CN113679295B - Floor sweeping robot escaping method, system and storage medium - Google Patents
Floor sweeping robot escaping method, system and storage medium Download PDFInfo
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- CN113679295B CN113679295B CN202110983667.8A CN202110983667A CN113679295B CN 113679295 B CN113679295 B CN 113679295B CN 202110983667 A CN202110983667 A CN 202110983667A CN 113679295 B CN113679295 B CN 113679295B
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/24—Floor-sweeping machines, motor-driven
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4002—Installations of electric equipment
- A47L11/4008—Arrangements of switches, indicators or the like
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L11/00—Machines for cleaning floors, carpets, furniture, walls, or wall coverings
- A47L11/40—Parts or details of machines not provided for in groups A47L11/02 - A47L11/38, or not restricted to one of these groups, e.g. handles, arrangements of switches, skirts, buffers, levers
- A47L11/4061—Steering means; Means for avoiding obstacles; Details related to the place where the driver is accommodated
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
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- A—HUMAN NECESSITIES
- A47—FURNITURE; DOMESTIC ARTICLES OR APPLIANCES; COFFEE MILLS; SPICE MILLS; SUCTION CLEANERS IN GENERAL
- A47L—DOMESTIC WASHING OR CLEANING; SUCTION CLEANERS IN GENERAL
- A47L2201/00—Robotic cleaning machines, i.e. with automatic control of the travelling movement or the cleaning operation
- A47L2201/04—Automatic control of the travelling movement; Automatic obstacle detection
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Abstract
The invention discloses a sweeping robot escaping method, a system and a storage medium, wherein when a sweeping robot is trapped due to faults, the sweeping robot is immediately in a power-saving state, sound waves in the environment are continuously detected, when the artificial sound waves are detected, a user is around the sweeping robot, and then the sweeping robot is awakened and is controlled to output a distress voice. Can not only improve the probability of getting rid of poverty of robot of sweeping the floor like this, can also preserve the electric quantity of the robot of sweeping the floor to solve among the prior art when the robot trouble of sweeping the floor is stranded the back, can continuously save oneself blindly, lead to battery power to exhaust easily, and then lead to the problem that the components and parts of the robot of sweeping the floor burnt out or lost connection.
Description
Technical Field
The invention relates to the field of smart home, in particular to a floor sweeping robot escaping method, a floor sweeping robot escaping system and a storage medium.
Background
With the development of the socioeconomic level, various sweeping robots have been gradually popularized. Through big data statistics, the condition that motors are blocked and machines are trapped at hidden positions often appears in the sweeping robot on the market when garbage is processed. Among the prior art, when the robot trouble of sweeping the floor is stranded after, can continuously blindly save oneself, because the action success rate of saving oneself is not high, and can consume the robot a large amount of electric quantities of sweeping the floor, consequently lead to the battery power to exhaust easily, and then lead to the components and parts of the robot of sweeping the floor to burn or lose the antithetical couplet.
Thus, there is a need for improvement and development of the prior art.
Disclosure of Invention
The invention aims to solve the technical problems that when a floor sweeping robot is trapped due to faults, blind self-rescue can be continuously performed, the electric quantity of a battery is easily exhausted, and further components of the floor sweeping robot are burnt or disconnected in the prior art.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides a floor sweeping robot escaping method, where the method includes:
acquiring fault trapped information of the sweeping robot, and entering a power saving state according to the fault trapped information;
acquiring environmental sound wave data in the power-saving state, and determining a sound wave type corresponding to the environmental sound wave data;
and outputting distress voice when the sound wave type is artificial sound wave.
In one embodiment, the acquiring fault trapped information of the sweeping robot includes:
acquiring working data of the sweeping robot, and judging a state type corresponding to the sweeping robot according to the working data;
and when the state type is a trapped state, generating the fault trapped information.
In an embodiment, the determining, according to the working data, a status type corresponding to the sweeping robot includes:
acquiring motor working data in the working data, and determining the idle time of the motor according to the motor working data;
and when the motor idling time length is larger than a first time length threshold value, judging that the state type is a trapped state.
