Data processing method and device for robot inspection

Abstract

The invention discloses a data processing method and device for robot inspection. The method comprises the steps of obtaining to-be-processed data, wherein the to-be-processed data is data collected in the process that a robot executes a first inspection task; performing target detection processing based on a visual route on the to-be-processed data 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 according to the second inspection task data, and after the second inspection task is executed, the robot continues to execute the first inspection task. Target detection based on a visual route is carried out on data collected in the inspection process of the robot, temporary inspection task generation is carried out on an inspection target detected in the first inspection process, and the robot continues to execute first inspection after executing the temporary inspection task. The automatic detection of the inspection target in the park and the execution of the inspection task are realized, and the autonomy of robot inspection is improved.

Description

Technical Field

[0001] The present application relates to the field of robots, and in particular, to a data processing method and device for robot inspection. Background Art

[0002] With the continuous development of robot technology, robots are widely used in various fields. In some industrial scenarios, such as parks and factories, where inspections are required, robots can monitor industrial production safety. The traditional manual inspection mode has problems such as high labor intensity, low work efficiency, and unstable inspection quality. Robots are gradually widely used in industrial scenarios such as parks and factories to perform inspection tasks in the scenarios.

[0003] In the prior art, robot inspections are mainly based on pre-fixed inspection modes, and the robots mainly rely on manually set inspection tasks, etc. The inventors found that when the robots conduct inspections, they plan their paths by determining the inspection locations, and realize the inspections of the inspection locations. It is difficult to conduct effective inspections on dynamic targets that need to be inspected in the park.

[0004] Therefore, this application is proposed to address the above-mentioned problems existing in robot inspection. Summary of the invention

[0005] The main purpose of this application is to provide a data processing method and device for robot inspection to solve the above-mentioned problems pointed out in the prior art.

[0006] In order to achieve the above-mentioned purpose, in a first aspect of the present application, a data processing method for robot inspection is proposed, comprising:

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

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

[0009] Performing inspection task generation processing on the temporary inspection task target data to obtain second inspection task data;

[0010] The robot performs the second inspection task according to the second inspection task data, and 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 a visual route, and the temporary inspection task target data obtained includes:

[0012] Performing recognition processing on 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;

[0013] Performing 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 used to represent image data corresponding to the visual route feature;

[0014] The visual route feature image data is subjected to target detection processing based on a preset target of interest to obtain the temporary inspection task target data, wherein the temporary inspection task target data is data for representing a preset target of interest 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] Performing image screening processing based on a visual route on the video frame image data to obtain visual route image data, wherein the visual route image data is data for representing the video frame image corresponding to the visual route direction;

[0017] Performing image extraction processing based on the first visual route feature 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 image data corresponding to the first visual route feature;

[0018] Performing image extraction processing based on the second visual route feature 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 image data corresponding to the second visual route feature;

[0019] 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.

[0020] Further, the temporary inspection task target data is subjected to inspection task generation processing to obtain the second inspection task data including:

[0021] Performing inspection path planning processing on the temporary inspection task target data to obtain temporary inspection path data;

[0022] Matching the inspection execution characteristic data corresponding to the temporary inspection task target data in a preset inspection database to obtain the inspection execution characteristic data;

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

[0024] Further, the temporary inspection task target data is processed by inspection path planning, and the temporary inspection path data obtained includes:

[0025] Performing execution point screening processing on the temporary inspection task target data to obtain execution point data, wherein the execution point data is point data used to indicate the execution of the inspection task corresponding to the temporary inspection target;

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

[0027] The operation point data and the execution point data are processed by path planning based on a preset global map to obtain the temporary inspection path data.

[0028] Further, the temporary inspection task target data is subjected to inspection task generation processing to obtain the second inspection task data including:

[0029] Identify and process the 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 the first temporary inspection target, and the second temporary inspection task target data is data used to represent the second temporary inspection target;

[0030] Match the 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 the first temporary inspection task feature data and the second temporary inspection task feature data;

[0031] The second inspection task data is generated according to the first temporary inspection task characteristic data and the second temporary inspection task characteristic data.

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

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

[0034] A target detection module, used for performing target detection processing based on a visual route on the data to be processed to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent a temporary inspection target detected based on a visual route;

[0035] A temporary inspection module, used for performing inspection task generation processing on the temporary inspection task target data to obtain second inspection task data;

[0036] The task execution module is used for the robot to execute the second inspection task according to the second inspection task data. After executing the second inspection task, the robot continues to execute the first inspection task.

[0037] Furthermore, the target detection module includes:

[0038] An identification module is used to identify 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] An image extraction module, used for performing 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 used to represent image data corresponding to the visual route feature;

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

[0041] According to a third aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the data processing method for robot inspection as claimed above.

