent the current operating position of the robot.

[0064] S202: Perform image extraction processing based on visual route features on the video frame image data to obtain visual route feature image data;

[0065] Visual route feature data is image data used to represent the visual route features.

[0066] In an optional embodiment of this application, a data processing method for robot inspection is proposed, including: performing image filtering processing on video frame image data based on visual route to obtain visual route image data, wherein the visual route image data is data used to represent the video frame image corresponding to the visual route direction.

[0067] In another optional embodiment of this application, the visual route features are obtained by visual distance-based segmentation of the visual route. The visual route is segmented based on visual distance. Depending on the setting of the visual distance, the visual route features may include a first visual route feature and a second visual route feature. Alternatively, the visual route features may include a first visual route feature, a second visual route feature, and a third visual route feature.

[0068] When the visual route features include both first and second visual route features, image extraction processing based on the first visual route features is performed on the visual route image data to obtain first visual route feature image data, where the first visual route feature image data represents the image data corresponding to the first visual route feature. Image extraction processing based on the second visual route features is then performed on the visual route image data to obtain second visual route feature image data, where the second visual route feature image data represents the image data corresponding to the second visual route feature. The visual route feature image data is then obtained based on the first and second visual route feature image data. For example, image extraction can be performed on the current visual route based on near and far views to obtain near-view image data and far-view image data respectively. During image extraction, the parameters of the robot's image acquisition device can be adjusted, such as camera focusing, to acquire video frame images that meet the requirements for near and far views.

[0069] When visual route features can include first visual route features, second visual route features, and third visual route features, image extraction processing based on the first visual route features is performed on the visual route image data to obtain first visual route feature image data, wherein the first visual route feature image data is used to represent the image data corresponding to the first visual route feature; image extraction processing based on the second visual route features is performed on the visual route image data to obtain second visual route feature image data, wherein the second visual route feature image data is used to represent the image data corresponding to the second visual route feature; image extraction processing based on the third visual route features is performed on the visual route image data to obtain third visual route feature image data, wherein the third visual route feature image data is used to represent the image data corresponding to the third visual route feature; and visual route feature image data is obtained based on the first visual route feature image data, second visual route feature image data, and third visual route feature image data. For example, images can be extracted from the near, medium, and far views along the current visual path to obtain near, medium, and far view image data, respectively. During image extraction, the parameters of the robot's image acquisition device can be adjusted, such as camera focusing, to acquire video frame images that meet the requirements for the near, medium, and far views, respectively.

[0070] S203: Perform target detection processing on the visual route feature image data based on preset interest targets to obtain temporary inspection task target data.

[0071] The target data for temporary inspection tasks is data used to represent preset targets of interest in the visual route feature image data.

[0072] In an optional embodiment of this application, preset interest targets are stored in a preset inspection database. The preset interest targets may include multiple interest targets. Target detection based on image recognition is performed on the first visual route feature image and the second visual route feature image to determine whether a preset interest target exists in the visual route feature image. If no preset interest target exists in the visual route feature image, the robot continues to run according to the inspection route of the first inspection task. If a preset interest target exists in the visual route feature image, temporary inspection task target data is generated based on the interest target present in the visual route feature image. Furthermore, if multiple preset interest targets exist in the visual route feature image, multiple temporary inspection task target data corresponding to the multiple preset interest targets are generated respectively.

[0073] S103: Perform inspection task generation processing on the temporary inspection task target data to obtain the second inspection task data;

[0074] In an optional embodiment of this application, a data processing method for robot inspection is proposed. Figure 3 A flowchart of a data processing method for robot inspection provided in this application is shown below. Figure 3 As shown, the method includes the following steps:

[0075] S301: Perform inspection path planning processing on the temporary inspection task target data to obtain temporary inspection path data;

[0076] In an optional embodiment of this application, a data processing method for robot inspection is proposed, comprising: performing execution point filtering processing on temporary inspection task target data to obtain execution point data, wherein the execution point data is point data used to represent the inspection task corresponding to the temporary inspection target; acquiring running point data, wherein the running point data is position data used to represent the current running point of the robot; and performing path planning processing on the running point data and execution point data based on a preset global map to obtain temporary inspection path data.

