A collaborative control system based on smart home and smart service robot

Abstract

The present invention discloses a collaborative control system based on a smart home and a smart service robot, which relates to the technical field of collaborative control and comprises an information input module, a robot positioning module, a path recognition module, an obstacle recognition module, a signal interference recognition module, a robot movement path planning module and a task receiving module. The collaborative control system based on the smart home and the smart service robot can obtain signal penetration interference information corresponding to obstacles of different shapes and materials according to obstacle shape information data and obstacle material information data through the setting of the obstacle recognition module, and perform targeted signal penetration performance calculation. Meanwhile, the setting of the robot movement path planning module can ensure that, under the condition of ensuring signal transmission strength when sending a smart home control signal, the signal communication distance is minimized, thereby reducing the movement distance of the smart service robot and increasing the working efficiency of the smart service robot.

Description

Technical Field

[0001] The present invention relates to the field of collaborative control technology, and in particular to a collaborative control system based on smart homes and smart service robots. Background Art

[0002] In recent years, with the development of communication technology, intelligent technology, and mobile Internet technology, smart home has become the inevitable direction of future home and residential development, and home service robots will become an important device. However, most of the existing home service robots do not have the function of controlling the home environment. Even if they do, they are only simple mechanical controls, lacking autonomy and intelligence. In addition, smart home devices are often scattered in different spaces in the room, requiring wiring and construction. Although some devices can be wirelessly remotely controlled through wireless transmission and sensing technology, these devices are not compatible and cannot be coordinated with each other.

[0003] At present, the existing collaborative work control system receives the smart home control signal through the intelligent service robot first, and then sends the control signal to the smart home during use. However, different smart homes receive control signals with different frequencies, which leads to interference between signals during the transmission of different control signals. At the same time, due to the different control signal receiving distances of different smart homes, the work order of the intelligent service robot is not arranged reasonably during the work process, thereby reducing the work efficiency of the intelligent service robot. Summary of the invention

[0004] The purpose of the present invention is to provide a collaborative control system based on smart home and smart service robot to solve the above-mentioned deficiencies in the prior art.

[0005] In order to achieve the above-mentioned purpose, the present invention provides the following technical solutions: a collaborative control system based on smart home and smart service robot, including an information input module, a robot positioning module, a path recognition module, an obstacle recognition module, a signal interference recognition module, a robot movement path planning module, and a task receiving module, characterized in that:

[0006] The information input module is used to input the intelligent service robot information and the smart home information corresponding to the multiple smart homes, wherein the smart home information includes the smart home location information, the smart home control signal receiving frequency, the smart home control signal wall attenuation information and the smart home control signal receiving distance;

[0007] The task receiving module is arranged inside the signal receiving module of the intelligent service robot, and is used to receive the control signal for the smart home sent by the user;

[0008] The robot positioning module is used to locate the position of the intelligent service robot at home in real time through the GPS positioning model, and send the position information of the intelligent service robot to the path recognition module and the robot movement path planning module;

[0009] The path recognition module is used to calculate the moving path of the intelligent service robot from each smart home through a path calculation model based on the position information of the intelligent service robot located by the robot positioning module and the position information of the smart home recorded by the information recording module;

[0010] The obstacle recognition module is used to identify the obstacle information between the intelligent service robot and the smart home in real time through the obstacle recognition model, and calculate the penetration interference of the obstacle to the smart home control signal, wherein the obstacle information includes obstacle shape information and obstacle material information;

[0011] The signal interference recognition module is used to recognize the signal interference in the transmission process of the smart home control signal based on the obstacle information recognized by the obstacle recognition module and the smart home information corresponding to the multiple smart homes entered by the information entry module, and transmit the recognition result to the robot movement path planning module;

[0012] The robot mobile path planning module is used to plan the robot movement path based on the signal interference identified by the signal interference identification module, the real-time positioning of the intelligent service robot determined by the robot positioning module, the smart home information corresponding to the smart home entered by the information entry module, and the distance between the intelligent service robot and each smart home identified by the path identification module, and through the robot path planning model.

