Cleaning robot and material identification and control method thereof, processor and cleaning system

Abstract

The invention provides a cleaning robot and a material identification and control method thereof, a processor and a cleaning system, and relates to the technical field of self-moving robots. The material identification method comprises the following steps: determining the material category of the target cleaning surface based on a first parameter of an echo signal detected by the detection device; wherein the first parameter is used for representing the integral area of the envelope curve corresponding to the echo signal to the time axis. According to the method, the influence of the interference peak on the judgment result can be reduced, so that the accuracy of material determination is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent robot technology, and in particular to a cleaning robot and its material identification, control method, processor and cleaning system. Background Art

[0002] When an autonomous mobile robot is working, it usually uses a detection device to detect obstacles on the path or material information of the target cleaning surface. The most commonly used detection device is an ultrasonic detection device.

[0003] Existing ultrasonic detection devices usually transmit and receive ultrasonic waves to obstacles or target cleaning surfaces, then process and convert the ultrasonic waves to obtain an analog voltage curve that changes with time. Since different materials will produce analog voltage curves of different shapes, the peaks in the analog voltage curve can be used to determine the type of obstacle or target cleaning surface.

[0004] However, the echo in the above manner may have a peak caused by unexpected energy reflection, which makes it impossible to accurately determine the voltage value of the echo peak, resulting in inaccurate identification of the ground material. Summary of the invention

[0005] The embodiments of the present application provide a cleaning robot and its material recognition, control method, processor and cleaning system, so as to achieve the effect that the echo may carry a peak caused by unexpected energy reflection, resulting in the inability to accurately determine the voltage value of the echo peak, causing inaccurate identification of the ground material.

[0006] In a first aspect, the present application provides a material identification method for a cleaning robot, wherein the robot comprises a detection device, wherein the detection device is used to transmit an ultrasonic signal to a target cleaning surface and receive an echo signal returned by the target cleaning surface; the method comprises:

[0007] The material category of the target cleaning surface is determined based on a first parameter of the echo signal detected by the detection device; wherein the first parameter is used to characterize the integral area size of the envelope curve corresponding to the echo signal on the time axis.

[0008] The method of the present application compares the integral area corresponding to the envelope curve of the ultrasonic wave with the preset material category corresponding to the preset integral area to determine the material category corresponding to the curve formed by the current ultrasonic wave. Compared with the determination methods such as peaks or troughs, it can reduce the influence of interference peaks on the judgment results, thereby improving the accuracy of material determination.

[0009] In a possible implementation manner, the first parameter includes:

[0010] The integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis;

[0011] Alternatively, the echo signal corresponds to the incremental percentage of the integral area of ​​the envelope curve on the time axis.

[0012] The method of this embodiment limits the specific area parameters used to determine the material category. The area parameter can be the area corresponding to the directly calculated curve figure to directly obtain the area corresponding to the curve figure of the same material, or it can be the normalized area corresponding to the curve figure to reduce the degree of differentiation of the areas corresponding to different materials and improve the accuracy of the detection results.

[0013] In a possible implementation manner, the integrated area is determined based on M echoes, where M is greater than or equal to 2.

[0014] The method of this embodiment is to limit the integral segment area of ​​the envelope curve. Generally speaking, the larger the integral area, the higher the corresponding material category matching accuracy. Since the envelope curve is mainly determined by the number of echoes, the more the number of echoes, the larger the corresponding integral area. Therefore, the size of the integral area used for determination can be limited by limiting the number of echoes.

[0015] In a possible implementation manner, the integrated area includes:

[0016] The integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the second echo;

[0017] Alternatively, the integrated area of ​​the continuous curve segment corresponding to the starting point of the first echo and the ending point of the second echo among the M echoes.

[0018] The method of this embodiment is to limit the front and rear positions of the echo. Since the waveform includes the starting point, peak and end point of the echo, when limiting the number of echoes, the starting point and end point of the area integral can be limited by the position of the waveform. It is only necessary to make the starting point and end point of the actually detected integral area correspond one by one with the starting point and end point of the integral area corresponding to the preset material category.

[0019] In a possible implementation manner, the M echoes include a primary echo and a secondary echo.

[0020] Since the first two echoes have higher intensities and corresponding integrated areas are also larger, it is easier to obtain the integrated area corresponding to the preset material category, making the recognition result more accurate.

[0021] In a possible implementation manner, the M is greater than 2, and the integrated area includes:

[0022] The integral area of ​​the continuous curve segment corresponding to the peak of the first echo to the peak of the last echo among the M echoes;

[0023] Or, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo of the M echoes to the peak of the last echo;

[0024] Or, the integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the last echo;

[0025] Alternatively, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo to the ending point of the last echo among the M echoes.

[0026] This embodiment limits how to select the integral area corresponding to the echo when there are more than two echoes. It is similar to the two echo situation, with the only difference being that the length range of the starting point and the ending point of the integral area is expanded, and the preset material category used as a reference also needs to be expanded to the integral area size corresponding to the corresponding starting point and the ending point position.

