Method and system for replacing wearable vision module of robot

Abstract

The present application relates to the technical field of wearable devices, and specifically discloses a method and system for replacing a wearable vision module of a robot. The current task requirements of the robot and / or the working environment information of the robot are obtained; based on the current task requirements and / or the working environment information, a target vision module is determined; based on the target vision module, a vision module replacement instruction is generated to control the robot to replace the vision module. The present application can select a target vision module that meets the current task requirements and / or working environment information according to the current task requirements and / or working environment information of the robot, and control the robot to replace the vision module without human intervention, so that the robot can quickly replace different vision modules according to actual needs, thereby improving the diversity of the robot's vision module, so that it can adapt to changing work scenarios and work requirements, and maintain low production, maintenance and operation costs.

Description

Technical Field

[0001] The present application relates to the technical field of wearable devices, and in particular to a method and system for replacing a wearable vision module of a robot. Background Art

[0002] With the rapid development of automation and intelligent technologies, automated equipment (such as robots) has been widely used in a variety of fields, including industrial manufacturing, medical surgery, and the service industry. Robots often require vision modules to perceive their environment and identify targets. In modern robot design, the robot's vision module is typically integrated as an integral component. Each robot is equipped with only a single vision module, making it difficult for the robot to adapt to changing work scenarios or work requirements. When performing tasks with different work scenarios or work requirements, different vision modules must be selected based on the developer's experience and different robots must be designed accordingly. This, combined with the need to maintain multiple robots, significantly increases the robot's production and maintenance costs. While integrating multiple vision modules (such as thermal imaging, infrared night vision, multispectral, and near- and far-focus vision) into the same robot can enable the robot to adapt to a variety of work scenarios and work requirements, the maintenance and operation of multiple vision modules increases the robot's maintenance and operating costs, limiting the robot's operation to short periods of time. Therefore, designing a robot vision system that can adapt to changing work scenarios and work requirements while maintaining low production, maintenance, and operating costs has become an urgent issue. Summary of the Invention

[0003] The present application provides a method and system for replacing a wearable vision module of a robot, so as to realize the replacement of the robot vision module and improve the diversity of the robot vision module, so that it can adapt to changing work scenarios and work requirements while maintaining low production, maintenance and operation costs.

[0004] In a first aspect, the present application provides a method for replacing a wearable vision module of a robot, the method comprising:

[0005] Obtaining the current task requirements of the robot and / or the working environment information of the robot;

[0006] Determining a target visual module based on the current task requirements and / or the working environment information;

[0007] Based on the target vision module, a vision module replacement instruction is generated to control the robot to replace the vision module.

[0008] In a second aspect, the present application further provides a system for replacing a wearable vision module of a robot, the system comprising:

[0009] An information acquisition module, configured to acquire the current task requirements of the robot and / or the working environment information of the robot;

[0010] An embedded computing module, configured to determine a target visual module based on the current task requirements and / or the working environment information;

[0011] The instruction execution module is used to generate a vision module replacement instruction based on the target vision module to control the robot to replace the vision module.

[0012] In one embodiment, the embedded computing module includes:

[0013] a visual demand index obtaining unit, configured to analyze the current task requirements and the working environment information based on a preset visual module recommendation model, and obtain visual demand indicators corresponding to the current task requirements and the working environment information;

[0014] The target visual module determination unit is used to match the visual demand index with the performance parameters of each visual module, obtain the matching degree between the visual demand index and each visual module, and use the visual module with the highest matching degree as the target visual module.

[0015] In a third aspect, the present application also provides a robot comprising a memory and a processor; the memory is used to store a computer program; the processor is used to execute the computer program and implement the method for replacing the wearable vision module of the robot as described above when executing the computer program.

[0016] In a fourth aspect, the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the method for replacing the wearable vision module of the robot as described above.

