Cleaning robot and cleaning robot control method

Abstract

The present application relates to the technical field of robots, and provides a cleaning robot and a cleaning robot control method. The cleaning robot comprises: a body; a detection unit comprising a first light source and an image sensor, wherein the detection unit is used for acquiring first multispectral data by using the image sensor, turning on the first light source when the acquired first multispectral data does not meet a preset condition, and acquiring second multispectral data by using the image sensor; and a control unit used for controlling the cleaning robot to determine medium information on a target ground according to the first multispectral data or the second multispectral data, and controlling the robot to perform a cleaning operation according to the medium information. By implementing the present application, the cleaning detection range can be widened, and the dirt detection accuracy can be improved.

Description

Cleaning robot and cleaning robot control method

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on June 16, 2023, with application number 202310723684.7 and invention name “A Cleaning Robot and Cleaning Robot Control Method”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of robotics technology, and in particular provides a cleaning robot and a cleaning robot control method. Background Art

[0003] In the prior art, a cleaning robot's mobile platform is equipped with a light emitting component and a light receiving component at the bottom. The light emitting component transmits a light signal toward the work surface, while the light receiving component receives the light signal reflected from the work surface and generates spectral information based on the work surface. After the light emitting and receiving components collect the spectral information, a controller controls the cleaning module to clean the work surface based on the work surface material and / or the type of stain on the work surface.

[0004] However, the existing technology places the light emitting and receiving components at the bottom of the mobile platform, significantly reducing the detection range. This results in detection only when the robot is about to pass through a dirty area. This approach fails to detect dirt in advance and exhibits a certain lag. Furthermore, the spectral information collected by the cleaning robot in the existing technology is generally generated by the reflection of a light source with a fixed frequency band, which cannot adapt to different working environments and results in poor dirt detection accuracy. Technical issues

[0005] The purpose of this application is to provide a cleaning robot and a cleaning robot control method, aiming to solve the existing problems, namely, the small cleaning detection range and low cleaning detection stability. Technical Solutions

[0006] To achieve the above objectives, the technical solution adopted in this application is:

[0007] In a first aspect, the present application provides a cleaning robot, comprising: a body; a detection unit, comprising a first light source and an image sensor, the detection unit being configured to acquire first multispectral data using the image sensor, and when the acquired first multispectral data does not meet a preset condition, turning on the first light source and acquiring second multispectral data using the image sensor; a control unit being configured to control the cleaning robot to determine medium information on the target ground based on the first multispectral data or the second multispectral data, and controlling the robot to perform a cleaning operation based on the medium information.

[0008] In a second aspect, the present application provides a control method for a cleaning robot, wherein the cleaning robot is provided with a detection unit and a cleaning component, the detection unit includes a first light source and an image sensor, and the method includes: obtaining first multispectral data, wherein the first multispectral data is determined based on a first multispectral light beam collected by the image sensor, and the first multispectral light beam is a light beam formed by ambient light reflected from the target ground; if the first multispectral data does not meet a preset condition, turning on the first light source; obtaining second multispectral data, wherein the second multispectral data is determined based on a second multispectral light beam collected by the image sensor, and the second multispectral light beam is a light beam formed by ambient light reflected from the target ground and light emitted by the first light source; determining medium information on the target ground based on the first multispectral data or the second multispectral data; and controlling the cleaning component of the robot to perform a cleaning operation based on the medium information. Beneficial effects

[0009] Beneficial effects of this application:

[0010] The present application provides a cleaning robot and a cleaning robot control method, which can increase the cleaning detection range and improve the accuracy of dirt detection.

[0011] Specifically, the detection unit uses an image sensor to acquire first multispectral data, thereby acquiring the spectral data required for detecting the cleaning range under ambient light. Under normal circumstances, the medium information on the target ground can be detected based on the first multispectral data. If the first multispectral data does not meet the preset conditions, it indicates that the current ambient light conditions are poor, and the medium information cannot be detected smoothly. It is necessary to turn on the first light source for auxiliary illumination. After turning on the first light source, second multispectral data is acquired, thereby acquiring spectral data generated by the ambient light and the first light source respectively. In other words, the medium information on the target ground is determined based on the first multispectral data under normal circumstances and based on the second multispectral data when the current ambient light conditions are poor. Thus, the medium information on the target ground is detected using the ambient light and the first light source in combination, thereby improving the accuracy of dirt detection.

[0012] In addition, the first light source is installed in front of the cleaning robot, which makes the cleaning detection range larger. The robot can detect the medium information in advance without driving to the target ground, thereby improving the detection efficiency.