In an embodiment, the determining, according to the working data, a status type corresponding to the sweeping robot includes:
acquiring motor working data in the working data, and determining motor stalling duration according to the motor working data;
and when the motor stalling time is longer than a second time length threshold value, judging that the state type is a trapped state.
In an embodiment, the determining, according to the working data, a status type corresponding to the sweeping robot includes:
acquiring gyroscope working data in the working data, and determining the deflection angle of the sweeping robot according to the gyroscope working data;
and when the deflection angle is larger than a preset angle threshold value, judging that the state type is a trapped state.
In one embodiment, the acquiring fault trapped information of the sweeping robot includes:
sending a steering instruction to the sweeping robot, and controlling the sweeping robot to adjust a direction wheel through the steering instruction;
acquiring motor working data of the sweeping robot, and determining the motor idling time length according to the motor working data;
and when the motor idling time length is larger than a third time length threshold value, generating the fault trapped information.
In one embodiment, the determining the type of sound wave corresponding to the environmental sound wave data includes:
matching the environmental sound wave data with a plurality of artificial sound wave data in a sound wave database, wherein the plurality of artificial sound wave data respectively correspond to different types of artificial sound waves;
and when the artificial sound wave data with the similarity higher than a preset threshold value with the environmental sound wave data is matched from the plurality of artificial sound wave data, judging that the sound wave type corresponding to the environmental sound wave data is the artificial sound wave.
In one embodiment, when the sound wave type is artificial sound wave, outputting a distress call voice, including:
when the sound wave type is artificial sound wave, a voice broadcast instruction is sent to the voice broadcast module, and the voice broadcast module outputs the distress calling voice based on the voice broadcast instruction.
In a second aspect, an embodiment of the present invention further provides a floor sweeping robot escaping system, where the system includes:
the power saving module is used for acquiring fault trapped information of the sweeping robot and entering a power saving state according to the fault trapped information;
the matching module is used for acquiring environmental sound wave data in the power-saving state and determining the sound wave type corresponding to the environmental sound wave data;
and the distress calling module is used for outputting distress calling voice when the sound wave type is artificial sound wave.
In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a plurality of instructions are stored, where the instructions are adapted to be loaded and executed by a processor, so as to implement any of the steps of the above-mentioned method for relieving from difficulty of a cleaning robot.
The invention has the beneficial effects that: according to the embodiment of the invention, the fault trapped information of the sweeping robot is acquired, and the sweeping robot enters the power-saving state according to the fault trapped information; acquiring environmental sound wave data in the power-saving state, and determining a sound wave type corresponding to the environmental sound wave data; and outputting distress voice when the sound wave type is artificial sound wave. When the sweeping robot is trapped in a fault, the sweeping robot can be immediately in a power-saving state, sound waves in the environment are continuously detected, when the artificial sound waves are detected, a user is around the sweeping robot, the sweeping robot is awakened at the moment, and the sweeping robot is controlled to call for help, so that the probability of getting rid of the sweeping robot is improved, the electric quantity of the sweeping robot can be stored, and the problems that in the prior art, when the sweeping robot is trapped in a fault, the electric quantity of a battery is exhausted, and further components of the sweeping robot are burnt or are not connected are solved.
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 described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a cleaning robot escaping method according to an embodiment of the present invention.
Fig. 2 is a reference diagram of the overall process of the robot for sweeping the floor, which is rescued and provided by the embodiment of the invention.
Fig. 3 is a connection diagram of internal modules of the cleaning robot escaping system according to the embodiment of the present invention.
Fig. 4 is a schematic block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, if directional indications (such as up, down, left, right, front, and back … …) are involved in the embodiment of the present invention, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indications are changed accordingly.
With the development of the social and economic level, various sweeping robots are gradually popularized. Through big data statistics, the floor sweeping robot on the market often appears in the condition that motor is dead and the machine is stranded in hidden position when handling rubbish. Among the prior art, when the robot trouble of sweeping the floor is stranded after, can continuously blindly save oneself, because the action success rate of saving oneself is not high, and can consume the robot a large amount of electric quantities of sweeping the floor, consequently lead to the battery power to exhaust easily, and then lead to the components and parts of the robot of sweeping the floor to burn or lose the antithetical couplet.
