A docking method and system for a pool robot

Abstract

The application discloses a docking method and system of a pool robot, and relates to the technical field of pool cleaning equipment. The method comprises the following steps: adjusting the sensing range of a ranging sensor, and controlling the ranging sensor to collect sensing data of the area where a base station is located; the ranging sensor is installed on the body of the pool robot; based on the sensing data, the position characteristics of the base station are determined; and according to the position characteristics, the body of the pool robot is controlled to dock with the base station. By using the method, high-precision identification of the base station by the pool robot and stable docking can be realized.

Description

Technical Field

[0001] This disclosure relates to the field of swimming pool cleaning equipment technology, and in particular to a docking method and system for a swimming pool robot. Background Technology

[0002] In related technologies, battery-powered pool cleaning robots need to automatically return to a base station for charging or standby after completing their pool cleaning tasks. Currently, in the docking solutions between pool robots and base stations, using 3D multi-line LiDAR for perception results in excessively high hardware costs and large size, making it unsuitable for consumer products. Using ordinary 2D LiDAR, however, only allows horizontal scanning and cannot capture the 3D shape of the base station, and it is difficult to detect the base station's location when there is a significant drop between the pool bottom and the base station on the shore. Therefore, how to achieve high-precision identification and stable docking of pool robots with base stations in scenarios with large drops, while maintaining low cost, has become a pressing technical problem to be solved in this field. Summary of the Invention

[0003] This disclosure provides a docking method and system for swimming pool robots. The technical solution of this disclosure is as follows: In a first aspect, this disclosure provides a docking method for a swimming pool robot, including: Adjust the sensing range of the ranging sensor to control the ranging sensor to collect sensing data of the area where the base station is located; the ranging sensor is installed on the body of the pool robot. Based on the sensed data, the location characteristics of the base station are determined; according to the location characteristics, the pool robot body is controlled to dock with the base station.

[0004] Secondly, this disclosure provides a docking system for a swimming pool robot, comprising: The swimming pool robot body includes a moving unit, a ranging sensor, and a control unit; the scanning angle of the ranging sensor is variable; the control unit is configured to determine the position characteristics of the base station based on the sensing data collected by the ranging sensor, and control the movement of the moving unit according to the position characteristics, so that the swimming pool robot docks with the base station. A base station, located on the edge of the pool, is used to dock with the pool robot body.

[0005] The technical solution disclosed in this paper brings at least the following beneficial effects: In the embodiments of this disclosure, by adjusting the sensing range of the ranging sensor, the ranging sensor is controlled to collect sensing data of the area where the base station is located; the ranging sensor is installed on the body of the swimming pool robot; based on the sensing data, the positional characteristics of the base station are determined; according to the positional characteristics, the swimming pool robot body is controlled to dock with the base station. In this way, the ranging sensor can change its sensing range, enabling the acquisition of the base station's positional characteristics at low cost, overcoming the problem of excessively high costs associated with directly using three-dimensional multi-line LiDAR; simultaneously, by adjusting the sensing range, the area where the base station is located can be perceived in scenarios with large elevation differences, solving the problem that traditional fixed-viewpoint sensors cannot perceive base stations, and improving the accuracy of identification.

[0006] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0007] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0008] Figure 1 A flowchart illustrating a first specific embodiment of a docking method for a swimming pool robot provided in this disclosure; Figure 2 A flowchart illustrating a second specific embodiment of a docking method for a swimming pool robot provided in this disclosure; Figure 3 This is a schematic diagram of the docking system for a swimming pool robot provided in an embodiment of this disclosure. Detailed Implementation

[0009] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0010] The following description, with reference to the accompanying drawings, illustrates a docking method and system for a swimming pool robot according to an embodiment of the present disclosure.

[0011] Figure 1 This is a schematic flowchart illustrating a docking method for a swimming pool robot provided in an embodiment of this disclosure. Figure 1 As shown, the method includes the following steps: S101, Adjust the sensing range of the ranging sensor and control the ranging sensor to collect sensing data of the area where the base station is located; The ranging sensor is installed on the body of the pool robot.

[0012] In the embodiments of this disclosure, a ranging sensor is installed on the pool robot body. This ranging sensor has a degree of freedom that allows for changing the scanning angle. The ranging sensor can be used to collect sensing data pointing towards the area where the base station is located. It should be noted that the "ranging sensor" proposed in this embodiment refers to a sensor capable of measuring the distance to a target object. Its specific implementation may include one or more combinations of time-of-flight ranging sensors, ultrasonic sensors, lidar sensors, depth cameras, and binocular cameras. "Having a degree of freedom that allows for changing the scanning angle" means that the scanning direction of the ranging sensor can be adjusted as needed to adjust the sensing range of the ranging sensor. For example, the pointing of the ranging sensor can be changed by a rotation mechanism, thereby enabling the ranging sensor to sense environmental information in different spatial areas.

[0013] S102, based on sensing data, determine the location characteristics of the base station; according to the location characteristics, control the pool robot to dock with the base station.

