Intelligent robot control system based on big data

Abstract

The invention discloses an intelligent robot control system based on big data, which comprises a data acquisition module, a monitoring module and a garbage cleaning module, and is characterized in that the data acquisition module is used for determining driving direction data of a robot and acquiring specific position information of the cleaning robot in a multi-angle area; and the monitoring module is used for shooting a road picture in the driving direction according to the driving direction of the robot, detecting the garbage position in the road picture and detecting environment wind power of a multi-angle area. The driving of the cleaning robot in the multi-angle area is monitored, the current area and the cleaning task of the cleaning robot are quickly positioned, and high-efficiency cleaning of the cleaning area is realized; according to the method, the garbage model is subjected to feature recognition, the pollution condition caused by garbage in the multi-angle area is accurately monitored, and the method has the advantages of being high in target monitoring accuracy and high in execution instruction adjusting capacity.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent robots, and in particular to an intelligent robot control system based on big data. Background Art

[0002] A cleaning robot is a robot used for urban sanitation work, which has the advantages of high efficiency, intelligence, and saving manpower and material resources. This robot can navigate through different technologies, such as lidar, GPS, cameras, etc., to achieve autonomous navigation and obstacle avoidance. They usually have devices such as mechanical arms and sensors, which can grab, transport and clean up garbage, as well as perform tasks such as road cleaning. The development of cleaning robots is of great significance in improving the level of urban environmental sanitation, reducing labor costs, and improving work efficiency. At the same time, due to its wide range of uses, it can be applied to many public places such as urban streets, parks, and squares.

[0003] In the prior art, the intelligent robot control system can identify and capture the garbage in the cleaning area and clean up the garbage in real time. However, when the environment around the target cleaning area is complex, the cleaning area environment will change the driving position of the cleaning robot, making it difficult to obtain the real-time position and cleaning direction of the cleaning robot in the target cleaning area. Especially in windy weather, the garbage will change position and pile up due to the influence of wind, making it difficult to capture, which greatly reduces the cleaning efficiency of the cleaning robot. Therefore, it is necessary to design an intelligent robot control system based on big data with high target monitoring accuracy and strong command execution and adjustment capabilities. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent robot control system based on big data to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an intelligent robot control system based on big data, comprising a data acquisition module, a monitoring module and a garbage cleaning module, wherein the data acquisition module is used to obtain control system operation data, determine the robot's driving direction data according to the real-time angle between the robot's running tires and the reference direction in the target cleaning area, and obtain the specific position information of the cleaning robot in a multi-angle area based on the determined robot driving direction data; the monitoring module is used to retrieve the camera usage permission, shoot the road picture in the driving direction according to the robot's driving direction, obtain the road picture, extract features from the picture, detect the garbage position in the road picture, and detect the environmental wind force in the multi-angle area; the garbage cleaning module is used to clean the target cleaning area based on the transformed garbage amount information, and control the robot to clean the garbage according to the preset driving path.

[0006] According to the above technical scheme, the data acquisition module includes a multi-angle area limitation module and a position detection module. The multi-angle area limitation module is used to obtain the range data of the target cleaning area and the specific position information of the cleaning robot in the multi-angle area; the position detection module is used to retrieve the location data of the target cleaning area in the map, collect the multi-angle area and the set regional screen markers corresponding to the map data in the navigation database, upload the collected multi-angle area and the set regional screen markers to the processing terminal, and calibrate multiple features of the screen area markers; obtain the specific position information of the regional positioning cleaning robot with the location of the marker as the reference point, retrieve the location data of the regional screen marker in the multi-angle area, and obtain the specific position information of the cleaning robot in the multi-angle area in combination with the specific position information of the regional positioning cleaning robot with the location of the marker as the reference point.

[0007] According to the above technical solution, the monitoring module includes a garbage recognition module and a cleaning detection module. The garbage recognition module is used to retrieve the cleanable garbage model data set by the robot cleaning end, use computer vision technology to analyze the garbage image data, obtain picture information, perform overlapping recognition of garbage in the picture information, analyze and judge whether the garbage is overlapping, and compare the current garbage information with the garbage feature information in the database in real time, decompose the accumulated picture information with garbage features, and obtain the individual garbage model in the overlapping garbage; the cleaning detection module is used to detect that the garbage has entered other target cleaning areas different from the target cleaning area where the cleaning robot is located, and count the target cleaning area with the smallest amount of regional transformation garbage in the multi-angle area.

