CN114643588A

CN114643588A - Control method, system and medium for autonomous mobile disinfection robot

Info

Publication number: CN114643588A
Application number: CN202210541187.0A
Authority: CN
Inventors: 吴继盛; 陈剑清; 贾睿; 余柯馨
Original assignee: Ruichi Shenzhen Intelligent Co ltd
Current assignee: Ruichi Shenzhen Intelligent Co ltd
Priority date: 2022-05-19
Filing date: 2022-05-19
Publication date: 2022-06-21
Anticipated expiration: 2042-05-19
Also published as: CN114643588B

Abstract

The invention relates to a control method, a system and a medium of an autonomous mobile disinfection robot, relating to the technical field of intelligent control of disinfection robots.A first disinfection range model diagram is established based on image information which is preprocessed and can be recognized by the robot; obtaining a target point cloud data coordinate number set according to the first disinfection range model diagram, and establishing a second disinfection range model diagram based on the target point cloud data number set; the second disinfection range model graph is used for disinfecting the target object, so that a redundant disinfection range with a larger range possibly existing due to different shooting angles of the cameras is avoided, the disinfection robot can correctly use the disinfectant and correctly correct the disinfection range, and the disinfection repeated operation range is greatly reduced; on the other hand, the invention disinfects the target object in a preset disinfection mode through the actual scene, so that the disinfection mode of the autonomous mobile disinfection robot is more reasonable.

Description

Control method, system and medium for autonomous mobile disinfection robot

Technical Field

The invention relates to the technical field of disinfection robot control, in particular to a control method, a system and a medium for an autonomous mobile disinfection robot.

Background

The traditional disinfection mode adopts the alcohol and the disinfectant to be sprayed on the spot of a public place by medical staff or disinfection staff wearing protective clothing, but the traditional disinfection mode has the defects that firstly, the disinfection staff frequently disinfect in the public place, the personnel gathering degree is increased, the risk of virus infection of the staff is increased, and the personal safety of disinfection and epidemic prevention staff cannot be ensured; secondly, the labor cost is invisibly increased, a large number of workers are inevitably needed to perform disinfection operation aiming at the areas with dense people flows, and more human resources are inevitably occupied by using the traditional manual disinfection; thirdly, the manual disinfection is greatly influenced by human factors, the disinfection quality cannot be guaranteed practically, the disinfectant is sprayed unevenly, and the situations that partial areas are not disinfected or disinfected incompletely, the disinfectant is wasted due to excessive disinfection of partial areas and the like are easy to occur. The intelligent disinfection approach is to adopt the intelligent epidemic prevention disinfection robot to spray the disinfection solution in public places including dense people areas such as hospitals, railway stations, airports, subways and schools, so as to carry out the intelligent and unmanned epidemic prevention disinfection work.

Nowadays, the disinfection robot also has many problems which are still not solved, such as that due to different angles of the target in the camera view field, a large-range redundancy may exist in the enclosure, so that the redundancy of the disinfection range is too large, partial disinfection liquid is wasted, and the disinfection efficiency is reduced. As in the prior art, the main target in the field cannot be disinfected according to the actual field situation, so that the risk factor of infecting bacteria in people is increased.

Disclosure of Invention

The invention overcomes the defects of the prior art and provides a control method, a system and a medium of an autonomous mobile disinfection robot.

In order to achieve the purpose, the invention adopts the technical scheme that:

the invention provides a control method of an autonomous mobile disinfection robot, which comprises the following steps:

acquiring video frame information within preset time, establishing a behavior recognition model to recognize the video frame information to obtain a recognition result, and judging whether the recognition result is a preset recognition result;

if the identification result is a preset identification result, acquiring image information of the target object within preset time, preprocessing the image information to obtain preprocessed image information, and establishing a first disinfection range model diagram based on the preprocessed image information;

obtaining a target point cloud data coordinate number set according to the first disinfection range model diagram, and establishing a second disinfection range model diagram based on the target point cloud data number set;

and generating a disinfection path diagram of the autonomous mobile disinfection robot based on the second disinfection range model diagram, and transmitting the disinfection path diagram to the control terminal of the autonomous mobile disinfection robot.

Further, in a preferred embodiment of the present invention, the establishing a behavior recognition model to recognize the video frame information to obtain a recognition result, and determining whether the recognition result is a preset recognition result includes the following steps:

establishing a behavior recognition model, and importing pre-trained preset behavior video frame information into the behavior recognition model for training to obtain a trained behavior recognition model;

importing the video frame information within the preset time into the behavior recognition model for recognition to obtain a recognition result;

and judging whether the identification result is a preset identification result.