[0013] It can be understood that the control method of the above-mentioned cleaning robot can achieve the same beneficial effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0015] FIG1 is a schematic diagram of a cleaning robot according to an embodiment of the present application;

[0016] FIG2 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0017] FIG3 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0018] FIG4 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0019] FIG5 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0020] FIG6 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0021] FIG7 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0022] FIG8 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0023] FIG9 is a diagram showing the positional relationship of the components of the detection unit of the cleaning robot embodiment of the present application;

[0024] FIG10 is a schematic diagram of a first installation orientation of an embodiment of the cleaning robot of the present application;

[0025] FIG11 is a schematic diagram of a second installation orientation of the cleaning robot embodiment of the present application;

[0026] FIG12 is a flow chart of an embodiment of a control method for a cleaning robot according to the present application;

[0027] FIG13 is a flow chart of an embodiment of a control method for a cleaning robot according to the present application;

[0028] FIG14 is a flow chart of an embodiment of a control method for a cleaning robot according to the present application;

[0029] FIG15 is a flow chart of an embodiment of a control method for a cleaning robot according to the present application;

[0030] FIG16 is a flow chart of an embodiment of a control method for a cleaning robot according to the present application;

[0031] FIG17 is a flow chart of an embodiment of a control method for a cleaning robot according to the present application;

[0032] FIG18 is a flow chart of an embodiment of a control method for a cleaning robot according to the present application;

[0033] FIG19 is a structural block diagram of the terminal device of the present application. Modes for Carrying Out the Invention

[0034] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0035] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. Throughout the description of this application, "plurality" means two or more, unless otherwise specifically defined.

[0036] In order to illustrate the technical solutions described in this application, the following examples are provided for illustration.

[0037] Example 1

[0038] As shown in FIG1 , the cleaning robot 100 provided in an embodiment of the present application includes:

[0039] fuselage 110;

[0040] In use, the robot's chassis can be equipped with various cleaning components, such as a mop, sweeping module, mopping module, and cleaning fluid container. These components are connected to and controlled by a processor. The chassis can also house motion modules, such as wheels, which operate under the control of the processor to propel the robot across the field.

[0041] The detection unit 120 includes a first light source 121 and an image sensor 122. The detection unit is configured to obtain first multispectral data using the image sensor. When the obtained first multispectral data does not meet a preset condition, the detection unit turns on the first light source and obtains second multispectral data using the image sensor.

[0042] When the cleaning robot begins operation, the first light source is off, and the image sensor collects ambient light (i.e., the first multispectral light beam) reflected from the target ground surface, thereby generating first multispectral data. The target ground surface refers to the current location of the cleaning robot and the ground in front of it, and can also be understood as the ground surface that the cleaning robot needs to clean. The cleaning robot's environment contains ambient light (e.g., sunlight and / or lamplight), which is reflected by the target ground surface. The first multispectral data is the ambient light reflected by the target ground surface, as collected by the image sensor.

[0043] Cases where the first multispectral data does not meet preset conditions may include: an incomplete optical frequency band of the first multispectral data, or the absence of data corresponding to the first multispectral data in the first spectral database. An incomplete optical frequency band indicates that the first spectral data lacks a complete full-band curve, making it unusable for subsequent comparison. In this case, the first light source must be activated for auxiliary illumination to obtain a complete full-band spectral curve. The absence of data corresponding to the first multispectral data in the first spectral database indicates that the medium information corresponding to the first multispectral data cannot be determined, requiring the first light source to be activated for auxiliary illumination to obtain recognizable spectral information.

[0044] The first light source emits a light beam toward the target ground for auxiliary illumination. After the light beam enters the target ground, it is reflected by the target ground. Because the cleaning robot is located in an environment with ambient light, the target ground also reflects the ambient light. The processor controls the image sensor to capture the light beam formed by the ambient light reflected from the target ground and the light emitted by the first light source, which is the second multispectral light beam. Second multispectral data is then generated based on the second multispectral data.

[0045] In some embodiments, the detection unit 120 is installed in front of the body 110 to detect the current location of the cleaning robot and the target ground in the area in front of it.

[0046] The control unit 130 is configured to control the cleaning robot to determine medium information on the target ground surface according to the first multispectral data or the second multispectral data, and control the robot to perform a cleaning operation according to the medium information.

[0047] In an application, the control unit may include a processor, a memory, and a computer program stored in the memory and executable on the processor. The processor is configured to receive a first multispectral signal and a second multispectral signal acquired by an image sensor, determine information about a medium on the target ground surface based on the first and second multispectral signals, and control the robot to perform a cleaning operation based on the information about the medium.

[0048] The spectral information corresponding to various types of media information may be pre-stored in a database. The database may be stored in a memory or a cloud server. When determining the media information on the target ground surface based on the first multispectral data or the second multispectral data, the control unit compares the first multispectral data or the second multispectral data with the spectral information corresponding to various types of media information in the database. If there is spectral information corresponding to matching media information, the media information is used as the media information corresponding to the first multispectral data or the second multispectral data.

[0049] After determining the media information of the target ground, the control unit controls the operating parameters of the cleaning component according to the type of media information, such as the operating speed of the sweeping module, the lifting of the mop, etc., so as to wash the target ground with heavy dirt and light dirt, thereby improving cleaning efficiency.

[0050] It should be noted that the first multispectral data is determined based on the first multispectral light beam received by the image sensor, wherein the first multispectral light beam is a light beam formed by the ambient light reflected by the target ground; the second multispectral data is determined based on the second multispectral light beam received by the image sensor, wherein the second multispectral light beam is a light beam formed by the ambient light reflected by the target ground and the light emitted by the first light source.