[0008] According to the above technical scheme, the cleaning detection module includes a cleaning discrimination submodule and a garbage transformation detection submodule. The cleaning discrimination submodule is used to compare the parameters of the individual garbage model in the overlapping garbage with the cleanable garbage data in the cleanable garbage model data to determine whether the current individual garbage model can be cleaned by the garbage cleaner; the garbage transformation detection module is used to retrieve the current multi-angle regional wind level data in real time, and obtain the comprehensive average wind speed in the multi-angle region through the wind level data; through the cleanable garbage data in the cleanable garbage model data, a quality assessment model for cleanable garbage is constructed, and the garbage quality in a single target cleaning area is obtained in turn, the total amount of garbage transformation is obtained, and the amount of garbage generated by the regional transformation in the single target cleaning area under the influence of wind is counted.

[0009] According to the above technical solution, a method for operating an intelligent robot control system based on big data includes:

[0010] Obtain the control system operation data, and determine the robot's driving direction data based on the real-time angle between the robot's running tires and the reference direction in the target cleaning area;

[0011] Based on the determined robot driving direction data, the range data of the target cleaning area is obtained, and the specific position information of the cleaning robot in the multi-angle area is detected;

[0012] Retrieve the camera usage permission, shoot the road picture in the driving direction according to the driving direction of the robot, obtain the road picture, extract features from the picture, detect the garbage position in the road picture, and determine whether the current individual garbage model can be cleaned by the garbage cleaner;

[0013] Detecting the environmental wind force in the multi-angle area, and counting the amount of garbage generated by the area transformation in a single target cleaning area under the influence of the wind force;

[0014] Based on the transformed garbage volume information, the target cleaning area is cleaned, the robot is controlled to clean the garbage according to the preset driving path, and the corresponding instructions are output through the output terminal.

[0015] According to the above technical solution, the step of obtaining the range data of the target cleaning area includes:

[0016] Acquire range data of a target cleaning area, wherein the range data of the target cleaning area is located, intercepted and marked by a processing system in a map navigation software, and the range data of the target cleaning area is obtained by outputting the map navigation software;

[0017] The specific position information of the cleaning robot in the multi-angle area is obtained, wherein the multi-angle area is composed of G target cleaning areas of the same area.

[0018] According to the above technical solution, the specific position information of the cleaning robot in the multi-angle area is detected, including:

[0019] Retrieving the location data of the target cleaning area in the map, collecting the multi-angle area and the set regional screen markers corresponding to the map data in the navigation database, uploading the collected multi-angle area and the set regional screen markers to the processing terminal, and calibrating multiple features of the screen area markers;

[0020] The location data of the target cleaning area in the map includes the coordinate data of the target cleaning area in the city expansion map, the length and width data of the target cleaning area, and the location data of the regional screen markers in the multi-angle region;

[0021] Perform feature recognition on the real-time image captured and compare it with the calibrated markers in the image area. When the marker features are recognized, obtain the angle information between the direction corresponding to the camera shooting angle and the plane where the X, Y, and Z axes are located in the spatial rectangular coordinate system established with the center of the cleaning robot as the coordinate origin and the current driving direction of the cleaning robot as the X-axis. The X-axis is rotated 90° clockwise through the coordinate origin in the driving plane to become the Y-axis. The coordinate origin is parallel to the X and Y axes and upwards is the positive semi-axis of the Z axis.

[0022] By identifying the size ratio information of the marker and the calibrated marker in the picture area in the shooting picture and the reference shooting distance information of the calibrated marker in the picture area, the distance information between the shooting head of the cleaning robot and the marker is calculated, and the specific position information of the regional positioning cleaning robot with the position of the marker as the reference point is obtained by combining the angle information corresponding to the shooting angle of the camera and the plane where the X, Y and Z axes are located;

[0023] The location data of the regional screen markers in the multi-angle area are retrieved, and combined with the specific location information of the regional positioning cleaning robot with the location of the markers as the reference point, the specific location information of the cleaning robot in the multi-angle area is obtained.