[0014] In embodiments of this disclosure, the sensed data is analyzed and processed to determine the location characteristics of the base station. For example, the location characteristics of the base station may include at least one of three-dimensional shape information and reflectivity information. Three-dimensional shape information refers to the spatial geometric contour features of the base station, and reflectivity information refers to the reflection characteristics of the base station surface to incident signals (such as lasers, ultrasound, etc.). By extracting these feature information, the control unit can identify the presence and precise location of the base station from the sensed data. Then, based on the location characteristics of the base station, the location of the base station can be determined, and docking with the base station can be achieved. For example, based on the location characteristics of the base station, control commands can be generated and sent to the mobile unit to control the pool robot to move towards the base station and complete the docking. The docking process may include multiple sub-stages such as navigation movement, posture adjustment, and final docking.

[0015] In the embodiments of this disclosure, by adjusting the sensing range of the ranging sensor, the ranging sensor is controlled to collect sensing data of the area where the base station is located; the ranging sensor is installed on the body of the swimming pool robot; based on the sensing data, the positional characteristics of the base station are determined; according to the positional characteristics, the swimming pool robot body is controlled to dock with the base station. In this way, the ranging sensor can change its sensing range, enabling the acquisition of the base station's positional characteristics at low cost, overcoming the problem of excessively high costs associated with directly using three-dimensional multi-line LiDAR; simultaneously, by adjusting the sensing range, the area where the base station is located can be perceived in scenarios with large elevation differences, solving the problem that traditional fixed-viewpoint sensors cannot perceive base stations, and improving the accuracy of identification.

[0016] In some possible implementations, the sensing range of the ranging sensor is adjusted to control the ranging sensor to collect sensing data of the area where the base station is located, including: In response to the docking command between the pool robot and the base station or the positional relationship between the pool robot and the base station, the scanning angle of the ranging sensor is adjusted so that the scanning range of the ranging sensor points to the area where the base station is located; the scanning angle includes at least one of the following: depression angle, elevation angle, left turn angle, and right turn angle.

[0017] In this embodiment of the disclosure, when a docking instruction between the pool robot and the base station is received or the positional relationship between the pool robot and the base station is determined, the scanning angle of the ranging sensor can be adjusted. For example, one or more of the tilt angle, elevation angle, left turn angle, and right turn angle can be adjusted so that the scanning range of the ranging sensor points to the area where the base station is located, so that the ranging sensor can collect sensing data of the area where the base station is located.

[0018] In some possible implementations, adjusting the scanning angle of the ranging sensor so that its scanning range points towards the area where the base station is located includes: In response to detecting that the pool robot and the base station are on different height planes, the scanning angle of the ranging sensor is adjusted so that the scanning range of the ranging sensor is tilted towards the area where the base station is located; the scanning angle includes at least one of depression and elevation angles; or In response to detecting that the pool robot body and the base station are at different heights on the same plane, the scanning angle of the ranging sensor is adjusted so that the scanning range of the ranging sensor is tilted towards the area where the base station is located; the scanning angle includes at least one of left turning angle and right turning angle.

[0019] In this embodiment, when the scanning angle of the ranging sensor is adjusted so that its scanning range points towards the area where the base station is located, if it is detected that the two are at different heights, the rotating mechanism can be controlled to rotate, causing the ranging sensor to change its elevation or depression angle, adjusting its scanning range from horizontal to angled upwards or downwards towards the area where the base station is located above or below the water surface. For example, by adjusting the elevation or depression angle, base station sensing data that was originally in its horizontal scanning blind zone can be collected. Alternatively, if it is detected that the pool robot and the base station are at different heights on the same plane, the left or right rotation angle of the ranging sensor can be adjusted so that the scanning range of the ranging sensor is tilted towards the area where the base station is located. In this way, cross-regional perception can be achieved in scenarios with large elevation differences.

[0020] In some possible implementations, the location characteristics of the base station are determined based on sensing data, including: Based on sensing data, the feature information of the base station is obtained to determine the positional relationship between the base station and the pool robot; wherein, the feature information includes at least one of three-dimensional shape information and reflection information.

[0021] In this embodiment of the disclosure, when determining the location characteristics of a base station, sensing data can be acquired to determine the three-dimensional shape information and reflection information of the base station. The three-dimensional shape information can be the spatial geometric contour features of the base station, and the reflectivity information can be the reflection characteristics of the base station surface to incident signals (such as lasers, ultrasound, etc.). Then, based on the three-dimensional shape information and reflection information of the base station, the positional relationship between the base station and the pool robot can be determined, such as the relative position of the base station to the pool robot.

[0022] In some possible implementations, characteristic information of the base station is obtained based on sensing data, including: Acquire two-dimensional scanning data collected at different scanning angles, and the angle information corresponding to each two-dimensional scanning data; Based on the angle information corresponding to each two-dimensional scan data, the three-dimensional point cloud information is generated by stitching together the two-dimensional scan data. The three-dimensional shape features of the base station and / or the relative positional relationship between the base station and the pool robot are extracted based on the three-dimensional point cloud information.