[0013] Furthermore, the obstacle recognition module includes:

[0014] An infrared information acquisition module, which is used to detect infrared detection information of obstacles encountered by the intelligent service robot during movement through an infrared detection device, and determine obstacle material information data corresponding to the infrared detection information based on network data and a data matching model;

[0015] A three-dimensional information scanning module, which is used to scan the shape information data of obstacles encountered by the intelligent service robot during movement based on a three-dimensional laser scanner;

[0016] A signal penetration calculation module is used to capture signal penetration parameters of different object materials in network information based on the obstacle material information data collected by the infrared information collection module and the obstacle shape information data scanned by the three-dimensional information scanning module through a data capture model, and convolve the captured signal penetration parameters with the obstacle shape information data scanned by the three-dimensional information scanning module, so as to obtain signal penetration interference information corresponding to obstacles of different shapes and materials.

[0017] Furthermore, the signal interference identification module includes:

[0018] A signal classification module, wherein the signal classification module is used to classify signals that can be interfered with among the multiple smart home control signals as interference signals based on the signal classification model, and the signal classification module is also used to classify signals that cannot be interfered with among the multiple smart home control signals as anti-interference signals;

[0019] A data selection module, wherein the data selection module is used to randomly select a smart home control signal A classified as an interference signal in the signal classification module,

[0020] A signal interference analysis model, wherein the signal interference analysis model is used to analyze the interference between other smart home control signals and the smart home control signal A through the interference analysis model.

[0021] Furthermore, the signal interference identification module includes the following working steps:

[0022] A1, receiving the smart home control signal receiving frequency, smart home control signal wall attenuation information and smart home control signal receiving distance in the smart home information entered by the receiving information entry module;

[0023] A2, receiving the interference of each obstacle on signal penetration calculated by the obstacle recognition module;

[0024] A3, based on the signal classification model, classifying the signals that can be interfered with among the multiple smart home control signals as interference signals, and classifying the signals that cannot be interfered with among the multiple smart home control signals as anti-interference signals;

[0025] A4, randomly selecting the smart home control signal A classified as the interference signal in step A3, and analyzing the interference between other smart home control signals and the smart home control signal A through the interference analysis model.

[0026] Furthermore, the robot movement path planning module includes:

[0027] A data association module, based on a data association model, performs data association on the distance between the intelligent service robot and each smart home identified by the path identification module and the signal penetration interference information identified by the signal interference identification module to obtain the signal penetration interference information at different distances from the smart home;

[0028] The data convolution module performs convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in the data association module to obtain the signal penetration strength ranking data at different distances under the condition of signal mutual interference;

[0029] A data selection module selects the distance of signal penetration strength of different signals in the data convolution module as the sending point of the smart home control signal through a data selection model;

[0030] The data matching module matches the smart home control signal sending points selected in the data selection module with the moving path identified by the path identification module based on the data matching model, and corrects the smart home control signal sending points that do not match the matching results based on the data correction model to ensure that all smart home control signal sending points are located on the moving path identified by the path identification module.

[0031] Furthermore, the robot movement path planning module includes the following working steps:

[0032] B1, based on the data association model, the distance between the intelligent service robot and each smart home identified by the path identification module and the signal penetration interference information identified by the signal interference identification module are data associated to obtain the signal penetration interference information at different distances from the smart home;

[0033] B2, sorting the signal penetration interference information obtained in step B1 based on the interference degree, thereby obtaining the control signal penetration strength ranking data for controlling the smart home;

[0034] B3, performing convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in step B2, to obtain signal penetration strength ranking data at different distances under the condition of signal mutual interference;

[0035] B4, selecting the distances of the signal penetration strengths of different signals in step B3 as the sending points of the smart home control signal through a data selection model, wherein the selection criterion of the data selection model is the principle of minimizing the sum of the distances of the signal penetration strengths of different signals;

[0036] B5, matching the smart home control signal sending point selected in step B4 with the moving path identified by the path identification module based on the data matching model, and correcting the smart home control signal sending point with inconsistent matching results based on the data correction model, to ensure that all smart home control signal sending points are located on the moving path identified by the path identification module;

[0037] B6, performing path planning for the smart home control signal sending point corrected in step B5 through a path planning model.

[0038] Further, the following working steps are included:

[0039] S1, inputting the information of the intelligent service robot and the smart home information corresponding to multiple smart homes;

[0040] S2, the intelligent service robot receives the control signal for the smart home sent by the user through the internal task receiving module;

[0041] S3, real-time positioning of the intelligent service robot at home through the GPS positioning model;

[0042] S4, based on the position information of the intelligent service robot located by the robot positioning module and the position information of the smart home recorded by the information recording module, the moving path of the intelligent service robot from each smart home is calculated by a path calculation model;

[0043] S5, using an obstacle recognition model to identify in real time obstacle information between the intelligent service robot and the smart home and signal penetration interference information corresponding to obstacles of different shapes and materials;

[0044] S6, analyzing interference between other smart home control signals and the smart home control signal A through a signal interference identification module;

[0045] S7, performing convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in the robot movement path planning module, to obtain signal penetration strength ranking data at different distances under the condition of signal mutual interference;

[0046] S8, selecting the distance of the signal penetration strength of different signals in step S7 as the sending point of the smart home control signal through the data selection model;

[0047] S9, matching the smart home control signal sending point selected in step S8 with the moving path identified by the path identification module based on the data matching model;

[0048] S10, performing path planning on the smart home control signal sending point corrected in step B5 through a path planning model.