[0017] The present application discloses a method and system for replacing a wearable vision module of a robot, which obtains the current task requirements of the robot and / or the working environment information of the robot; determines a target vision module based on the current task requirements and / or the working environment information; and generates a vision module replacement instruction based on the target vision module to control the robot to replace the vision module. The present application can select a target vision module that meets the current task requirements and / or working environment information of the robot according to the current task requirements and / or working environment information, and control the robot to replace the vision module without human intervention, so that the robot can quickly replace different vision modules according to actual needs, thereby improving the diversity of the robot's vision module, enabling it to adapt to changing work scenarios and work requirements while maintaining low production, maintenance and operating costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 This is a schematic flow chart of a first embodiment of a method for replacing a wearable vision module of a robot provided in an embodiment of the present application;

[0020] Figure 2 This is a schematic flow chart of a second embodiment of a method for replacing a wearable vision module of a robot provided in an embodiment of the present application;

[0021] Figure 3 A schematic block diagram of a replacement system for a wearable robot vision module provided in an embodiment of the present application;

[0022] Figure 4 A schematic block diagram of the structure of a robot provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0024] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may be decomposed, combined, or partially merged, so the actual execution order may vary depending on the actual situation.

[0025] It should be understood that the terms used in this specification are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in this specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0026] It should be further understood that the term “and / or” used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0027] The embodiments of the present application provide a method and system for replacing a wearable vision module of a robot. The method can be applied to a replacement system for a wearable vision module of a robot. The method selects a target vision module that meets the current task requirements and / or working environment information of the robot, and controls the robot to replace the vision module. This allows the robot to quickly replace different vision modules according to actual needs, thereby increasing the diversity of the robot's vision modules and enabling it to adapt to changing work scenarios and work requirements while maintaining low production, maintenance, and operating costs.

[0028] The following describes some embodiments of the present application in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features therein may be combined with each other.

[0029] See also Figure 1 , Figure 1 This is a schematic flow chart of a first embodiment of a method for replacing a wearable vision module of a robot provided in an embodiment of the present application. The method for replacing a wearable vision module of a robot can be applied to a replacement system of a wearable vision module of a robot, and is used to select a target vision module that meets the current task requirements and / or working environment information of the robot according to the current task requirements and / or working environment information of the robot, and control the robot to replace the vision module, so that the robot can quickly replace different vision modules according to actual needs, thereby improving the diversity of the robot's vision module, enabling it to adapt to changing work scenarios and work requirements while maintaining low production, maintenance and operating costs.

[0030] like Figure 1As shown, the method for replacing the robot wearable vision module specifically includes steps S101 to S103.

[0031] S101, obtaining the current task requirements of the robot and / or the working environment information of the robot;

[0032] In one embodiment, the current mission requirement is a requirement related to the mission the robot is currently performing or awaiting execution. For example, mining or search and rescue missions require enhanced robot performance in diverse terrain conditions, requiring the robot's vision module to be able to capture images in different frequency bands and possess advanced image processing capabilities.

[0033] In one embodiment, the current task requirements can be extracted from user input or obtained through task analysis. Specifically, by analyzing the robot's current task, the specific objectives of the task are determined, such as identifying specific objects, tracking motion trajectories, and analyzing scene changes. The specific operations involved in the task, including the identification and processing of static and dynamic elements, are also determined. Based on the task objectives, the required visual features to be extracted and processed, such as color, shape, texture, size, and position, are then determined. The accuracy, processing speed, and stability requirements of the visual module are also determined.

[0034] In one embodiment, the working environment information is environmental information of the robot's current location, such as lighting information, color changes, background complexity, humidity, and temperature information.

[0035] In one embodiment, the working environment information can be obtained through a vision module currently worn by the robot, where the worn vision module includes a wearable vision module or the robot's native vision module. Specifically, the data module collects an image of the environment at the robot's current location and recognizes the image to obtain the working environment information.

[0036] Furthermore, the obtaining of the working environment information of the robot includes: collecting an environmental image of the working environment based on a visual module worn by the robot; and identifying the environmental image based on preset environmental information parameters to obtain the working environment information.

[0037] In one embodiment, the worn vision module may be a wearable vision module currently worn by the robot, or may be the original vision module of the robot.

[0038] In one embodiment, the preset environmental information parameters may include temperature, humidity, light level, visibility, etc., which are used to guide the recognition of environmental images and obtain required data.

[0039] In one embodiment, the robot first uses a worn vision module to capture an image of its current working environment. Then, based on preset environmental information parameters, the robot recognizes the environmental image and obtains data corresponding to the environmental information parameters, i.e., working environment information. Specifically, this can be accomplished using machine learning algorithms, image processing techniques, or pattern recognition technologies.

[0040] In a specific embodiment, feature information corresponding to environmental information parameters can be extracted from environmental images through image processing and computer vision technologies such as edge detection, corner detection, and texture analysis. Then, the extracted feature information can be analyzed and processed using machine learning or deep learning algorithms to obtain data corresponding to the environmental information parameters.

