Cleaning robot and material identification method and control method therefor, processor, and cleaning system
By calculating the integral area of the envelope curve of the echo signal, the problem of wave peak interference caused by unexpected energy reflection in ultrasonic detection devices was solved, enabling more accurate material identification and more efficient cleaning operations.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- DREAM INNOVATION TECH (SUZHOU) CO LTD
- Filing Date
- 2025-11-21
- Publication Date
- 2026-06-11
Smart Images
Figure CN2025136933_11062026_PF_FP_ABST
Abstract
Description
Cleaning robots and their material recognition, control methods, processors and cleaning systems
[0001] This application claims priority to Chinese Patent Application No. 202411776938.2, filed on December 4, 2024, entitled "Cleaning Robot and Material Identification, Control Method, Processor and Cleaning System thereof", the entire contents of which are incorporated herein by reference. Technical Field
[0002] This application relates to the field of intelligent robot technology, and in particular to a cleaning robot and its material recognition, control method, processor and cleaning system. Background Technology
[0003] When autonomous mobile robots are working, they usually use detection devices to detect obstacles or the material information of the target clean surface in their travel path. The most commonly used detection device is the ultrasonic detection device.
[0004] Existing ultrasonic detection devices typically emit and receive ultrasonic waves at obstacles or target clean surfaces, then process and convert the ultrasonic waves to obtain a simulated voltage curve that changes over time. Since different materials will produce simulated voltage curves of different shapes, the type of obstacle or target clean surface can be determined by using the peaks in the simulated voltage curve.
[0005] However, the echoes generated by the above methods may contain peaks caused by unexpected energy reflections, making it impossible to accurately determine the voltage value of the echo peaks and resulting in inaccurate identification of the ground material. Summary of the Invention
[0006] This application provides a cleaning robot and its material identification and control method, processor and cleaning system, which are used to achieve the effect that the echo may have a peak caused by unexpected energy reflection, which makes it impossible to accurately determine the voltage value of the echo peak and causes inaccurate identification of the ground material.
[0007] In a first aspect, this application provides a material identification method for a cleaning robot, the robot including a detection device for emitting ultrasonic signals toward a target cleaning surface and receiving echo signals returned from the target cleaning surface; the method includes:
[0008] The material type of the target clean 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 of the envelope curve corresponding to the echo signal with respect to the time axis.
[0009] The present application uses the integral area corresponding to the envelope curve of the ultrasonic wave to compare with the preset material category corresponding to the preset integral area in order to determine the material category corresponding to the curve formed by the current ultrasonic wave. Compared with determination methods such as peaks or troughs, it can reduce the influence of interference peaks on the determination results, thereby improving the accuracy of material determination.
[0010] In one possible implementation, the first parameter includes:
[0011] The area of the envelope curve corresponding to the echo signal integrated over the time axis;
[0012] Alternatively, the percentage increment corresponding to the integral area of the envelope curve of the echo signal with respect to the time axis.
[0013] This embodiment limits the specific area parameters used to determine the material category. The area parameters can be the area corresponding to the curve graph directly calculated to obtain the area corresponding to the curve graph of the same material, or they can be based on the normalized area corresponding to the curve graph to reduce the degree of difference in the area corresponding to different materials and improve the accuracy of the detection results.
[0014] In one possible implementation, the integral area is determined based on M echoes, where M is greater than or equal to 2.
[0015] This embodiment defines the integration region of the envelope curve. Generally, the larger the integration area, the higher the accuracy of material category matching. Since the envelope curve is mainly determined by the number of echoes, the more echoes, the larger the corresponding integration area. Therefore, the size of the integration area used for determination can be limited by limiting the number of echoes.
[0016] In one possible implementation, the integral area includes:
[0017] The area of the continuous curve segment between the crest of the first echo and the end point of the second echo out of M echoes;
[0018] Alternatively, the area of the continuous curve segment between the starting point of the first echo and the ending point of the second echo out of the M echoes.
[0019] In this embodiment, the position of the echo is defined. Since the waveform includes the start point, peak and end point of the echo, the start point and end point of the area integration can be defined by the position of the waveform when limiting the number of echoes. It is only necessary to match the start point and end point of the actual detected integrated area with the start point and end point of the integrated area corresponding to the preset material category.
[0020] In one possible implementation, the M echoes include primary echoes and secondary echoes.
[0021] Since the first two echoes have higher intensities, the corresponding integral areas are also larger, making it easier to obtain the integral area corresponding to the preset material category, thus making the recognition results more accurate.
[0022] In one possible implementation, M is greater than 2, and the integral area includes:
[0023] The area of the continuous curve segment between the peak of the first echo and the peak of the last echo out of M echoes;
[0024] Alternatively, the area of the continuous curve segment from the starting point of the first echo in the M echoes to the peak of the last echo.