[0049] Compared with the prior art, the collaborative control system based on smart home and smart service robot provided by the present invention can obtain signal penetration interference information corresponding to obstacles of different shapes and materials according to obstacle shape information data and obstacle material information data through the setting of obstacle recognition module, and perform targeted signal penetration performance calculation. At the same time, through the setting of robot movement path planning module, it can ensure that when sending smart home control signals, the signal communication distance is minimized under the condition of ensuring signal transmission strength, thereby reducing the moving distance of the smart service robot and increasing the working efficiency of the smart service robot. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0051] Figure 1 A system structure block diagram provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0052] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings.

[0053] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0054] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0055] Example embodiments will be described more fully below with reference to the accompanying drawings, but the example embodiments may be embodied in different forms and should not be construed as limited to the embodiments set forth herein. On the contrary, the purpose of providing these embodiments is to make the present disclosure thorough and complete and to enable those skilled in the art to fully understand the scope of the present disclosure.

[0056] In the absence of conflict, the various embodiments of the present disclosure and the various features therein may be combined with each other.

[0057] As used herein, the term "and / or" includes any and all combinations of one or more of the associated listed items.

[0058] The terms used herein are only used to describe specific embodiments and are not intended to limit the present disclosure. As used herein, the singular forms "a", "an" and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will also be understood that when the terms "comprising" and / or "made of" are used in this specification, the presence of the features, wholes, steps, operations, elements and / or components is specified, but the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof is not excluded.

[0059] The embodiments described herein may be described with reference to plan views and / or cross-sectional views by means of idealized schematic diagrams of the present disclosure. Therefore, the example illustrations may be modified according to manufacturing techniques and / or tolerances. Therefore, the embodiments are not limited to the embodiments shown in the accompanying drawings, but include modifications of the configurations formed based on the manufacturing process. Therefore, the regions illustrated in the accompanying drawings have schematic properties, and the shapes of the regions shown in the figures illustrate the specific shapes of the regions of the elements, but are not intended to be limiting.

[0060] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those of ordinary skill in the art. It will also be understood that terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and the present disclosure, and will not be interpreted as having an idealized or overly formal meaning unless explicitly defined as such herein.

[0061] See also Figure 1 A collaborative control system based on smart home and smart service robots, including an information input module, a robot positioning module, a path recognition module, an obstacle recognition module, a signal interference recognition module, a robot movement path planning module, and a task receiving module, characterized in that:

[0062] The information input module is used to input the intelligent service robot information and the smart home information corresponding to multiple smart homes, the smart home information includes the smart home location information, the smart home control signal receiving frequency, the smart home control signal wall attenuation information and the smart home control signal receiving distance;

[0063] The task receiving module is arranged inside the signal receiving module of the intelligent service robot, and is used to receive the control signal for the smart home sent by the user;

[0064] The robot positioning module is used to locate the position of the intelligent service robot at home in real time through the GPS positioning model, and send the position information of the intelligent service robot to the path recognition module and the robot movement path planning module;

[0065] The path recognition module is used to calculate the moving path of the intelligent service robot from each smart home based on the location information of the intelligent service robot located by the robot positioning module and the location information of the smart home recorded by the information recording module, and through the path calculation model;

[0066] The obstacle recognition module is used to identify the obstacle information between the intelligent service robot and the smart home in real time through the obstacle recognition model, and calculate the penetration interference of the obstacle to the smart home control signal. The obstacle information includes obstacle shape information and obstacle material information;

[0067] The signal interference recognition module is used to recognize the signal interference in the transmission process of the smart home control signal based on the obstacle information recognized by the obstacle recognition module and the smart home information corresponding to the multiple smart homes entered by the information entry module, and transmit the recognition result to the robot movement path planning module;

[0068] The robot mobile path planning module is used to plan the robot's motion path based on the signal interference identified by the signal interference recognition module, the real-time positioning of the intelligent service robot determined by the robot positioning module, the smart home information corresponding to the smart home entered by the information entry module, and the distance between the intelligent service robot and each smart home identified by the path recognition module, and through the robot path planning model.