Further, in a preferred embodiment of the present invention, the preprocessing the image information to obtain the preprocessed image information specifically includes the following steps:

denoising and image enhancement processing are carried out on the image information, information characteristic points of the image information are extracted, and sparse characteristic points are obtained through characteristic point matching;

acquiring coordinate information of the sparse feature points, and generating sparse three-dimensional point cloud data of an area to be disinfected based on the coordinate information of the sparse feature points;

and performing dense extraction according to the sparse three-dimensional point cloud data to obtain dense three-dimensional point cloud data, and establishing a fuzzy disinfection area range matrix of an area to be disinfected based on the dense three-dimensional point cloud data to obtain a first disinfection range model diagram.

Further, in a preferred embodiment of the present invention, a coordinate number set of target point cloud data is obtained according to the first disinfection range model map, and a second disinfection range model map is established based on the coordinate number set of target point cloud data, which specifically includes the following steps:

establishing a characteristic vector decomposition model, and introducing the first disinfection range model diagram into the characteristic vector decomposition model for characteristic vector decomposition to obtain an orthogonal matrix formed by characteristic vectors according to the groups and a diagonal matrix formed by the characteristic vectors;

selecting an orthogonal matrix formed by the characteristic vectors according to the columns and a limit characteristic vector in a diagonal matrix formed by the characteristic vectors as a construction reference point, and constructing a new coordinate system based on the construction reference point;

importing the feature vectors in an orthogonal matrix formed by the feature vectors according to the columns and a diagonal matrix formed by the feature vectors into the new coordinate system to generate a target point cloud data matrix, and taking the target point cloud data matrix as a target point cloud data coordinate set;

and acquiring a limit coordinate point number set in the target point cloud data coordinate number set, importing the limit coordinate point number set into a world coordinate system, and recombining the limit coordinate point number set in the world coordinate system to generate a second disinfection range model diagram.

Further, in a preferred embodiment of the present invention, the generating a disinfection path map of the autonomous mobile disinfection robot based on the second disinfection range model map specifically includes the following steps:

acquiring a working area range of the current autonomous mobile disinfection robot during single disinfection, and dividing the second disinfection range model diagram into a plurality of disinfection area ranges by taking the working area range as a reference to generate a plurality of disinfection area sub-ranges;

calculating a plurality of disinfection position points based on the working area range and the disinfection area sub-range, generating one or more disinfection path diagrams based on the disinfection position points, and acquiring path values of the disinfection path diagrams;

establishing a sequencing table, and leading the path map of the disinfection path map into the sequencing table to obtain the disinfection path map with the minimum path value;

and outputting the disinfection path diagram of the minimum path value as a disinfection path diagram of the final autonomous mobile disinfection robot.

Further, in a preferred embodiment of the present invention, the control method of the autonomous mobile sterilization robot further includes the following steps:

acquiring the number of people streams in a target preset area range within preset time, and judging whether the number of people streams is greater than the preset number of people streams or not;

if so, retrieving the target object in the preset area range, and acquiring the number of times that the target object is touched;

presetting a disinfection mode, and judging whether the number of times that the target object is touched is greater than a preset number of times;

and if so, disinfecting the target object according to a preset disinfection mode by the autonomous mobile disinfection robot according to the number of times that the target object is touched.

A second aspect of the present invention provides a control system of an autonomous mobile sterilization robot, the control system of the autonomous mobile sterilization robot including a memory and a processor, the memory including a control method of the autonomous mobile sterilization robot, the control method of the autonomous mobile sterilization robot being implemented by the processor as follows:

A third aspect of the present invention provides a computer-readable storage medium containing a control method program of an autonomous mobile disinfecting robot, which when executed by a processor, implements the steps of any one of the control methods of the autonomous mobile disinfecting robot.