[0042] According to the fourth aspect of the present application, an electronic device is proposed, 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, and the computer program is executed by the at least one processor so that the at least one processor executes the above-mentioned data processing method for robot inspection.

[0043] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0044] In the present application, data to be processed is obtained, wherein the data to be processed is used to represent the data collected during the robot's execution of the first inspection task; the data to be processed is subjected to target detection processing based on the visual route to obtain temporary inspection task target data, wherein the temporary inspection task target data is used to represent the temporary inspection target detected based on the visual route; the temporary inspection task target data is subjected to inspection task generation processing to obtain second inspection task data; the robot performs the second inspection task according to the second inspection task data, and after performing the second inspection task, the robot continues to perform the first inspection task. By performing target detection based on the visual route on the data collected during the robot's inspection, the inspection target detected during the first inspection is subjected to temporary inspection task generation processing, and the robot continues to perform the first inspection task after performing the temporary inspection task. The inspection targets that dynamically change in the park are detected during the execution of the inspection task, and the inspection is performed. The automatic detection of the inspection targets in the park and the execution of its inspection tasks are realized, and the autonomy of the robot inspection is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] The drawings constituting a part of this application are used to provide a further understanding of this application, so that other features, purposes and advantages of this application become more obvious. The schematic embodiment drawings and their descriptions of this application are used to explain this application and do not constitute an improper limitation on this application. In the drawings:

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

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

[0048] Figure 3 A flow chart 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 by the present application;

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

[0051] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work 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 and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present application described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0053] In the present application, the terms "upper", "lower", "left", "right", "front", "back", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings. These terms are mainly used to better describe the present application and its embodiments, and are not used to limit the indicated devices, elements or components to have a specific orientation, or to be constructed and operated in a specific orientation.

[0054] In addition, some of the above terms may be used to express other meanings in addition to indicating orientation or positional relationship. For example, the term "on" may also be used to express a certain dependency or connection relationship in some cases. For those of ordinary skill in the art, the specific meanings of these terms in this application can be understood according to specific circumstances.

[0055] In addition, the terms "installed", "set", "provided with", "connected", "connected", and "socketed" should be understood in a broad sense. 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 it can be an internal connection between two devices, elements, or components. For those of ordinary skill in the art, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0056] In an optional embodiment of the present 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, such as Figure 1 As shown, the method comprises the following steps:

[0057] S101: Obtaining data to be processed;

[0058] The data to be processed is used to represent the data collected during the robot's execution of the first inspection task. The first inspection task can be a daily inspection task or a regular inspection task. The first inspection task has a corresponding inspection route. The robot operates according to the inspection route of the above-mentioned first inspection task. When the robot operates according to the inspection route of the first inspection task, the robot collects environmental information in real time. The robot information collection device includes an image collection device, an ultrasonic collection device, etc. The robot uses the image collection device to collect video frame images of the robot when it operates according to the inspection route of the first inspection task in real time, and performs inspection target identification based on the collected video frame images, so that the robot can generate and execute autonomous inspection tasks according to the identified inspection targets, thereby improving the degree of autonomy of the robot's inspection.

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

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

[0061] In an optional embodiment of the present 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, such as Figure 2 As shown, the method comprises the following steps:

[0062] S201: performing 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: performing image extraction processing based on visual route features on the video frame image data to obtain visual route feature image data;

[0065] The visual route feature data is used to represent image data corresponding to the visual route feature.

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

[0067] In another optional embodiment of the present application, the visual route feature is obtained by performing visual distance-based segmentation on the visual route, and the visual route is segmented based on the visual distance. According to the setting of the visual distance, the visual route feature may include a first visual route feature and a second visual route feature, and the visual route feature may include a first visual route feature, a second visual route feature and a third visual route feature.

[0068] When the visual route feature includes a first visual route feature and a second visual route feature, the visual route image data is subjected to image extraction processing based on the first visual route feature to obtain first visual route feature image data, wherein the first visual route feature image data is used to represent image data corresponding to the first visual route feature; the visual route image data is subjected to image extraction processing based on the second visual route feature 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 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. For example, if image extraction is performed on the current visual route according to the near view and the far view, near view image data and far view image data are obtained respectively. When performing image extraction, the parameters of the robot image acquisition device can be adjusted, such as camera focus, etc., to collect video frame images that meet the requirements for the near view and the far view, respectively.

[0069] When the visual route feature may include a first visual route feature, a second visual route feature and a third visual route feature, the visual route image data is subjected to image extraction processing based on the first visual route feature to obtain first visual route feature image data, wherein the first visual route feature image data is used to represent image data corresponding to the first visual route feature; the visual route image data is subjected to image extraction processing based on the second visual route feature 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 feature; the visual route image data is subjected to image extraction processing based on the third visual route feature to obtain third visual route feature image data, wherein the third visual route feature image data is used to represent image data corresponding to the third visual route feature; the visual route feature image data is obtained according to the first visual route feature image data, the second visual route feature image data and the third visual route feature image data. For example, on the current visual route, image extraction is performed based on the close-up, mid-range, and long-range images to obtain close-up image data, mid-range image data, and long-range image data, respectively. When performing image extraction, the parameters of the robot's image acquisition device can be adjusted, such as camera focus, to acquire video frame images that meet the requirements for the close-up, mid-range, and long-range images, respectively.