[0069] The obstacle recognition module includes:

[0070] The infrared information acquisition module is used to detect the infrared detection information of obstacles encountered by the intelligent service robot during movement through an infrared detection device, and determine the obstacle material information data corresponding to the infrared detection information based on network data and a data matching model;

[0071] A three-dimensional information scanning module is used to scan the shape information data of obstacles encountered by the intelligent service robot during movement based on a three-dimensional laser scanner;

[0072] The signal penetration calculation module is used to capture the signal penetration parameters of different object materials in the network information based on the obstacle material information data collected by the infrared information acquisition module and the obstacle shape information data scanned by the three-dimensional information scanning module through the data capture model, and convolve the captured signal penetration parameters with the obstacle shape information data scanned by the three-dimensional information scanning module, so as to obtain the signal penetration interference information corresponding to obstacles of different shapes and materials.

[0073] This setting can obtain the signal penetration interference information corresponding to obstacles of different shapes and materials based on the obstacle shape information data and the obstacle material information data. At the same time, this setting can ensure real-time calculation of the interference of the same obstacle on signal penetration at different angles during the movement of the intelligent service robot.

[0074] The signal interference identification module includes:

[0075] A signal classification module, the signal classification module is used to classify the signals that can be interfered with in the multiple smart home control signals as interference signals based on the signal classification model, and the signal classification module is also used to classify the signals that cannot be interfered with in the multiple smart home control signals as anti-interference signals;

[0076] The data selection module is used to randomly select the smart home control signal A classified as an interference signal in the signal classification module.

[0077] The signal interference analysis model is used to analyze the interference between other smart home control signals and the smart home control signal A through the interference analysis model.

[0078] The signal interference identification module includes the following working steps:

[0079] A1, receiving the smart home control signal receiving frequency, smart home control signal wall attenuation information and smart home control signal receiving distance in the smart home information entered by the receiving information entry module;

[0080] A2, receiving the interference of each obstacle on signal penetration calculated by the obstacle recognition module;

[0081] A3, based on the signal classification model, classifying the signals that can be interfered with among the multiple smart home control signals as interference signals, and classifying the signals that cannot be interfered with among the multiple smart home control signals as anti-interference signals;

[0082] A4, randomly selecting the smart home control signal A classified as the interference signal in step A3, and analyzing the interference between other smart home control signals and the smart home control signal A through the interference analysis model.

[0083] The robot mobile path planning module includes:

[0084] A data association module, based on a data association model, performs data association on the distance between the intelligent service robot and each smart home identified by the path identification module and the signal penetration interference information identified by the signal interference identification module to obtain the signal penetration interference information at different distances from the smart home;

[0085] The data convolution module performs convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in the data association module to obtain the signal penetration strength ranking data at different distances under the condition of signal mutual interference;

[0086] A data selection module selects the distance of signal penetration strength of different signals in the data convolution module as the sending point of the smart home control signal through a data selection model;

[0087] The data matching module matches the smart home control signal sending points selected in the data selection module with the moving path identified by the path identification module based on the data matching model, and corrects the smart home control signal sending points that do not match the matching results based on the data correction model to ensure that all smart home control signal sending points are located on the moving path identified by the path identification module.

[0088] The robot movement path planning module includes the following working steps:

[0089] B1, based on the data association model, the distance between the intelligent service robot and each smart home identified by the path identification module and the signal penetration interference information identified by the signal interference identification module are data associated to obtain the signal penetration interference information at different distances from the smart home;

[0090] B2, sorting the signal penetration interference information obtained in step B1 based on the interference degree, thereby obtaining the control signal penetration strength ranking data for controlling the smart home;

[0091] B3, performing convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in step B2, to obtain signal penetration strength ranking data at different distances under the condition of signal mutual interference;

[0092] B4, selecting the distances of the signal penetration strengths of different signals in step B3 as the sending points of the smart home control signal through a data selection model, wherein the selection criterion of the data selection model is the principle of minimizing the sum of the distances of the signal penetration strengths of different signals;

[0093] B5, matching the smart home control signal sending point selected in step B4 with the moving path identified by the path identification module based on the data matching model, and correcting the smart home control signal sending point with inconsistent matching results based on the data correction model, to ensure that all smart home control signal sending points are located on the moving path identified by the path identification module;

[0094] B6, performing path planning for the smart home control signal sending point corrected in step B5 through a path planning model.