Aiming at the defects in the prior art, the invention provides a floor sweeping robot escaping method, which comprises the steps of obtaining fault trapped information of a floor sweeping robot and entering a power saving state according to the fault trapped information; acquiring environmental sound wave data in the power-saving state, and determining a sound wave type corresponding to the environmental sound wave data; and outputting distress voice when the sound wave type is artificial sound wave. When the sweeping robot is trapped in a fault, the sweeping robot can be immediately in a power-saving state, sound waves in the environment are continuously detected, when the artificial sound waves are detected, a user is around the sweeping robot, the sweeping robot is awakened at the moment, and the sweeping robot is controlled to call for help, so that the probability of getting rid of the sweeping robot is improved, the electric quantity of the sweeping robot can be stored, and the problems that in the prior art, when the sweeping robot is trapped in a fault, the electric quantity of a battery is exhausted, and further components of the sweeping robot are burnt or are not connected are solved.
As shown in fig. 1, the method comprises the steps of:
and S100, acquiring fault trapped information of the sweeping robot, and entering a power-saving state according to the fault trapped information.
Specifically, when the fault trapped information of the sweeping robot is acquired, it indicates that the sweeping robot is currently trapped or blocked at a certain position and is difficult to move. At this time, the sweeping robot is only moved or rotated by itself and is difficult to leave the position, so that in order to guarantee the electric quantity of the sweeping robot and wait for the rescue of a user, the sweeping robot needs to be controlled to enter a power saving state from a working state. In the power-saving state, the sweeping robot can turn off unnecessary working modules such as a driving motor, a gyroscope, an indicator light and the like, and the main IC enters a power-saving mode, so that most energy consumption of the sweeping robot can be effectively reduced.
In one implementation, the acquiring fault trapped information of the sweeping robot includes:
s101, acquiring working data of the sweeping robot, and judging a state type corresponding to the sweeping robot according to the working data;
and step S102, when the state type is a trapped state, generating the fault trapped information.
Specifically, in order to determine whether the sweeping robot is trapped, the working data of the sweeping robot needs to be acquired in real time or at preset intervals, and the working data of the sweeping robot can reflect the mobile information of the sweeping robot, so that the current normal state or the trapped state of the sweeping robot can be determined by analyzing the working data of the sweeping robot. When the sweeping robot is in a trapped state, fault trapped information needs to be generated.
In an implementation manner, the determining a status type corresponding to the sweeping robot according to the working data specifically includes the following steps:
step S1011, obtaining motor working data in the working data, and determining the motor idling time length according to the motor working data;
and step S1012, when the motor idling time length is greater than a first time length threshold, determining that the state type is a trapped state.
Specifically, the working data of the sweeping robot includes the working data of each component, which is used for reflecting the working state of each component, so that the working data of the motor of the sweeping robot can be obtained based on the working data of the sweeping robot. Since the operating data of the motor can reflect the operating state of the motor at different time points, the time point of the idling state of the motor can be determined based on the operating data of the motor, and the idling time period of the motor can be determined. Since the sweeping robot may occasionally idle the motor in the normal moving process, the first time threshold is preset in this embodiment, and it is determined whether the detected motor idle is generated in a normal situation or an abnormal situation based on the first time threshold. If the motor idling time length is longer than the first time length threshold value, the time that the motor is in the idling state is longer, and therefore the sweeping robot is judged to be in the trapped state currently. If the motor idling time length is less than or equal to the first time length threshold value, the time length that the motor is in the idling state is within an acceptable range, and the motor idling is happened under normal conditions, so that the sweeping robot is judged to be in a normal state currently.
In another implementation manner, the determining a state type corresponding to the sweeping robot according to the working data specifically includes the following steps:
step S1013, motor working data in the working data are obtained, and motor stalling duration is determined according to the motor working data;
and step S1014, when the motor stalling time is longer than a second time threshold, judging that the state type is a trapped state.