[0024] According to the above technical solution, the step of judging whether the current individual garbage model can be cleaned by the garbage cleaner includes:

[0025] Retrieving the cleanable garbage model data set by the robot cleaning end, wherein the cleanable garbage model data includes the maximum height, maximum width, maximum length and flexibility information of the garbage that can be cleaned by the robot cleaning end;

[0026] Using computer vision technology to analyze junk image data, including object detection, image segmentation, and feature extraction technology, wherein analyzing junk in image data is achieved through a deep learning model;

[0027] Collect at least N labeled image data for building the garbage monitoring AI algorithm, including garbage items of various types and states, where N is the minimum number of labeled image data for training;

[0028] The system obtains the image information, identifies the overlapping garbage in the image information, analyzes and determines whether the garbage is overlapping, compares the current garbage information with the garbage feature information in the database in real time, decomposes the accumulated image information with garbage features, obtains the individual garbage model in the overlapping garbage, and compares the parameters of the individual garbage model with the cleanable garbage data in the cleanable garbage model data, determines whether the current individual garbage model can be cleaned by the garbage cleaner, and if so, outputs a cleanable instruction.

[0029] According to the above technical solution, the statistics of the amount of garbage generated by the area transformation of a single target cleaning area under the influence of wind include:

[0030] Retrieve the current multi-angle regional wind level data in real time, obtain the wind level as Q, and obtain the comprehensive average wind speed in the multi-angle region as A through the wind level data;

[0031] A quality assessment model for cleanable garbage is constructed based on the cleanable garbage data in the cleanable garbage model data, and the qualities of cleanable garbage in a single target cleaning area are obtained in sequence, namely M1, M2, ..., M c , then the total amount of garbage that can be cleaned up is F = M1 + M2...M c , count the amount of cleanable garbage generated by the area transformation of a single target cleaning area under the influence of wind Where c is the number of statistics on the mass of cleanable garbage within the statistical time period, λ is the unit conversion parameter, and μ is the robot cleaning limit value for the amount of cleanable garbage accumulation in the multi-angle area.

[0032] According to the above technical solution, the garbage cleaning of the target cleaning area includes:

[0033] When it is detected that garbage enters other target cleaning areas different from the target cleaning area where the cleaning robot is located, the target cleaning area with the smallest amount of garbage generated in the multi-angle area is counted, and after the statistical time period ends, the robot drives to the target cleaning area with the smallest amount of garbage generated in the area transformation to clean the garbage;

[0034] According to the information of garbage volume generated by regional transformation during the statistical time period, the accumulation amount of garbage near the target cleaning under the condition of low wind force is calculated S=K1+K2...K G When it is detected that S>S1 and the average wind level in the statistical time period is less than 3, the information prompting the staff to maintain the multi-angle area will be output to the mobile terminal carried by the staff, where S1 is the maximum manual cleaning limit value of garbage accumulation in the multi-angle area.

[0035] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, by locating the specific position information of the cleaning robot in the area and monitoring the driving of the cleaning robot in multi-angle areas, quickly locates the current area and cleaning tasks of the cleaning robot, arranges cleaning tasks based on the existing position environment of the cleaning robot, and realizes efficient cleaning of the cleaning area; by performing feature recognition on the garbage model and retrieving relevant data of the garbage model, it can confirm whether the cleaning robot can remove the target garbage, and effectively distinguish the garbage in multi-angle areas according to whether it can be removed; the accumulation amount of garbage in multi-angle areas under the influence of different wind forces is calculated, and the amount of cleanable garbage that produces regional changes is obtained through changes in wind level parameters, which solves the difficulty of real-time and accurate capture of the amount of garbage in multi-angle areas, and helps the system to more accurately monitor the pollution caused by garbage in multi-angle areas, and take appropriate measures to control it. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0037] Figure 1 It is a flow chart of an operation method of an intelligent robot control system based on big data provided by the present invention. DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] See also Figure 1 The present invention provides a technical solution: an intelligent robot control system based on big data, comprising:

[0040] The data acquisition module, monitoring module and garbage cleaning module, the data acquisition module is used to obtain the control system operation data, determine the robot's driving direction data according to the real-time angle between the robot's running tires and the reference direction in the target cleaning area, and obtain the specific position information of the cleaning robot in the multi-angle area based on the determined robot driving direction data; the monitoring module is used to retrieve the camera usage permission, shoot the road picture in the driving direction according to the robot's driving direction, obtain the road picture, extract features from the picture, detect the garbage position in the road picture, and detect the environmental wind force in the multi-angle area; the garbage cleaning module is used to clean the target cleaning area based on the transformed garbage amount information, and control the robot to clean the garbage according to the preset driving path.

[0041] The present invention locates the specific position information of the cleaning robot in the area and monitors the driving of the cleaning robot in multi-angle areas, quickly locates the current area and cleaning tasks of the cleaning robot, arranges cleaning tasks based on the existing position environment of the cleaning robot, and realizes efficient cleaning of the cleaning area; by performing feature recognition on the garbage model and retrieving relevant data of the garbage model, it can confirm whether the cleaning robot can remove the target garbage, and effectively distinguish the garbage in multi-angle areas according to whether it can be removed; the accumulation amount of garbage in multi-angle areas under the influence of different wind forces is calculated, and the amount of cleanable garbage that produces regional changes is obtained through changes in wind level parameters, which solves the difficulty of real-time and accurate capture of the amount of garbage in multi-angle areas, and helps the system to more accurately monitor the pollution caused by garbage in multi-angle areas, and take appropriate measures to control it.

[0042] The data acquisition module includes a multi-angle area limitation module and a position detection module. The multi-angle area limitation module is used to obtain the range data of the target cleaning area and the specific position information of the cleaning robot in the multi-angle area; the position detection module is used to retrieve the location data of the target cleaning area in the map, collect the multi-angle area and the set regional screen markers corresponding to the map data in the navigation database, upload the collected multi-angle area and the set regional screen markers to the processing terminal, and calibrate multiple features of the screen area markers; obtain the specific position information of the regional positioning cleaning robot with the marker location as the reference point, retrieve the location data of the regional screen marker in the multi-angle area, and obtain the specific position information of the cleaning robot in the multi-angle area in combination with the specific position information of the regional positioning cleaning robot with the marker location as the reference point.

[0043] The monitoring module includes a garbage recognition module and a cleaning detection module. The garbage recognition module is used to retrieve the cleanable garbage model data set by the robot cleaning end, use computer vision technology to analyze garbage image data, obtain picture information, identify overlapping garbage in the picture information, analyze and judge whether the garbage is overlapping, and compare the current garbage information with the garbage feature information in the database in real time. The accumulated picture information with garbage features is decomposed to obtain individual garbage models in the overlapping garbage; the cleaning detection module is used to count the target cleaning area with the smallest amount of regional transformation garbage in the multi-angle area when it detects that the garbage has entered other target cleaning areas different from the target cleaning area where the cleaning robot is located.

[0044] The cleaning detection module includes a cleaning discrimination submodule and a garbage transformation detection submodule. The cleaning discrimination submodule is used to compare the parameters of the individual garbage model in the overlapping garbage with the cleanable garbage data in the cleanable garbage model data to determine whether the current individual garbage model can be cleaned by the garbage cleaner; the garbage transformation detection module is used to retrieve the current multi-angle regional wind level data in real time, and obtain the comprehensive average wind speed in the multi-angle region through the wind level data; the cleanable garbage data in the cleanable garbage model data is used to construct a quality assessment model for cleanable garbage, and the garbage quality in a single target cleaning area is obtained in turn, the total amount of garbage transformation is obtained, and the amount of garbage generated by the regional transformation in a single target cleaning area under the influence of wind is counted.