[0095] The following steps are included:

[0096] S1, inputting the information of the intelligent service robot and the smart home information corresponding to multiple smart homes;

[0097] S2, the intelligent service robot receives the control signal for the smart home sent by the user through the internal task receiving module;

[0098] S3, real-time positioning of the intelligent service robot at home through the GPS positioning model;

[0099] S4, based on the position information of the intelligent service robot located by the robot positioning module and the position information of the smart home recorded by the information recording module, the moving path of the intelligent service robot from each smart home is calculated by a path calculation model;

[0100] S5, using an obstacle recognition model to identify in real time obstacle information between the intelligent service robot and the smart home and signal penetration interference information corresponding to obstacles of different shapes and materials;

[0101] S6, analyzing interference between other smart home control signals and the smart home control signal A through a signal interference identification module;

[0102] S7, performing convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in the robot movement path planning module, to obtain signal penetration strength ranking data at different distances under the condition of signal mutual interference;

[0103] S8, selecting the distance of the signal penetration strength of different signals in step S7 as the sending point of the smart home control signal through the data selection model;

[0104] S9, matching the smart home control signal sending point selected in step S8 with the moving path identified by the path identification module based on the data matching model;

[0105] S10, performing path planning on the smart home control signal sending point corrected in step B5 through a path planning model.

[0106] The above description is only by way of illustration of certain exemplary embodiments of the present invention. It is undoubted that those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. A collaborative control system based on smart home and smart service robots, including an information input module, a robot positioning module, a path recognition module, an obstacle recognition module, a signal interference recognition module, a robot movement path planning module, and a task receiving module, characterized in that: The information input module is used to input the intelligent service robot information and the smart home information corresponding to the multiple smart homes, wherein the smart home information includes the smart home location information, the smart home control signal receiving frequency, the smart home control signal wall attenuation information and the smart home control signal receiving distance; The task receiving module is arranged inside the signal receiving module of the intelligent service robot, and is used to receive the control signal for the smart home sent by the user; The robot positioning module is used to locate the position of the intelligent service robot at home in real time through the GPS positioning model, and send the position information of the intelligent service robot to the path recognition module and the robot movement path planning module; The path recognition module is used to calculate the moving path of the intelligent service robot from each smart home through a path calculation model based on the position information of the intelligent service robot located by the robot positioning module and the position information of the smart home recorded by the information recording module; The obstacle recognition module is used to recognize obstacle information between the intelligent service robot and the smart home in real time through an obstacle recognition model, and calculate the penetration interference of obstacles on the smart home control signal, and calculate the penetration interference of obstacles on the smart home control signal, the obstacle information includes obstacle shape information and obstacle material information, the obstacle recognition module includes an infrared information acquisition module, a three-dimensional information scanning module and a signal penetration calculation module, the infrared information acquisition module is used to detect infrared detection information of obstacles encountered by the intelligent service robot during movement through an infrared detection device, and judge obstacle material information data corresponding to the infrared detection information based on network data and a data matching model, the three-dimensional information scanning module is used to scan obstacle shape information data encountered by the intelligent service robot during movement based on a three-dimensional laser scanner, the signal penetration calculation module is used to capture signal penetration parameters of different material materials in network information through a data capture model based on the obstacle material information data collected by the infrared information acquisition module and the obstacle shape information data scanned by the three-dimensional information scanning module, and perform convolution calculation on the captured signal penetration parameters and the obstacle shape information data scanned by the three-dimensional information scanning module, so as to obtain signal penetration interference information corresponding to obstacles of different shapes and materials; The signal interference recognition module is used to recognize the signal interference in the transmission process of the smart home control signal based on the obstacle information recognized by the obstacle recognition module and the smart home information corresponding to the multiple smart homes entered by the information entry module, and transmit the recognition result to the robot movement path planning module; The robot movement path planning module is used to plan the robot movement path through the robot path planning model based on the signal interference identified by the signal interference identification module, the real-time positioning of the intelligent service robot determined by the robot positioning module, the smart home information corresponding to the smart home entered by the information entry module, and the distance between the intelligent service robot and each smart home identified by the path identification module. The robot movement path planning module includes: A data association module, based on a data association model, performs data association on the distance between the intelligent service robot and each smart home identified by the path identification module and the signal penetration interference information identified by the signal interference identification module to obtain the signal penetration interference information at different distances from the smart home; The data convolution module performs convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in the data association module to obtain the signal penetration strength ranking data at different distances under the condition of signal mutual interference; A data selection module selects the distance of signal penetration strength of different signals in the data convolution module as the sending point of the smart home control signal through a data selection model; The data matching module matches the smart home control signal sending points selected in the data selection module with the moving path identified by the path identification module based on the data matching model, and corrects the smart home control signal sending points that do not match the matching results based on the data correction model to ensure that all smart home control signal sending points are located on the moving path identified by the path identification module.