Specifically, the present embodiment may further determine a time point when the motor is in the locked-rotor state according to the motor working data, so as to determine the locked-rotor time of the motor. Since the sweeping robot may occasionally block the rotation of the motor during the normal moving process, the second duration threshold is preset in this embodiment, and it is determined whether the detected motor blocking occurs under the normal condition or the abnormal condition based on the second duration threshold. If the motor locked-rotor time length is longer than the second time length threshold value, the motor locked-rotor time is longer, and therefore the sweeping robot is judged to be in the trapped state currently. If the motor locked-rotor time length is less than or equal to the second time length threshold value, the motor locked-rotor time length is within the acceptable range, and the motor locked-rotor time length may be accidental motor locked-rotor under normal conditions, so that the sweeping robot is judged to be in a normal state currently.
In another implementation manner, the determining a state type corresponding to the sweeping robot according to the working data specifically includes the following steps:
step S1015, acquiring gyroscope working data in the working data, and determining the deflection angle of the sweeping robot according to the gyroscope working data;
and step S1016, when the deflection angle is larger than a preset angle threshold value, judging that the state type is a trapped state.
Specifically, the gyroscope working data can be obtained from the working data of the sweeping robot, and the gyroscope working data is mainly used for reflecting the deflection state of the sweeping robot, so that the deflection angle of the sweeping robot can be determined based on the gyroscope working data. Since the sweeping robot can also deflect in the normal moving process, but the deflection angle is usually not too large, an angle threshold is preset in the embodiment, and whether the current deflection angle of the sweeping robot is normal or not can be determined based on the angle threshold. If the deflection angle is larger than a preset angle threshold value, the sweeping robot is possibly turned over or inclined, and therefore the sweeping robot is judged to be in a trapped state currently; if the deflection angle is smaller than or equal to the preset angle threshold value, the sweeping robot is still in a normal state.
In another implementation manner, the acquiring fault trapped information of the sweeping robot specifically includes the following steps:
step S103, sending a steering instruction to the sweeping robot, and controlling the sweeping robot to adjust a direction wheel through the steering instruction;
step S104, obtaining motor working data of the sweeping robot, and determining the idle time of a motor according to the motor working data;
and step S105, when the idle time of the motor is greater than a third time threshold, generating the fault trapped information.
Specifically, because the sweeping robot can get rid of difficulties by changing the moving direction in some positions without the help of a user, the embodiment can send a steering instruction to the sweeping robot in advance, so that the sweeping robot can actively adjust the self direction wheel to save self based on the steering instruction. After the sweeping robot adjusts the direction wheels for a certain time, the working data of the motor is acquired, the time point of the motor in an idle running state is determined according to the working data of the motor, the idle running time of the motor is further obtained, if the idle running time of the motor is larger than a preset third time threshold value at the moment, the self-rescue failure of the sweeping robot is indicated, the sweeping robot is still in a trapped state, and then fault trapped information is generated.
As shown in fig. 1, the method further comprises the steps of:
and S200, acquiring environmental sound wave data in the power-saving state, and determining the sound wave type corresponding to the environmental sound wave data.
Specifically, after the floor sweeping robot is determined to be in the trapped state, the floor sweeping robot enters a power saving state to avoid consuming electric power by doing useless work. In order to enable the sweeping robot to get rid of difficulties with the help of a user, whether people pass around the sweeping robot needs to be judged constantly, therefore, the embodiment is provided with the sound wave collecting sensor in advance, and the sound wave collecting sensor can continuously work or intermittently work (for example, detect once every 1500 ms) after the sweeping robot enters a power saving state so as to acquire sound wave data around the sweeping robot and obtain environment sound wave data. After the environmental sound wave data is acquired, whether the environmental sound wave data is sent manually or not needs to be judged, if yes, the environmental sound wave data is artificial sound waves, and the situation that people around the current sweeping robot can help the robot to get rid of the trouble is shown; if not, the environmental sound wave data is the non-artificial sound wave, possibly natural noise existing in the environment, and the situation that no person around the current sweeping robot can help the robot to get rid of the trouble is indicated, and the sweeping robot is controlled to continue to keep the power saving state.
In one implementation, the power saving state is implemented based on a hardware design: the circuit design adopts low-power consumption design, the standby current is controlled at microampere level, and power consumption modules such as a voltage stabilizing chip, a driving circuit, an MCU peripheral circuit and an MCU are all designed by low power consumption.