[0045] In a preferred embodiment, a method for operating an intelligent robot control system based on big data includes:

[0046] Obtain the control system operation data, and determine the robot's driving direction data based on the real-time angle between the robot's running tires and the reference direction in the target cleaning area;

[0047] Based on the determined robot driving direction data, the range data of the target cleaning area is obtained, and the specific position information of the cleaning robot in the multi-angle area is detected;

[0048] Retrieve the camera usage permission, take a picture of the road in the driving direction according to the robot's driving direction, obtain the road picture, extract features from the picture, detect the location of garbage in the road picture, and determine whether the current individual garbage model can be cleaned by the garbage cleaner;

[0049] Detect the environmental wind force in multiple angles and count the amount of garbage generated by the area change in a single target cleaning area under the influence of wind force;

[0050] Based on the transformed garbage volume information, the target cleaning area is cleaned, the robot is controlled to clean the garbage according to the preset driving path, and the corresponding instructions are output through the output terminal.

[0051] In this embodiment, obtaining the range data of the target cleaning area includes:

[0052] Acquire the range data of the target cleaning area, the range data of the target cleaning area is located, intercepted and marked by the processing system in the map navigation software, and the range data of the target cleaning area is obtained by outputting the map navigation software;

[0053] The specific position information of the cleaning robot in the multi-angle area is obtained, where the multi-angle area is composed of G target cleaning areas of the same area.

[0054] In this embodiment, detecting the specific position information of the cleaning robot in the multi-angle area includes:

[0055] Retrieving the location data of the target cleaning area in the map, collecting the multi-angle area and the set regional screen markers corresponding to the map data in the navigation database, uploading the collected multi-angle area and the set regional screen markers to the processing terminal, and calibrating multiple features of the screen area markers;

[0056] The location data of the target cleaning area in the map include the coordinate data of the target cleaning area in the city expansion map, the length and width data of the target cleaning area, and the location data of the regional screen markers in the multi-angle area;

[0057] The real-time image is identified and compared with the calibrated image area markers. When the marker features are identified, the angle information between the camera shooting angle and the plane where the X, Y, and Z axes are located is obtained. The X-axis is rotated 90° clockwise through the coordinate origin in the driving plane to form the Y-axis. The coordinate origin is parallel to the X and Y axes and upward is the positive semi-axis of the Z axis.

[0058] By identifying the size ratio information of the marker and the calibrated screen area marker in the shooting screen and the reference shooting distance information of the calibrated screen area marker in the shooting screen, the distance information between the shooting head of the cleaning robot and the marker is calculated, and the specific position information of the regional positioning cleaning robot with the marker as the reference point is obtained by combining the angle information between the corresponding direction of the camera shooting angle and the plane where the X, Y, and Z axes are located;

[0059] The location data of the regional screen markers in the multi-angle area are retrieved, and the specific location information of the cleaning robot in the multi-angle area is obtained by combining the specific location information of the regional positioning cleaning robot with the location of the markers as the reference point.

[0060] This technical solution solves the problem of difficulty in obtaining the real-time position and cleaning direction of the cleaning robot in the target cleaning area when the surrounding environment of the cleaning area is complex, so as to achieve efficient cleaning of the cleaning area. By constructing a coordinate system and calculating the proportional difference between the shooting image and the size of the marker, the specific position information of the cleaning robot in the area is located, and by monitoring the driving of the cleaning robot in the multi-angle area, the current area and cleaning task of the cleaning robot can be quickly located, and the cleaning task can be arranged based on the current position environment of the cleaning robot to achieve efficient cleaning of the cleaning area.

[0061] In this embodiment, judging whether the current individual garbage model can be cleaned by the garbage cleaner includes:

[0062] Retrieving the cleanable garbage model data set by the robot cleaning end, the cleanable garbage model data including the maximum height, maximum width, maximum length and flexibility information of the garbage that can be cleaned by the robot cleaning end;

[0063] Use computer vision techniques to analyze junk image data, including object detection, image segmentation, and feature extraction techniques. Analyzing junk in image data is accomplished through deep learning models.

[0064] Collect at least N labeled image data for building the garbage monitoring AI algorithm, including garbage items of various types and states, where N is the minimum number of labeled image data for training;

[0065] Acquire the image information, identify the overlapping garbage in the image information, analyze and judge whether the garbage is overlapping, compare the current garbage information with the garbage feature information in the database in real time, decompose the accumulated image information with garbage features, obtain the individual garbage model in the overlapping garbage, and compare the parameters of the individual garbage model with the cleanable garbage data in the cleanable garbage model data, judge whether the current individual garbage model can be cleaned by the garbage cleaner, and if so, output the cleanable instruction.