[0027] In a possible implementation manner, the M echoes include a primary echo, a secondary echo, and a tertiary echo.

[0028] Using the integrated area corresponding to three echoes can improve the recognition accuracy. Compared with the method of determining the material using the integrated area of ​​only two echoes, it can further reduce the interference of miscellaneous peaks such as ultrasonic aftershocks in the previous echoes and improve the accuracy of the judgment results.

[0029] In a possible implementation manner, the integrated area is determined based on all echo signals.

[0030] During the ultrasonic emission process, there may be peaks caused by unexpected energy reflections such as vibrations during excitation and aftershocks when the excitation stops, and these fluctuations themselves have nothing to do with the material. However, when the reference preset material category comparison includes all peak integral areas, all peak areas obviously include the integral area of ​​this part. That is, it is not enough to only use the integral area of ​​the echo in the above embodiment, and it is necessary to further expand the starting and ending points of the integral area so that all echo signals are included.

[0031] In a possible implementation manner, the first parameter includes: an increment percentage; and the method further includes:

[0032] Obtaining the integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis;

[0033] The integral area of ​​the envelope curve corresponding to the echo signal on the time axis is normalized to obtain the increment percentage.

[0034] The method of this embodiment further defines how to determine the incremental percentage of the integrated area, and converts the absolute value of the area into a normalized percentage, which can further improve the accuracy of the obtained integrated area and improve the credibility of the material determination result.

[0035] In a possible implementation manner, the normalizing the integral area of ​​the envelope curve corresponding to the echo signal on the time axis includes:

[0036] Determine a first integral difference value according to a difference between an integral area of ​​the envelope curve corresponding to the echo signal on the time axis and a preset first integral area; wherein the preset first integral area is an integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the fully absorbed target cleaning surface on the time axis;

[0037] Determine a second integral difference value according to the difference between a preset second integral area and a preset first integral area; wherein the preset second integral area is the integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the completely non-absorbent target cleaning surface on the time axis;

[0038] A normalized value is obtained according to the ratio of the first integral difference value to the second integral difference value.

[0039] The method of this embodiment specifically defines how to perform normalization processing, and defines normalization processing under the conditions of complete absorption and complete non-absorption of the same ultrasonic wave. The processing method is relatively reliable, thereby improving the credibility of the material determination result.

[0040] In a second aspect, the present application provides a processor of a cleaning robot, the robot comprising a detection device, the detection device being communicatively connected to the processor;

[0041] The detection device is used to transmit ultrasonic signals to the target cleaning surface and receive echo signals returned by the target cleaning surface;

[0042] The processor comprises:

[0043] An acquisition module, used for acquiring the echo signal detected by the detection device;

[0044] A processing module is used to determine the material category of the target cleaning surface based on a first parameter of the echo signal detected by the detection device; wherein the first parameter is used to characterize the integral area size of the envelope curve corresponding to the echo signal on the time axis.

[0045] In a possible implementation manner, the first parameter includes:

[0046] The integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis;

[0047] Alternatively, the echo signal corresponds to the incremental percentage of the integral area of ​​the envelope curve on the time axis.

[0048] In a possible implementation manner, the integrated area is determined based on M echoes, where M is greater than or equal to 2.

[0049] In a possible implementation manner, the integrated area includes:

[0050] The integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the second echo;

[0051] Alternatively, the integrated area of ​​the continuous curve segment corresponding to the starting point of the first echo and the ending point of the second echo among the M echoes.

[0052] In a possible implementation manner, the M echoes include a primary echo and a secondary echo.

[0053] In a possible implementation manner, the M is greater than 2, and the integrated area includes:

[0054] The integral area of ​​the continuous curve segment corresponding to the peak of the first echo to the peak of the last echo among the M echoes;

[0055] Or, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo of the M echoes to the peak of the last echo;

[0056] Or, the integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the last echo;

[0057] Alternatively, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo to the ending point of the last echo among the M echoes.

[0058] In a possible implementation manner, the M echoes include a primary echo, a secondary echo, and a tertiary echo.

[0059] In a possible implementation manner, the integrated area is determined based on all echo signals.

[0060] In a possible implementation manner, the first parameter includes: an increment percentage; and the method further includes:

[0061] Obtaining the integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis;

[0062] The integral area of ​​the envelope curve corresponding to the echo signal on the time axis is normalized to obtain the increment percentage.

[0063] In a possible implementation manner, the normalizing the integral area of ​​the envelope curve corresponding to the echo signal on the time axis includes:

[0064] Determine a first integral difference value according to a difference between an integral area of ​​the envelope curve corresponding to the echo signal on the time axis and a preset first integral area; wherein the preset first integral area is an integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the fully absorbed target cleaning surface on the time axis;

[0065] Determine a second integral difference value according to the difference between a preset second integral area and a preset first integral area; wherein the preset second integral area is the integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the completely non-absorbent target cleaning surface on the time axis;

[0066] A normalized value is obtained according to the ratio of the first integral difference value to the second integral difference value.

