Automatic pool cleaning equipment and control method thereof

Abstract

Disclosed are an automatic pool cleaning apparatus and a method of controlling the same. The method comprises the steps that in the process of controlling the automatic pool cleaning equipment to move on the water surface, distance data between the automatic pool cleaning equipment and surrounding objects is determined based on detection data from a distance sensor; determining the category of the object based on the variation amplitude of the distance data; and adjusting a moving path of the automatic pool cleaning equipment based on the type of the object.

Description

Technical Field

[0001] The present disclosure relates to an automatic pool cleaning device and a method for controlling the automatic pool cleaning device in the field of automatic cleaning. Background Art

[0002] For pool facilities such as swimming pools, automatic pool cleaning equipment can be utilized to perform automatic cleaning or auxiliary cleaning. For example, the automatic pool cleaning equipment can be designed to filter the pool water and absorb dirt while moving on the bottom, wall and / or surface of the pool. Summary of the Invention

[0003] Disclosed is a method for controlling an automatic pool cleaning device, comprising: determining distance data between the automatic pool cleaning device and surrounding objects based on detection data from a distance sensor during the process of controlling the automatic pool cleaning device to move on a water surface; determining the category of the object based on a variation in the distance data; and adjusting the movement path of the automatic pool cleaning device based on the category of the object.

[0004] In one or more embodiments, determining the category of the object based on the change amplitude of the distance data includes: if the change amplitude of the distance data of adjacent frames within a specified time period is unstable, determining that the object corresponding to the distance data is a floating object.

[0005] In one or more embodiments, determining the category of the object based on the change amplitude of the distance data includes: if the change amplitude of the distance data of adjacent frames continues to decrease within a specified time period, determining that the object corresponding to the distance data is a fixed object.

[0006] In one or more embodiments, determining the category of the object based on the change amplitude of the distance data includes: when the change amplitude of the distance data of adjacent frames within a specified time length is greater than or equal to a specified threshold, determining that the object corresponding to the distance data is a fixed object.

[0007] In one or more embodiments, determining the category of the object based on the change amplitude of the distance data includes: if the change amplitude of the distance data of adjacent frames within a specified time period is less than a specified threshold, determining that the object corresponding to the distance data is a floating object.

[0008] In one or more embodiments, determining the category of the object based on the magnitude of change of the distance data includes: determining multiple clusters of the distance data based on the magnitude of change of the distance data of adjacent frames within a specified time length; determining the object corresponding to the cluster with the largest magnitude of change among the multiple clusters as a fixed object; and determining the objects corresponding to other clusters among the multiple clusters as floating objects.

[0009] In one or more embodiments, adjusting the movement path of the automatic pool cleaning device based on the category of the object includes: controlling the automatic pool cleaning device to turn and move to another movement path when the distance between the object and the object reaches a specified distance, when the object is determined to be a fixed object and the object is located in front of the current travel direction of the automatic pool cleaning device.

[0010] In one or more embodiments, adjusting the movement path of the automatic pool cleaning device based on the category of the object includes: controlling the automatic pool cleaning device to move toward or avoid the object when the object is determined to be a floating object and the object is located in front of the current travel direction of the automatic pool cleaning device.

[0011] In one or more embodiments, controlling the automatic pool cleaning device to move toward the object or avoid the object includes controlling the automatic pool cleaning device to move toward the object or avoid the object based on a size of the object.

[0012] Also disclosed is an automatic pool cleaning device, comprising: a distance sensor configured to detect the distance between the automatic pool cleaning device and surrounding objects while the automatic pool cleaning device moves on a water surface; and a controller configured to execute the method described above.

[0013] In one or more embodiments, the distance sensor includes at least one of an ultrasonic sensor, a lidar, an infrared sensor, a time-of-flight sensor, and a visual sensor. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 An example of an automatic pool cleaning device according to an embodiment of the present disclosure is schematically shown.

[0015] Figure 2 An example of a method for controlling an automatic pool cleaning device according to an embodiment of the present disclosure is schematically shown.

[0016] Figure 3 An example of distance data according to an embodiment of the present disclosure is schematically shown.

[0017] Figure 4 An example of distance data according to an embodiment of the present disclosure is schematically shown.

[0018] Figure 5 An example of distance data according to an embodiment of the present disclosure is schematically shown.

[0019] Figure 6 An example of distance data according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0020] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. In the drawings, the same or corresponding parts are given the same reference numerals, and their description will not be repeated.

[0021] Figure 1 An exemplary automatic pool cleaning device 100 (hereinafter also referred to as “device 100 ”) in an embodiment of the present disclosure is illustrated.