[0077] In an optional embodiment of this application, a data processing method for robot inspection is proposed. The method involves filtering execution point data for temporary inspection task target data to obtain execution point data. This includes: performing location judgment processing based on a global map on the temporary inspection task target data to determine whether the location of the temporary inspection task target is within a robot-operable area of ​​the global map; if the location of the temporary inspection task target is within a robot-operable area of ​​the global map, generating execution point data based on the location of the temporary inspection task target; if the location of the temporary inspection task target is within a robot-restricted area or boundary of the global map, searching for points within the operable area based on the location of the temporary inspection task target and the global map to obtain multiple process execution points; performing information gain-based filtering processing on the multiple process execution points; calculating and processing the information of the temporary inspection task target that can be collected from the multiple process execution points; selecting the process execution point with the largest information gain of the collected temporary inspection task target to obtain the execution point; and having the robot run to the execution point to collect information from the temporary inspection task target in order to execute a second inspection task.

[0078] S302: Match the inspection execution feature data corresponding to the temporary inspection task target data in the preset inspection database to obtain the inspection execution feature data;

[0079] In an optional embodiment of this application, a data processing method for robot inspection is proposed, comprising: identifying and processing temporary inspection task target data to obtain first temporary inspection task target data and second temporary inspection task target data, wherein the first temporary inspection task target data is data used to represent a first temporary inspection target, and the second temporary inspection task target data is data used to represent a second temporary inspection target; matching inspection task features corresponding to the first temporary inspection task target data and the second temporary inspection task target data in a preset inspection database to obtain first temporary inspection task feature data and second temporary inspection task feature data; and generating second inspection task data based on the first temporary inspection task feature data and the second temporary inspection task feature data.

[0080] The target data for the temporary inspection task is a preset target of interest in the visual route feature image corresponding to any of the above visual route features. For example, if the target data for the temporary inspection task is a preset target of interest in the visual route feature image corresponding to the close-up view, and if the number of preset targets of interest in the visual route feature image corresponding to the first visual route feature is unique, the inspection task feature corresponding to the target of interest is matched in the preset inspection database. For example, the inspection task corresponding to the target of interest is executed as target image acquisition, and the inspection task execution feature for acquiring the image of the target of interest is generated; the inspection task corresponding to the target of interest is executed as target following, and the inspection task execution feature for following the image of the target of interest is generated, and prompt information is generated and output.

[0081] If the number of preset interest targets in the visual route feature image corresponding to the first visual route feature is not unique, the category of interest targets in the visual route feature image corresponding to the first visual route feature is judged. If they are of the same category, the inspection task execution feature corresponding to the interest target of that category is matched. If they are of different categories, the priority of different interest targets is judged, and the inspection task execution order of different interest targets is determined according to the priority. For different interest targets with the same priority, the corresponding inspection task execution feature is matched.

[0082] After performing the inspection task of the preset target of interest in the visual route feature image corresponding to any visual route feature, the detection of preset targets of interest and the execution of temporary inspection tasks in the visual route feature images corresponding to other visual route features are then performed.

[0083] S303: Generate second inspection task data based on temporary inspection path data and inspection execution characteristic data.

[0084] S104: The robot performs the second inspection task based on the second inspection task data. After performing the second inspection task, the robot continues to perform the first inspection task.

[0085] In an optional embodiment of this application, the robot detects targets of interest within the park during routine inspection tasks, generates temporary inspection tasks based on the detection results, and continues to perform the routine inspection tasks after completing the temporary inspection tasks. By inspecting and detecting simultaneously, the robot can autonomously inspect dynamically changing targets within the park without needing to determine the location or other information of the dynamically changing targets. The robot performs autonomous detection and generates inspection tasks, thereby improving the autonomy of robot inspection.

[0086] In an optional embodiment of this application, a data processing device for robot inspection is proposed. Figure 4 A schematic diagram of a data processing device for robot inspection provided in this application is shown below. Figure 4 As shown,

[0087] The data acquisition module 41 is used to acquire data to be processed, wherein the data to be processed is data collected during the robot's execution of the first inspection task;

[0088] The target detection module 42 is used to perform target detection processing on the data to be processed based on the visual route to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent the temporary inspection targets detected based on the visual route.

[0089] Temporary inspection module 43 is used to process the temporary inspection task target data to generate inspection tasks and obtain the second inspection task data.

[0090] Task execution module 44: The robot executes the second inspection task based on the second inspection task data. After executing the second inspection task, the robot continues to execute the first inspection task.

[0091] In an optional embodiment of this application, a data processing device for robot inspection is proposed. Figure 5 A schematic diagram of another data processing device for robot inspection provided in this application is shown below. Figure 5 As shown,

[0092] The recognition module 51 is used to recognize and process the data to be processed to obtain video frame image data, wherein the video frame image data is video frame image data collected to represent the current running position of the robot;

[0093] Image extraction module 52 is used to perform image extraction processing on video frame image data based on visual route features to obtain visual route feature image data, wherein the visual route feature data is image data used to represent the visual route features;

[0094] The task target detection module 53 is used to perform target detection processing on the visual route feature image data based on preset interest targets to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent preset interest targets present in the visual route feature image data.