[0023] In this embodiment, the control unit sequentially stitches together multiple two-dimensional scan data collected at different elevation angles with the corresponding elevation angle information to generate three-dimensional point cloud information. The control unit then segments the three-dimensional point cloud information into multiple candidate target regions using a point cloud segmentation algorithm and extracts the three-dimensional shape features of each candidate target region, including geometric features such as the bounding rectangle size, aspect ratio, and straightness of the contour edges. For example, the control unit can use a template matching algorithm to search for targets in the three-dimensional point cloud that are similar in shape to a standard template of the base station. Simultaneously, the control unit acquires the echo signal intensity information contained in the sensing data. Different materials have different reflectivities for lasers; metal surfaces have higher reflectivity, while plastic or rubber surfaces have lower reflectivity. In practical applications, high-reflectivity areas can be set on the base station surface to enhance the base station's recognizability. For example, reflective materials can be pasted around the edge of the base station base or around the charging port, making these areas exhibit significantly higher echo intensity than the surrounding environment. The control unit extracts the reflectivity features of each candidate target region based on the echo signal intensity information, including average reflectivity, maximum reflectivity, and the proportion of high-reflectivity areas.

[0024] Alternatively, the relative positional relationship between the base station and the pool robot can be determined. For example, the control unit fuses the extracted 3D shape features and reflectivity features to comprehensively determine whether a candidate target is a base station. Fusion recognition can employ methods such as weighted scoring, feature matching, or machine learning classifiers. For instance, in a weighted scoring method, the control unit sets weight coefficients for the 3D shape features and reflectivity features respectively; when the comprehensive score of a candidate target exceeds a preset threshold, it is determined to be a base station.

[0025] In some possible implementations, determining the characteristic information of the base station based on the sensing data further includes: Obtain the echo signal strength information from the sensed data; The reflectivity characteristics of the base station and / or the relative positional relationship between the base station and the swimming pool robot are determined based on the echo signal strength information.

[0026] In this embodiment, the ranging sensor, when emitting a detection signal and receiving reflected echoes, can not only measure distance but also acquire the intensity information of the echo signal. Taking a two-dimensional lidar as an example, the lidar emits a laser beam to illuminate the surface of a target object. Different materials have different reflectivities to the laser. Metal surfaces have higher reflectivity and stronger echo signals; plastic, rubber, or the inner wall of a swimming pool have lower reflectivity and weaker echo signals. The control unit can acquire the echo signal intensity information contained in the sensing data and determine the material characteristics of the target object based on the intensity value. For example, when the echo signal intensity exceeds a preset threshold, the area is determined to be a high-reflectivity area; when the echo signal intensity is lower than the preset threshold, it is determined to be a low-reflectivity area. Alternatively, the relative positional relationship between the base station and the pool robot can be determined based on the echo signal intensity information. In practical applications, a high-reflectivity area (such as a reflective film or metal patch) can be set on the surface of the base station so that the base station exhibits a significantly higher echo intensity than the surrounding environment when scanned by the lidar. The control unit can quickly identify the location of the base station from the sensing data and eliminate interference objects in the pool environment by filtering through intensity thresholds.

[0027] In some possible implementations, the pool robot body is controlled to dock with the base station based on its positional relationship, including: Once the base station is identified, the pool robot is controlled to move towards the base station based on its location information.

[0028] In this embodiment of the disclosure, if a base station is identified, the pool robot can be controlled to move towards the location of the base station based on the base station's location information, thereby achieving docking between the pool robot and the base station. For example, during the movement, the control unit continuously acquires sensing data and adjusts the robot's direction and speed in real time until the robot reaches the docking position at the base station and completes the docking.

[0029] In some possible implementations, the pool robot body is controlled to dock with the base station based on its positional relationship, including: When the three-dimensional shape features match the standard shape of a base station, and the reflectivity features match a preset reflectivity threshold, the base station is confirmed to be identified. Control the swimming pool robot to move towards the base station.

[0030] In this embodiment of the present disclosure, the control unit compares the extracted three-dimensional shape features and reflectivity features with preset conditions respectively, and makes a comprehensive judgment on whether the base station is identified.

[0031] In one implementation, the control unit pre-stores a standard 3D template of the base station. When the matching degree between the 3D shape features extracted from the sensing data and the standard template exceeds a preset threshold, the 3D shape feature is considered to be successfully matched. Simultaneously, the control unit acquires the echo signal intensity information of the candidate region. When the average reflectivity or the proportion of high reflectivity regions exceeds a preset threshold, the reflectivity feature is considered to be successfully matched. Only when both the 3D shape feature and the reflectivity feature are successfully matched does the control unit confirm that the base station has been identified.

[0032] In another implementation, the control unit employs a weighted scoring method, assigning weight coefficients to the three-dimensional shape features and reflectivity features respectively, and calculating a comprehensive score. When the comprehensive score exceeds a preset threshold, a base station is confirmed to have been identified. For example, if the weight of the three-dimensional shape features is 0.6 and the weight of the reflectivity features is 0.4, a sum of their weighted scores greater than 0.8 indicates a base station has been identified. After confirming the base station's identification, the control unit can determine the precise location and orientation of the base station based on the sensing data, generate a navigation path, and control the mobile unit to drive the pool robot towards the base station. During the movement, the control unit continuously acquires sensing data and adjusts the robot's direction and speed in real time until the robot reaches the docking position at the base station and completes docking.