[0022] The device 100 may be configured with a housing, and a travel mechanism such as travel wheels, tracks, water nozzles, propellers, etc. The housing may be provided with a water inlet and outlet, etc., and a suction device, a filtering device, and a drive mechanism, etc., may be provided within the housing. The suction device may, for example, include at least one water pump. The filtering device may, for example, include a trash basket having at least one layer of filter mesh. The drive mechanism may, for example, include components such as a motor, a water pump, and gears that can provide and / or transmit driving force to drive the travel mechanism to operate, thereby driving the device 100 to move or swim in the water, on the water surface, and / or on the pool wall.

[0023] For example, when the device 100 moves on the bottom, wall or water surface of the pool, the suction device of the device 100 can work to suck the water in the pool together with the garbage or dirt in the water from the water inlet of the device 100 into the filtering device of the device 100, and then suck the water in the filtering device out of the filtering device and guide it to the water outlet of the device 100, and finally discharge it into the pool from the water outlet, while the garbage or dirt in the pool water is adsorbed by the filter element of the filtering device or intercepted in the filtering device, thereby cleaning the pool.

[0024] like Figure 1 As shown, the device 100 may also be configured with a controller 110. The controller 110 may include any circuit and / or module with data processing capability and / or instruction execution capability and suitable for the device 100, such as a central processing unit (CPU), a graphics processing unit (GPU), a field programmable gate array (FPGA), etc., and may be configured to perform data processing and / or control related to the cleaning operation and / or other functions of the device 100 according to a program stored in a memory (not shown) of the device 100 and / or a signal and / or instruction from a control panel or a control terminal (not shown) of the device 100 and / or sensing data from one or more sensors (e.g., a spatial attitude sensor, an odometer, etc.) of the device 100.

[0025] In addition, the device 100 may also include at least one distance sensor 120 such as an ultrasonic sensor, a lidar, a visual sensor, an infrared sensor, a time-of-flight (ToF) sensor, etc., so as to detect the distance between the device 100 and surrounding objects (for example, cleanable objects in the pool such as garbage, uncleanable objects or fixed obstacles such as pool walls, escalators, etc., etc.) when the device 100 moves on the water surface or in the pool.

[0026] In a pool or on the water surface, there may be various types of floating objects, such as leaves, lifebuoys, water toys, and fixed objects such as pool walls and ladders. For example, when the device 100 performs a cleaning task on the water surface, the detection data of the distance sensor 120 may come from different objects. If the detection data of the distance sensor 120 itself does not contain semantic information, it may not be possible to accurately determine whether the detected object is an uncleanable obstacle such as the pool wall or a cleanable floating object such as a leaf, thereby affecting the environmental perception and path planning capabilities of the device 100.

[0027] Figure 2 An exemplary method 200 for controlling the device 100 according to an embodiment of the present disclosure is schematically shown. The method 200 may be implemented by the controller 110 by executing corresponding program instructions, for example, and may improve the environmental perception capability and path planning capability of the device 100.

[0028] like Figure 2 As shown, method 200 may include steps 210 , 220 , and 230 .

[0029] For example, when the device 100 moves on the water surface, the controller 110 may perform step 210 to determine distance data between the device 100 and the detected object based on detection data about the object around the device 100 from the distance sensor 120 .

[0030] For example, if the distance sensor 120 includes an ultrasonic sensor, when the device 100 moves on the water surface, the distance sensor 120 can transmit an ultrasonic signal in the surrounding area or in a specified direction and receive a feedback signal. The distance sensor 120 or the controller 110 can then determine the real-time distance between the device 100 and objects detected in the surrounding area (e.g., in front) based on the time difference between the transmitted ultrasonic signal and the received feedback signal, the propagation speed of ultrasonic waves in the air and / or water surface and / or water, etc.

[0031] In some embodiments, the device 100 may also include a temperature sensor to compensate for the propagation speed of the ultrasound wave according to the monitored temperature value, and then determine the real-time distance between the device 100 and the objects detected in the surroundings (for example, in front) based on the time difference between the transmitted ultrasound signal and the received feedback signal, the compensated ultrasound propagation speed, etc.

[0032] For example, in the case where the distance sensor 120 includes a lidar, the controller 110 may determine the real-time distance between the device 100 and surrounding objects based on point cloud data about the surrounding environment of the device 100 acquired by the lidar.

[0033] For example, in the case where the distance sensor 120 includes a visual sensor such as a monocular camera or a binocular camera, the controller 110 can identify objects around the device 100 and determine the real-time distance between the device 100 and the surrounding objects based on real-time images of the surrounding environment of the device 100 obtained through the visual sensor through any suitable image analysis and processing method or model such as an image convolutional neural network or a target recognition method or model.