[0067] In a third aspect, the present application provides a control method for a cleaning robot, wherein the robot comprises a detection device, wherein the detection device is used to transmit an ultrasonic signal to a target cleaning surface and receive an echo signal returned by the target cleaning surface; the method comprises:

[0068] In the process of performing a target task on a target cleaning surface, the material category of the target cleaning surface is determined based on the material recognition method of the cleaning robot; the target task includes at least a cleaning task or a mapping task;

[0069] Based on the material category of the target cleaning surface, a target task is performed on the target cleaning surface.

[0070] In a fourth aspect, the present application provides a cleaning robot, the robot comprising a detection device, a processor communicatively connected to the detection device, and a memory communicatively connected to the processor;

[0071] The detection device is used to transmit ultrasonic signals to the target cleaning surface and receive echo signals returned by the target cleaning surface;

[0072] The memory is used to store computer-executable instructions;

[0073] The processor is used to execute the computer execution instructions stored in the memory based on the detection results of the detection device to implement the robot control method.

[0074] In a fifth aspect, the present application provides a cleaning system, the cleaning system comprising a cleaning robot and a user terminal, the robot being communicatively connected with the user terminal;

[0075] The robot is further configured to send material information of the target cleaning surface to the user terminal based on the determined material category of the target cleaning surface.

[0076] In a possible implementation manner, the material information of the target cleaning surface is displayed on the user terminal in at least one of the following ways:

[0077] Text information of the material, or image information of the material, or voice information of the material.

[0078] In a sixth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to implement a robot control method when executed by a processor.

[0079] In a seventh aspect, the present application provides a computer program product, comprising a computer program, which implements a robot control method when executed by a processor.

[0080] The cleaning robot and its material identification, control method, processor and cleaning system provided in the present application determine the material category of the target cleaning surface by a first parameter based on the echo signal detected by the detection device; wherein the first parameter is used to characterize the integral area of ​​the envelope curve corresponding to the echo signal on the time axis. Compared with the defect of the prior art that material categories are determined by the number of peaks or troughs, the present application utilizes the integral area of ​​the echo peak to reduce the integral area of ​​the peak caused by unexpected energy reflection, thereby reducing the influence of interference peaks on the judgment results, thereby improving the accuracy of material determination. BRIEF DESCRIPTION OF THE DRAWINGS

[0081] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0082] Figure 1 A schematic diagram of an envelope curve of a carpet material that is misjudged as a floor provided in this embodiment;

[0083] Figure 2 A schematic diagram of an application scenario of the material recognition method for a cleaning robot provided in an embodiment of the present application;

[0084] Figure 3 A schematic diagram of a carpet envelope curve detected by an ultrasonic detection device provided in an embodiment of the present application;

[0085] Figure 4 A schematic diagram of a ceramic tile envelope curve detected by an ultrasonic detection device provided in an embodiment of the present application;

[0086] Figure 5A schematic diagram of an envelope curve of a tile containing unexpected energy reflection detected by an ultrasonic detection device provided in an embodiment of the present application;

[0087] Figure 6 A schematic diagram of a possible scenario of unexpected energy reflection causing a wave peak provided in an embodiment of the present application;

[0088] Figure 7 A schematic diagram of a normalization processing method provided in an embodiment of the present application;

[0089] Figure 8 A schematic diagram of the processor structure of the cleaning robot provided in an embodiment of the present application;

[0090] Fig. 9 A schematic diagram of the hardware structure of the cleaning robot provided in an embodiment of the present application;

[0091] Fig.10 This is a schematic diagram of the cleaning system structure provided in an embodiment of the present application.

[0092] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0093] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0094] The autonomous cleaning robot needs to traverse the target cleaning area during the cleaning process, so as to improve the cleaning effect and not miss the area to be cleaned. In the present application, the cleaning robot has the function of self-movement, including but not limited to sweeping robots, vacuum cleaners, sweeping and mopping machines, etc.

[0095] Taking a sweeping robot as an example, when cleaning a room, different cleaning strategies need to be implemented for different floor materials.

[0096] For example, for carpets, dirt has stronger adhesion, so greater suction is required, and try not to perform wet cleaning on carpets to increase the dirtiness of the carpets. For solid wood floors and tiles, there may be no need to distinguish between suction settings, but since solid wood floors may absorb water and deteriorate, when wet cleaning, measures such as reducing the amount of water sprayed are needed to minimize the adverse effects of wet cleaning on solid wood floors.

[0097] Therefore, the cleaning robot needs to identify the material of the area to be cleaned before cleaning, so as to determine the appropriate cleaning mode and improve the cleaning quality.

[0098] It should be understood that the term "before cleaning" here refers to before the actual cleaning, including but not limited to the period when the cleaning robot builds a map and the moment before the cleaning robot actually cleans.