[0025] Alternatively, the area of the continuous curve segment from the crest of the first echo to the end point of the last echo out of the M echoes;
[0026] Alternatively, the area of the continuous curve segment corresponding to the starting point of the first echo and the ending point of the last echo out of the M echoes.
[0027] This embodiment defines how to select the integral area corresponding to the echo when there are more than two echoes. It is similar to the case of two echoes, except that the length range of the start and end points of the integral area is expanded. The preset material category used as a reference also needs to be expanded to the size of the integral area corresponding to the start and end point positions.
[0028] In one possible implementation, the M echoes include a first echo, a second echo, and a third echo.
[0029] Using the integral area corresponding to three echoes can improve the accuracy of identification. Compared with the method of determining the material by using the integral area of only two echoes, it can further reduce the interference of noise peaks such as ultrasonic aftershocks in the previous echoes and improve the accuracy of the judgment result.
[0030] In one possible implementation, the integral area is determined based on all echo signals.
[0031] During the transmission of ultrasound, unexpected energy reflections, such as vibrations during excitation and aftershocks when excitation stops, may cause wave peaks to be collected. These fluctuations are independent of the material itself. However, when the reference preset material category comparison includes the integral area of all peaks, the integral area of all peaks obviously includes this part. That is, in the above embodiment, it is not enough to use only the integral area of the echo. It is necessary to further expand the starting and ending points of the integral area so that all echo signals are included.
[0032] In one possible implementation, the first parameter includes: an incremental percentage; the method further includes:
[0033] Obtain the area of the envelope curve corresponding to the echo signal integrated with respect to the time axis;
[0034] The integral area of the envelope curve corresponding to the echo signal with respect to the time axis is normalized to obtain the increment percentage.
[0035] The method in this embodiment further defines how to determine the incremental percentage of the integrated area. By converting the absolute value of the area into a normalized percentage, the accuracy of the obtained integrated area can be further improved, and the reliability of the material determination result can be increased.
[0036] In one possible implementation, normalizing the integral area of the envelope curve corresponding to the echo signal with respect to the time axis includes:
[0037] The first integral difference value is determined based on the difference between the integral area of the envelope curve corresponding to the echo signal with respect to the time axis and the preset first integral area; wherein, 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 target clean surface that is completely absorbed with respect to the time axis.
[0038] The second integral difference is determined based on the difference between the preset second integral area and the 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 target clean surface that does not absorb at all, over the time axis.
[0039] The normalized value is obtained by comparing the ratio of the first integral difference to the second integral difference.
[0040] This embodiment specifically defines how to perform normalization processing, and limits it to normalization processing under the same conditions of complete absorption and complete non-absorption of ultrasonic waves. The processing method is relatively reliable, thereby improving the credibility of the material determination results.
[0041] Secondly, this application provides a processor for a cleaning robot, the robot including a detection device, the detection device and the processor being communicatively connected;
[0042] The detection device is used to transmit ultrasonic signals to the target clean surface and receive the echo signals returned by the target clean surface.
[0043] The processor includes:
[0044] An acquisition module is used to acquire the echo signal detected by the detection device;
[0045] The processing module is used to determine the material type of the target clean 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 of the envelope curve corresponding to the echo signal with respect to the time axis.
[0046] In one possible implementation, the first parameter includes:
[0047] The area of the envelope curve corresponding to the echo signal integrated over the time axis;
[0048] Alternatively, the percentage increment corresponding to the integral area of the envelope curve of the echo signal with respect to the time axis.
[0049] In one possible implementation, the integral area is determined based on M echoes, where M is greater than or equal to 2.
[0050] In one possible implementation, the integral area includes:
[0051] The area of the continuous curve segment between the crest of the first echo and the end point of the second echo out of M echoes;
[0052] Alternatively, the area of the continuous curve segment between the starting point of the first echo and the ending point of the second echo out of the M echoes.
[0053] In one possible implementation, the M echoes include primary echoes and secondary echoes.
[0054] In one possible implementation, M is greater than 2, and the integral area includes:
[0055] The area of the continuous curve segment between the peak of the first echo and the peak of the last echo out of M echoes;
[0056] Alternatively, the area of the continuous curve segment from the starting point of the first echo in the M echoes to the peak of the last echo.
[0057] Alternatively, the area of the continuous curve segment from the crest of the first echo to the end point of the last echo out of the M echoes;
[0058] Alternatively, the area of the continuous curve segment corresponding to the starting point of the first echo and the ending point of the last echo out of the M echoes.
[0059] In one possible implementation, the M echoes include a first echo, a second echo, and a third echo.
[0060] In one possible implementation, the integral area is determined based on all echo signals.