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

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

[0072] In an optional embodiment of the present application, preset targets of interest are stored in a preset inspection database, and the preset targets of interest may include multiple targets of interest. Image recognition-based target detection is performed on the above-mentioned first visual route feature image and the second visual route feature image, respectively, to determine whether there is a preset target of interest in the visual route feature image. If there is no preset target of interest in the visual route feature image, the robot continues to operate according to the inspection route of the first inspection task; if there is a preset target of interest in the visual route feature image, temporary inspection task target data is generated according to the target of interest in the visual route feature image. Further, if there are multiple preset targets of interest in the visual route feature image, multiple temporary inspection task target data corresponding to the multiple preset targets of interest are generated respectively.

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

[0074] In an optional embodiment of the present 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, such as Figure 3 As shown, the method comprises the following steps:

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

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

[0077] In an optional embodiment of the present application, a data processing method for robot inspection is proposed, and execution point screening processing is performed on temporary inspection task target data to obtain execution point data, including: performing position judgment processing on the temporary inspection task target data based on the global map to determine 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 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 prohibited area and boundary in the global map, performing point search in the operable area according to the position of the temporary inspection task target and the global map to obtain multiple process execution points, performing information gain screening processing on the multiple process execution points, calculating and processing the information of the temporary inspection task target that can be collected by the above-mentioned 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 the robot runs to the execution point to collect information on the temporary inspection task target in order to perform the second inspection task.

[0078] S302: Matching inspection execution characteristic data corresponding to the temporary inspection task target data in a preset inspection database to obtain the inspection execution characteristic data;

[0079] In an optional embodiment of the present application, a data processing method for robot inspection is proposed, including: 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 the first temporary inspection target, and the second temporary inspection task target data is data used to represent the second temporary inspection target; matching the 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 respectively to obtain first temporary inspection task feature data and second temporary inspection task feature data; generating second inspection task data based on the first temporary inspection task feature data and the second temporary inspection task feature data.

[0080] The temporary inspection task target data is the preset target of interest in the visual route feature image corresponding to any of the above-mentioned visual route features. For example, the temporary inspection task target data is the preset target of interest in the visual route feature image corresponding to the foreground. 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 features corresponding to the target of interest are matched in the preset inspection database, such as the inspection task corresponding to the target of interest is executed as target image acquisition, and the inspection task execution features of acquiring the image of the target of interest are generated; the inspection task corresponding to the target of interest is executed as target following, and the inspection task execution features of following the image of the target of interest are 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 the 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 features corresponding to the interest targets of this category are matched; if they are of different categories, the priorities of different interest targets are judged, and the inspection task execution order of different interest targets is determined according to the priority sorting, and the corresponding inspection task execution features are matched for different interest targets of the same priority.

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

[0083] S303: Generate second inspection task data according to the temporary inspection path data and the inspection execution characteristic data.

[0084] S104: The robot performs the second inspection task according to 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 the present application, while performing routine inspection tasks, the robot detects targets of interest in the park, generates temporary inspection tasks based on the detection results, and continues to perform the above-mentioned routine inspection tasks after completing the temporary inspection tasks. The robot patrols and detects at the same time and performs autonomous inspections on dynamically changing inspection targets in the park. There is no need to determine information such as the location of the dynamically changing inspection targets. The robot performs autonomous detection and generates inspection tasks, thereby improving the autonomy of the robot's inspections.

[0086] In an optional embodiment of the present 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, such as Figure 4 As shown,

[0087] A data acquisition module 41 is used to acquire data to be processed, wherein the data to be processed is used to represent 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 based on the visual route on the data to be processed to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent the temporary inspection target detected based on the visual route;

[0089] A temporary inspection module 43 is used to perform inspection task generation processing on the temporary inspection task target data to obtain second inspection task data;

[0090] The task execution module 44, 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.

[0091] In an optional embodiment of the present 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, such as Figure 5 As shown,

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

[0093] An image extraction module 52 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 used to represent image data corresponding to the visual route feature;

[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 existing in the visual route feature image data.

[0095] The specific manner of executing the operation of each unit in the above embodiment has been described in detail in the embodiment of the method, and will not be elaborated here.