[0099] The existing ground material identification method mainly uses detection devices for detection and identification. Detection devices include but are not limited to ultrasonic detection devices, laser detection devices, and visual detection devices. Among them, the cost of ultrasonic detection devices is relatively low, and general materials can be distinguished. The laser detection device can be a distance sensor LDS (Laser Distance Sensor, referred to as LDS) or a direct time of flight sensor dTOF (direct Time OF Flight, referred to as dTOF), which can provide distance information while identifying the material, but the cost of these sensors is usually high. The visual detection device at least includes a camera, and has certain requirements for the focal length of the camera, which may cause the problem of high device cost and the setting position to meet the recognition design requirements. Therefore, among the existing detection devices, ultrasonic detection devices are most likely to be widely used in material identification.

[0100] For example, the ultrasonic detection device mainly includes an ultrasonic transducer, which is a device that can convert input electrical power into mechanical power (i.e., ultrasonic waves) and transmit it out, or convert input mechanical power (i.e., ultrasonic waves) into electrical power. For example, when detecting the material of the ground, ultrasonic waves are mainly emitted to the ground through the ultrasonic transducer, and then the echoes returned from the ground are received. By analyzing the returned echoes, the changes in the electrical signals of the ultrasonic transducer during this period can be obtained.

[0101] The electrical signal may be a discrete digital voltage value. The analog digital converter (ADC) samples at a preset time step t to obtain a series of discrete digital voltage values, such as {V1, V2, V3, ..., Vn}. The difference between the horizontal axes of adjacent Vn and Vn-1 is the time step t. The integral area can be obtained by integration. Therefore, the ADC converts the analog voltage curve into a discrete digital voltage signal.

[0102] Existing ultrasonic detection devices are prone to misjudgment when identifying materials, resulting in poor compatibility and limited application scope. By analyzing the changes in electrical signals in misjudgment situations, it is found that electrical signals are voltage values ​​that change over time. These voltage values ​​will form multiple peaks and troughs. Different materials will form different peaks and troughs. Therefore, by comparing the position information of the peaks, the matching material information can be obtained.

[0103] Figure 1 The following is a schematic diagram of an envelope curve of a carpet material that is misjudged as a floor provided in this embodiment. Figure 1 As shown, the envelope curve has 4 peaks, which are consistent with the echo peak characteristics of the floor, so it will be judged as the floor material. However, the envelope curve is actually the echo peak of the carpet. Therefore, the peak judgment method is not accurate enough.

[0104] Based on the above technical problems, the inventive concept of the present application is to calculate the peak area of ​​the detected envelope curve echo peak of the unknown material, compare it with the peak area of ​​the envelope curve echo peak collected from the known material, and select the known material with the same peak area as the identification result output of the unknown material, aiming to solve the above technical problems of the prior art.

[0105] The specific application scenarios of this application are as follows:

[0106] Figure 2 Schematic diagram of the application scenario of the material recognition method of the cleaning robot provided in the embodiment of the present application. Figure 2As shown, the room 200 is provided with floor conditions of different materials, such as wooden floor 201, ceramic tile 202 and carpet 203. When the sweeping and mopping machine 100 intelligently cleans the room 200, different cleaning actions need to be performed according to different materials. For example, when performing wet cleaning, since the wooden floor 201 is easier to absorb water than the ceramic tile 202, the carpet 203 does not need wet cleaning, otherwise the dirtiness of the carpet 203 will be increased. Therefore, when moving to the wooden floor 201, ceramic tile 202 and carpet 203, it is necessary to determine the type of floor material according to the detection device installed on the sweeping and mopping machine 100, and then control the water output of the sweeping and mopping machine 100 according to the type of material, so that the sweeping and mopping machine 100 can complete the cleaning of multiple materials in one cleaning task, and achieve better cleaning effect.

[0107] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0108] The ultrasonic transducer is driven by the circuit to vibrate and emit ultrasonic waves to the material to be tested. If there is no obstruction between the ultrasonic transducer and the material, and it is all air, after the ultrasonic wave hits the material, it will absorb part of the ultrasonic wave through the material, and the remaining ultrasonic wave will be reflected back to the ultrasonic transducer by the material. The reflected ultrasonic wave is called an echo. The softer the material, the more ultrasonic waves it absorbs and the less ultrasonic waves it reflects back. The harder the material, the more ultrasonic waves it reflects back.

[0109] Figure 3 This is a schematic diagram of the envelope curve of a carpet detected by the ultrasonic detection device provided in the embodiment of the present application. The carpet is made of soft material. When the ultrasonic wave is projected onto the carpet, the soft material will absorb the ultrasonic wave. Therefore, there should be no echo peak in the envelope curve. Figure 3 As shown in the figure, the envelope curve still has two large peaks, which are mainly caused by the vibration generated by the ultrasonic detection device when emitting ultrasonic waves. Figure 3 The first peak shown is the vibration during excitation, and the second peak is the aftershock when excitation is stopped.

[0110] It should be understood that when the stability of the ultrasonic detection device is high, there may be no Figure 3 There are two peaks shown. At this time, the carpet envelope curve detected by the ultrasonic detection device is a curve close to a horizontal state, and there is no peak.