[0095] The specific methods of execution of each unit in the above embodiments have been described in detail in the embodiments of the method, and will not be elaborated here.

[0096] In summary, this application involves: acquiring data to be processed, wherein the data to be processed represents data collected by the robot during the execution of a first inspection task; performing target detection processing based on visual routes on the data to be processed to obtain temporary inspection task target data, wherein the temporary inspection task target data represents data representing temporary inspection targets detected based on visual routes; performing inspection task generation processing on the temporary inspection task target data to obtain second inspection task data; the robot executes the second inspection task based on the second inspection task data, and after executing the second inspection task, the robot continues to execute the first inspection task. By performing target detection based on visual routes on the data collected by the robot during the inspection process, and performing temporary inspection task generation processing on the inspection targets detected during the first inspection process, the robot executes the temporary inspection task and then continues to execute the first inspection task. This enables the detection and inspection of dynamically changing inspection targets within the park during the execution of inspection tasks. It achieves automatic detection of inspection targets within the park and the execution of inspection tasks, improving the autonomy of robot inspection.

[0097] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0098] Obviously, those skilled in the art should understand that the various units or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0099] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A data processing method for robot patrol, characterized in that, The method comprises: acquiring to-be-processed data, wherein the to-be-processed data is data for representing data collected by a robot in performing a first inspection task; performing visual route-based target detection processing on the to-be-processed data to obtain temporary inspection task target data, wherein the temporary inspection task target data is data for representing temporary inspection targets detected based on a visual route, and comprises: if the number of preset interest targets in the visual route feature image corresponding to the visual route feature is not unique, performing category judgment on the interest targets existing in the visual route feature image corresponding to the visual route feature, if the interest targets are of the same category, matching the inspection task execution features corresponding to the interest targets of the same category, if the interest targets are of different categories, judging the priorities of the different interest targets, determining the inspection task execution order of the different interest targets according to the priority order, and matching the inspection task execution features corresponding to the different interest targets of the same priority; performing inspection task generation processing on the temporary inspection task target data to obtain second inspection task data; the robot performing a second inspection task according to the second inspection task data, and the robot continuing to perform the first inspection task after performing the second inspection task; wherein the robot performing a second inspection task according to the second inspection task data comprises performing inspection path planning processing on the temporary inspection task target data to obtain temporary inspection path data; performing execution point position screening processing on the temporary inspection task target data to obtain execution point position data, comprising: performing global map-based position judgment processing on the temporary inspection task target data to judge whether the position of the temporary inspection task target is located in the robot operable area in the global map, if the position of the temporary inspection task target is located in the robot operable area in the global map, generating execution point position data according to the position of the temporary inspection task target, if the position of the temporary inspection task target is located in the robot forbidden area and the boundary in the global map, searching for point positions in the operable area according to the position of the temporary inspection task target and the global map to obtain a plurality of process execution point positions, performing information gain-based screening processing on the plurality of process execution point positions, calculating the information of the temporary inspection task target that can be collected by the plurality of process execution point positions, selecting a process execution point position with the greatest information gain of the collected temporary inspection task target information, obtaining an execution point position, and the robot running to the execution point position to collect information of the temporary inspection task target and perform a second inspection task.

2. The data processing method according to claim 1, characterized in that, The method comprises: performing visual route-based target detection processing on the to-be-processed data to obtain temporary inspection task target data, comprising: performing recognition processing on the to-be-processed data to obtain video frame image data, wherein the video frame image data is video frame image data collected by the robot at a current running position; performing visual route feature-based image extraction processing on the video frame image data to obtain visual route feature image data, wherein the visual route feature data is image data corresponding to the visual route feature. The visual route feature image data is subjected to target detection processing based on a preset target of interest, to obtain temporary inspection task target data, wherein the temporary inspection task target data is data for indicating a preset target of interest present in the visual route feature image data.

3. The data processing method of claim 2, wherein, The video frame image data is subjected to image extraction processing based on a visual route feature, to obtain visual route feature image data, including: The video frame image data is subjected to image screening processing based on a visual route, to obtain visual route image data, wherein the visual route image data is data for indicating a video frame image corresponding to the visual route direction; The visual route image data is subjected to image extraction processing based on a first visual route feature, to obtain first visual route feature image data, wherein the first visual route feature image data is data for indicating image data corresponding to the first visual route feature; The visual route image data is subjected to image extraction processing based on a second visual route feature, to obtain second visual route feature image data, wherein the second visual route feature image data is data for indicating image data corresponding to the second visual route feature; The visual route feature image data is obtained according to the first visual route feature image data and the second visual route feature image data.