2. A collaborative control system based on smart home and smart service robot according to claim 1, characterized in that: The signal interference identification module includes: A signal classification module, wherein the signal classification module is used to classify signals that can be interfered with among the multiple smart home control signals as interference signals based on the signal classification model, and the signal classification module is also used to classify signals that cannot be interfered with among the multiple smart home control signals as anti-interference signals; A data selection module, wherein the data selection module is used to randomly select a smart home control signal A classified as an interference signal in the signal classification module, A signal interference analysis model, wherein the signal interference analysis model is used to analyze the interference between other smart home control signals and the smart home control signal A through the interference analysis model.

3. The collaborative control system based on smart home and smart service robot according to claim 1, characterized in that: The signal interference identification module includes the following working steps: A1, receiving the smart home control signal receiving frequency, smart home control signal wall attenuation information and smart home control signal receiving distance in the smart home information entered by the receiving information entry module; A2, receiving the interference of each obstacle on signal penetration calculated by the obstacle recognition module; A3, based on the signal classification model, classifying the signals that can be interfered with among the multiple smart home control signals as interference signals, and classifying the signals that cannot be interfered with among the multiple smart home control signals as anti-interference signals; A4, randomly selecting the smart home control signal A classified as the interference signal in step A3, and analyzing the interference between other smart home control signals and the smart home control signal A through the interference analysis model.

4. A collaborative control system based on smart home and smart service robot according to claim 3, characterized in that: The robot movement path planning module includes the following working steps: B1, based on the data association model, the distance between the intelligent service robot and each smart home identified by the path identification module and the signal penetration interference information identified by the signal interference identification module are data associated to obtain the signal penetration interference information at different distances from the smart home; B2, sorting the signal penetration interference information obtained in step B1 based on the interference degree, thereby obtaining the control signal penetration strength ranking data for controlling the smart home; B3, performing convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in step B2, to obtain signal penetration strength ranking data at different distances under the condition of signal mutual interference; B4, selecting the distances of the signal penetration strengths of different signals in step B3 as the sending points of the smart home control signal through a data selection model, wherein the selection criterion of the data selection model is the principle of minimizing the sum of the distances of the signal penetration strengths of different signals; B5, matching the smart home control signal sending point selected in step B4 with the moving path identified by the path identification module based on the data matching model, and correcting the smart home control signal sending point with inconsistent matching results based on the data correction model, to ensure that all smart home control signal sending points are located on the moving path identified by the path identification module; B6, performing path planning for the smart home control signal sending point corrected in step B5 through a path planning model.

5. A collaborative control system based on smart home and smart service robot according to claim 4, characterized in that: The following steps are included: S1, inputting the information of the intelligent service robot and the smart home information corresponding to multiple smart homes; S2, the intelligent service robot receives the control signal for the smart home sent by the user through the internal task receiving module; S3, real-time positioning of the intelligent service robot at home through the GPS positioning model; S4, based on the position information of the intelligent service robot located by the robot positioning module and the position information of the smart home recorded by the information recording module, the moving path of the intelligent service robot from each smart home is calculated by a path calculation model; S5, using an obstacle recognition model to identify in real time obstacle information between the intelligent service robot and the smart home and signal penetration interference information corresponding to obstacles of different shapes and materials; S6, analyzing interference between other smart home control signals and the smart home control signal A through a signal interference identification module; S7, performing convolution calculation on the interference information of other smart home control signals identified by the signal interference identification module and the smart home control signal A and the control signal control strength ranking data obtained in the robot movement path planning module, to obtain signal penetration strength ranking data at different distances under the condition of signal mutual interference; S8, selecting the distance of the signal penetration strength of different signals in step S7 as the sending point of the smart home control signal through the data selection model; S9, matching the smart home control signal sending point selected in step S8 with the moving path identified by the path identification module based on the data matching model; S10, performing path planning on the smart home control signal sending point corrected in step B5 through a path planning model.

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