[0061] In one possible implementation, the first parameter includes: an incremental percentage; the method further includes:
[0062] Obtain the area of the envelope curve corresponding to the echo signal integrated with respect to the time axis;
[0063] The integral area of the envelope curve corresponding to the echo signal with respect to the time axis is normalized to obtain the increment percentage.
[0064] In one possible implementation, normalizing the integral area of the envelope curve corresponding to the echo signal with respect to the time axis includes:
[0065] The first integral difference value is determined based on the difference between the integral area of the envelope curve corresponding to the echo signal with respect to the time axis and the preset first integral area; wherein, 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 target clean surface that is completely absorbed with respect to the time axis.
[0066] The second integral difference is determined based on the difference between the preset second integral area and the 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 target clean surface that does not absorb at all, over the time axis.
[0067] The normalized value is obtained by comparing the ratio of the first integral difference to the second integral difference.
[0068] Thirdly, this application provides a control method for a cleaning robot, the robot including a detection device for emitting ultrasonic signals toward a target cleaning surface and receiving echo signals returned from the target cleaning surface; the method includes:
[0069] During the execution of the target task on the target cleaning surface, the material category of the target cleaning surface is determined based on the material identification method of the cleaning robot described above; the target task includes at least a cleaning task or a mapping task.
[0070] Based on the material type of the target cleaning surface, perform the target cleaning task on the target cleaning surface.
[0071] Fourthly, this application provides a cleaning robot, the robot including a detection device, a processor communicatively connected to the detection device, and a memory communicatively connected to the processor;
[0072] The detection device is used to transmit ultrasonic signals to the target clean surface and receive the echo signals returned by the target clean surface.
[0073] The memory is used to store computer-executed instructions;
[0074] The processor is used to execute computer execution instructions stored in the memory based on the detection results of the detection device, so as to realize the robot control method.
[0075] Fifthly, this application provides a cleaning system, which includes a cleaning robot and a user terminal, wherein the robot is communicatively connected to the user terminal;
[0076] The robot is also used to send material information of the target cleaning surface to the user terminal based on the determined material category of the target cleaning surface.
[0077] In one possible implementation, the material information of the target cleaning surface is displayed on the user terminal in at least one of the following ways:
[0078] The material's textual information, or the material's image information, or the material's audio information.
[0079] Sixthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a robot control method.
[0080] In a seventh aspect, this application provides a computer program product, including a computer program that, when executed by a processor, implements a robot control method.
[0081] The cleaning robot, its material identification and control method, processor, and cleaning system provided in this application determine the material category of the target cleaning surface by using a first parameter based on the echo signal detected by the detection device. The first parameter characterizes the integral area of the envelope curve corresponding to the echo signal over the time axis. Compared to the shortcomings of existing technologies that determine material categories by the number of peaks or troughs, this application utilizes the integral area of the echo peaks to reduce the peak integral area caused by unexpected energy reflection, thereby reducing the influence of interference peaks on the determination result and improving the accuracy of material determination. Attached Figure Description
[0082] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0083] Figure 1 is a schematic diagram of the envelope curve of a carpet material being misidentified as flooring in this embodiment;
[0084] Figure 2 is a schematic diagram of the application scenario of the material identification method for cleaning robots provided in the embodiments of this application;
[0085] Figure 3 is a schematic diagram of the carpet envelope curve detected by the ultrasonic detection device provided in the embodiment of this application;
[0086] Figure 4 is a schematic diagram of the envelope curve of the ceramic tile detected by the ultrasonic detection device provided in the embodiment of this application;
[0087] Figure 5 is a schematic diagram of the envelope curve of a ceramic tile containing unexpected energy reflection detected by the ultrasonic detection device provided in the embodiment of this application;
[0088] Figure 6 is a schematic diagram of a possible scenario where unexpected energy reflection causes a wave peak, as provided in an embodiment of this application.
[0089] Figure 7 is a schematic flowchart of the normalization processing method provided in the embodiment of this application;
[0090] Figure 8 is a schematic diagram of the processor structure of the cleaning robot provided in an embodiment of this application;
[0091] Figure 9 is a schematic diagram of the hardware structure of the cleaning robot provided in the embodiment of this application;
[0092] Figure 10 is a schematic diagram of the cleaning system structure provided in an embodiment of this application.
[0093] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation
[0094] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.
[0095] Autonomous cleaning robots need to traverse the target cleaning area along their path to improve cleaning efficiency and ensure no area is missed. In this application, the cleaning robot has self-moving capabilities, including but not limited to robotic vacuum cleaners, sweeping robots, and combined sweeping and mopping robots.
[0096] Taking a robot vacuum cleaner as an example, different cleaning strategies need to be applied to different floor materials when cleaning a room.