[0111] Figure 4This is a schematic diagram of the envelope curve of a tile detected by the ultrasonic detection device provided in the embodiment of the present application. Tiles are made of hard materials. When ultrasonic waves are directed to tiles, there will be echo peaks in the envelope curve because the hard materials will not absorb ultrasonic waves. Figure 4 As shown, Figure 3 The same envelope curve diagram shown in the figure is a schematic diagram of the tile envelope curve detected by the ultrasonic detection device, based on Figure 3 There are two large non-echo peaks in Figure 4 The first two peaks are also not echo peaks. Therefore, the third peak can be used as the primary echo peak, and the fourth peak, fifth peak, etc. can be used as the secondary echo peak, tertiary echo peak, etc.

[0112] Figure 5 This is a schematic diagram of the envelope curve of a tile containing unexpected energy reflection detected by the ultrasonic detection device provided in an embodiment of the present application. Figure 4 and Figure 5 ,Although the material type detected is the same, the number of peaks is inconsistent, mainly due to the peaks caused by the unexpected ,energy reflection.

[0113] Figure 6 A schematic diagram of a possible scenario of unexpected energy reflection causing a wave peak is provided in an embodiment of the present application. Figure 6 As shown, an ultrasonic detection device 101 is installed at the bottom of the cleaning robot 100. When the ultrasonic detection device 101 transmits ultrasonic waves 102 to the ground 200, they will be reflected back to the ultrasonic detection device 101. However, the ultrasonic waves 102 may first be reflected to the bottom mounting plate of the cleaning robot 100, and then reflected from the bottom mounting plate to the ground again, and then reflected from the ground back to the ultrasonic detection device 101. If the distance from the bottom mounting plate of the cleaning robot 100 to the ground is d, then the ultrasonic wave 102 travels about 2d more than the direct reflection case, which is reflected in the envelope curve as a delay in the reception time of the echo signal, as shown in FIG. Figure 5 Interference peaks are shown within circles.

[0114] Continue to refer to Figure 4 and Figure 5 ,Although the number of peaks is different, the integral area corresponding to the ,overall echo peak is not much different, therefore, the integral area corresponding to the ,peak can be used to distinguish different material types, thereby reducing the ,peak misleading phenomenon caused by unexpected energy reflection.

[0115] Based on the above solution, the present application sets a processor on the cleaning robot, and the processor may include one or more circuits or chips with control functions. For example, the processor is set as a micro-control unit (MCU), and the ADC may be built into the MCU or separated from the MCU.

[0116] The processor is used to control the operation of the floor scrubber and respond to user operations through various software control programs stored in the memory.

[0117] The execution subject of the embodiment of the present application can be a processor in the cleaning robot, or a server corresponding to the cleaning robot. The server is located in the cloud, connected to the processor of the cleaning robot through the network, and issues control instructions to the cleaning robot, or forwards the control instructions sent by the user through the terminal device to the cleaning robot, etc.

[0118] In some embodiments, the cleaning robot is also provided with a storage component, and the processor and the storage component can be arranged inside the cleaning robot. Optionally, the storage component can be integrated with the processor, or can be two independent components of the processor.

[0119] The storage component is used to store data; for example, various software control programs, some modes and / or parameters of the cleaning robot, etc. Specifically, the program may include a program code, and the program code includes a computer operation instruction.

[0120] The following takes the processor in the sweeping and mopping machine as an example to explain the technical solution of the present application and how the technical solution of the present application solves the above technical problems in detail through specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments.

[0121] Exemplary methods for determining the type of ground material using the integrated area include:

[0122] The material type of the target cleaning surface is determined based on the first parameter of the echo signal detected by the detection device.

[0123] The first parameter is used to characterize the integral area of ​​the envelope curve corresponding to the echo signal on the time axis.

[0124] Optionally, the first parameter includes:

[0125] The echo signal corresponds to the integral area of ​​the envelope curve with respect to the time axis;

[0126] Alternatively, the echo signal corresponds to the incremental percentage of the integrated area of ​​the envelope curve with respect to the time axis.

[0127] Specifically, the integral area is calculated mainly by multiplying the voltage corresponding to the discrete digital voltage value by the time step. For example, if the discrete digital voltage value is {V1, V2, V3, ..., Vn}, the area can be calculated as: S = V1*t + V2*t + V3*t + ... + Vn*t. The smaller the step length t, the closer the obtained S value is to the area of ​​the true curve.

[0128] Therefore, the size of the integral area calculated within the same time range is limited to the peak value, and accordingly, the obtained integral area corresponds to the acquisition of the time period.

[0129] It should be understood that when using the integral area of ​​the envelope curve of a known material type to determine the integral area of ​​the envelope curve of an unknown type to the time axis, it is necessary to limit it to the same time period to have a reference basis. The start and end time of the time period can be selected by referring to the following methods:

[0130] Method 1: The integrated area is determined based on 2 echoes.