[0041] In another embodiment, after obtaining the environment image, the environment image may be pre-processed, which may include operations such as adjusting the image size, cropping the image, and enhancing the image contrast, so as to improve the image recognition accuracy.

[0042] S102, determining a target visual module based on the current task requirements and / or the working environment information;

[0043] Furthermore, determining the target visual module based on the current task requirement or the working environment information includes: determining the visual module corresponding to the current task requirement based on a preset task and visual module mapping table as the target visual module; or determining the visual module corresponding to the environment and visual module mapping table based on a preset environment and visual module mapping table as the target visual module.

[0044] In one embodiment, the task-to-vision module mapping table stores different task requirements and the vision modules corresponding to each task requirement, and is used to search for a vision module that matches the current task requirement.

[0045] In one embodiment, the task-to-vision module mapping table can be configured by the user based on actual needs. The task-to-vision module mapping table can also be generated by analyzing historical task requirements and the optimal vision modules corresponding to the historical task requirements to obtain a mapping relationship between tasks and vision modules.

[0046] In one embodiment, the environment and visual module mapping table stores different working environment information and the visual modules corresponding to each working environment information, and is used to search for a visual module that matches the current working environment information.

[0047] In one embodiment, the environment and vision module mapping table can be set by the user according to actual needs, and can also be obtained by analyzing historical working environment information and the optimal vision module corresponding to the historical working environment information.

[0048] In another embodiment, the target vision module may be determined based on a comprehensive analysis of current task requirements and the working environment.

[0049] S103. Generate a vision module replacement instruction based on the target vision module to control the robot to replace the vision module.

[0050] In one embodiment, the vision module replacement instruction includes an instruction to remove the worn vision module and an instruction to wear the target vision module. The vision module replacement instruction includes an identifier corresponding to the target vision module so that the robot can accurately identify and grasp the target vision module.

[0051] In one embodiment, the robot is controlled by a visual module replacement instruction to remove the worn visual module and wear the target visual module. There is no need for manual disassembly of the visual module. The robot can automatically remove and wear the visual module, thereby realizing rapid replacement of the visual module.

[0052] Furthermore, after generating a visual module replacement instruction based on the target visual module to control the robot to replace the visual module, it also includes: based on the device information of the target visual module, determining and loading the driver and dependent library corresponding to the target visual module to support the successful operation of the target visual module.

[0053] In one embodiment, to ensure the successful operation of the target vision module, the corresponding driver and dependent libraries must be loaded. First, the device information of the target vision module, including manufacturer, model, operating system version, etc., is obtained. This information can be obtained by viewing the device label or using the device manager. Then, based on the device information, the corresponding driver and dependent libraries are searched within the robot. Finally, the driver and dependent libraries are loaded.

[0054] In one embodiment, after the driver and dependent libraries are loaded, they can be tested to see if they are functioning properly. This can be done by running a test program built into the device or using a test tool provided by the operating system. When the driver and dependent libraries are installed and pass the test, they can support the successful operation of the target vision module.

[0055] The above embodiment provides a method and system for replacing a wearable vision module of a robot, which obtains the current task requirements of the robot and / or the working environment information of the robot; determines the target vision module based on the current task requirements and / or the working environment information; generates a vision module replacement instruction based on the target vision module to control the robot to replace the vision module. The present application can select a target vision module that meets the current task requirements and / or working environment information of the robot according to the current task requirements and / or working environment information, and control the robot to replace the vision module without human intervention, so that the robot can quickly replace different vision modules according to actual needs, thereby improving the diversity of the robot's vision module. Secondly, the implementation of the replaceable robot vision module eliminates the need for developers to design robots with different vision modules for different tasks or working environments, nor does it require integrating multiple vision modules into one robot, thereby avoiding resource consumption caused by the operation of multiple vision modules and reducing the production cost, maintenance cost and operating cost of the robot.

[0056] See also Figure 2 , Figure 2 This is a schematic flow chart of a second embodiment of a method for replacing a wearable vision module of a robot provided in an embodiment of the present application. This method for replacing a wearable vision module of a robot can be applied to a replacement system for a wearable vision module of a robot, and is used to determine a target vision module based on the robot's current task requirements and working environment information, and then control the robot to quickly replace the target vision model, so that the robot can quickly replace different vision modules according to actual needs, thereby increasing the diversity of the robot's vision modules, enabling the robot to quickly adapt to changing work scenarios and work requirements, and reducing the production, maintenance, and operating costs of the robot.