[0097] For example, carpets have stronger adhesion to dirt, requiring greater suction power. It's also best to avoid wet cleaning carpets, as this can worsen the soiling. While suction power settings may not differ between solid wood and tile floors, solid wood floors can absorb water and deteriorate. Therefore, when wet cleaning both types of wood, measures such as reducing the amount of water sprayed should be taken to minimize the adverse effects of wet cleaning on solid wood floors.
[0098] Therefore, cleaning robots need to identify the material of the area to be cleaned before cleaning to determine the appropriate cleaning mode and improve cleaning quality.
[0099] It should be understood that "before cleaning" here refers to the period before actual cleaning, including but not limited to the mapping period of the cleaning robot and the moment before the actual cleaning by the cleaning robot.
[0100] Current methods for identifying ground materials primarily utilize detection devices. These devices include, but are not limited to, ultrasonic detectors, laser detectors, and visual detectors. Among these, ultrasonic detectors are relatively inexpensive and can distinguish most materials. Laser detectors can be range sensors (LDS) or direct time-of-flight (dTOF) sensors, providing distance information while identifying materials; however, these sensors are typically expensive. Visual detectors require at least a camera and have specific focal length requirements, which can lead to higher costs and challenges in placement to meet design requirements. Therefore, among existing detection devices, ultrasonic detectors are the most widely used for material identification.
[0101] For example, an 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, or it can convert input mechanical power (i.e., ultrasonic waves) into electrical power. For instance, when detecting ground materials, the ultrasonic transducer emits ultrasonic waves into the ground and then receives the echoes returned from the ground. By analyzing the returned echoes, the changes in the electrical signal of the ultrasonic transducer during this period can be obtained.
[0102] The electrical signal can be a discrete digital voltage value. The analog-to-digital converter (ADC) samples the voltage 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 area of integration can be obtained by integration. Therefore, the ADC converts the analog voltage curve into a discrete digital voltage signal.
[0103] Existing ultrasonic detection devices are prone to misidentification when identifying materials, resulting in poor compatibility and limited application range. Analysis of the electrical signal changes in these misidentification scenarios reveals that the electrical signal is a voltage value that varies over time, forming multiple peaks and troughs. Different materials exhibit different peaks and troughs; therefore, by comparing the positional information of the peaks, the corresponding material information can be obtained.
[0104] Figure 1 is a schematic diagram of the envelope curve of a carpet material being misidentified as flooring in this embodiment. As shown in Figure 1, the envelope curve has four peaks, which match the echo peak characteristics of flooring, and therefore it is identified as flooring material. However, the envelope curve is actually the echo peak of carpet. Therefore, the peak-based identification method is not accurate enough.
[0105] Based on the above-mentioned technical problems, the inventive concept of this application is: by calculating the peak area of the envelope curve echo peak of the detected unknown material, comparing it with the peak area of the envelope curve echo peak of the known material, and selecting the known material with the same peak area as the identification result of the unknown material, the invention aims to solve the above-mentioned technical problems of the prior art.
[0106] The specific application scenarios for this application are as follows:
[0107] Figure 2 is a schematic diagram of the application scenario of the material recognition method for the cleaning robot provided in this application embodiment. As shown in Figure 2, the room 200 has different floor materials, such as wooden floor 201, tile 202, and carpet 203. When the robot vacuum and mop 100 intelligently cleans the room 200, it needs to perform different cleaning actions according to different materials. For example, when performing wet cleaning, wooden floor 201 absorbs water more easily than tile 202, while carpet 203 does not require wet cleaning, otherwise it would increase the degree of dirt on carpet 203. Therefore, when moving to wooden floor 201, tile 202, and carpet 203, it is necessary to determine the type of floor material according to the detection device installed on the robot vacuum and mop 100, and then control the water output of the robot vacuum and mop 100 according to the type of material, so that the robot vacuum and mop 100 can complete the cleaning of multiple materials in one cleaning task and achieve better cleaning results.
[0108] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.
[0109] An ultrasonic transducer vibrates, driven by a circuit, and emits ultrasonic waves towards the material being tested. If there is no obstruction between the ultrasonic transducer and the material, and only air, the ultrasonic waves will be partially absorbed by the material after hitting it, and the remaining ultrasonic waves will be reflected back to the ultrasonic transducer. The reflected ultrasonic waves are called echoes. 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.
[0110] Figure 3 is a schematic diagram of the carpet envelope curve detected by the ultrasonic detection device provided in this embodiment. The carpet is a soft material; after ultrasonic waves are emitted towards it, the soft material absorbs the waves, so there should be no echo peak in the envelope curve. However, as shown in Figure 3, the envelope curve still has two large peaks. This is mainly due to the vibration generated by the ultrasonic detection device when emitting ultrasonic waves. For example, the first peak shown in Figure 3 is the vibration during excitation, and the second peak is the aftershock when excitation stops.