[0066] This technical solution solves the problem of difficulty in confirming whether the garbage can be cleaned by the cleaning robot when the garbage overlaps. By identifying the features of the garbage model and retrieving the relevant data of the garbage model, it is possible to confirm whether the cleaning robot can remove the target garbage and effectively distinguish the garbage in multiple angles based on whether it can be removed.

[0067] In this embodiment, the amount of garbage generated by the area change of a single target cleaning area under the influence of wind is counted, including:

[0068] Retrieve the current multi-angle regional wind level data in real time, obtain the wind level as Q, and obtain the comprehensive average wind speed in the multi-angle region as A through the wind level data;

[0069] Through the cleanable garbage data in the cleanable garbage model data, a quality assessment model for cleanable garbage is constructed, and the quality of cleanable garbage in a single target cleaning area is obtained in turn, which are M1, M2, ..., M c , then the total amount of garbage that can be cleaned up is F = M1 + M2...M c , count the amount of cleanable garbage generated by the area transformation of a single target cleaning area under the influence of wind Wherein c is the statistical number of cleanable garbage mass within the statistical time period, λ is the unit conversion parameter, μ is the robot cleaning limit value for the amount of cleanable garbage accumulation in the multi-angle area, and in a preferred embodiment, 25000<μ<35000.

[0070] When the wind speed is low, the amount of garbage that changes the area is small. The value is small; when the wind level gradually increases, the amount of garbage that produces regional changes will increase rapidly with the increase of wind speed. The value soared.

[0071] The amount of garbage accumulated in multi-angle areas under the influence of different wind forces is calculated. According to the huge difference in the regional change amount of cleanable garbage under the influence of different wind levels, the amount of cleanable garbage that produces regional change is obtained through the change of wind level parameters through the base change of wind speed and the exponential transformation of wind level. This solves the difficulty of capturing the amount of garbage in multi-angle areas in real time and accurately, and helps the system to more accurately monitor the pollution caused by garbage in multi-angle areas and take appropriate measures to control it.

[0072] In this embodiment, cleaning the target cleaning area includes:

[0073] When it is detected that garbage enters other target cleaning areas different from the target cleaning area where the cleaning robot is located, the target cleaning area with the smallest amount of garbage generated in the multi-angle area is counted, and after the statistical time period ends, the robot drives to the target cleaning area with the smallest amount of garbage generated in the area transformation to clean the garbage;

[0074] According to the information of garbage volume generated by regional transformation during the statistical time period, the accumulation amount of garbage near the target cleaning under the condition of low wind force is calculated S=K1+K2...K G When it is detected that S>S1 and the average wind level during the statistical time period is less than 3, the information prompting the staff to maintain the multi-angle area will be output to the mobile terminal carried by the staff, where S1 is the maximum manual cleaning limit value for garbage accumulation in the multi-angle area.

[0075] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0076] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent robot control system based on big data, characterized by: It includes a data acquisition module, a monitoring module and a garbage cleaning module. The data acquisition module is used to obtain the control system operation data, determine the robot's driving direction data according to the real-time angle between the robot's running tires and the reference direction in the target cleaning area, and obtain the specific position information of the cleaning robot in the multi-angle area based on the determined robot driving direction data; the monitoring module is used to retrieve the camera usage authority, shoot the road picture in the driving direction according to the robot's driving direction, obtain the road picture, extract features from the picture, detect the garbage position in the road picture, and detect the environmental wind force in the multi-angle area; the garbage cleaning module is used to clean the target cleaning area based on the transformed garbage amount information, and control the robot to clean the garbage according to the preset driving path.