In one implementation, the determining the type of the sound wave corresponding to the environmental sound wave data specifically includes the following steps:
step S201, matching the environmental sound wave data with a plurality of artificial sound wave data in a sound wave database, wherein the artificial sound wave data correspond to different types of artificial sound waves respectively;
step S202, when artificial sound wave data with the similarity higher than a preset threshold value with the environmental sound wave data is matched from the plurality of pieces of artificial sound wave data, judging that the sound wave type corresponding to the environmental sound wave data is artificial sound wave.
Specifically, in order to determine whether the detected environmental sound wave data is an artificial sound wave, the present embodiment constructs a sound wave database in advance, where multiple types of artificial sound wave data are stored in the sound wave database, and the sound wave database may include, for example, a human speaking sound, a door opening sound, a footstep sound, a switching sound of a household appliance, a mobile phone ringtone, a clock alarm, a mechanical vibration sound, and the like. And after the environmental sound wave data are detected, matching the environmental sound wave data with the artificial sound wave data in the sound wave database in sequence, and calculating the similarity. If the artificial sound wave data with the similarity higher than a preset threshold (for example, 70%) is matched, which indicates that the sound characteristics of the environmental sound wave data and the currently matched artificial sound wave data are very similar, it is determined that the environmental sound wave data is the artificial sound wave. If all people in the sound wave database are matched with the sound wave data, artificial sound wave data with the similarity higher than a preset threshold value are not matched, and the fact that the environmental sound wave data are not artificial sound waves is shown.
In one implementation, when matching the environmental sound wave data with each artificial sound wave data in the sound wave database, matching is performed according to frequency characteristics, timbre characteristics, tone characteristics, and the like of the two sound waves, so as to calculate the similarity between the two sound waves. In addition, the acoustic information frequency of the environmental acoustic data needs to be within a preset range (e.g., 20-20000Hz), otherwise, an invalid determination is made.
In one implementation, the acoustic database may employ a hierarchical model. Specifically, the basic sub-functions related to the bottom access of the file are used as the bottom module, other modules are designed from bottom to top, the modules are called hierarchically, and only the upper layer is allowed to call the lower layer, so that the modification and expansion of the modules in the future are facilitated. In addition, the hierarchical model also needs to follow the principle of compressibility, minimize the use of RAM, minimize write operation to reduce write cost, fully utilize fast read operation, utilize low granularity and the direct access capability of stable memory to read and write, protect data from accidents and malicious damage, minimize the complexity of algorithm to avoid security holes, and the like. And the hierarchical model also adopts a rough analysis system bottom layer module, takes a function module related to a file operation or an operating system as the bottom layer, analyzes the basic data type of the bottom layer module and the data structure of the bottom layer, and provides a module function list. Wherein, the module function list includes but is not limited to: module function specification, entry parameters, return values, local data structures. In addition, the hierarchical model can also adopt a hierarchical design high-level module. Specifically, a high-level module and a corresponding data structure are designed according to a bottom-level module and a lower-level module, and a module function detailed description, an entry parameter, a return value, a local data structure and a calling module are given. And analyzing and designing a global basic data structure on the basis to obtain a module level calling topology.
In one implementation, before the acoustic database is constructed, various artificial acoustic waves need to be sampled to obtain a plurality of original artificial acoustic wave data, and then, for each original artificial acoustic wave data, a frequency type corresponding to the original artificial acoustic wave data is determined, where the frequency type includes, but is not limited to, a high frequency, a medium frequency, and a low frequency. And filtering the original artificial sound wave data according to the frequency type, thereby filtering burrs and peak signals which have no value in the original artificial sound wave data, ensuring the sampling purity, and avoiding the distortion of artificial sound wave data sampling caused by disturbance such as voltage source ripples of the circuit and unstable factors such as crosstalk of sound wave acquisition signals.