[0051] In some embodiments, the detection unit further includes a second light source 123 , and the image sensor receives one of the first multi-spectral data and the second multi-spectral data and the ranging data in a time-sharing manner.

[0052] In applications, the second light source can be a laser. It should be noted that the laser is used to detect obstacles on the target surface. Distance measurement data is determined based on the image sensor receiving a laser beam, where the laser beam is composed of light emitted by the second light source and a beam formed by light reflected from an external object. In some embodiments, the light emitted by the second light source is a horizontal line laser.

[0053] The image sensor can be configured to receive the second multispectral data and ranging data at different time intervals. For example, a 0.5-second interval can be set, and the image sensor will receive ranging data for 0.5 seconds after receiving the second multispectral data, and so on. Different time intervals can also be set for receiving different light signals as needed. For example, if the interval for receiving the second multispectral data is set to 0.7 seconds and the interval for receiving ranging data is set to 0.3 seconds, the image sensor will receive ranging data for 0.3 seconds after receiving the second multispectral data for 0.7 seconds, and then receive the second multispectral data for 0.7 seconds, and so on.

[0054] In some embodiments, the first light source, the second light source, and the image sensor are distributed in a line; or, the first light source, the second light source, and the image sensor are distributed at right angles.

[0055] The image sensor, the first light source, and the second light source can be positioned in a variety of ways, such as the straight line arrangement shown in FIG2 , where the second light source 123, the image sensor 122, and the first light source 121 are arranged sequentially from left to right. Alternatively, the image sensor 122, the first light source 121, and the second light source 123 can be positioned in a right-angle arrangement as shown in FIG3 , where the image sensor 122, the second light source 123, and the first light source 121 are located in the upper left, upper right, and lower left, respectively.

[0056] In some embodiments, if the first light source, the second light source and the image sensor are distributed in a line, when the light signal emitted by the second light source is of the first type, the image sensor is located between the first light source and the second light source; when the light signal emitted by the second light source is of the second type, the first light source is located between the image sensor and the second light source, or the second light source is located between the image sensor and the first light source.

[0057] The first type can be a laser pulse signal, which is used in laser time of flight (TOF) ranging. Laser TOF ranging uses a second light source to emit a laser. The light generated will bounce off any object and return to the image sensor. The distance between the external object and the image sensor is measured based on the time difference between the laser pulse signal emitted by the second light source and the laser pulse signal reflected by the object being measured and received by the image sensor. When using laser TOF ranging, the laser emitting the laser and the image sensor receiving the laser cannot be too far apart. Therefore, the image sensor is located between the first and second light sources, as shown in Figure 4, from left to right, they are the first light source 121, the image sensor 122, and the second light source 123.

[0058] The second type can be a continuous laser signal, which is used in laser triangulation. Laser triangulation involves emitting laser light from a second light source. After striking an object, the reflected light is received by an image sensor. Because the second light source and the image sensor are separated by a distance, objects at different distances will be imaged at different locations on the image sensor, depending on the optical path. Therefore, by calculating the position of the image sensor where the continuous laser signal, after being reflected by an external object, is imaged by the image sensor using triangulation formulas, the distance between the object and the image sensor can be measured. Because the distance between the second light source and the image sensor does not affect ranging accuracy, the image sensor can be arranged adjacent to the second light source, as shown in Figure 5 , where, from left to right, they are image sensor 122, second light source 123, and first light source 121. Alternatively, the image sensor can be arranged with the second light source separated by the first light source, as shown in Figure 6 , where, from left to right, they are image sensor 122, first light source 121, and second light source 123.

[0059] In some embodiments, if the first light source, the second light source, and the image sensor are arranged at right angles, the image sensor is adjacent to the second light source.

[0060] Whether in the laser TOF ranging method or the laser triangulation ranging method, the position setting of the image sensor and the second light source adjacent to each other is a position setting with better ranging accuracy. Under this position setting, the user can set different position combinations as needed. For example, as shown in Figure 7, the second light source 123, the image sensor 122, and the first light source 121 are respectively located in the upper left, upper right, and lower right. For another example, as shown in Figure 8, the second light source 123, the image sensor 122, and the first light source 121 are respectively located in the upper left, lower left, and lower right. For another example, as shown in Figure 9, the image sensor 122, the second light source 123, and the first light source 121 are respectively located in the upper left, lower left, and lower right.

[0061] In some embodiments, the first light source has a first installation direction, and the second light source has a second installation direction.

[0062] In application, the first installation direction can be an installation direction that is tilted downward. As shown in FIG10 , the first light source 121 is arranged in front of the robot. The first light source emits a light beam tilted downward. The installation direction that is tilted downward can make the light beam emitted by the first light source cover a larger range of the target ground in front of the cleaning robot, so that the processor can predict the medium information of the target ground in advance, and then control the cleaning robot to perform cleaning operations in time. The second installation direction can be an installation direction that is tilted downward. As shown in FIG11 , the second light source 123 is arranged in front of the cleaning robot. The second light source emits a light beam tilted downward. The installation direction that is tilted downward can make the light beam emitted by the second light source cover a larger range of the target ground in front of the cleaning robot, which is convenient for measuring the distance to obstacles on the target ground and performing obstacle avoidance operations.