[0131] For example, the integral area of ​​the continuous curve segment corresponding to the peak of any first echo of at least two echoes to the end point of the second echo;

[0132] For another example, the integral area of ​​the continuous curve segment corresponding to the starting point of any first echo of the two echoes to the ending point of the second echo.

[0133] Optionally, the two echoes select the continuous curve segment integral area corresponding to the first echo and the second echo with stronger echo signals. Since the first two echoes have higher intensities, the corresponding integral areas are also larger, so it is easier to obtain the integral area corresponding to the preset material category, making the recognition result more accurate.

[0134] The method of this embodiment is to limit the front and rear positions of the echo. Since the waveform includes the starting point, peak and end point of the echo, when limiting the number of echoes, the starting point and end point of the area integral can be limited by the position of the waveform. It is only necessary to make the starting point and end point of the actually detected integral area correspond one by one with the starting point and end point of the integral area corresponding to the preset material category.

[0135] Mode 2: The integrated area is determined based on at least two echoes.

[0136] For example, the integral area of ​​the continuous curve segment corresponding to the peak of the first echo to the peak of the last echo among the three echoes;

[0137] Or, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo of the three echoes to the peak of the last echo;

[0138] Or, the integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the three echoes to the end point of the last echo;

[0139] Alternatively, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo of the three echoes to the ending point of the last echo.

[0140] Optionally, the three echoes are selected as the first echo, the second echo and the third echo with stronger echo signals. The stronger the echo signal, the larger the corresponding peak area, which can make the recognition result more accurate.

[0141] Method 3: The integrated area is determined based on all echo signals.

[0142] During the ultrasonic emission process, there may be peaks caused by unexpected energy reflections such as vibrations during excitation and aftershocks when the excitation stops, and these fluctuations themselves have nothing to do with the material. However, when the reference preset material category comparison includes all peak integral areas, all peak areas obviously include the integral area of ​​this part. That is, it is not enough to only use the integral area of ​​the echo in the above embodiment, and it is necessary to further expand the starting and ending points of the integral area so that all echo signals are included.

[0143] In some embodiments, in addition to the above-mentioned integral area calculation method, the calculated integral area may also be processed for accuracy by a normalization method.

[0144] Figure 7 The following is a flow chart of the normalization processing method provided in the embodiment of the present application. Figure 7 As shown, the normalization methods include:

[0145] S701: Obtain the integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis.

[0146] S702: Determine a first integral difference value according to a difference between an integral area of ​​an envelope curve corresponding to the echo signal on the time axis and a preset first integral area.

[0147] The preset first integral area is the integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the completely absorbed target cleaning surface on the time axis.

[0148] S703: Determine a second integral difference value according to a difference between a preset second integral area and a preset first integral area.

[0149] The preset second integral area is the integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the completely non-absorbent target clean surface on the time axis.

[0150] S704: Obtain a normalized value according to a ratio of the first integral difference to the second integral difference.

[0151] Specifically, the detection device detects the echo signal of the target clean surface of unknown material. The integral area of ​​the envelope curve on the time axis is, and the normalized value P can be calculated using the following formula:

[0152]

[0153] In the formula, the integral area of ​​the envelope curve corresponding to the echo signal of the target clean surface of unknown material on the time axis is S, the preset first integral area is F, and the preset second integral area is C.

[0154] Figure 8 This is a schematic diagram of the processor structure of the cleaning robot provided in the embodiment of the present application. Figure 8 As shown, the processor includes:

[0155] An acquisition module 801 is used to acquire the echo signal detected by the detection device;

[0156] The processing module 802 is used to determine the material type of the target cleaning surface based on the first parameter of the echo signal detected by the detection device; wherein the first parameter is used to characterize the integral area size of the envelope curve corresponding to the echo signal on the time axis.

[0157] In a possible implementation, the first parameter includes:

[0158] The echo signal corresponds to the integral area of ​​the envelope curve with respect to the time axis;

[0159] Alternatively, the echo signal corresponds to the incremental percentage of the integrated area of ​​the envelope curve with respect to the time axis.

[0160] In a possible implementation manner, the integrated area is determined based on M echoes, where M is greater than or equal to 2.

[0161] In a possible implementation, the integrated area includes:

[0162] The integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the second echo;

[0163] Alternatively, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo and the ending point of the second echo among the M echoes is calculated.

[0164] In a possible implementation manner, the M echoes include a primary echo and a secondary echo.

[0165] In a possible implementation manner, M is greater than 2, and the integrated area includes:

[0166] The integral area of ​​the continuous curve segment corresponding to the peak of the first echo to the peak of the last echo among the M echoes;

[0167] Or, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo of the M echoes to the peak of the last echo;

[0168] Or, the integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the last echo;

[0169] Alternatively, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo to the ending point of the last echo among the M echoes.

[0170] In a possible implementation manner, the M echoes include a primary echo, a secondary echo, and a tertiary echo.

[0171] In a possible implementation, the integrated area is determined based on all echo signals.