After sampling is finished, a plurality of artificial sound wave data of analog signal types are obtained, and therefore the artificial sound wave data need to be converted from analog signals into digital signals to construct a sound wave database. Specifically, the analog signal is generally quantized and converted into a digital signal using a PCM (pulse code modulation) method. The PCM method is to make different ranges of analog signals correspond to different binary values. For example, if an 8-bit code is used, the analog signal can be quantized to 2^8 ^ 256 orders of magnitude. The more points the analog signal is converted into a digital signal, the higher the sound fidelity. In terms of a sampling conversion algorithm, the embodiment can select a proper coding algorithm, so that the purpose of small size and high quality is achieved.
As shown in fig. 1, the method further comprises the steps of:
and S300, outputting the distress voice when the sound wave type is the artificial sound wave.
Specifically, if the environmental sound wave data is determined to be artificial sound waves, it indicates that people pass around the sweeping robot, and the sweeping robot can be controlled to output a distress voice to prompt a user to help the sweeping robot to get rid of trouble. If the environmental sound wave data are determined to be non-artificial sound waves, the situation that no person passes by the periphery of the sweeping robot is indicated, and the sweeping robot is controlled to keep a power-saving state so as to avoid consuming a large amount of electric quantity per se.
In an implementation manner, the step S300 specifically includes the following steps:
and S301, when the sound wave type is the artificial sound wave, sending a voice broadcasting instruction to a voice broadcasting module, and enabling the voice broadcasting module to output the distress calling voice based on the voice broadcasting instruction.
Specifically, this embodiment has set up a voice broadcast module in the robot of sweeping the floor in advance. When confirming that there is the artificial sound wave around the robot of sweeping the floor, will send a voice broadcast instruction to the voice broadcast module, after the voice broadcast module acquires this voice broadcast instruction, will broadcast the voice of calling for help to the suggestion user helps the robot of sweeping the floor to get rid of poverty. Aiming at the distress voice, the user can use default options of the system, can also customize the design, record in advance, provide personalized selection and meet the personalized requirements of the user.
Based on the above embodiment, the present invention further provides a floor sweeping robot escaping system, as shown in fig. 3, the system includes:
the power saving module 01 is used for acquiring fault trapped information of the sweeping robot and entering a power saving state according to the fault trapped information;
the matching module 02 is used for acquiring environmental sound wave data in the power-saving state and determining the sound wave type corresponding to the environmental sound wave data;
and the distress calling module 03 is used for outputting distress calling voice when the sound wave type is artificial sound wave.
Based on the above embodiments, the present invention further provides a terminal, and a schematic block diagram thereof may be as shown in fig. 4. The terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein the processor of the terminal is configured to provide computing and control capabilities. The memory of the terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the terminal is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to realize the escaping method of the sweeping robot. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen.
It will be understood by those skilled in the art that the block diagram of fig. 4 is a block diagram of only a portion of the structure associated with the inventive arrangements and is not intended to limit the terminals to which the inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may have some components combined, or may have a different arrangement of components.
In one implementation, one or more programs are stored in a memory of the terminal and configured to be executed by one or more processors include instructions for performing a method of freeing a sweeping robot.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the invention discloses a floor-sweeping robot escaping method, a system and a storage medium, wherein the method obtains fault trapped information of the floor-sweeping robot, and enters a power-saving state according to the fault trapped information; acquiring environmental sound wave data in the power-saving state, and determining a sound wave type corresponding to the environmental sound wave data; and outputting distress voice when the sound wave type is artificial sound wave. When the sweeping robot is trapped in a fault, the sweeping robot can be immediately in a power-saving state, sound waves in the environment are continuously detected, when the artificial sound waves are detected, a user is around the sweeping robot, the sweeping robot is awakened at the moment, and the sweeping robot is controlled to call for help, so that the probability of getting rid of the sweeping robot is improved, the electric quantity of the sweeping robot can be stored, and the problems that in the prior art, when the sweeping robot is trapped in a fault, the electric quantity of a battery is exhausted, and further components of the sweeping robot are burnt or are not connected are solved.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.
Claims (10)
1. A method for relieving floor sweeping robots, which is characterized by comprising the following steps:
acquiring fault trapped information of the sweeping robot, and entering a power saving state according to the fault trapped information;
acquiring environmental sound wave data in the power-saving state, and determining a sound wave type corresponding to the environmental sound wave data;
and outputting distress voice when the sound wave type is artificial sound wave.