2. The intelligent robot control system based on big data according to claim 1, characterized in that: The data acquisition module includes a multi-angle area limitation module and a position detection module. The multi-angle area limitation module is used to obtain the range data of the target cleaning area and the specific position information of the cleaning robot in the multi-angle area; the position detection module is used to retrieve the location data of the target cleaning area in the map, collect the multi-angle area corresponding to the map data and the set area screen markers in the navigation database, upload the collected multi-angle area and the set area screen markers to the processing terminal, and calibrate multiple features of the screen area markers; Get the specific position information of the regional positioning cleaning robot with the marker location as the reference point, retrieve the location data of the regional screen marker in the multi-angle area, and combine the specific position information of the regional positioning cleaning robot with the marker location as the reference point to get the specific position information of the cleaning robot in the multi-angle area.

3. The intelligent robot control system based on big data according to claim 2 is characterized in that: The monitoring module includes a garbage recognition module and a cleaning detection module. The garbage recognition module is used to retrieve the cleanable garbage model data set by the robot cleaning end, use computer vision technology to analyze garbage image data, obtain picture information, perform overlapping recognition on garbage in the picture information, analyze and judge whether the garbage is overlapping, and compare the current garbage information with the garbage feature information in the database in real time, decompose the accumulated picture information with garbage features, and obtain individual garbage models in the overlapping garbage; the cleaning detection module is used to count the target cleaning area with the smallest amount of regional transformation garbage in the multi-angle area after detecting that the garbage has entered other target cleaning areas different from the target cleaning area where the cleaning robot is located.

4. The intelligent robot control system based on big data according to claim 3 is characterized in that: The cleaning detection module includes a cleaning discrimination submodule and a garbage transformation detection submodule. The cleaning discrimination submodule is used to compare the parameters of the individual garbage model in the overlapping garbage with the cleanable garbage data in the cleanable garbage model data to determine whether the current individual garbage model can be cleaned by the garbage cleaner; the garbage transformation detection module is used to retrieve the current multi-angle regional wind level data in real time, and obtain the comprehensive average wind speed in the multi-angle region through the wind level data; through the cleanable garbage data in the cleanable garbage model data, a quality assessment model for cleanable garbage is constructed, and the garbage quality in a single target cleaning area is obtained in turn, the total amount of garbage transformation is obtained, and the amount of garbage generated by the regional transformation in the single target cleaning area under the influence of wind is counted.

5. A method for operating an intelligent robot control system based on big data, comprising: Obtain the control system operation data, and determine the robot's driving direction data based on the real-time angle between the robot's running tires and the reference direction in the target cleaning area; Based on the determined robot driving direction data, the range data of the target cleaning area is obtained, and the specific position information of the cleaning robot in the multi-angle area is detected; Retrieve the camera usage permission, shoot the road picture in the driving direction according to the driving direction of the robot, obtain the road picture, extract features from the picture, detect the garbage position in the road picture, and determine whether the current individual garbage model can be cleaned by the garbage cleaner; Detecting the environmental wind force in the multi-angle area, and counting the amount of garbage generated by the area transformation in a single target cleaning area under the influence of the wind force; Based on the transformed garbage volume information, the target cleaning area is cleaned, the robot is controlled to clean the garbage according to the preset driving path, and the corresponding instructions are output through the output terminal.

6. The operating method of the intelligent robot control system based on big data according to claim 5 is characterized in that: The step of obtaining the range data of the target cleaning area includes: Acquire range data of a target cleaning area, wherein the range data of the target cleaning area is located, intercepted and marked by a processing system in a map navigation software, and the range data of the target cleaning area is obtained by outputting the map navigation software; The specific position information of the cleaning robot in the multi-angle area is obtained, wherein the multi-angle area is composed of G target cleaning areas of the same area.