[0096] In summary, in the present application, the data to be processed is obtained, wherein the data to be processed is used to represent the data collected during the robot's execution of the first inspection task; the data to be processed is subjected to target detection processing based on the visual route to obtain temporary inspection task target data, wherein the temporary inspection task target data is used to represent the temporary inspection target detected based on the visual route; the temporary inspection task target data is subjected to inspection task generation processing to obtain the second inspection task data; the robot performs the second inspection task according to the second inspection task data, and after performing the second inspection task, the robot continues to perform the first inspection task. By performing target detection based on the visual route on the data collected during the robot's inspection, the inspection target detected during the first inspection is subjected to temporary inspection task generation processing, and the robot continues to perform the first inspection task after performing the temporary inspection task. The inspection targets that dynamically change in the park are detected during the execution of the inspection task, and the inspection is performed. The automatic detection of the inspection targets in the park and the execution of its inspection tasks are realized, and the autonomy of the robot inspection is improved.

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

[0098] Obviously, those skilled in the art should understand that the above-mentioned units or steps of the present application can be implemented by a general-purpose computing device, they can be concentrated on a single computing device, or distributed on a network composed of multiple computing devices, and optionally, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. In this way, the present application is not limited to any specific combination of hardware and software.

[0099] The above description is only the preferred embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A data processing method for robot inspection, characterized in that: include: Acquire data to be processed, wherein the data to be processed is used to represent data collected during the robot's execution of the first inspection task; Performing target detection processing based on the visual route on the data to be processed to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent the temporary inspection target detected based on the visual route; Performing inspection task generation processing on the temporary inspection task target data to obtain second inspection task data; The robot performs the second inspection task according to the second inspection task data, and after performing the second inspection task, the robot continues to perform the first inspection task.

2. The data processing method according to claim 1, characterized in that: The data to be processed is subjected to target detection processing based on the visual route, and the temporary inspection task target data obtained includes: Performing recognition processing on 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; Performing 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 used to represent 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 the temporary inspection task target data, wherein the temporary inspection task target data is data for representing a preset target of interest present in the visual route feature image data.

3. The data processing method according to claim 2, characterized in that: The video frame image data is subjected to image extraction processing based on visual route features to obtain visual route feature image data including: Performing image screening processing based on a visual route on the video frame image data to obtain visual route image data, wherein the visual route image data is data for representing the video frame image corresponding to the visual route direction; Performing image extraction processing based on the first visual route feature 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 image data corresponding to the first visual route feature; Performing image extraction processing based on the second visual route feature 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 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 according to claim 1, characterized in that: Performing inspection task generation processing on the temporary inspection task target data to obtain the second inspection task data includes: Performing inspection path planning processing on the temporary inspection task target data to obtain temporary inspection path data; Matching the inspection execution characteristic data corresponding to the temporary inspection task target data in a preset inspection database to obtain the inspection execution characteristic data; The second inspection task data is generated according to the temporary inspection path data and the inspection execution characteristic 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: Performing execution point screening processing on the temporary inspection task target data to obtain execution point data, wherein the execution point data is point data used to indicate the execution of the inspection task corresponding to the temporary inspection target; Acquire operation point data, wherein the operation point data is position data used to indicate the current operation point of the robot; The operation point data and the execution point data are processed by path planning based on a preset global map to obtain the temporary inspection path data.

6. The data processing method according to claim 1, characterized in that: Performing inspection task generation processing on the temporary inspection task target data to obtain the second inspection task data includes: Identify and process the 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 the first temporary inspection target, and the second temporary inspection task target data is data used to represent the second temporary inspection target; Match the 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 the first temporary inspection task feature data and the second temporary inspection task feature data; The second inspection task data is generated according to the first temporary inspection task characteristic data and the second temporary inspection task characteristic data.

7. A data processing device for robot inspection, characterized in that: include: A data acquisition module, used to acquire data to be processed, wherein the data to be processed is used to represent data collected during the robot's execution of the first inspection task; A target detection module, used for performing target detection processing based on a visual route on the data to be processed to obtain temporary inspection task target data, wherein the temporary inspection task target data is data used to represent a temporary inspection target detected based on a visual route; A temporary inspection module, 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 the robot to execute the second inspection task according to the second inspection task data. After executing the second inspection task, the robot continues to execute the first inspection task.

8. The data processing device according to claim 7, characterized in that: The object detection module includes: An identification module is used to identify 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; An image extraction module, used for performing 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 used to represent image data corresponding to the visual route feature; The task target detection module is used to perform target detection processing on the visual route feature image data based on a preset target of interest to obtain the temporary inspection task target data, wherein the temporary inspection task target data is data used to represent the preset target of interest 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, and the computer instructions are used to enable the computer to execute the data processing method for robot inspection according to any one of claims 1-6.

10. An electronic device, characterized in that: include: 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, and the computer program is executed by the at least one processor so that the at least one processor executes the data processing method for robot inspection described in any one of claims 1-6.

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