[0033] To make the method provided in this disclosure clearer, the docking method of the pool robot will be described in detail below with reference to the following examples, such as... Figure 2 As shown, the following processes are included: Step S201: In response to detecting that the pool robot body and the base station are in different height areas, the control unit controls the rotation mechanism to change the elevation angle of the ranging sensor.

[0034] For example, the pool robot is equipped with a ranging sensor and a rotation mechanism. The ranging sensor can be implemented as a two-dimensional LiDAR, and the rotation mechanism can be implemented as a rotating component driven by a pitch motor. The two-dimensional LiDAR is mechanically connected to the pitch motor, and the control unit dynamically changes the scanning direction of the two-dimensional LiDAR by controlling the rotation angle of the pitch motor.

[0035] When the pool robot completes its cleaning task and needs to return to the base station, the robot itself is located at the bottom of the pool, while the base station is located above the water surface on the pool's edge, placing them at different heights with a significant difference in elevation. In this scenario, the control unit first detects the relative position of the robot and the base station. When it determines that they are at different heights, it controls the pitch motor to rotate the 2D LiDAR upwards by a certain angle, tilting its scanning range towards the area where the base station is located, thereby achieving scanning and perception of the space above the water surface.

[0036] Step S202: Control the ranging sensor to collect sensing data pointing to the area where the base station is located.

[0037] After adjusting the elevation angle of the ranging sensor, the control unit controls the 2D lidar to begin collecting sensing data pointing towards the area where the base station is located. When placed horizontally, the 2D lidar can only scan a horizontal plane, but by changing its elevation angle using the pitch motor, it can scan three-dimensional space.

[0038] For example, the control unit controls the pitch motor to drive the 2D LiDAR to scan at multiple elevation angles, collecting 2D scan data at different elevation angles, and simultaneously recording the elevation angle information corresponding to each 2D scan data. In this way, a single pitch motor adds a degree of freedom to the 2D LiDAR, achieving a 3D perception effect that originally required expensive 3D multi-line LiDAR at a low cost.

[0039] Step S203: Generate three-dimensional point cloud information based on the sensing data, and extract the three-dimensional shape features of the base station based on the three-dimensional point cloud information.

[0040] The control unit processes the acquired sensing data. First, it sequentially stitches together multiple two-dimensional scan data collected at different elevation angles with the corresponding elevation angle information to generate three-dimensional point cloud information. This three-dimensional point cloud information contains the spatial coordinates of various objects in the pool environment.

[0041] Subsequently, the control unit extracts the three-dimensional shape features of the base station from the three-dimensional point cloud using algorithms such as point cloud segmentation, clustering, and feature extraction. For example, geometric features such as the edge contour of the base station base, the shape of the pillar, and the location of the charging interface can all be identified from the three-dimensional point cloud.

[0042] Step S204: Obtain the echo signal strength information contained in the sensing data, and determine the reflectivity characteristics of the base station based on the echo signal strength information.

[0043] Simultaneously, the control unit also acquires the echo signal intensity information contained in the sensing data. Taking a two-dimensional lidar as an example, when a lidar emits a laser beam and receives the reflected echo, it can not only measure the distance but also obtain the intensity value of the echo signal. Different materials have different reflectivities to lasers; for example, metal surfaces have higher reflectivity, while plastic or rubber surfaces have lower reflectivity.

[0044] In practical applications, high-reflectivity areas can be created on the surface of base stations to enhance their identifiability. For example, highly reflective material can be affixed around the base station's base or charging port, causing this area to exhibit a significantly higher echo intensity than the surrounding environment during LiDAR scanning. By setting an intensity threshold, the control unit can quickly filter out underwater background noise and similarly shaped interference objects, thereby identifying the base station's location from the sensing data.

[0045] Step S205: Fuse the three-dimensional shape features with the reflectivity features to identify the base station.

[0046] The control unit fuses three-dimensional shape features with reflectivity features to comprehensively determine whether the target in the sensed data is a base station. Fusion recognition can employ various methods, such as weighted scoring, feature matching, and machine learning classifiers.

[0047] Through multimodal fusion recognition, even if there are interfering objects in the pool environment that are similar in shape to the base station (such as metal handrails or chair legs at the edge of the pool), the control unit can accurately distinguish them due to their different reflectivity characteristics, thereby greatly improving the recognition accuracy.

[0048] Step S206: Based on the recognition result, control the mobile unit to drive the pool robot body to dock with the base station.

[0049] After successfully identifying the base station, the control unit generates a navigation path and control commands based on the base station's position and attitude information, and controls the mobile units (such as drive wheels, tracks, etc.) to drive the pool robot body towards the base station. During the docking process, the control unit can also dynamically adjust the angle of the pitch motor based on real-time acquired sensing data, continuously tracking the position of the base station until docking is completed, ensuring the stability and success rate of the docking process.