[0111] It should be understood that when the ultrasonic detection device is highly stable, the two peaks shown in Figure 3 may not exist. In this case, the carpet envelope curve detected by the ultrasonic detection device is a nearly horizontal curve without peaks.
[0112] Figure 4 is a schematic diagram of the envelope curve of a ceramic tile detected by the ultrasonic detection device provided in this embodiment. Ceramic tiles are hard materials; when ultrasonic waves are emitted towards them, they do not absorb the waves, resulting in echo peaks in the envelope curve. As shown in Figure 4, which is a schematic diagram of the ceramic tile envelope curve detected by the same ultrasonic detection device as the one shown in Figure 3, and considering that there are two large non-echo peaks in Figure 3, and the first two peaks in Figure 4 are also non-echo peaks, the third peak can be considered as the first echo peak, and the fourth, fifth, and so on, as the second, third, and so on.
[0113] Figure 5 is a schematic diagram of the envelope curve of a ceramic tile containing unexpected energy reflection detected by the ultrasonic detection device provided in the embodiment of this application. Comparing Figure 4 and Figure 5, although the detected material type is the same, the number of peaks is different, mainly due to the peaks caused by unexpected energy reflection.
[0114] Figure 6 is a schematic diagram of a possible scenario where an unexpected energy reflection causes a wave peak, as provided in an embodiment of this application. As shown in Figure 6, an ultrasonic detection device 101 is installed on the bottom of the cleaning robot 100. When the ultrasonic detection device 101 emits an ultrasonic wave 102 to the ground 200, it will be reflected back to the ultrasonic detection device 101. However, the ultrasonic wave 102 may first reflect onto the bottom mounting plate of the cleaning robot 100, then reflect again from the bottom mounting plate to the ground, and then reflect back to the ultrasonic detection device 101 from the ground. If the distance from the bottom mounting plate of the cleaning robot 100 to the ground is d, then the ultrasonic wave 102 travels a distance of about 2d longer than in the case of direct reflection. This is reflected in the envelope curve as a delay in the echo signal reception time, as shown by the interference peak within the circle in Figure 5.
[0115] Referring to Figures 4 and 5, although the number of peaks differs, the integral area corresponding to the overall echo peaks is not significantly different. Therefore, the integral area corresponding to the peaks can be used to distinguish different material types, thereby reducing the peak misleading phenomenon caused by unexpected energy reflection.
[0116] Based on the above solution, this application incorporates a processor into the cleaning robot. The processor may include one or more circuits or chips with control functions. For example, the processor may be configured as a micro-control unit (MCU), and the ADC may be built into the MCU or separated from the MCU.
[0117] The processor is used to control the operation of the floor scrubber and respond to user operations through various software control programs stored in memory.
[0118] The execution entity in this application embodiment can be the processor in the cleaning robot or the server corresponding to the cleaning robot. The server is located in the cloud and is connected to the processor of the cleaning robot through a network to issue control commands to the cleaning robot, or to forward control commands sent by the user through a terminal device to the cleaning robot, etc.
[0119] In some embodiments, the cleaning robot also includes a storage component, and the processor and storage component may be located inside the cleaning robot. Optionally, the storage component may be integrated with the processor, or they may be two separate components.
[0120] Storage components are used to store data; for example, various software control programs, patterns and / or parameters of cleaning robots, etc. Specifically, programs may include program code, which includes computer operation instructions.
[0121] The following uses the processor in a robot vacuum cleaner as an example to illustrate the technical solution of this application and how it solves the aforementioned technical problems through specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.
[0122] For example, methods for determining the type of ground material using integrated area include:
[0123] The material type of the target clean surface is determined based on the first parameter of the echo signal detected by the detection device.
[0124] The first parameter is used to characterize the size of the integral area of the envelope curve corresponding to the echo signal with respect to the time axis.
[0125] Optionally, the first parameter includes:
[0126] The echo signal corresponds to the area of the envelope curve integrated over the time axis;
[0127] Alternatively, the percentage increment corresponding to the integral area of the envelope curve of the echo signal with respect to the time axis.
[0128] Specifically, the integral area is mainly calculated by multiplying the voltage corresponding to the discrete digital voltage value with 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 t is, the closer the obtained S value is to the area of the true curve.
[0129] Therefore, the size of the integral area calculated within the same time range is limited to the peak value, and correspondingly, the obtained integral area corresponds to the acquisition of the time period.