[0034] Affected by factors such as water surface fluctuations, the positions of device 100 and floating objects on the water surface may not be fixed. In addition, the movement of floating objects on the water surface may cause the distance sensor to sometimes sense the floating object and sometimes not sense the floating object, making the distance change between device 100 and the floating object less stable. However, fixed objects such as the pool wall will not float due to the water flow. As device 100 moves, the distance between device 100 and the fixed object generally changes steadily, such as gradually decreasing. However, because the position of device 100 is affected by the water flow, the change in the distance between device 100 and the fixed object may also fluctuate, but the overall change trend is stable. If there is a floating object between device 100 and the pool wall, the data detected by the distance sensor may correspond to the floating object or the pool wall, and the change in distance data will be more chaotic.

[0035] like Figure 3 As shown, the distance data at different time points about the distance between the device 100 and the detected same object determined by step 210 may not fall within the same range. Figure 3 In addition, the detection data of the distance sensor 120 may come from different objects, such as Figure 4 As shown, for example, after a period of time, distance detection data related to different detection objects may be mixed together, making it difficult to directly determine based on the detection data of the distance sensor 120 whether the object corresponding to the current distance data portion is cleanable floating garbage or an uncleanable obstacle.

[0036] In this regard, the controller 110 may execute step 220 to determine the category of the object detected in step 210 based on the magnitude of the change in the distance data determined in step 210 .

[0037] In step 220, for example, if the change amplitude of the distance data of adjacent frames (i.e., two sampling data points or determined distance data points adjacent in time) within the specified time period is unstable, it can be determined that there is a floating object around the device 100 (if there is a floating object in front of the robot, the distance data will fluctuate); and if the change amplitude of the distance data of adjacent frames within the specified time period continues to decrease (for example, Figure 3 ), the object corresponding to the data portion is determined to be a fixed object. The variation range of the distance data of two adjacent frames may be the difference between the distance data of the previous frame and the distance data of the next frame.

[0038] When there are floating objects between the device 100 and the pool wall, the distance sensor 120 may sometimes sense the pool wall and sometimes sense the floating objects, and the change range of the distance data of adjacent frames will be different.

[0039] Floating objects may drift forward as the device 100 moves. If two consecutive frames sense only floating objects, the change in distance data between the two frames will generally be small, or even zero. The pool wall is generally farther from the device 100 than floating objects. If the previous frame senses a floating object and the next frame senses the pool wall, or if the previous frame senses the pool wall and the next frame senses a floating object, the change in distance data between the two frames will be larger. If the two consecutive frames sense only the pool wall, as the device moves forward, the change in distance data between the two frames will generally be larger than if both frames sense only floating objects.

[0040] Therefore, in step 220, when the change in the distance data of adjacent frames within the specified time period is less than the specified threshold, for example Figure 4 The data part in the dotted box on the left and Figure 5 The data part of the hollow circle determines that the object corresponding to the distance data is a floating object. If the change in the distance data of adjacent frames within the specified time is greater than or equal to the specified threshold, for example Figure 4 The data part in the dotted box on the right and Figure 5 The data in the solid circle is considered a fixed object. The threshold can be set based on experimental or practical needs. This allows for filtering distance data with significant differences between the previous and next frames, allowing for the identification of fixed objects such as the pool wall.

[0041] In addition, in step 220, for example, multiple clusters of data within the data portion may be determined based on the magnitude of change in data between adjacent frames of distance data within a specified time period using any suitable clustering algorithm, such as K-means. The object corresponding to the cluster with the largest magnitude of data change among the multiple clusters determined may then be determined as a fixed object, and the objects corresponding to the other clusters may be determined as floating objects.

[0042] In addition, in step 220, if Figure 6 As shown, linear interpolation can also be performed on the data points in the determined cluster (for example, the cluster with the largest data variation), so that Figure 6 As shown by the dotted line in , a distance regression curve for the object corresponding to the distance class (e.g., the pool wall) is obtained. Further, in step 220, the distance between the device 100 and the object corresponding to the distance class (e.g., the pool wall) can be determined or predicted based on the distance regression curve.

[0043] The controller 110 may then perform step 230 to adjust a movement path of the device, for example, on a water surface, based on the category of the object determined in step 220 .

[0044] For example, in step 230, when the object is determined to be a fixed object and the object is located in front of the current travel direction of the device 100, the controller 110 can control the travel mechanism of the control device 100 through an instruction signal, and drive the device 100 to turn and move to another moving path when the distance between the device 100 and the object reaches a specified distance.

[0045] For example, in step 230, if an object is determined to be a floating object and is located in front of the current travel direction of the device 100, the controller 110 may control the travel mechanism of the device 100 through a command signal to drive the device 100 to move toward or avoid the object. For example, if the size of the object exceeds a predetermined threshold, the device 100 may be controlled to avoid the object; otherwise, the device 100 may be controlled to determine that it is moving toward the object in order to clear the object.