7. The operating method of the intelligent robot control system based on big data according to claim 6 is characterized in that: The detecting of specific position information of the cleaning robot in the multi-angle area includes: Retrieving the location data of the target cleaning area in the map, collecting the multi-angle area and the set regional screen markers corresponding to the map data in the navigation database, uploading the collected multi-angle area and the set regional screen markers to the processing terminal, and calibrating multiple features of the screen area markers; The location data of the target cleaning area in the map includes the coordinate data of the target cleaning area in the city expansion map, the length and width data of the target cleaning area, and the location data of the regional screen markers in the multi-angle region; Perform feature recognition on the real-time image captured and compare it with the calibrated markers in the image area. When the marker features are recognized, obtain the angle information between the direction corresponding to the camera shooting angle and the plane where the X, Y, and Z axes are located in the spatial rectangular coordinate system established with the center of the cleaning robot as the coordinate origin and the current driving direction of the cleaning robot as the X-axis. The X-axis is rotated 90° clockwise through the coordinate origin in the driving plane to become the Y-axis. The coordinate origin is parallel to the X and Y axes and upwards is the positive semi-axis of the Z axis. By identifying the size ratio information of the marker and the calibrated marker in the picture area in the shooting picture and the reference shooting distance information of the calibrated marker in the picture area, the distance information between the shooting head of the cleaning robot and the marker is calculated, and the specific position information of the regional positioning cleaning robot with the position of the marker as the reference point is obtained by combining the angle information corresponding to the shooting angle of the camera and the plane where the X, Y and Z axes are located; The location data of the regional screen markers in the multi-angle area are retrieved, and combined with the specific location information of the regional positioning cleaning robot with the location of the markers as the reference point, the specific location information of the cleaning robot in the multi-angle area is obtained.

8. The operating method of the intelligent robot control system based on big data according to claim 7 is characterized in that: The step of judging whether the current individual garbage model can be cleaned by a garbage cleaner includes: Retrieving the cleanable garbage model data set by the robot cleaning end, wherein the cleanable garbage model data includes the maximum height, maximum width, maximum length and flexibility information of the garbage that can be cleaned by the robot cleaning end; Using computer vision technology to analyze junk image data, including object detection, image segmentation, and feature extraction technology, wherein analyzing junk in image data is achieved through a deep learning model; Collect at least N labeled image data for building the garbage monitoring AI algorithm, including garbage items of various types and states, where N is the minimum number of labeled image data for training; The system obtains the image information, identifies the overlapping garbage in the image information, analyzes and determines whether the garbage is overlapping, compares the current garbage information with the garbage feature information in the database in real time, decomposes the accumulated image information with garbage features, obtains the individual garbage model in the overlapping garbage, and compares the parameters of the individual garbage model with the cleanable garbage data in the cleanable garbage model data, determines whether the current individual garbage model can be cleaned by the garbage cleaner, and if so, outputs a cleanable instruction.

9. The operating method of the intelligent robot control system based on big data according to claim 8 is characterized in that: The statistics of the amount of garbage generated by the area transformation of a single target cleaning area under the influence of wind include: Retrieve the current multi-angle regional wind level data in real time, obtain the wind level as Q, and obtain the comprehensive average wind speed in the multi-angle region as A through the wind level data; A quality assessment model for cleanable garbage is constructed based on the cleanable garbage data in the cleanable garbage model data, and the qualities of cleanable garbage in a single target cleaning area are obtained in sequence, namely M1, M2, ..., M c , then the total amount of garbage that can be cleaned up is F = M1 + M2...M c , count the amount of cleanable garbage generated by the area transformation of a single target cleaning area under the influence of wind Where c is the statistical number of times the mass of cleanable garbage is counted within the statistical time period, λ is the unit conversion parameter, and μ is the robot cleaning limit value for the amount of cleanable garbage accumulation in the multi-angle area.

10. The operating method of the intelligent robot control system based on big data according to claim 9, characterized in that: The cleaning of the target cleaning area includes: When it is detected that garbage enters other target cleaning areas different from the target cleaning area where the cleaning robot is located, the target cleaning area with the smallest amount of garbage generated in the multi-angle area is counted, and after the statistical time period ends, the robot drives to the target cleaning area with the smallest amount of garbage generated in the area transformation to clean the garbage; According to the information of garbage volume generated by regional transformation during the statistical time period, the accumulation amount of garbage near the target cleaning under the condition of low wind force is calculated S=K1+K2...K G When it is detected that S>S1 and the average wind level in the statistical time period is less than 3, the information prompting the staff to maintain the multi-angle area will be output to the mobile terminal carried by the staff, where S1 is the maximum manual cleaning limit value of garbage accumulation in the multi-angle area.

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