[0172] In a possible implementation manner, the first parameter includes: an increment percentage; the processing module 802 is specifically configured to:

[0173] Obtaining the integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis;

[0174] The integral area of ​​the envelope curve corresponding to the echo signal on the time axis is normalized to obtain the increment percentage.

[0175] Optionally, the processing module 802 is specifically configured to:

[0176] Determine a first integral difference value according to a difference between an integral area of ​​the envelope curve corresponding to the echo signal on the time axis and a preset first integral area; wherein the preset first integral area is an integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the fully absorbed target cleaning surface on the time axis;

[0177] Determine a second integral difference value according to the difference between a preset second integral area and a preset first integral area; wherein the preset second integral area is the integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the completely non-absorbent target clean surface on the time axis;

[0178] A normalized value is obtained according to the ratio of the first integral difference value to the second integral difference value.

[0179] Fig. 9 This is a schematic diagram of the hardware structure of the cleaning robot provided in the embodiment of the present application. Fig. 9 As shown, the cleaning robot comprises:

[0180] A detection device 901, a processor 902 communicatively connected to the detection device 901, and a memory 903 communicatively connected to the processor 902;

[0181] The detection device 901 is used to transmit ultrasonic signals to the target cleaning surface and receive echo signals returned by the target cleaning surface;

[0182] The memory 903 is used to store computer-executable instructions;

[0183] The processor 902 is used to execute the computer execution instructions stored in the memory 903 based on the detection results of the detection device 901 to implement the robot control method.

[0184] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0185] The memory may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk storage.

[0186] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of this application is not limited to only one bus or one type of bus.

[0187] The above describes the solutions provided by the embodiments of the present invention with respect to the functions implemented by the electronic device and the main control device.

[0188] It is understandable that, in order to realize the above functions, the electronic device or the main control device includes the corresponding hardware structure and / or software module for executing each function.

[0189] In combination with the units and algorithm steps of each example described in the embodiment disclosed in the embodiment of the present invention, the embodiment of the present invention can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the technical solution of the embodiment of the present invention.

[0190] The present application also provides a computer program product, including a computer program, which implements a robot control method when executed by a processor.

[0191] The computer program product provided in this embodiment can execute the robot control method of the above-mentioned embodiment. Its implementation principle and technical effect are similar, and this embodiment will not be repeated here.

[0192] The present application also provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, the control method of the robot as described above is implemented.

[0193] The computer-readable storage medium provided in this embodiment can execute the robot control method of the above-mentioned embodiment, and its implementation principle and technical effect are similar, which will not be described in detail in this embodiment.

[0194] The present application also provides a cleaning system, which includes a cleaning robot 100 and a user terminal 300, wherein the cleaning robot 100 is communicatively connected with the user terminal 300;

[0195] The cleaning robot 100 is further configured to send material information of the target cleaning surface to the user terminal 300 based on the determined material category of the target cleaning surface.

[0196] Optionally, the material information of the target cleaning surface is displayed on the user terminal 300 in at least one of the following ways:

[0197] Text information of the material, or image information of the material, or voice information of the material.

[0198] The computer-readable storage medium mentioned above may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The readable storage medium may be any available medium that can be accessed by a general or special-purpose computer.

[0199] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in an electronic device or a main control device.

[0200] Those skilled in the art can understand that all or part of the steps of implementing the above-mentioned method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, the steps of the above-mentioned method embodiments are executed; and the aforementioned storage medium includes: ROM, RAM, disk or optical disk and other media that can store program codes.

[0201] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0202] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A material recognition method for a cleaning robot, characterized in that: The robot includes a detection device, which is used to transmit an ultrasonic signal to a target cleaning surface and receive an echo signal returned by the target cleaning surface; the method includes: The material category of the target cleaning surface is determined based on a first parameter of the echo signal detected by the detection device; wherein the first parameter is used to characterize the integral area size of the envelope curve corresponding to the echo signal on the time axis.

2. The method according to claim 1, characterized in that The first parameter includes: The integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis; Alternatively, the echo signal corresponds to the incremental percentage of the integral area of ​​the envelope curve on the time axis.

3. The method according to claim 2, characterized in that The integrated area is determined based on M echoes, where M is greater than or equal to 2.

4. The method according to claim 3, characterized in that The integral area includes: The integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the second echo; Alternatively, the integrated area of ​​the continuous curve segment corresponding to the starting point of the first echo and the ending point of the second echo among the M echoes.

5. The method according to claim 4, characterized in that The M echoes include a primary echo and a secondary echo.

6. The method according to claim 3, characterized in that: The M is greater than 2, and the integral area includes: The integral area of ​​the continuous curve segment corresponding to the peak of the first echo to the peak of the last echo among the M echoes; Or, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo of the M echoes to the peak of the last echo; Or, the integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the last echo; Alternatively, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo to the ending point of the last echo among the M echoes.

7. The method according to claim 6, characterized in that The M echoes include a primary echo, a secondary echo and a tertiary echo.