[0050] This embodiment addresses the issue of traditional fixed-viewpoint sensors failing to detect blind spots in the pool robot and base station locations by controlling a rotation mechanism to change the elevation angle of the ranging sensor. This allows the sensor's scanning range to tilt towards the base station's area, solving the problem of blind spots in traditional fixed-viewpoint sensors. For example, when the robot is deep in the pool and the base station is on the shore, a pitch motor drives the 2D LiDAR to rotate upwards, enabling it to scan the space above the water surface at an angle. This facilitates docking guidance across large elevation differences, expanding the application scenarios of the pool robot. By changing the scanning angle of the 2D LiDAR through the rotation mechanism, multiple 2D scan data collected after the angle change are sequentially stitched with the corresponding angle information to generate 3D spatial environment information. Using a single rotation mechanism adds a degree of freedom to the 2D LiDAR, achieving a 3D perception effect that previously required expensive multi-line 3D LiDAR with low-cost hardware. This reduces product costs while maintaining perception accuracy, making it suitable for widespread application in consumer products. By fusing 3D shape features with reflectivity features, this embodiment implements a multimodal base station identification scheme. On the one hand, by extracting the three-dimensional shape features of the base station from three-dimensional point cloud information, the spatial geometric contour of the base station can be identified; on the other hand, by determining the reflectivity characteristics of the base station through echo signal intensity information, the special design of high reflectivity areas on the base station surface can be utilized. After the two are combined, even if there are interfering objects in the pool environment that are similar in shape to the base station (such as metal handrails, chair legs, etc.), the control unit can accurately distinguish them due to their different reflectivity characteristics, greatly reducing the false identification rate and improving the success rate of docking.

[0051] This embodiment provides a swimming pool robot system for performing the steps in the above method embodiments. For example... Figure 3 As shown, the pool robot system provided in this embodiment includes a pool robot body and a base station.

[0052] The pool robot body includes a moving unit, a ranging sensor, a control unit, and a rotating mechanism; the scanning angle of the ranging sensor is variable; the control unit is configured to determine the position characteristics of the base station based on the sensing data collected by the ranging sensor, and control the movement of the moving unit according to the position characteristics, so that the pool robot can dock with the base station. The base station, located on the edge of the pool, is used to dock with the pool robot.

[0053] In embodiments of this disclosure, the mobile unit can be used to drive the pool robot body to move underwater and may include components such as drive wheels, tracks, and propellers. A ranging sensor has a degree of freedom that allows for changing the scanning angle and is used to collect sensing data pointing towards the area where the base station is located. The ranging sensor may include one or more combinations of time-of-flight ranging sensors, ultrasonic sensors, lidar sensors, depth cameras, and binocular cameras. The control unit is configured to determine the positional characteristics of the base station based on the sensing data collected by the ranging sensor, and control the movement of the mobile unit according to the positional characteristics, enabling the pool robot to dock with the base station. When the ranging sensor includes a combination of multiple sensors, the control unit can fuse the data collected by the multiple sensors. For example, the ranging sensor may be a two-dimensional lidar.

[0054] The base station can be installed on the poolside for docking with the pool robot. The base station is characterized by at least one of the following: its three-dimensional shape and surface laser reflectivity. The base station surface has high-reflectivity areas or color-coded areas to enhance its visibility. For example, highly reflective material can be affixed to the edge of the base station's base or around the charging port, enabling the ranging sensor to quickly distinguish the base station from interfering objects in the pool environment based on reflectivity characteristics.

[0055] In some possible implementations, determining the location features of the base station includes: acquiring feature information of the base station and determining the positional relationship between the base station and the pool robot; wherein the feature information includes at least one of three-dimensional shape information and reflection information.

[0056] In some possible implementations, the scanning angle of the ranging sensor can be variable, including pitch and / or lateral rotation.

[0057] In some possible implementations, the pool robot body also includes: A rotating mechanism, connected to the range sensor, or mechanically connected to the range sensor via an optical mirror that mates with the range sensor, is used to change the scanning angle of the range sensor. The rotating mechanism includes a motor-driven rotating component. The control unit adjusts the scanning direction of the ranging sensor by controlling the rotation angle of the motor of the rotating mechanism.

[0058] In embodiments of this disclosure, a rotating mechanism is mechanically connected to a ranging sensor or an optical mirror that cooperates with the ranging sensor, used to change the scanning angle of the ranging sensor. The rotating mechanism may include a motor-driven rotating assembly. The control unit dynamically adjusts the scanning direction of the ranging sensor by controlling the rotation angle of the motor, enabling the ranging sensor to scan environmental information in different spatial areas. Exemplarily, the rotating mechanism may include a pitch motor or a yaw motor, mechanically connected to the two-dimensional lidar. As an example, the rotating mechanism can be a pitch motor, fixedly connected to the housing of the two-dimensional lidar, used to drive the two-dimensional lidar to rotate around a horizontal axis, thereby changing the pitch angle of its scanning plane. The control unit can control the pitch motor to drive the two-dimensional lidar to rotate in steps within a preset pitch angle range, for example, from -30° to +30°, acquiring one frame of two-dimensional scan data every 1°. Alternatively, the rotating mechanism can be a yaw motor, fixedly connected to the housing of the two-dimensional lidar, used to drive the two-dimensional lidar to rotate around a vertical axis, thereby changing the yaw angle of its scanning plane, achieving three-dimensional scanning of a 360° range in the horizontal direction. Alternatively, the rotation mechanism can include a combination of pitch and yaw motors, enabling the 2D lidar to rotate in both pitch and yaw degrees of freedom, achieving more flexible 3D spatial scanning.