The invention solves the defects in the background technology, and has the following beneficial effects:

according to the method, video frame information in a preset time is obtained, a behavior recognition model is established to recognize the video frame information, a recognition result is obtained, and whether the recognition result is a preset recognition result is judged; if the identification result is a preset identification result, acquiring image information of the target object within preset time, preprocessing the image information to obtain preprocessed image information, and establishing a first disinfection range model diagram based on the preprocessed image information; obtaining a target point cloud data coordinate number set according to the first disinfection range model diagram, and establishing a second disinfection range model diagram based on the target point cloud data number set; generating a disinfection pathway map for the autonomous mobile disinfection robot based on the second disinfection range model map. The second disinfection range model graph is utilized to disinfect the target object, which is beneficial to avoiding the situation that a large-range redundant disinfection range possibly exists due to different shooting angles of the cameras, the disinfection robot corrects the disinfection range and saves the use of disinfectant, the disinfection redundancy is greatly reduced, and the disinfection efficiency is improved; on the other hand, the invention disinfects the target object in a preset disinfection mode through the actual scene, so that the disinfection mode of the autonomous mobile disinfection mobile robot is more reasonable.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings of the embodiments can be obtained according to the drawings without creative efforts.

Fig. 1 shows an overall method flow diagram of a control method of an autonomous mobile sterilization robot;

FIG. 2 illustrates a flow chart of a method of identifying video frame information;

FIG. 3 illustrates a flow chart of a method of obtaining a first disinfection range model map;

FIG. 4 illustrates a flow chart of a method of obtaining a second disinfection range model map;

FIG. 5 shows a flow chart of a method of generating a disinfection path;

FIG. 6 illustrates a second method flow diagram of a method of controlling an autonomous mobile sterilization robot;

fig. 7 shows a system block diagram of a control system of an autonomous mobile disinfecting robot.

Detailed Description

In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be further described in detail with reference to the accompanying drawings and the detailed description, wherein the drawings are simplified schematic drawings and only the basic structure of the present invention is illustrated schematically, so that only the structure related to the present invention is shown, and it is to be noted that the embodiments and features of the embodiments in the present application can be combined with each other without conflict.

In the description of the present application, it is to be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like are used in the orientation or positional relationship indicated in the drawings for convenience in describing the present application and for simplicity in description, and are not intended to indicate or imply that the referenced devices or elements must have a particular orientation, be constructed in a particular orientation, and be operated in a particular manner, and are not to be considered limiting of the scope of the present application. Furthermore, the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating a limited number of the technical features indicated. "first" means the originally created meaning and "second" means the meaning deriving from a multitude of quantities. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the invention, the meaning of "a plurality" is two or more unless otherwise specified.

In the description of the present application, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art through specific situations.

To facilitate an understanding of the invention, the invention will now be described more fully with reference to the accompanying drawings. Preferred embodiments of the present invention are shown in the drawings. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.

s102, acquiring video frame information within a preset time, establishing a behavior recognition model to recognize the video frame information to obtain a recognition result, and judging whether the recognition result is a preset recognition result;

s104, if the identification result is a preset identification result, acquiring image information of the target object within preset time, preprocessing the image information to obtain preprocessed image information, and establishing a first disinfection range model diagram based on the preprocessed image information;

s106, obtaining a target point cloud data coordinate number set according to the first disinfection range model diagram, and establishing a second disinfection range model diagram based on the target point cloud data coordinate number set;

and S108, generating a disinfection path diagram of the autonomous mobile disinfection robot based on the second disinfection range model diagram, and transmitting the disinfection path diagram to the control terminal of the autonomous mobile disinfection robot.

It should be noted that, the video frame information within the preset time is acquired by the camera, the preset result at least includes actions of sneezing, coughing and touching important objects, such as door handles, elevator buttons, armrests, tables and chairs, etc., and when the recognition result is the preset recognition result, the disinfection robot can acquire image information of the objects within the preset time from the cameras, the camera, etc. arranged in the environment, so as to preprocess the image.

s202, establishing a behavior recognition model, and importing pre-trained preset behavior video frame information into the behavior recognition model for training to obtain a trained behavior recognition model;

s204, importing the video frame information in the preset time into the behavior recognition model for recognition to obtain a recognition result;

and S206, judging whether the identification result is a preset identification result.

The behavior recognition model is built by using a convolutional neural network, a deep learning network, a machine learning method and the like, and the pre-trained preset behavior video frame information at least comprises behaviors of sneezing, coughing and touching important targets of the user. Thereby identifying the behavior in the video frame information by using the behavior identification model.

s302, denoising and image enhancement processing are carried out on the image information, information characteristic points of the image information are extracted, and sparse characteristic points are obtained through characteristic point matching;

s304, acquiring coordinate information of the sparse feature points, and generating sparse three-dimensional point cloud data of an area to be disinfected based on the coordinate information of the sparse feature points;

s306, performing dense extraction according to the sparse three-dimensional point cloud data to obtain dense three-dimensional point cloud data, and establishing a fuzzy disinfection area range matrix of an area to be disinfected based on the dense three-dimensional point cloud data to obtain a first disinfection range model map.