8. The method according to claim 2, characterized in that: The integrated area is determined based on all echo signals.

9. The method according to claim 2, characterized in that: The first parameter includes: an increment percentage; the method further includes: Obtaining the integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis; The integral area of ​​the envelope curve corresponding to the echo signal on the time axis is normalized to obtain the increment percentage.

10. The method according to claim 9, characterized in that The normalizing of the integral area of ​​the envelope curve corresponding to the echo signal on the time axis includes: Determine a first integral difference value according to a difference between an integral area of ​​the envelope curve corresponding to the echo signal on the time axis and a preset first integral area; wherein the preset first integral area is an integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the fully absorbed target cleaning surface on the time axis; Determine a second integral difference value according to the difference between a preset second integral area and a preset first integral area; wherein the preset second integral area is the integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the completely non-absorbent target cleaning surface on the time axis; A normalized value is obtained according to the ratio of the first integral difference value to the second integral difference value.

11. A processor for a cleaning robot, characterized in that: The robot comprises a detection device, wherein the detection device is communicatively connected to the processor; The detection device is used to transmit ultrasonic signals to the target cleaning surface and receive echo signals returned by the target cleaning surface; The processor comprises: An acquisition module, used for acquiring the echo signal detected by the detection device; A processing module is used to determine the material category of the target cleaning surface based on a first parameter of the echo signal detected by the detection device; wherein the first parameter is used to characterize the integral area size of the envelope curve corresponding to the echo signal on the time axis.

12. The processor according to claim 11, characterized in that The first parameter includes: The integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis; Alternatively, the echo signal corresponds to the incremental percentage of the integral area of ​​the envelope curve on the time axis.

13. The processor according to claim 12, characterized in that The integrated area is determined based on M echoes, where M is greater than or equal to 2.

14. The processor according to claim 13, characterized in that The integral area includes: The integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the second echo; Alternatively, the integrated area of ​​the continuous curve segment corresponding to the starting point of the first echo and the ending point of the second echo among the M echoes.

15. The processor according to claim 14, characterized in that The M echoes include a primary echo and a secondary echo.

16. The processor according to claim 15, characterized in that The M is greater than 2, and the integral area includes: The integral area of ​​the continuous curve segment corresponding to the peak of the first echo to the peak of the last echo among the M echoes; Or, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo of the M echoes to the peak of the last echo; Or, the integral area of ​​the continuous curve segment corresponding to the peak of the first echo of the M echoes to the end point of the last echo; Alternatively, the integral area of ​​the continuous curve segment corresponding to the starting point of the first echo to the ending point of the last echo among the M echoes.

17. The processor according to claim 16, characterized in that The M echoes include a primary echo, a secondary echo and a tertiary echo.

18. The processor according to claim 12, wherein: The integrated area is determined based on all echo signals.

19. The processor according to claim 12, wherein: The first parameter includes: an increment percentage; the method further includes: Obtaining the integral area of ​​the envelope curve corresponding to the echo signal with respect to the time axis; The integral area of ​​the envelope curve corresponding to the echo signal on the time axis is normalized to obtain the increment percentage.

20. The processor according to claim 19, characterized in that The normalizing of the integral area of ​​the envelope curve corresponding to the echo signal on the time axis includes: Determine a first integral difference value according to a difference between an integral area of ​​the envelope curve corresponding to the echo signal on the time axis and a preset first integral area; wherein the preset first integral area is an integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the fully absorbed target cleaning surface on the time axis; Determine a second integral difference value according to the difference between a preset second integral area and a preset first integral area; wherein the preset second integral area is the integral area of ​​the envelope curve corresponding to the echo signal sent and received by the detection device to the completely non-absorbent target cleaning surface on the time axis; A normalized value is obtained according to the ratio of the first integral difference value to the second integral difference value.

21. A control method for a cleaning robot, characterized in that: The robot includes a detection device, which is used to transmit an ultrasonic signal to a target cleaning surface and receive an echo signal returned by the target cleaning surface; the method includes: In the process of performing a target task on a target cleaning surface, determining a material category of the target cleaning surface based on the material recognition method described in any one of claims 1 to 10; the target task at least includes a cleaning task or a mapping task; Based on the material category of the target cleaning surface, a target task is performed on the target cleaning surface.

22. A cleaning robot, characterized in that: The robot includes a detection device, a processor communicatively connected to the detection device, and a memory communicatively connected to the processor; The detection device is used to transmit ultrasonic signals to the target cleaning surface and receive echo signals returned by the target cleaning surface; The memory is used to store computer-executable instructions; The processor is used to execute the computer-executable instructions stored in the memory based on the detection results of the detection device to implement the robot control method as described in claim 21.

23. A cleaning system, characterized in that: The cleaning system comprises the cleaning robot as claimed in claim 22 and a user terminal, wherein the robot is communicatively connected with the user terminal; The robot is further configured to send material information of the target cleaning surface to the user terminal based on the determined material category of the target cleaning surface.

24. The cleaning system according to claim 23, characterized in that The material information of the target cleaning surface is displayed on the user terminal in at least one of the following ways: Text information of the material, or image information of the material, or voice information of the material.

Images