[0059] Understandably, the control unit can be connected to the mobile unit, the ranging sensor, and the rotating mechanism respectively to execute the docking method described in any of the above-described embodiments. For example, the control unit can be used to control the ranging sensor to collect sensing data pointing towards the area where the base station is located, determine the characteristic information of the base station based on the sensing data, and control the mobile unit to dock with the base station according to the characteristic information. The characteristic information includes at least one of three-dimensional shape information and reflectivity information. In response to detecting that the pool robot body and the base station are in different height areas, the control unit controls the rotating mechanism to change the elevation angle of the ranging sensor, causing the scanning range of the ranging sensor to tilt towards the area where the base station is located. As an example, when the pool robot body is located at the bottom of the pool and the base station is located at the shore, the control unit controls the pitch motor to drive the two-dimensional lidar to rotate upwards, causing it to scan the base station above the water surface at an angle; the control unit is used to generate three-dimensional point cloud information based on the sensing data, and extract the three-dimensional shape features of the base station based on the three-dimensional point cloud information; acquire the echo signal intensity information contained in the sensing data, and determine the reflectivity features of the base station based on the echo signal intensity information; fuse the three-dimensional shape features and reflectivity features to identify the base station. For example, the control unit uses weighted scoring, feature matching, or machine learning classifiers to fuse and judge 3D shape features and reflectivity features. The control unit changes the scanning angle of the 2D LiDAR through a rotation mechanism, and then performs time-series stitching of multiple 2D scan data acquired after changing the scanning angle with the corresponding angle information to generate 3D spatial environment information.

[0060] In some possible implementations, the ranging sensor includes one or more combinations of time-of-flight ranging sensors, ultrasonic sensors, lidar sensors, depth cameras, and binocular cameras; When the ranging sensor includes a combination of multiple sensors, the control unit fuses the data collected by the multiple sensors.

[0061] In the embodiments of this disclosure, the ranging sensor can be implemented in various types according to actual needs.

[0062] When the ranging sensor is a single type of sensor, such as a two-dimensional lidar, it measures distance by emitting a laser beam and obtains the echo signal intensity, making it suitable for scenarios requiring high-precision three-dimensional perception. In another embodiment, the ranging sensor can be an ultrasonic sensor, which is low-cost and has good propagation characteristics in water. In yet another embodiment, the ranging sensor can be a time-of-flight ranging sensor, capable of quickly acquiring depth information. In yet another embodiment, the ranging sensor can be a depth camera or a binocular camera, capable of simultaneously acquiring image and depth information.

[0063] When the ranging sensor is a multi-sensor fusion system, the control unit can fuse data collected by multiple sensors. For example, when using a combination of a 2D LiDAR and a binocular camera, the control unit fuses the 3D point cloud from the LiDAR with the color image from the camera, using color information to assist in identification and distance information for precise positioning. Similarly, when using a combination of an ultrasonic sensor and a depth camera, the control unit uses different sensor data as the primary basis at different distance ranges to achieve stable perception across the entire range. During data fusion, the control unit first performs time synchronization and spatial alignment of the multi-sensor data, transforming the data collected by different sensors to the same coordinate system. Then, it uses algorithms such as weighted averaging or Kalman filtering to synthesize and generate environmental perception results, improving the system's adaptability and robustness under various environmental conditions.

[0064] In some possible implementations, the ranging sensor has a waterproof structure and is configured to acquire sensing data in an underwater environment. The ranging sensor is configured with a waterproof structure to operate normally in an underwater environment. The housing of the ranging sensor can be a sealed design, with waterproof sealing rings at the housing seams to prevent water from seeping into the internal circuitry. The optical window of the ranging sensor can be encapsulated with a waterproof and light-transmitting material to ensure that laser or ultrasonic waves can be transmitted and received normally while preventing water from entering the sensor. Critical electronic components of the ranging sensor can be coated with a waterproof coating to ensure normal circuit operation even if small amounts of water seep in. Through these waterproof structures, the ranging sensor can stably acquire sensing data over a long period in an underwater swimming pool environment.

[0065] In some possible implementations, the base station's characteristic information includes a combination of one or more of the following: the base station's three-dimensional shape, surface color, and surface laser reflectivity. This characteristic information can be used for the pool robot's identification and positioning.

[0066] In embodiments of this disclosure, the three-dimensional shape includes geometric features such as the rectangular outline of the base station base, the columnar structure of the column, and the recessed shape of the charging interface. Surface color may be used, for example, the base station body may adopt a specific color distinct from the pool environment (such as red or yellow), or a colored marking area may be provided on the base station surface. Surface laser reflectivity may be achieved, for example, by providing high reflectivity areas (such as reflective films or metal patches) on the base station surface, so that these areas exhibit significantly higher echo intensity than the surrounding environment during lidar scanning. Alternatively, the base station may be characterized by a combination of the above features, such as simultaneously possessing a specific three-dimensional shape and high reflectivity areas, to improve the accuracy and robustness of identification.