It should be noted that, the image may be processed in a manner of denoising, filtering, etc. by using a nonlinear filter, a median filter, a morphological filter, etc., and the dense three-dimensional point cloud data may be subjected to layered convolution and pooling by a convolutional neural network, thereby completing feature extraction of the image information, and establishing a fuzzy disinfection area range matrix of the area to be disinfected, which represents an initial disinfection area range established according to the image.

s402, establishing a characteristic vector decomposition model, and importing the first disinfection range model diagram into the characteristic vector decomposition model for characteristic vector decomposition to obtain an orthogonal matrix formed by characteristic vectors according to the groups and a diagonal matrix formed by the characteristic vectors;

s404, selecting an orthogonal matrix formed by the characteristic vectors according to the columns and a limit characteristic vector in a diagonal matrix formed by the characteristic vectors as a construction reference point, and constructing a new coordinate system based on the construction reference point;

s406, importing the feature vectors in an orthogonal matrix formed by the feature vectors according to the columns and a diagonal matrix formed by the feature vectors into the new coordinate system to generate a target point cloud data matrix, and taking the target point cloud data matrix as a target point cloud data coordinate set;

s408, acquiring a limit coordinate point number set in the target point cloud data coordinate number set, importing the limit coordinate point number set into a world coordinate system, recombining the limit coordinate point number set in the world coordinate system, and generating a second disinfection range model diagram.

It should be noted that the first disinfection range model map is decomposed by a decomposition method such as a spectrum decomposition method, a singular value feature decomposition method and the like, thereby obtaining an orthogonal matrix formed by the characteristic vectors according to the columns and a diagonal matrix formed by the characteristic vectors, selecting the characteristic vector of an extreme position in the orthogonal matrix and the diagonal matrix as a construction datum point, establishing a new coordinate system by using the reference point as a coordinate origin, introducing the feature vector of a limit position in the orthogonal matrix and the diagonal matrix after decomposition into the new coordinate system to form a new target point cloud data matrix, therefore, the range of the initial disinfection area can be reduced by using the mode to form a disinfection area with smaller range, by using the method, the disinfection efficiency can be improved, wherein in the decomposition process, the characteristic vector decomposition model comprises the following steps:

wherein Σ is a diagonal matrix after decomposition of the fuzzy disinfection area range matrix is utilized; m is a fuzzy disinfection area range matrix; k is an orthogonal matrix formed by the characteristic vectors in columns; l is a target point cloud data matrix;

it should be noted that the target point cloud data matrix is calculated in the above manner, a new coordinate system is established according to any limit eigenvector in the target point cloud data matrix, the eigenvector therein is subjected to point description, the sterilization range is reduced under the new coordinate system by calculating the eigenvector, and the optimized sterilization range has a plurality of limit position coordinate points under the new coordinate system, so that the coordinate points are reintegrated under the world coordinate system, the sterilization range is reduced, the sterilization range of the sterilization robot is smaller, the sterilization efficiency is improved, and the sterilization position points are more accurate.

FIG. 5 shows a flow chart of a method of generating a disinfection path;

s502, acquiring a working area range of the current autonomous mobile disinfection robot during single disinfection, and dividing the second disinfection range model diagram into a plurality of disinfection area ranges by taking the working area range as a reference to generate a plurality of disinfection area sub-ranges;

s504, calculating a plurality of disinfection position points based on the working area range and the disinfection area sub-range, generating one or more disinfection path diagrams based on the disinfection position points, and acquiring path values of the disinfection path diagrams;

s506, establishing a sorting table, and leading the path map of the disinfection path map into the sorting table to obtain the disinfection path map with the minimum path value;

and S508, outputting the disinfection path diagram of the minimum path value as a final disinfection path diagram of the autonomous mobile disinfection robot.

It should be noted that the working area range during single disinfection is arranged in the autonomous disinfection robot, so that disinfection points required to pass through during complete disinfection are calculated by using the disinfection range and the second disinfection range model diagram, one or more disinfection path diagrams can be planned according to the disinfection points through algorithms such as an ant colony algorithm and a genetic algorithm, one or more disinfection path diagrams are obtained, the disinfection path diagram with the minimum path value is selected to be output as the final disinfection path diagram of the autonomous mobile disinfection robot, and therefore the reduction of the disinfection path of the disinfection robot is facilitated, and the disinfection efficiency of the disinfection robot is improved.

s602, acquiring the number of people in a target preset area range within preset time, and judging whether the number of people is greater than the preset number of people;

s604, if the touch frequency is larger than the preset touch frequency, retrieving the target object in the preset area range, and acquiring the touch frequency of the target object;

s606, presetting a disinfection mode, and judging whether the number of times that the target object is touched is greater than the preset number of times;

and S608, if so, disinfecting the target object according to a preset disinfection mode by the autonomous mobile disinfection robot according to the number of times that the target object is touched.