[0057] like Figure 2 As shown, the method for replacing the robot wearable vision module specifically includes steps S201 to S202.

[0058] S201: Analyze the current task requirements and the work environment information based on a preset visual module recommendation model to obtain visual requirement indicators corresponding to the current task requirements and the work environment information;

[0059] S202: Match the visual demand index with the performance parameters of each visual module to obtain the matching degree between the visual demand index and each visual module, and use the visual module with the highest matching degree as the target visual module.

[0060] In one embodiment, the vision module recommendation model can recommend the vision module that best suits the current task requirements and working environment based on different tasks and environmental conditions.

[0061] In one embodiment, a visual module recommendation model is used to comprehensively analyze the current task requirements and work environment information to determine the visual requirement indicators required to complete the current task in the current work environment. Specifically, the visual module recommendation model analyzes the current task requirements to determine the initial task requirement indicators. The work environment information is then analyzed to determine the stability of the lighting in the work environment, possible lighting changes, and environmental complexity, thereby assessing the degree of environmental interference with the work of the visual module. Finally, the initial task requirement indicators are modified based on the interference level to obtain the visual requirement indicators required to complete the current task in the current work environment.

[0062] In one embodiment, the visual demand indicators are the demand values ​​of various visual indicators, which may include image clarity, color reproduction, contrast, field of view, response speed stability and robustness, visual feature recognition ability, scene understanding ability, three-dimensional reconstruction ability, etc.

[0063] In one embodiment, the performance parameters of the vision module are actual performance values ​​of various vision indicators, which can be obtained from device information of the vision module.

[0064] In a specific embodiment, the performance parameters of each visual module are compared with the visual requirement index to evaluate their matching degree. Specifically, the actual performance value and the required value corresponding to each visual indicator are compared, and the matching degree of each visual module with the visual requirement index is calculated by combining the weights. The visual modules are then ranked according to the matching scores, and the visual module with the highest matching degree is selected as the target visual module.

[0065] In one embodiment, after a robot completes a task while wearing the target vision module, its performance can be evaluated and verified. If the actual performance meets expectations, the module can be confirmed as a suitable solution. Otherwise, the relevant parameters of the matching evaluation are adjusted, and the target vision module corresponding to the aforementioned visual requirement indicators is re-obtained during the next replacement.

[0066] Furthermore, the preset visual module recommendation model analyzes the current task requirements and the working environment information, and before determining the target visual module, it also includes: obtaining historical task requirements, historical working environment information and historical target visual modules; analyzing the historical task requirements and historical working environment information based on a preset pre-trained model to obtain a historical recommended visual module; comparing the historical recommended visual module with the historical target visual module to obtain a recommendation success rate of the pre-trained model; when the recommendation success rate is not less than a preset success rate threshold, using the pre-trained model as the visual module recommendation module.

[0067] In one embodiment, the task requirements, working environment information, and target vision module selected for tasks that the robot has previously performed are obtained. Specifically, the information can be obtained from a database, log files, user feedback, etc.

[0068] In one embodiment, a pre-trained model is used to analyze historical task requirements and historical work environment information to obtain historical visual demand indicators corresponding to the historical task requirements and historical work environment information, and a historical recommended visual module is obtained based on the historical visual demand indicators. The historically recommended visual module is compared with the target visual module actually used, and the recommendation success rate of the model is calculated. Specifically, the success rate can be calculated by the ratio of the recommended visual module to the target visual module actually used. The pre-trained model can be a convolutional neural network model, a recurrent neural network model, etc.

[0069] In one embodiment, if the recommendation success rate is not less than a preset success rate threshold, the pre-trained model can be used as a visual module recommendation module. Otherwise, the pre-trained model is adjusted or optimized until its recommendation success rate reaches the preset threshold.

[0070] In the above embodiment, the visual module recommendation model can recommend different visual modules according to different task requirements and working environment information, and then control the robot to quickly change the target visual model, thereby improving the diversity of the robot's visual modules and enabling it to quickly adapt to changing work scenarios and work requirements. There is no need to design robots with different visual modules for different tasks or working environments or integrate multiple visual modules into one robot, which reduces the production cost and maintenance cost of the robot, and at the same time avoids the resource consumption caused by the operation of multiple visual modules, thereby reducing the operating cost of the robot.