[0130] It should be understood that when determining the integral area of an envelope curve of an unknown type across the time axis using the integral area of the envelope curve of a known material type across the time axis, it is necessary to limit the calculation to the same time period to have a basis for reference. The start and end times of the time period can be selected in the following ways:
[0131] Method 1: The integral area is determined based on two echoes.
[0132] For example, the area of the continuous curve segment corresponding to the peak of any first echo in at least two echoes to the end point of the second echo;
[0133] For example, the area of the continuous curve segment between the starting point of any first echo and the ending point of the second echo.
[0134] Optionally, the two echoes are selected from the continuous curve segments corresponding to the first and second echoes with stronger echo signals, with integrated areas. Since the first two echoes have higher intensities, their corresponding integrated areas are also larger, making it easier to obtain the integrated area corresponding to the preset material category, thus making the recognition results more accurate.
[0135] In this embodiment, the position of the echo is defined. Since the waveform includes the start point, peak and end point of the echo, the start point and end point of the area integration can be defined by the position of the waveform when limiting the number of echoes. It is only necessary to match the start point and end point of the actual detected integrated area with the start point and end point of the integrated area corresponding to the preset material category.
[0136] Method 2: The integral area is determined based on at least two echoes.
[0137] For example, the area of the continuous curve segment from the peak of the first echo to the peak of the last echo out of three echoes;
[0138] Alternatively, the area of the continuous curve segment from the starting point of the first echo to the peak of the last echo out of the three echoes.
[0139] Alternatively, the area of the continuous curve segment from the peak of the first echo to the end point of the last echo out of the three echoes.
[0140] Alternatively, the area of the continuous curve segment corresponding to the starting point of the first echo out of the three echoes and the ending point of the last echo out of the three echoes.
[0141] Optionally, the three echoes are selected from the first, second, and third echoes, which have stronger echo signals. Stronger echo signals correspond to larger peak areas, which can make the recognition results more accurate.
[0142] Method 3: The integral area is determined based on all echo signals.
[0143] During the transmission of ultrasound, unexpected energy reflections, such as vibrations during excitation and aftershocks when excitation stops, may cause wave peaks to be collected. These fluctuations are independent of the material itself. However, when the reference preset material category comparison includes the integral area of all peaks, the integral area of all peaks obviously includes this part. That is, in the above embodiment, it is not enough to use only the integral area of the echo. It is necessary to further expand the starting and ending points of the integral area so that all echo signals are included.
[0144] In some embodiments, in addition to the above-described method for calculating the integral area, the accuracy of the calculated integral area can also be improved by normalization.
[0145] Figure 7 is a schematic flowchart of the normalization processing method provided in an embodiment of this application. Specifically, referring to Figure 7, the normalization method includes:
[0146] S701. Obtain the integral area of the envelope curve corresponding to the echo signal with respect to the time axis.
[0147] S702. Determine the first integral difference value based on the difference between the integral area of the envelope curve corresponding to the echo signal with respect to the time axis and the preset first integral area.
[0148] Wherein, the preset first integral area is the integral area of the envelope curve of the echo signal sent and received by the detection device to the target clean surface that has been completely absorbed, over the time axis.
[0149] S703. Determine the second integral difference value based on the difference between the preset second integral area and the preset first integral area.
[0150] The preset second integral area is the integral area of the envelope curve of the echo signal sent and received by the detection device to the target clean surface that does not absorb at all, over the time axis.
[0151] S704. Based on the ratio of the first integral difference to the second integral difference, the normalized value is obtained.
[0152] Specifically, if the area of the envelope curve corresponding to the echo signal of the target clean surface of unknown material detected by the detection device is integrated with respect to the time axis, then the normalized value P can be calculated using the following formula:
[0153] In the formula, the integral area of the envelope curve corresponding to the echo signal of the target cleaning surface of unknown material with respect to the time axis is S, the first integral area is preset to F, and the second integral area is preset to C.
[0154] Figure 8 is a schematic diagram of the processor structure of the cleaning robot provided in an embodiment of this application. As shown in Figure 8, the processor includes:
[0155] 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 clean 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 of the envelope curve corresponding to the echo signal with respect to the time axis.
[0157] In one possible implementation, the first parameter includes:
[0158] The echo signal corresponds to the area of the envelope curve integrated over the time axis;
[0159] Alternatively, the percentage increment corresponding to the integral area of the envelope curve of the echo signal with respect to the time axis.
[0160] In one possible implementation, the integral area is determined based on M echoes, where M is greater than or equal to 2.
[0161] In one possible implementation, the integral area includes:
[0162] The area of the continuous curve segment between the crest of the first echo and the end point of the second echo out of M echoes;
[0163] Alternatively, the area of the continuous curve segment between the starting point of the first echo and the ending point of the second echo out of the M echoes.
[0164] In one possible implementation, the M echoes include primary echoes and secondary echoes.