4. The data processing method of claim 1, wherein, The temporary inspection task target data is subjected to inspection task generation processing, to obtain second inspection task data, including: The temporary inspection task target data is subjected to inspection path planning processing, to obtain temporary inspection path data; Inspection execution feature data corresponding to the temporary inspection task target data is matched in a preset inspection database, to obtain inspection execution feature data; The second inspection task data is generated according to the temporary inspection path data and the inspection execution feature data.

5. The data processing method according to claim 4, characterized in that, The temporary inspection task target data is subjected to inspection path planning processing, to obtain temporary inspection path data, including: The temporary inspection task target data is subjected to execution point position screening processing, to obtain execution point position data, wherein the execution point position data is point position data for indicating an inspection task corresponding to a temporary inspection target; Running point position data is obtained, wherein the running point position data is position data for indicating a current running point position of a robot; The running point position data and the execution point position data are subjected to path planning processing based on a preset global map, to obtain the temporary inspection path data.

6. The data processing method of claim 1, wherein, The temporary inspection task target data is subjected to inspection task generation processing, to obtain second inspection task data, including: The temporary inspection task target data is subjected to identification processing, to obtain first temporary inspection task target data and second temporary inspection task target data, wherein the first temporary inspection task target data is data for indicating a first temporary inspection target, and the second temporary inspection task target data is data for indicating a second temporary inspection target; Match the first temporary inspection task target data and the second temporary inspection task target data with the corresponding inspection task features in the preset inspection database respectively to obtain the first temporary inspection task feature data and the second temporary inspection task feature data; Generate the second inspection task data according to the first temporary inspection task feature data and the second temporary inspection task feature data.

7. A data processing device for robot inspection, characterized in that, Comprise: The data acquisition module is used for acquiring the to-be-processed data, wherein the to-be-processed data is data used for representing data collected in the process of executing the first inspection task by the robot; The target detection module is used for performing target detection processing based on a visual route on the to-be-processed data to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used for representing temporary inspection targets detected based on a visual route, and comprises: If the number of preset interest targets in the visual route feature image corresponding to the visual route feature is not unique, the class of the interest target existing in the visual route feature image corresponding to the visual route feature is judged, if the classes are the same, the inspection task execution feature corresponding to the class interest target is matched; if the classes are different, the priorities of different interest targets are judged, the inspection task execution order of different interest targets is determined according to the priority order, and the inspection task execution feature corresponding to the same priority different interest target is matched; The temporary inspection module is used for performing inspection task generation processing on the temporary inspection task target data to obtain second inspection task data; The task execution module is used for executing the second inspection task by the robot according to the second inspection task data, and after executing the second inspection task, the robot continues to execute the first inspection task; The robot executes the second inspection task according to the second inspection task data, which comprises performing inspection path planning processing on the temporary inspection task target data to obtain temporary inspection path data; The execution point position data is obtained by performing execution point position screening processing on the temporary inspection task target data, which comprises performing position judgment processing on the temporary inspection task target data based on a global map to judge whether the position of the temporary inspection task target is located in the robot executable area in the global map, if the position of the temporary inspection task target is located in the robot executable area in the global map, generating execution point position data according to the position of the temporary inspection task target; if the position of the temporary inspection task target is located in the robot forbidden area and the boundary of the global map, searching for point positions in the executable area according to the position of the temporary inspection task target and the global map to obtain a plurality of process execution point positions, performing information gain screening processing on the plurality of process execution point positions, calculating the information of the temporary inspection task target that can be collected by the plurality of process execution point positions, selecting the process execution point position with the maximum information gain of the collected temporary inspection task target, and obtaining the execution point position, so that the robot runs to the execution point position to collect information of the temporary inspection task target and execute the second inspection task.

8. The data processing apparatus according to claim 7, characterized in that, The target detection module comprises: An identification module is configured to perform identification processing on the to-be-processed data to obtain video frame image data, wherein the video frame image data is video frame image data collected at a current running position of the robot. An image extraction module is configured to perform image extraction processing on the video frame image data based on a visual route feature to obtain visual route feature image data, wherein the visual route feature data is image data corresponding to the visual route feature. A task target detection module is configured to perform target detection processing on the visual route feature image data based on a preset interest target to obtain the temporary inspection task target data, wherein the temporary inspection task target data is data indicating the preset interest target existing in the visual route feature image data.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing the computer to execute the data processing method for robot inspection according to any one of claims 1-6.

10. An electronic device, comprising: comprise: at least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to cause the at least one processor to execute the data processing method for robot inspection according to any one of claims 1-6.

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