[0046] As described above, in method 200, the category of objects surrounding the device 100 is determined based on the magnitude of the change in the distance data, and the moving path of the device 100 is adjusted based on the determined object category, so that the device 100 can quickly filter out the interference of floating obstacles in the pool on the distance data, and can accurately output the true distance or predicted value between the device 100 and fixed obstacles such as the pool wall, thereby improving the environmental perception ability and navigation planning readiness of the device 100.

[0047] The basic principles of the present disclosure have been described above in conjunction with the embodiments. However, it should be noted that the advantages, strengths, and effects mentioned in this disclosure are merely illustrative and non-restrictive, and should not be construed as necessarily possessed by each embodiment of the present disclosure. Furthermore, the aforementioned details are provided for illustrative purposes and to facilitate understanding, not for limitation, and do not limit the present disclosure to necessarily being implemented using the aforementioned details.

[0048] The block diagrams of the devices, apparatuses, equipment, and systems involved in this disclosure are intended to be illustrative examples only and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. In different embodiments, these devices, apparatuses, equipment, and systems may be connected, arranged, or configured in any appropriate manner.

[0049] In addition, words such as "including," "comprising," and "having" are open-ended words that mean "including but not limited to," and are used interchangeably therewith. The words "or" and "and" used herein mean the words "and / or" and are used interchangeably therewith unless the context clearly indicates otherwise. The word "such as" used herein means the phrase "such as, but not limited to," and is used interchangeably therewith.

[0050] It should also be noted that in the apparatus, device, and method of the present disclosure, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present disclosure.

[0051] In this document, modifiers such as "first" and "second" without quantifiers are intended to distinguish different elements / components / circuits / modules / devices / steps, and are not used to emphasize the order, positional relationship, importance, priority, etc. In contrast, modifiers such as "first" and "second" with quantifiers can be used to emphasize the order, positional relationship, importance, priority, etc. of different elements / components / circuits / modules / devices / steps.

[0052] The above description is provided for the purpose of illustration and description. This description is not intended to limit the embodiments of the present disclosure to the forms disclosed herein. Although a number of example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.

Claims

1. A method for controlling an automatic pool cleaning device, comprising: In the process of controlling the automatic pool cleaning device to move on the water surface, determining distance data between the automatic pool cleaning device and surrounding objects based on detection data from a distance sensor; determining a category of the object based on a magnitude of a change in the distance data; as well as The moving path of the automatic pool cleaning device is adjusted based on the category of the object.

2. The method according to claim 1, wherein Determining the category of the object based on the magnitude of the change in the distance data includes: When the change amplitude of the distance data between adjacent frames within the specified time period is unstable, the object corresponding to the distance data is determined to be a floating object.

3. The method according to claim 1, wherein Determining the category of the object based on the magnitude of the change in the distance data includes: When the change amplitude of the distance data of adjacent frames continues to decrease within the specified time period, it is determined that the object corresponding to the distance data is a fixed object.

4. The method according to claim 1, wherein Determining the category of the object based on the magnitude of the change in the distance data includes: When the variation range of the distance data between adjacent frames within a specified time period is greater than or equal to a specified threshold, it is determined that the object corresponding to the distance data is a fixed object.

5. The method according to claim 1, wherein Determining the category of the object based on the magnitude of the change in the distance data includes: When the change amplitude of the distance data between adjacent frames within a specified time period is less than a specified threshold, the object corresponding to the distance data is determined to be a floating object.

6. The method of claim 1, wherein: Determining the category of the object based on the magnitude of the change in the distance data includes: determining a plurality of clusters of the distance data based on a change in the distance data of adjacent frames within a specified time period; determining an object corresponding to a cluster with the largest variation among the plurality of clusters as a fixed object; and Objects corresponding to other clusters among the plurality of clusters are determined as floating objects.

7. The method according to any one of claims 1 to 6, wherein: Adjusting the movement path of the automatic pool cleaning device based on the category of the object includes: If the object is determined to be a fixed object and is located ahead of the current travel direction of the automatic pool cleaning device, the automatic pool cleaning device is controlled to turn and move to another movement path when the distance between the object and the device reaches a specified distance.

8. The method according to any one of claims 1 to 6, wherein: Adjusting the movement path of the automatic pool cleaning device based on the category of the object includes: In a case where the object is determined to be a floating object and the object is located ahead of the current traveling direction of the automatic pool cleaning device, the automatic pool cleaning device is controlled to move toward the object or avoid the object.

9. An automatic pool cleaning device comprising: a distance sensor configured to detect the distance between the automatic pool cleaning device and surrounding objects during the movement of the automatic pool cleaning device on the water surface; as well as A controller configured to execute the method according to any one of claims 1 to 8.

10. The automatic pool cleaning device according to claim 9, wherein: The distance sensor includes at least one of an ultrasonic sensor, a laser radar, an infrared sensor, a time-of-flight sensor, and a visual sensor.

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