It should be noted that, because the key object is contacted in a main mode causing personnel infection, the method can effectively reduce the virus infection rate in public places or working places, the preset disinfection mode can be used for disinfection according to the number of times that the object is touched, for example, a light disinfection mode is adopted in a certain touch number range, a heavy disinfection mode is adopted in another touch number range, and the like, so that the disinfection mode can be adjusted according to the actual condition when the autonomous mobile disinfection robot is disinfected by using the mode, and the disinfection is more reasonable.

In addition, the invention can also comprise disinfection index evaluation, which comprises the following steps:

constructing a disinfection evaluation index system, and extracting disinfection evaluation indexes according to the evaluation index system;

determining index score information of a disinfection mode according to the number of times that the target object is touched, and calculating weight information of the disinfection evaluation index according to an analytic hierarchy process;

obtaining an evaluation score of the disinfection manner based on the index score information of the disinfection manner and the weight information of the disinfection evaluation index, and judging whether the evaluation score is within a preset evaluation score;

if the target object is within the preset evaluation score, the target object is qualified for disinfection, and if the target object is not within the preset evaluation score, the target object is replaced and disinfected by the disinfection robot.

It should be noted that by the method, the number of times that the target object is touched can be evaluated by using an analytic hierarchy process, so that the sterilization mode of the sterilization robot is more reasonable. The hierarchy analysis method is a systematic method which takes a complex multi-target decision problem as a system, decomposes a target into a plurality of targets or criteria and further decomposes the targets into a plurality of layers of multi-index (or criteria and constraint), and calculates the hierarchical single sequence (weight) and the total sequence by a qualitative index fuzzy quantization method to be taken as the target (multi-index) and multi-scheme optimization decision.

In addition, the invention can also comprise the following steps of counting the total amount of bacteria:

acquiring the bacterial content in a unit area of the range of an area to be disinfected, and judging whether the bacterial content in the unit area is greater than a preset bacterial content value or not;

if the bacteria content in the unit area is larger than the preset bacteria content value, marking the point as a heavy disinfection point;

if the bacteria content in the unit area is not larger than the preset bacteria content value, marking the point as a light disinfection point, and acquiring the current light disinfection point and a disinfection mode of the heavy disinfection point during disinfection through a big data network;

and updating the disinfection modes of the light disinfection points and the heavy disinfection points according to the disinfection mode, and transmitting the disinfection modes to the control terminal of the autonomous mobile disinfection robot.

It should be noted that the fluorescence detection instrument arranged on the disinfection robot is used for acquiring the bacteria content in the unit area of the range of the area to be disinfected, so that the disinfection mode of the area to be disinfected can be updated by the method, the disinfection process is more reasonable, and the disinfection mode can be effectively selected according to the actual situation.

Fig. 7 shows a system block diagram of a control system of an autonomous mobile sterilization robot.

A second aspect of the present invention provides a control system of an autonomous mobile sterilization robot, the control system of the autonomous mobile sterilization robot including a memory 41 and a processor 62, the memory 41 including a control method of the autonomous mobile sterilization robot, the control method of the autonomous mobile sterilization robot being implemented by the processor 62 as follows:

It should be noted that, the video frame information within the preset time is acquired by the camera, the preset result at least includes actions of sneezing, coughing and touching important objects, such as door handles, elevator buttons, handrails, etc., and when the recognition result is the preset recognition result, the disinfection robot can acquire image information of the objects within the preset time from the cameras, etc. arranged in the environment, so as to preprocess the image.

In this embodiment, establishing a behavior recognition model to recognize the video frame information to obtain a recognition result, and determining whether the recognition result is a preset recognition result, specifically includes the following steps:

The behavior recognition model is established by using a convolutional neural network, a deep learning network, a machine learning method, and the like, and the pre-trained preset behavior video frame information at least comprises behaviors of sneezing, coughing, and touching important targets of the user. Thereby identifying the behavior in the video frame information by using the behavior identification model.