2. The sweeping robot escaping method according to claim 1, wherein the acquiring fault escaping information of the sweeping robot comprises:
acquiring working data of the sweeping robot, and judging a state type corresponding to the sweeping robot according to the working data;
and when the state type is a trapped state, generating the fault trapped information.
3. The method for relieving the floor sweeping robot according to claim 2, wherein the step of judging the state type corresponding to the floor sweeping robot according to the working data comprises the following steps:
acquiring motor working data in the working data, and determining the idle time of the motor according to the motor working data;
and when the motor idling time length is larger than a first time length threshold value, judging that the state type is a trapped state.
4. The method for relieving the floor sweeping robot according to claim 2, wherein the step of judging the state type corresponding to the floor sweeping robot according to the working data comprises the following steps:
acquiring motor working data in the working data, and determining motor stalling duration according to the motor working data;
and when the motor stalling time is longer than a second time length threshold value, judging that the state type is a trapped state.
5. The method for relieving the floor sweeping robot according to claim 2, wherein the step of judging the state type corresponding to the floor sweeping robot according to the working data comprises the following steps:
acquiring gyroscope working data in the working data, and determining the deflection angle of the sweeping robot according to the gyroscope working data;
and when the deflection angle is larger than a preset angle threshold value, judging that the state type is a trapped state.
6. The sweeping robot escaping method according to claim 1, wherein the acquiring fault escaping information of the sweeping robot comprises:
sending a steering instruction to the sweeping robot, and controlling the sweeping robot to adjust a direction wheel through the steering instruction;
acquiring motor working data of the sweeping robot, and determining the motor idling time length according to the motor working data;
and when the motor idling time length is larger than a third time length threshold value, generating the fault trapped information.
7. The method for relieving floor sweeping robot difficulty according to claim 1, wherein the determining the type of the sound wave corresponding to the environmental sound wave data comprises:
matching the environmental sound wave data with a plurality of artificial sound wave data in a sound wave database, wherein the plurality of artificial sound wave data respectively correspond to different types of artificial sound waves;
and when artificial sound wave data with the similarity higher than a preset threshold value with the environmental sound wave data are matched from the plurality of artificial sound wave data, judging that the sound wave type corresponding to the environmental sound wave data is an artificial sound wave.
8. The method for relieving floor sweeping robot according to claim 1, wherein when the sound wave type is artificial sound wave, outputting distress voice comprises:
when the sound wave type is artificial sound wave, a voice broadcast instruction is sent to the voice broadcast module, and the voice broadcast module outputs the distress calling voice based on the voice broadcast instruction.
9. A floor sweeping robot escaping system, the system comprising:
the power saving module is used for acquiring fault trapped information of the sweeping robot and entering a power saving state according to the fault trapped information;
the matching module is used for acquiring environmental sound wave data in the power-saving state and determining the sound wave type corresponding to the environmental sound wave data;
and the distress calling module is used for outputting distress calling voice when the sound wave type is artificial sound wave.
10. A computer-readable storage medium having stored thereon a plurality of instructions, wherein the instructions are adapted to be loaded and executed by a processor to implement the steps of the method for relieving trouble of a cleaning robot as claimed in any one of the above claims 1-8.
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| CN109480708A (en) * | 2018-12-19 | 2019-03-19 | 珠海市微半导体有限公司 | The position reminding method of clean robot |
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| CN113100663A (en) * | 2020-01-10 | 2021-07-13 | 必胜公司 | Autonomous floor cleaner and method for autonomous floor cleaning |
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| KR101356165B1 (en) * | 2012-03-09 | 2014-01-24 | 엘지전자 주식회사 | Robot cleaner and controlling method of the same |
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| CN109480708A (en) * | 2018-12-19 | 2019-03-19 | 珠海市微半导体有限公司 | The position reminding method of clean robot |
| CN110244743A (en) * | 2019-07-03 | 2019-09-17 | 浙江大学 | A kind of mobile robot merging multi-sensor information is independently got rid of poverty method |
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