[0063] The present application provides a cleaning robot and a cleaning robot control method, which can increase the cleaning detection range and improve the accuracy of dirt detection.

[0064] Specifically, the detection unit uses an image sensor to acquire first multispectral data, thereby obtaining the spectral data required for detecting the cleaning range under ambient light. Under normal circumstances, the medium information on the target ground surface can be detected based on the first multispectral data. If the first multispectral data does not meet the preset conditions, it indicates that the current ambient light conditions are poor and the medium information cannot be detected smoothly. It is necessary to activate the first light source for auxiliary illumination. After activating the first light source, second multispectral data is acquired, thereby obtaining spectral data generated by the ambient light and the first light source respectively. The medium information on the target ground surface is then determined based on the second multispectral data. The medium information on the target ground surface is then detected using the combination of ambient light and the first light source, thereby improving the accuracy of dirt detection.

[0065] In addition, the first light source is installed in front of the cleaning robot, which makes the cleaning detection range larger. The robot can detect the medium information in advance without driving to the target ground, thereby improving the detection efficiency.

[0066] Example 2

[0067] The control method of the cleaning robot provided in the embodiment of the present application can be applied to terminal devices such as the cleaning robot in embodiment 1. The cleaning robot is provided with a detection unit, and the detection unit includes a first light source and an image sensor.

[0068] FIG12 is a flow chart of a control method for a cleaning robot according to an embodiment of the present application.

[0069] Users can select two nodes to begin the process. The first start node begins by determining whether the first multispectral data meets the preset conditions. It then proceeds through the steps of activating the first light source, searching for the target object, identifying obstacles, and avoiding them. It then begins to sequentially identify whether the second multispectral data represents carpet, stubborn solids, liquid stains, or fine solid stains, and adopts different cleaning modes based on the different media information. The second start node directly identifies whether the second multispectral data represents carpet, stubborn solids, liquid stains, or fine solid stains, and adopts different cleaning modes based on the different media information. Compared to the second start node, the first start node primarily adds two additional steps: determining whether to activate the first light source based on whether the first multispectral data meets the preset conditions, and identifying obstacles and avoiding them. This allows the use of ambient light and the first light source to improve detection stability, enhance the cleaning robot's mobility, and enhance cleaning efficiency. Users can also directly activate the first light source and begin from the second start node as needed, making control of the cleaning robot simpler and more direct.

[0070] The specific content of this embodiment is described below.

[0071] Referring to FIG. 13 , the control method of the cleaning robot provided in an embodiment of the present application includes:

[0072] Step S11: Acquire first multispectral data.

[0073] The first multispectral data is determined according to a first multispectral light beam collected by the image sensor, and the first multispectral light beam is a light beam formed by ambient light reflected from the target ground.

[0074] In application, when the cleaning robot begins operation, the first light source is off, and the processor controls the sensor to collect ambient light reflected from the target ground surface (i.e., the first multispectral light beam), thereby generating first multispectral data. The target ground surface refers to the current location of the cleaning robot and the ground in front of it, and can also be understood as the ground the cleaning robot needs to clean. The cleaning robot's environment contains ambient light (e.g., sunlight and / or lighting), which is reflected by the target ground surface. The first multispectral data is the ambient light reflected by the target ground surface, collected by the sensor.

[0075] The sensor can be an image sensor, which includes a spectral information acquisition unit and an image information acquisition unit, capable of simultaneously acquiring spectral and image information. Specifically, the spectral information acquisition unit is used to acquire the first multispectral data or the second multispectral data, and the image information acquisition unit is used to acquire ranging data. The sensor can also be a sensor group, comprising two or more sensors, such as a spectral sensor and an image sensor, or other sensors to meet the needs of different users.

[0076] Step S12: When the first multispectral data does not meet a preset condition, turn on a first light source installed in front of the cleaning robot.

[0077] In some embodiments, the first multispectral data does not meet a preset condition, including:

[0078] The optical frequency band of the first multi-spectral data is incomplete, or there is no data corresponding to the first multi-spectral data in the first spectral database.

[0079] An incomplete optical band indicates that the first spectral data lacks a complete full-band curve and cannot be used alone for subsequent comparison. In this case, the first light source must be activated for auxiliary illumination to obtain a complete full-band spectral curve. The absence of data corresponding to the first multispectral data in the first spectral database indicates that the medium information corresponding to the first multispectral data cannot be determined. The first light source must be activated for auxiliary illumination to obtain recognizable spectral information.

[0080] In another embodiment, the first multispectral data does not meet the preset conditions, or the current ambient light brightness is lower than the preset threshold. In this case, it is difficult to obtain a complete and clear spectral curve. The first light source can be turned on to obtain a complete and clear spectral curve.

[0081] In an application, the first spectral database does not contain data corresponding to the first multispectral data, including:

[0082] There is no spectral data in the first spectral database that has a reflectance consistent with the first multi-spectral data.