In this embodiment, the preprocessing the image information to obtain the preprocessed image information specifically includes the following steps:

In this embodiment, obtaining a target point cloud data coordinate number set according to the first disinfection range model map, and establishing a second disinfection range model map based on the target point cloud data number set specifically includes the following steps:

The first disinfection range model map is decomposed through a spectrum decomposition mode, a singular value feature decomposition mode and other decomposition modes, so that an orthogonal matrix formed by feature vectors and a diagonal matrix formed by the feature vectors are obtained, the feature vector of one limit position in the orthogonal matrix and the diagonal matrix is selected as a construction reference point, a new coordinate system is established by taking the reference point as a coordinate origin, the feature vector of one limit position in the orthogonal matrix and the diagonal matrix after decomposition is introduced into the new coordinate system to form a new target point cloud data matrix, so that the range of an initial disinfection area can be reduced by using the method, a disinfection area with a smaller range is formed, and the disinfection efficiency can be improved by using the method, wherein in the decomposition process, the calculation mode is as follows:

In this embodiment, generating a disinfection path map of the autonomous mobile disinfection robot based on the second disinfection range model map specifically includes the following steps:

It should be noted that the working area range during single disinfection is arranged in the autonomous disinfection robot, so that disinfection points required to pass through during complete disinfection are calculated by using the disinfection range and the second disinfection range model map, one or more disinfection path maps are planned according to the disinfection points through algorithms such as an ant colony algorithm and a genetic algorithm, one or more disinfection path maps are obtained, and the disinfection path map with the minimum path value is selected to be output as the final disinfection path map of the autonomous mobile disinfection robot.

In this embodiment, the control method for an autonomous mobile sterilization robot further includes the following steps:

and if so, disinfecting the target object according to the preset disinfection mode by the autonomous mobile disinfection robot according to the preset disinfection mode and the number of times that the target object is touched.

It should be noted that the preset disinfection mode can be used for disinfecting according to the number of times that the target object is touched, if the preset disinfection mode is a common disinfection mode within a certain touch number range, the preset disinfection mode is a thorough disinfection mode within another touch number range, so that the mode can be used for adjusting the disinfection mode of the autonomous mobile disinfection robot according to the actual condition during disinfection, and the disinfection is more reasonable.

A third aspect of the invention provides a computer-readable storage medium comprising a control method program for an autonomous mobile disinfection robot, which when executed by a processor 62, carries out the steps of any of the methods of control for an autonomous mobile disinfection robot.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. The above-described device embodiments are merely illustrative, for example, the division of the unit is only a logical functional division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.

Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A control method of an autonomous mobile disinfecting robot, characterized by comprising the steps of:

2. The method as claimed in claim 1, wherein a behavior recognition model is established to recognize the video frame information to obtain a recognition result, and whether the recognition result is a preset recognition result is determined, comprising the following steps:

3. The method as claimed in claim 1, wherein the step of preprocessing the image information to obtain preprocessed image information comprises the steps of:

4. The method as claimed in claim 1, wherein a target point cloud data coordinate number set is obtained according to the first disinfection range model map, and a second disinfection range model map is established based on the target point cloud data coordinate number set, specifically comprising the steps of:

5. The method as claimed in claim 1, wherein the step of generating a disinfection path map of the autonomous mobile disinfection robot based on the second disinfection range model map comprises the steps of:

6. The control method of an autonomous mobile sterilization robot according to claim 1, further comprising the steps of:

if the number of the touched target object is larger than the preset value, retrieving the target object in the preset area range, and acquiring the number of times that the target object is touched;

presetting a disinfection mode, and judging whether the number of times that the target object is touched is more than a preset number of times;

7. A control system for an autonomous mobile disinfecting robot, characterized in that the control system for the autonomous mobile disinfecting robot comprises a memory and a processor, the memory comprising a control method for the autonomous mobile disinfecting robot, the control method for the autonomous mobile disinfecting robot being implemented, when executed by the processor, as follows:

8. The control system of claim 7, wherein the image information is pre-processed to obtain pre-processed image information, and the method comprises the following steps:

9. The control system of claim 7, wherein a target point cloud data coordinate number set is obtained according to the first disinfection range model map, and a second disinfection range model map is established based on the target point cloud data coordinate number set, the method comprising the following steps:

10. A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a control method program of an autonomous mobile disinfecting robot, which when executed by a processor, carries out the steps of a control method of an autonomous mobile disinfecting robot as recited in any one of claims 1-6.