[0165] In one possible implementation, M is greater than 2, and the integral area includes:
[0166] The area of the continuous curve segment between the peak of the first echo and the peak of the last echo out of M echoes;
[0167] Alternatively, the area of the continuous curve segment from the starting point of the first echo in the M echoes to the peak of the last echo.
[0168] Alternatively, the area of the continuous curve segment from the crest of the first echo to the end point of the last echo out of the M echoes;
[0169] Alternatively, the area of the continuous curve segment corresponding to the starting point of the first echo and the ending point of the last echo out of the M echoes.
[0170] In one possible implementation, the M echoes include a first echo, a second echo, and a third echo.
[0171] In one possible implementation, the integral area is determined based on all echo signals.
[0172] In one possible implementation, the first parameter includes: an incremental percentage; the processing module 802 is specifically used for:
[0173] Obtain the area of the envelope curve corresponding to the echo signal integrated with respect to the time axis;
[0174] The integral area of the envelope curve corresponding to the echo signal with respect to the time axis is normalized to obtain the percentage increment.
[0175] Optionally, the processing module 802 is specifically used for:
[0176] The first integral difference value is determined based on the difference between the integral area of the envelope curve corresponding to the echo signal with respect to the time axis and the preset first integral area; wherein, 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 target clean surface that is completely absorbed with respect to the time axis.
[0177] The second integral difference is determined based on the difference between the preset second integral area and the 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 target clean surface that does not absorb at all, over the time axis.
[0178] The normalized value is obtained by comparing the ratio of the first integral difference to the second integral difference.
[0179] Figure 9 is a schematic diagram of the hardware structure of the cleaning robot provided in an embodiment of this application. As shown in Figure 9, the cleaning robot includes:
[0180] The detection device 901, the processor 902 which is communicatively connected to the detection device 901, and the memory 903 which is communicatively connected to the processor 902;
[0181] The detection device 901 is used to transmit ultrasonic signals to the target clean surface and receive the echo signals returned by the target clean surface.
[0182] This memory 903 is used to store computer-executed instructions;
[0183] The processor 902 is used to execute computer execution instructions stored in the memory 903 based on the detection results of the detection device 901, so as to realize the robot control method.
[0184] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.
[0185] The memory may include high-speed RAM, and may also include 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. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.
[0187] The above describes the solutions provided by the embodiments of the present invention for the functions implemented by the electronic device and the main control device.
[0188] It is understandable that electronic devices or main control devices include hardware structures and / or software modules that perform the above functions in order to achieve the above functions.
[0189] By combining the units and algorithm steps of the various examples described in the embodiments of this invention, the embodiments of this invention can be implemented in hardware or a combination of hardware and computer software. Whether a certain function is executed by hardware or by 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 be beyond the scope of the technical solutions of the embodiments of this invention.
[0190] This application also provides a computer program product, including a computer program that, when executed by a processor, implements a method for controlling a robot.
[0191] The computer program product provided in this embodiment can execute the robot control method of the above embodiment. Its implementation principle and technical effect are similar, and will not be described again in this embodiment.
[0192] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the robot control method described above.
[0193] The computer-readable storage medium provided in this embodiment can execute the robot control method of the above embodiment. Its implementation principle and technical effect are similar, and will not be described again here.
[0194] This 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 to the user terminal 300.
[0195] The cleaning robot 100 is also used 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 may be displayed on the user terminal 300 in at least one of the following ways:
[0197] The material's textual information, or the material's image information, or the material's audio information.
[0198] The aforementioned computer-readable storage medium can 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 storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.
[0199] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from 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 reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in an electronic device or a host device.
[0200] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.
[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, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided 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, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions 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 method for material identification in a cleaning robot, characterized in that, The robot includes a detection device for emitting ultrasonic signals toward a target clean surface and receiving echo signals returned from the target clean surface; the method includes: The material type of the target clean 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 of the envelope curve corresponding to the echo signal with respect to the time axis.
2. The method according to claim 1, characterized in that, The first parameter includes: The area of the envelope curve corresponding to the echo signal integrated over the time axis; Alternatively, the percentage increment corresponding to the integral area of the envelope curve of the echo signal with respect to the time axis.
3. The method according to claim 2, characterized in that, The integral 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 area of the continuous curve segment between the crest of the first echo and the end point of the second echo out of M echoes; Alternatively, the area of the continuous curve segment between the starting point of the first echo and the ending point of the second echo out of the M echoes.