[0071] See also Figure 3 , Figure 3 This is a schematic block diagram of a replacement system for a robot wearable vision module provided in an embodiment of the present application.

[0072] like Figure 3 As shown, the replacement system 300 of the wearable vision module of the robot includes:

[0073] An information acquisition module 301 is used to obtain the current task requirements of the robot and / or the working environment information of the robot;

[0074] An embedded computing module 302 is configured to determine a target visual module based on the current task requirements and / or the working environment information;

[0075] The instruction execution module 303 is used to generate a vision module replacement instruction based on the target vision module to control the robot to replace the vision module.

[0076] Furthermore, the embedded computing module includes:

[0077] a visual demand index obtaining unit, configured to analyze the current task requirements and the working environment information based on a preset visual module recommendation model, and obtain visual demand indicators corresponding to the current task requirements and the working environment information;

[0078] The target visual module determination unit is used to match the visual demand index with the performance parameters of each visual module, obtain the matching degree between the visual demand index and each visual module, and use the visual module with the highest matching degree as the target visual module.

[0079] In one embodiment, the embedded computing module provides the necessary computing resources for the wearable vision modules. Each vision module is equipped with an embedded processor capable of performing advanced data processing, such as image recognition and machine learning algorithms. This allows for rapid local decision-making without transmitting data back to the robot's main computing system, thereby reducing latency and improving responsiveness.

[0080] In one embodiment, the replacement system of the robot wearable vision module also includes: a universal adaptation framework for wearing the target vision module; a data transmission module for transmitting information acquired by the vision module; and a software adaptation module for determining and loading the driver and dependent library corresponding to the target vision module based on the device information of the target vision module.

[0081] It should be noted that those skilled in the art will clearly understand that, for the sake of convenience and brevity of description, the specific working processes of the above-described system and each module can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0082] The above system can be implemented in the form of a computer program. Figure 4 Run on the robot shown.

[0083] See also Figure 4 , Figure 4 This is a schematic block diagram of the structure of a robot provided by an embodiment of the present application. Figure 4 The robot includes a processor, a memory, and a network interface connected through a system bus, wherein the memory may include a non-volatile storage medium and an internal memory.

[0084] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions, which, when executed, can cause a processor to execute any method for replacing a wearable vision module of a robot.

[0085] The processor is used to provide computing and control capabilities to support the operation of the entire robot.

[0086] The internal memory provides an environment for the operation of the computer program in the non-volatile storage medium. When the computer program is executed by the processor, the processor can execute any method for replacing the wearable vision module of the robot.

[0087] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the robot to which the solution of the present application is applied. The specific robot may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0088] It should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc.

[0089] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0090] Obtaining the current task requirements of the robot and / or the working environment information of the robot;

[0091] Determining a target visual module based on the current task requirements and / or the working environment information;

[0092] Based on the target vision module, a vision module replacement instruction is generated to control the robot to replace the vision module.

[0093] In one embodiment, after generating a vision module replacement instruction based on the target vision module to control the robot to replace the vision module, the processor is further configured to implement:

[0094] Based on the device information of the target vision module, determine and load the driver and dependent library corresponding to the target vision module to support the successful operation of the target vision module.

[0095] In one embodiment, when obtaining the working environment information of the robot, the processor is configured to implement:

[0096] collecting an environmental image of the working environment based on a worn vision module of the robot;

[0097] Based on preset environmental information parameters, the environmental image is identified to obtain the working environment information.

[0098] In one embodiment, when determining the target visual module based on the current task requirements and the working environment information, the processor is configured to implement:

[0099] Analyzing the current task requirements and the working environment information based on a preset visual module recommendation model to obtain visual requirement indicators corresponding to the current task requirements and the working environment information;

[0100] The visual demand index is matched with the performance parameters of each visual module to obtain the matching degree between the visual demand index and each visual module, and the visual module with the highest matching degree is used as the target visual module.

[0101] In one embodiment, before implementing the preset visual module recommendation model to analyze the current task requirements and the working environment information and determine the target visual module, the processor is further configured to implement:

[0102] Obtain historical task requirements, historical work environment information, and historical target visual modules;

[0103] Analyze the historical task requirements and historical work environment information based on a preset pre-trained model to obtain a historical recommendation visual module;

[0104] Comparing the historical recommendation visual module with the historical target visual module to obtain the recommendation success rate of the pre-trained model;

[0105] When the recommendation success rate is not less than a preset success rate threshold, the pre-trained model is used as the visual module recommendation module.