[0083] Ambient light is primarily visible light. By collecting ambient light reflected from the target ground, we obtain the spectral frequency, which is the first multispectral data. This first multispectral data is then algorithmically calculated to determine the reflectance corresponding to the spectral frequency. The percentage of radiant energy reflected by an object as a percentage of the total radiant energy is called reflectivity. Each substance has a specific reflectivity, meaning that a specific substance can be identified by its specific reflectivity. The calculated reflectivity is compared with the reflectivity of the material in the first spectral database (this comparison may be for a single frequency point, several frequencies, or a frequency band). If the first spectral database does not contain a medium reflectivity that matches the reflectivity calculated for the first multispectral data, it indicates that the medium to which the first multispectral data corresponds cannot be determined. In this case, the first light source needs to be activated for auxiliary illumination to obtain the second multispectral information for comparison.

[0084] Step S13: Acquire second multispectral data, where the second multispectral data is determined based on a second multispectral light beam collected by the image sensor, where the second multispectral light beam is a light beam formed by ambient light reflected from the target ground and light emitted from the first light source.

[0085] The first light source emits a light beam toward the target ground for auxiliary illumination. After the light beam enters the target ground, it is reflected by the target ground. Because the cleaning robot is located in an environment with ambient light, the target ground also reflects the ambient light. The processor controls the image sensor to capture the light beam formed by the ambient light reflected from the target ground and the light emitted by the first light source, which is the second multispectral light beam. Second multispectral data is then generated based on the second multispectral data.

[0086] By acquiring the second multispectral data, the deficiency of the first multispectral data not meeting the preset conditions can be compensated, so that the detection will not be interrupted due to the deficiency of the first multispectral data, and is more stable.

[0087] Step S14: determining medium information on the target ground according to the first multispectral data or the second multispectral data.

[0088] In an application, spectral information corresponding to various types of media information may be pre-stored in a database. When determining the media information on the target ground surface based on the first multispectral data or the second multispectral data, the first multispectral data or the second multispectral data is compared with the spectral information corresponding to various types of media information in the database. If spectral information corresponding to the media information still matches, the media information is used as the media information corresponding to the first multispectral data or the second multispectral data.

[0089] As shown in FIG14 , in some embodiments, determining medium information on the target ground according to the first multispectral data or the second multispectral data includes:

[0090] Step S141, determining third multispectral data and fourth multispectral data in the second multispectral data, wherein the third multispectral data is spectral data of a light beam formed by ambient light reflected from the target ground surface, and the fourth multispectral data is spectral data of a light beam formed by light emitted from the first light source reflected from the target ground surface;

[0091] Step S142 : determining medium information on the target ground based on a comparison result between the third multispectral data and the data in the first spectral database, and a comparison result between the fourth multispectral data and the data in the second spectral database.

[0092] The image sensor includes a spectral information acquisition unit and an image information acquisition unit. The spectral information acquisition unit is used to collect second multispectral data of the target ground, and then third and fourth multispectral data are determined from the second multispectral data. Because ambient light (such as sunlight) is a full-band spectral light source, and the activated first light source is a partial-band spectral light source, the wavelengths of the two differ significantly. A filter algorithm can be used to determine the third and fourth multispectral data. Specifically, the filter algorithm may include a first filter algorithm and a second filter algorithm. The first filter algorithm is used to filter out the spectral information of the first light source from the second multispectral data to obtain the third multispectral data. The second filter algorithm is used to filter out the spectral information of the ambient light from the second multispectral data to obtain the fourth multispectral data.

[0093] After determining the third and fourth multispectral data, the third multispectral data is compared with the data in the first spectral database, and the fourth multispectral data is compared with the data in the second spectral database. If no corresponding relationship exists between the third multispectral data and the data in the first spectral database, or between the fourth multispectral data and the data in the second spectral database, data is collected again for comparison. If no successful comparison is found after a preset number of comparisons, steps S11 to S14 are repeated.

[0094] In one embodiment, the process for determining medium information by a cleaning robot is shown in FIG15 . A sensor collects light reflected from a first light source illuminating an object to be detected in front of it, generating second multispectral data. The sensor then determines third and fourth multispectral data from the second multispectral data. A microprocessor then compares the third multispectral data with the first spectral database and the fourth multispectral data with the second spectral database. Upon successful comparison of either the third or fourth multispectral data, the microprocessor outputs the determined medium information and its similarity, such as "more than 98% confidence that it is carpet" or "more than 95% confidence that it is solid dirt." If the comparison fails, the output remains unchanged and the comparison is repeated. After consecutive comparison failures, the external light source is re-collected and the comparison is repeated. Furthermore, the microprocessor can output point cloud data of the object to be detected in front of it, which can be used for subsequent control. For example, if the medium information cannot be determined, the microprocessor uses the point cloud data of the object to be detected in front of it to determine whether it is other medium information not entered into the database. If so, the spectral information of the object to be detected is entered into the database.

[0095] In an application, determining the medium information on the target ground based on the comparison result of the third multispectral data with the data in the first spectral database, and the comparison result of the fourth multispectral data with the data in the second spectral database, includes:

[0096] If the first spectral database contains first data corresponding to the third multispectral data, or the second spectral database contains second data corresponding to the fourth multispectral data, medium information of the target ground is determined according to the first data or the second data.