5. The method according to claim 4, characterized in that, The M echoes include primary echoes and secondary echoes.
6. The method according to claim 3, characterized in that, Where M is greater than 2, the integral area includes: The area of the continuous curve segment between the peak of the first echo and the peak of the last echo out of M echoes; Alternatively, the area of the continuous curve segment from the starting point of the first echo in the M echoes to the peak of the last echo. Alternatively, the area of the continuous curve segment from the crest of the first echo to the end point of the last echo out of the M echoes; Alternatively, the area of the continuous curve segment corresponding to the starting point of the first echo and the ending point of the last echo out of the M echoes.
7. The method according to claim 6, characterized in that, The M echoes include a first echo, a second echo, and a third echo.
8. The method according to claim 2, characterized in that, The integral 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: Obtain the area of the envelope curve corresponding to the echo signal integrated with respect to the time axis; The integral area of the envelope curve corresponding to the echo signal with respect to the time axis is normalized to obtain the increment percentage.
10. The method according to claim 9, characterized in that, The normalization process for the integral area of the envelope curve corresponding to the echo signal with respect to the time axis includes: The first integral difference value is determined based on the difference between the integral area of the envelope curve corresponding to the echo signal with respect to the time axis and the preset first integral area; wherein, 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 target clean surface that is completely absorbed with respect to the time axis. The second integral difference is determined based on the difference between the preset second integral area and the 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 target clean surface that does not absorb at all, over the time axis. The normalized value is obtained by comparing the ratio of the first integral difference to the second integral difference.
11. A processor for a cleaning robot, characterized in that, The robot includes a detection device, which is communicatively connected to the processor. The detection device is used to transmit ultrasonic signals to the target clean surface and receive the echo signals returned by the target clean surface. The processor includes: An acquisition module is used to acquire the echo signal detected by the detection device; The processing module is used to determine the material type of the target clean 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 of the envelope curve corresponding to the echo signal with respect to the time axis.
12. The processor according to claim 11, characterized in that, The first parameter includes: The area of the envelope curve corresponding to the echo signal integrated over the time axis; Alternatively, the percentage increment corresponding to the integral area of the envelope curve of the echo signal with respect to the time axis.
13. The processor according to claim 12, characterized in that, The integral 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 area of the continuous curve segment between the crest of the first echo and the end point of the second echo out of M echoes; Alternatively, the area of the continuous curve segment between the starting point of the first echo and the ending point of the second echo out of the M echoes.
15. The processor according to claim 14, characterized in that, The M echoes include primary echoes and secondary echoes.
16. The processor according to claim 15, characterized in that, Where M is greater than 2, the integral area includes: The area of the continuous curve segment between the peak of the first echo and the peak of the last echo out of M echoes; Alternatively, the area of the continuous curve segment from the starting point of the first echo in the M echoes to the peak of the last echo. Alternatively, the area of the continuous curve segment from the crest of the first echo to the end point of the last echo out of the M echoes; Alternatively, the area of the continuous curve segment corresponding to the starting point of the first echo and the ending point of the last echo out of the M echoes.
17. The processor according to claim 16, characterized in that, The M echoes include a first echo, a second echo, and a third echo.
18. The processor according to claim 12, characterized in that, The integral area is determined based on all echo signals.
19. The processor according to claim 12, characterized in that, The first parameter includes: an increment percentage; the method further includes: Obtain the area of the envelope curve corresponding to the echo signal integrated with respect to the time axis; The integral area of the envelope curve corresponding to the echo signal with respect to the time axis is normalized to obtain the increment percentage.
20. The processor according to claim 19, characterized in that, The normalization process for the integral area of the envelope curve corresponding to the echo signal with respect to the time axis includes: The first integral difference value is determined based on the difference between the integral area of the envelope curve corresponding to the echo signal with respect to the time axis and the preset first integral area; wherein, 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 target clean surface that is completely absorbed with respect to the time axis. The second integral difference is determined based on the difference between the preset second integral area and the 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 target clean surface that does not absorb at all, over the time axis. The normalized value is obtained by comparing the ratio of the first integral difference to the second integral difference.
21. A control method for a cleaning robot, characterized in that, The robot includes a detection device for emitting ultrasonic signals toward a target clean surface and receiving echo signals returned from the target clean surface; the method includes: During the execution of a target task on a target cleaning surface, the material category of the target cleaning surface is determined based on any one of the material identification methods described in claims 1-10; the target task includes at least a cleaning task or a mapping task. Based on the material type of the target cleaning surface, perform the target cleaning task 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 clean surface and receive the echo signals returned by the target clean surface. The memory is used to store computer-executed instructions; The processor is configured to execute computer execution instructions stored in the memory based on the detection results of the detection device, so as to implement the robot control method as described in claim 21.
23. A cleaning system, characterized in that, The cleaning system includes a cleaning robot as described in claim 22 and a user terminal, wherein the robot is communicatively connected to the user terminal. The robot is also used 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: The material's textual information, or the material's image information, or the material's audio information.