[0106] In one embodiment, when determining the target visual module based on the current task requirement or the working environment information, the processor is configured to implement:

[0107] Based on a preset task and visual module mapping table, determining a visual module corresponding to the current task requirement as the target visual module;

[0108] Alternatively, based on a preset environment and visual module mapping table, a visual module corresponding to the environment and visual module mapping table is determined as the target visual module.

[0109] A computer-readable storage medium is also provided in an embodiment of the present application, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and the processor executes the program instructions to implement any method for replacing a robot wearable vision module provided in an embodiment of the present application.

[0110] The computer-readable storage medium may be an internal storage unit of the robot described in the aforementioned embodiment, such as a hard disk or memory of the robot. The computer-readable storage medium may also be an external storage device of the robot, such as a plug-in hard disk, a smart memory card (SMC), a secure digital (SD) card, a flash memory card, etc., equipped on the robot.

[0111] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and such modifications or substitutions should be included in the scope of protection of the present application. Therefore, the scope of protection of the present application should be based on the scope of protection of the claims.

Claims

1. A method for replacing a wearable vision module of a robot, characterized in that: include: Obtaining the current task requirements of the robot and the working environment information of the robot; Determining a target visual module based on the current task requirements and the working environment information; Based on the target vision module, generating a vision module replacement instruction to control the robot to grab the target vision module and wear it on the universal adaptation frame; Wherein, the obtaining of the working environment information of the robot includes: collecting an environmental image of the working environment based on a worn vision module of the robot; Based on preset environmental information parameters, the environmental image is identified to obtain the working environment information; The step of determining a target visual module based on the current task requirements and the working environment information includes: Analyzing the current task requirements and the working environment information based on a preset visual module recommendation model to obtain visual requirement indicators corresponding to the current task requirements and the working environment information; The visual demand index is matched with the performance parameters of each visual module to obtain the matching degree between the visual demand index and each visual module, and the visual module with the highest matching degree is used as the target visual module.

2. The method for replacing a wearable robot vision module according to claim 1, wherein: After generating a vision module replacement instruction based on the target vision module to control the robot to grab the target vision module and wear it on the universal adaptation frame, the method further includes: Based on the device information of the target vision module, determine and load the driver and dependent library corresponding to the target vision module to support the successful operation of the target vision module.

3. The method for replacing a wearable robot vision module according to claim 1, wherein: Before analyzing the current task requirements and the working environment information based on the preset visual module recommendation model and determining the target visual module, the method further includes: Obtain historical task requirements, historical work environment information, and historical target visual modules; Analyze the historical task requirements and the historical working environment information based on a preset pre-trained model to obtain a historical recommended visual module; Comparing the historical recommendation visual module with the historical target visual module to obtain the recommendation success rate of the pre-trained model; When the recommendation success rate is not less than a preset success rate threshold, the pre-trained model is used as the visual module recommendation model.

4. A replacement system for a wearable vision module of a robot, characterized in that: include: An information acquisition module, used to obtain the current task requirements of the robot and the working environment information of the robot; An embedded computing module, configured to determine a target visual module based on the current task requirements and the working environment information; An instruction execution module is used to generate a vision module replacement instruction based on the target vision module to control the robot to replace the vision module; Wherein, the obtaining of the working environment information of the robot includes: collecting an environmental image of the working environment based on a worn vision module of the robot; Based on preset environmental information parameters, the environmental image is identified to obtain the working environment information; Wherein, the embedded computing module includes: a visual demand index obtaining unit, configured to analyze the current task requirements and the working environment information based on a preset visual module recommendation model, and obtain visual demand indicators corresponding to the current task requirements and the working environment information; The target visual module determination unit is used to match the visual demand index with the performance parameters of each visual module, obtain the matching degree between the visual demand index and each visual module, and use the visual module with the highest matching degree as the target visual module.

5. A robot, characterized in that: The robot includes a memory and a processor; The memory is used to store computer programs; The processor is used to execute the computer program and implement the method for replacing the robot wearable vision module as described in any one of claims 1 to 3 when executing the computer program.

6. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, enables the processor to implement the method for replacing a wearable vision module of a robot according to any one of claims 1 to 3.

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