[0097] In applications, the first and second data can be spectral information corresponding to specific media, such as carpet, stubborn solid stains, liquid stains, fine solid stains, and other dirty media. If the third multispectral data corresponds to the first data, and the fourth multispectral data corresponds to the second data, the first and second data can be simultaneously determined to determine whether they are spectral information corresponding to carpet. If not, the first and second data can be simultaneously determined to determine whether they are spectral information corresponding to stubborn solid stains. If not, the first and second data can be simultaneously determined to determine whether they are spectral information corresponding to liquid stains. If not, the first and second data can be simultaneously determined to determine whether they are spectral information corresponding to fine solid stains. If any of these determinations succeed, the determination process ends, and no further determinations are made. For example, if both the third and fourth multispectral data match the spectral information corresponding to liquid stains, the determination of the medium as liquid stains is output, and the determination of whether the third and fourth multispectral data are fine solid stains is no longer made, thus ending the determination process. If only the third multispectral data corresponds to the first data, or only the fourth multispectral data corresponds to the second data, the above determination process may be performed on the third multispectral data or the fourth multispectral data separately.

[0098] As shown in FIG16 , in some embodiments, determining the medium information on the target ground according to the second multispectral data includes:

[0099] Step S143, when the medium information on the target ground cannot be determined according to the second multispectral data, changing the intensity of the light emitted by the first light source;

[0100] Step S144: reacquire the second multispectral data, and determine the medium information on the target ground according to the second multispectral data.

[0101] In the application, the user can set different intensity levels for the first light source. If the target surface's medium information cannot be determined based on the second multispectral data, the intensity level is increased to enhance the first light source's illumination intensity. If the target surface's medium information cannot be determined based on the second multispectral data, the intensity level is further increased to further enhance the illumination intensity of the first light source. In other words, by setting different "gears" for the first light source's intensity, the intensity of the first light source can be easily adjusted. In step S15, the robot's cleaning components are controlled to perform cleaning operations based on the medium information.

[0102] The cleaning components of the robot, such as the mopping module and the sweeping module, are adjusted according to different media information, thereby specifying different working modes according to the media information to achieve a good cleaning effect of light cleaning for light dirt and heavy cleaning for heavy dirt.

[0103] As shown in FIG17 , in some embodiments, controlling the robot to perform a cleaning operation according to the medium information includes:

[0104] Step S151: If the medium information is carpet, the robot is controlled to lift the mop in the cleaning component so that the mopping module does not work and only the sweeping module works.

[0105] Carpet stains are mainly dust, which is difficult to clean with the mopping module. The mopping module may also stain the carpet while working. Use the sweeping module to clean the carpet. Wait until the sweeping module has finished cleaning the carpet before lowering the mop.

[0106] Step S152: If the medium information is stubborn solid stains, the robot is controlled to increase the operating speed of the cleaning component, or the robot is controlled to move forward and backward, or the robot is controlled to increase the water output and cleaning liquid.

[0107] Stubborn solid stains are more difficult to deal with, and cleaning components (such as sweeping modules and mopping modules) are difficult to clean thoroughly at normal operating speeds. Therefore, the cleaning effect of heavy stains and heavy washes can be achieved by increasing the operating speed of the cleaning components, controlling the robot to move back and forth on the stubborn solid stains, increasing the water output and the amount of cleaning liquid, etc.

[0108] Step S153: If the medium information is liquid stains or small solid stains, the cleaning robot is controlled to move forward and backward, or the robot is controlled to increase the suction strength of the cleaning component.

[0109] Liquid stains are easy to remain, so the cleaning robot needs to be controlled to move back and forth so that the mopping module can repeatedly wipe the liquid stains. At the same time, the suction strength of the cleaning component needs to be increased to thoroughly clean the liquid stains.

[0110] Small solid stains, such as wood chips and hair fragments, cannot be cleaned in one go by the sweeping module. It is necessary to control the cleaning robot to move back and forth so that the sweeping module repeatedly cleans the ground where the small solid stains are located, and at the same time increase the suction intensity of the cleaning component to clean more thoroughly.

[0111] The above embodiment refines the cleaning mode according to specific medium information to achieve the effect of heavy cleaning for heavy contamination and light cleaning for light contamination.

[0112] As shown in FIG18 , in some embodiments, the control method of the cleaning robot provided in the embodiments of the present application further includes:

[0113] Step S161, obtaining ranging data, wherein the ranging data is determined after the image sensor receives a laser beam, wherein the laser beam is a beam formed by light emitted by the second light source and light emitted by the second light source reflected by an external object;

[0114] Step S162: If it is determined that there is an obstacle on the target ground according to at least one of the first multispectral data, the second multispectral data, and the ranging data, an obstacle avoidance operation is performed.

[0115] Specifically, a ranging module consisting of a second light source (such as a laser) and an image information acquisition unit measures materials on the target ground surface to determine whether they are obstacles. Its obstacle avoidance sensing technology can utilize line laser technology. Line laser can be understood as multiple laser points evenly distributed along a straight line. In practice, it is a single-line light source implemented by an optical structure, and the shape it projects onto a flat object is a straight line. The line laser can be a transverse single-line laser, which detects the flatness of the ground within a certain angle directly in front of the machine. If a clear obstacle is detected, it will distort or change its flight time. If an obstacle is detected, obstacle avoidance measures are performed, such as changing the direction of travel to circumvent it. If no obstacle is detected, the step of determining the medium information of the target ground surface based on the second multispectral data is performed.