[0067] In some possible implementations, the base station includes: The base is located on the edge of the pool. A high-reflectivity marker, located on the edge or top of the base, is configured to reflect the detection signal emitted by the ranging sensor. The arrangement of the high-reflectivity marker corresponds to the upward scanning range of the ranging sensor, so that the pool robot body located at the bottom of the pool can detect the high-reflectivity marker by adjusting its elevation angle.

[0068] To make the docking method for a swimming pool robot provided in this disclosure clearer, it is described below with reference to the following example. The steps are as follows: As an example, this system can employ a ranging sensor with increased degrees of freedom. Considering that conventional 2D LiDAR can only scan horizontal slices, this embodiment introduces a rotation mechanism to increase the 2D LiDAR's degrees of freedom (even dual-axis degrees of freedom). By continuously changing the rotation angle during motion, two-dimensional data can be sequentially stitched into three-dimensional point cloud data. In this way, the sensing effect of 3D radar can be achieved at extremely low cost.

[0069] During the docking phase, not only can the three-dimensional geometric contours of the base station be matched, but data docking can also be achieved using data such as the signal strength of the lidar. For example, since different materials have different reflectivities to lasers, high reflectivity areas (high reflectivity markings) can be set on the surface of the base station. By setting a threshold for the intensity of reflectivity information, underwater background noise and similarly shaped interference objects can be filtered out instantly, thereby greatly improving the recognition accuracy. In addition, for scenarios with a large drop from the pool bottom to the shore, the pool robot can actively change the sensor elevation angle to scan upwards. Even if the line of sight is obstructed by the edge of the pool, as long as the high reflectivity features exposed on the base station (such as the highly reflective strips on the base station base) are scanned, the control unit can calculate the location of the base station and achieve cross-regional guided docking.

[0070] In another embodiment, the pool robot system includes a movable robot body and a base station. The robot body may include a control unit, a movement unit, and a ranging sensor. The base station can be located on the poolside; the ranging sensor can be configured to sense the characteristic information of the base station; the control unit can control the movement unit to dock with the base station based on the base station characteristics sensed by the ranging sensor. A wireless communication connection exists between the base station and the robot, allowing the base station to send commands to change the robot's state.

[0071] The robot body may also include at least one rotating mechanism, which can be connected to a ranging sensor, or connected to the ranging sensor via a mirror that cooperates with the ranging sensor, enabling the robot to change the scanning angle of the sensor to measure environmental information at different angles. During docking with a base station, the rotating mechanism can adjust the scanning angle of the ranging sensor by changing its angle to detect feature information including the base station. (The mirror or reflective surface can also be part of the ranging sensor). For example, the ranging sensor can be a two-dimensional LiDAR, and the rotating mechanism can be driven by a motor; the LiDAR can gain additional degrees of freedom through the rotating mechanism, allowing the control unit to combine angle information to generate three-dimensional spatial environmental information. For instance, the rotating mechanism can change the elevation angle of the ranging sensor, tilting the scanning range towards the area where the base station is located to detect environmental features including the base station. Base station features may include one or more combinations of the base station's three-dimensional shape, surface color, and surface laser reflectivity; that is, the base station perception data acquired by the ranging sensor may include one or more of the base station's shape, color, and reflectivity.

[0072] At least some components of the ranging sensor and at least some components of the base station can be in an underwater environment. The ranging sensor may include one or more combinations of a Time-of-Flight (ToF) Ranging Sensor, an ultrasonic sensor, a LiDAR sensor, a depth camera, a binocular camera, and a visible light ranging sensor.

[0073] As an example, the ranging sensor or reflector can also be connected to at least two rotating mechanisms, enabling the robot to measure environmental information in different spatial planes.

[0074] Understandably, the robot may also have other sensing base station features, and the ranging sensor can calibrate these other sensing units. When the robot has other sensing base station features, if these other sensing base station features do not meet preset conditions, the ranging sensor can also be used for alignment.

[0075] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0076] Embodiments of this disclosure also provide an electronic device including a memory and a processor, the memory storing a computer program and the processor being configured to run the computer program to perform the steps in any of the above method embodiments.

[0077] Embodiments of this disclosure also provide a computer-readable storage medium storing a computer program configured to perform the steps in any of the above method embodiments when executed.

[0078] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0079] Embodiments of this disclosure also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0080] Embodiments of this disclosure also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0081] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0082] The method provided in this disclosure has been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this disclosure. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and its core ideas. It should be noted that those skilled in the art can make various improvements and modifications to this disclosure without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this disclosure.

Claims

1. A docking method for a swimming pool robot, characterized in that, include: Adjust the sensing range of the ranging sensor to control the ranging sensor to collect sensing data of the area where the base station is located; the ranging sensor is installed on the body of the pool robot. Based on the sensed data, the location characteristics of the base station are determined; according to the location characteristics, the pool robot body is controlled to dock with the base station.