[0116] The above embodiment adds an obstacle avoidance function, which can improve the mobility and cleaning efficiency of the cleaning robot.

[0117] The embodiments of the present application can increase the clean detection range and improve the accuracy of dirt detection.

[0118] Specifically, acquiring the first multispectral data provides the spectral data required for detecting the cleaning range under ambient light. Under normal circumstances, the first multispectral data can be used to detect the media information on the target surface. If the first multispectral data does not meet the preset conditions, it indicates that the current ambient light conditions are poor and the media information cannot be detected smoothly. The first light source needs to be activated for auxiliary illumination. After activating the first light source, second multispectral data is acquired to obtain spectral data generated by both the ambient light and the first light source. The media information on the target surface is then determined based on the second multispectral data. This allows the use of ambient light and the first light source to detect the media information on the target surface, thereby improving the accuracy of contamination detection.

[0119] In addition, the first light source is installed in front of the cleaning robot, which makes the cleaning detection range larger. The robot can detect the medium information in advance without driving to the target ground, thereby improving the detection efficiency.

[0120] Example 3

[0121] As shown in FIG19 , the present application further provides a terminal device 180, comprising a memory 181, a processor 182, and a computer program 183 stored in the memory and executable on the processor, for example. When the processor 182 executes the computer program 183, the steps in the above-mentioned embodiments of the control method of the cleaning robot are implemented, such as the method steps in Example 2. When the processor 182 executes the computer program 183, the functions of the modules in the above-mentioned embodiments of the device are implemented, such as the functions of the modules and units in Example 1.

[0122] Exemplarily, the computer program 183 may be divided into one or more modules, which are stored in the memory 181 and executed by the processor 182 to implement the second embodiment of the present application. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 183 in the terminal device 180. For example, the computer program 183 may be divided into a detection unit, a control unit, etc. The specific functions of each module have been described in the above-mentioned first embodiment and will not be repeated here.

[0123] The terminal device may include, but is not limited to, a memory 181 and a processor 182. Those skilled in the art will appreciate that FIG19 is merely an example of the terminal device 180 and does not limit the terminal device 180. The terminal device may include more or fewer components than shown in the figure, or may combine certain components or different components. For example, the terminal device may also include input and output devices, network access devices, buses, etc.

[0124] The memory 181 can be an internal storage unit of the terminal device 180, such as a hard drive or memory of the terminal device 180. The memory 181 can also be an external storage device of the terminal device 180, such as a plug-in hard drive, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash memory card, etc. equipped with the terminal device 180. Furthermore, the memory 181 can include both an internal storage unit of the terminal device 180 and an external storage device. The memory 181 is used to store the computer program and other programs and data required by the terminal device. The memory 181 can also be used to temporarily store data that has been output or is about to be output.

[0125] The processor 182 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0126] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0127] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0128] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0129] In the embodiments provided in this application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are merely illustrative. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0130] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0131] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0132] If the integrated module is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application can implement all or part of the process steps in the above-mentioned method embodiments by using a computer program to instruct the relevant hardware. The computer program can be stored in a computer-readable storage medium. When executed by a processor, the computer program can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium. It should be noted that the content of the computer-readable medium can be appropriately increased or decreased based on the requirements of legislation and patent practice in a jurisdiction. For example, in some jurisdictions, based on legislation and patent practice, computer-readable media does not include electric carrier signals and telecommunication signals.

[0133] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application 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 make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A cleaning robot, characterized in that: include: body; A detection unit, comprising a first light source and an image sensor, wherein the detection unit is used to obtain first multispectral data using the image sensor, and when the obtained first multispectral data does not meet a preset condition, the first light source is turned on, and second multispectral data is obtained using the image sensor; A control unit is used to control the cleaning robot to determine medium information on a target ground surface according to the first multi-spectral data or the second multi-spectral data, and control the robot to perform a cleaning operation according to the medium information.

2. The cleaning robot according to claim 1, characterized in that: The first multispectral data is determined based on a first multispectral light beam received by the image sensor, wherein the first multispectral light beam is a light beam formed by ambient light reflected from the target ground; the second multispectral data is determined based on a second multispectral light beam received by the image sensor, wherein the second multispectral light beam is a light beam formed by ambient light reflected from the target ground and light emitted by the first light source.

3. The cleaning robot according to claim 1 or 2, characterized in that: The detection unit also includes a second light source, and the image sensor receives one of the first multi-spectral data and the second multi-spectral data and ranging data in a time-sharing manner, wherein the ranging data is determined based on the image sensor receiving a laser beam, and the laser beam is a beam formed by light emitted by the second light source and light emitted by the second light source reflected by an external object.

4. The cleaning robot according to claim 3, characterized in that: The light emitted by the second light source is a transverse line laser.

5. The cleaning robot according to claim 3 or 4, characterized in that: The first light source, the second light source and the image sensor are distributed in a straight line; or, the first light source, the second light source and the image sensor are distributed at right angles.

6. The cleaning robot according to claim 5, characterized in that: If the first light source, the second light source and the image sensor are arranged in a line, when the light signal emitted by the second light source is of the first type, the image sensor is located between the first light source and the second light source; when the light signal emitted by the second light source is of the second type, the first light source is located between the image sensor and the second light source, or the second light source is located between the image sensor and the first light source.

7. The cleaning robot according to claim 6, characterized in that: The first type is a laser pulse signal, which is used to measure the distance between the external object and the image sensor according to the time difference between the laser pulse signal emitted by the second light source and the laser pulse signal received by the image sensor after being reflected by the external object; The second type is a laser continuous signal, which is used to measure the distance between the external object and the image sensor according to the imaging of the laser continuous signal at the position of the image sensor after being reflected by the external object.

8. The cleaning robot according to claim 5, characterized in that: If the first light source, the second light source and the image sensor are distributed at right angles, the image sensor is adjacent to the second light source.

9. The cleaning robot according to any one of claims 3 to 8, characterized in that: The first light source has a first installation direction, and the second light source has a second installation direction.

10. The cleaning robot according to claim 9, characterized in that: The first installation direction is an installation direction that is tilted downward, and the first light source emits a light beam that is tilted downward; the second installation direction is an installation direction that is tilted downward, and the second light source emits a light beam that is tilted downward.

11. The cleaning robot according to any one of claims 3 to 10, characterized in that: The image sensor includes a spectral information acquisition unit and an image information acquisition unit, wherein the spectral information acquisition unit is used to acquire the first multi-spectral data or the second multi-spectral data, and the image information acquisition unit is used to acquire the ranging data.

12. The cleaning robot according to any one of claims 1 to 11, characterized in that: The detection unit is installed in front of the fuselage.

13. A control method for a cleaning robot, wherein the cleaning robot is provided with a detection unit and a cleaning component, wherein the detection unit comprises a first light source and an image sensor, wherein: The method comprises: Acquire first multispectral data, where the first multispectral data is determined according to a first multispectral light beam collected by the image sensor, where the first multispectral light beam is a light beam formed by ambient light reflected from a target ground surface; When the first multi-spectral data does not meet a preset condition, turning on the first light source; Acquire second multispectral data, where the second multispectral data is determined according to a second multispectral light beam collected by the image sensor, where the second multispectral light beam is a light beam formed by ambient light reflected from the target ground and light emitted by the first light source; Determine medium information on the target ground according to the first multispectral data or the second multispectral data; The cleaning component of the robot is controlled to perform a cleaning operation according to the medium information.

14. The method according to claim 13, characterized in that The first multispectral data does not meet the preset conditions, including: The optical frequency band of the first multispectral data is incomplete, or, There is no data corresponding to the first multi-spectral data in the first spectral database.

15. The method according to claim 13 or 14, characterized in that The determining the medium information on the target ground according to the first multi-spectral data or the second multi-spectral data includes: When the medium information on the target ground cannot be determined according to the second multi-spectral data, changing the intensity of the light emitted by the first light source; The second multispectral data is reacquired, and medium information on the target ground is determined according to the second multispectral data.

16. The method according to any one of claims 13 to 15, characterized in that The controlling the robot to perform a cleaning operation according to the medium information includes: If the medium information is a carpet, controlling the robot to lift the mop in the cleaning component; or, If the medium information is stubborn solid stains, the robot is controlled to increase the operating speed of the cleaning component, or the robot is controlled to move forward and backward, or the robot is controlled to increase the water output and cleaning liquid; or, If the medium information is liquid stains or tiny solid stains, the cleaning robot is controlled to move forward and backward, or the robot is controlled to increase the suction strength of the cleaning component.

17. The method according to any one of claims 13 to 16, characterized in that The determining of medium information on the target ground according to the first multispectral data or the second multispectral data includes: Determine third multispectral data and fourth multispectral data in the second multispectral data, wherein the third multispectral data is spectral data of a light beam formed by the target ground reflecting ambient light, and the fourth multispectral data is spectral data of a light beam formed by the target ground reflecting light emitted by the first light source; The medium information on the target ground is determined according to the comparison result between the third multi-spectral data and the data in the first spectral database, and the comparison result between the fourth multi-spectral data and the data in the second spectral database.

18. The method according to claim 17, characterized in that The determining of the third multi-spectral data and the fourth multi-spectral data in the second multi-spectral data includes: The first filter algorithm is used to filter out the spectral information of the first light source in the second multispectral data to obtain third multispectral data, and the second filter algorithm is used to filter out the spectral information of the ambient light in the second multispectral data to obtain fourth multispectral data.

19. The method according to any one of claims 13 to 18, characterized in that: The detection unit further includes a second light source, and the method further includes: Acquire distance measurement data, where the distance measurement data is determined according to a laser beam collected by the image sensor, where the laser beam is emitted by the second light source and is collected by the image sensor after being reflected by an external object; If it is determined that there is an obstacle on the target ground according to at least one of the first multi-spectral data, the second multi-spectral data and the ranging data, an obstacle avoidance operation is performed.

Images