2. The docking method for the pool robot according to claim 1, characterized in that, The adjustment of the ranging sensor's sensing range, controlling the ranging sensor to collect sensing data from the area where the base station is located, includes: In response to the docking command between the pool robot and the base station or the positional relationship between the pool robot and the base station, the scanning angle of the ranging sensor is adjusted so that the scanning range of the ranging sensor points to the area where the base station is located; the scanning angle includes at least one of the following: depression angle, elevation angle, left turn angle, and right turn angle.

3. The docking method for the pool robot according to claim 2, characterized in that, Adjusting the scanning angle of the ranging sensor so that its scanning range points towards the area where the base station is located includes: In response to detecting that the pool robot body and the base station are at different heights, the scanning angle of the ranging sensor is adjusted so that the scanning range of the ranging sensor is tilted towards the area where the base station is located; the scanning angle includes at least one of depression angle and elevation angle; or In response to detecting that the pool robot body and the base station are at different heights on the same plane, the scanning angle of the ranging sensor is adjusted so that the scanning range of the ranging sensor is tilted towards the area where the base station is located; the scanning angle includes at least one of left turning angle and right turning angle.

4. The docking method for the pool robot according to claim 1, characterized in that, Based on the sensed data, the location characteristics of the base station are determined, including: Based on the sensing data, the feature information of the base station is obtained to determine the positional relationship between the base station and the pool robot; wherein, the feature information includes at least one of three-dimensional shape information and reflection information.

5. The docking method for the pool robot according to claim 4, characterized in that, The step of obtaining the feature information of the base station based on the sensing data includes: The sensing data is acquired by collecting two-dimensional scanning data at different scanning angles, and the angle information corresponding to each two-dimensional scanning data. Based on the angle information corresponding to each of the two-dimensional scan data, three-dimensional point cloud information is generated by stitching together the two-dimensional scan data. Based on the three-dimensional point cloud information, the three-dimensional shape features of the base station are extracted and / or the relative positional relationship between the base station and the swimming pool robot is determined.

6. The docking method for the pool robot according to claim 4, characterized in that, The step of determining the feature information of the base station based on the sensing data further includes: Obtain the echo signal strength information from the sensed data; The reflectivity characteristics of the base station and / or the relative positional relationship between the base station and the swimming pool robot are determined based on the echo signal strength information.

7. The docking method for the pool robot according to claim 1 or 4, characterized in that, The step of controlling the pool robot body to dock with the base station according to the positional relationship includes: Once the base station is identified, the pool robot is controlled to move toward the base station based on its location information.

8. The docking method for the pool robot according to claim 7, characterized in that, The step of controlling the pool robot body to dock with the base station according to the positional relationship includes: When the three-dimensional shape feature matches the standard shape of a base station and the reflectivity feature matches a preset reflectivity threshold, the base station is confirmed to be identified. Control the swimming pool robot to move towards the base station.

9. A docking system for a swimming pool robot, characterized in that, include: The pool robot body includes a moving unit, a ranging sensor, and a control unit; the scanning angle of the ranging sensor is variable. The control unit is configured to determine the location characteristics of the base station based on the sensing data collected by the ranging sensor, and control the movement of the mobile unit according to the location characteristics, so that the pool robot docks with the base station; A base station, located on the edge of the pool, is used to dock with the pool robot body.

10. The docking system according to claim 9, characterized in that, Determining the location features of the base station includes: acquiring feature information of the base station and determining the positional relationship between the base station and the pool robot; wherein the feature information includes at least one of three-dimensional shape information and reflection information.

11. The docking system according to claim 9, characterized in that, The scanning angle of the ranging sensor is variable, including pitch angle and / or lateral rotation angle.

12. The docking system for the pool robot according to claim 9, characterized in that, The pool robot body also includes: A rotating mechanism, connected to the ranging sensor, or mechanically connected to the ranging sensor via an optical mirror that cooperates with the ranging sensor, is used to change the scanning angle of the ranging sensor; The rotating mechanism includes a motor-driven rotating component, and the control unit adjusts the scanning direction of the ranging sensor by controlling the rotation angle of the motor of the rotating mechanism.

13. The docking system for the pool robot according to claim 9, characterized in that, The ranging sensor includes at least one of the following: time-of-flight ranging sensor, ultrasonic sensor, lidar sensor, depth camera, and binocular camera; When the ranging sensor includes multiple sensors, the control unit fuses the data collected by the multiple sensors to obtain the sensing data of the base station.

14. The docking system for the pool robot according to claim 9, characterized in that, The location characteristics of the base station include a combination of one or more of the following: the base station's three-dimensional shape, surface color, and surface laser reflectivity.

15. The docking system for the pool robot according to claim 9, characterized in that, The base station includes: The base is placed on the edge of the pool. A high-reflectivity marker, located on the edge or top of the base, is configured to reflect the detection signal emitted by the ranging sensor; the arrangement of the high-reflectivity marker corresponds to the upward scanning range of the ranging sensor, so that the pool robot body located at the bottom of the pool can detect the high-reflectivity marker by adjusting its elevation angle.

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