Charging position identification method and device, equipment and storage medium

Abstract

The invention provides a charging position identification method and device, equipment and a storage medium, relates to the technical field of intelligent equipment control, and solves the problem that accurate positioning is difficult due to the fact that identification of a charging contact is easily interfered in the prior art. According to the scheme, the position of the charging contact relative to the multi-point ToF sensor is determined on the basis of the multi-point ToF sensor by sensing the intensity of the reflected signal of the charging contact in the charging interface area, the implementation cost of the scheme is low, and the multi-point ToF sensor can automatically transmit and receive the signal without being influenced by the environment, so that the reliability of the system is improved. According to the scheme, the charging position can be accurately and efficiently recognized, the recognition efficiency of the scheme is improved, and equipment can efficiently achieve automatic charging operation.

Description

Technical Field

[0001] This application relates to the field of intelligent device control technology, and in particular to a charging position identification method, device, equipment and storage medium. Background Technology

[0002] Mobile smart devices such as robot vacuum cleaners and robot dogs usually need to return to fixed charging locations such as charging base stations, charging compartments, and charging piles to charge. They need to identify and align with the corresponding charging contacts to form a charging circuit and then charge.

[0003] In related technologies, smart devices typically achieve accurate identification and docking of charging contacts through techniques such as infrared guidance, visual guidance, magnetic guidance, or wireless signal strength positioning. Infrared guidance involves the charging base station emitting modulated infrared signals, and the smart device uses multiple infrared receiving sensors to detect signal strength differences or angles for positioning. However, the need for multiple infrared receiving sensors places high demands on the smart device's structure. Visual guidance relies on cameras to identify visual markings (such as QR codes or specific patterns) on the charging device; however, this method is greatly affected by lighting conditions, and changes in environmental characteristics can easily lead to visual failure. Wireless signal strength positioning estimates distance by measuring the strength of Wi-Fi or Bluetooth signals between the smart device and the charging device, but this method suffers from low positioning accuracy and unstable signal strength due to environmental multipath effects. In short, the identification and positioning of charging contacts in these technologies are easily affected by device structure and the external environment, making it difficult for smart devices to efficiently complete automatic charging operations. Summary of the Invention

[0004] This application provides a charging position identification method, apparatus, device, and storage medium, which solves the problem in related technologies that charging contact identification is easily interfered with and difficult to accurately locate. This solution uses a multi-point ToF sensor to acquire detection data in a dot matrix transceiver mode, thereby accurately determining the position of the charging contact relative to the multi-point ToF sensor.

[0005] Firstly, this application provides a charging location identification method applied to a smart device. The smart device includes a multi-point ToF sensor, wherein the data transmission and reception of the multi-point ToF sensor is in the form of dot matrix transmission and reception for generating detection data. The charging location identification method includes: In response to receiving target detection data of the corresponding charging interface area obtained by the multi-point ToF sensor, the channel parameter values ​​of the corresponding dot matrix channels in the target detection data are determined. Based on the channel parameter values ​​in the target detection data, the position of the target channel and the cluster center corresponding to the target channel in the first coordinate system of the corresponding charging interface area is determined in all the dot matrix channels. The target channel corresponds to the charging contact in the charging interface area, and the cluster center corresponds to the center point of the charging contact. Based on the mapping origin and cluster center of the multi-point ToF sensor in the first coordinate system, the offset angle of the cluster center relative to the multi-point ToF sensor is determined. Based on the offset angle and the distance between the multi-point ToF sensor and the charging interface area, the coordinates of the cluster center in the second coordinate system of the corresponding multi-point ToF sensor are determined.

[0006] Secondly, this application also provides a charging location identification device for use in smart devices. The smart device includes a multi-point ToF sensor, wherein the data transmission and reception of the multi-point ToF sensor is in the form of dot matrix transmission and reception for generating detection data. The charging location identification device includes: The data detection module is configured to, in response to receiving target detection data of the corresponding charging interface area obtained by the multi-point ToF sensor, determine the channel parameter values ​​of different dot matrix channels in the target detection data; The channel determination module is configured to determine the target channel and the position of the cluster center corresponding to the target channel in the first coordinate system of the corresponding charging interface area based on the channel parameter values ​​in the target detection data. The target channel corresponds to the charging contact in the charging interface area, and the cluster center corresponds to the center point of the charging contact. The angle detection module is configured to determine the offset angle of the cluster center relative to the multi-point ToF sensor based on the mapping origin and cluster center of the multi-point ToF sensor in the first coordinate system. The coordinate transformation module is configured to determine the coordinates of the cluster center in the second coordinate system of the corresponding multi-point ToF sensor based on the offset angle and the distance value of the multi-point ToF sensor relative to the charging interface area.

[0007] Thirdly, this application also provides an electronic device comprising: One or more processors; A storage device is provided for storing one or more programs, which, when executed by one or more processors, enable the one or more processors to implement the charging position identification method of this application.

[0008] Fourthly, this application also provides a storage medium for storing computer-executable instructions, which, when executed by a processor, are used to perform the charging position identification method of this application.

[0009] This application's solution is based on a multi-point ToF sensor and determines the position of the charging contacts relative to the multi-point ToF sensor by sensing and receiving the reflected signal intensity of the charging contacts in the charging interface area. The solution has a low implementation cost, and the multi-point ToF sensor can transmit and receive signals independently without being affected by the environment. This allows the solution to accurately and efficiently identify the charging position, improves the identification efficiency of the solution, and helps the device to achieve efficient automatic charging operation. Attached Figure Description

[0010] Figure 1 This is a schematic diagram illustrating the steps of a charging location identification method provided in an embodiment of this application.

[0011] Figure 2 This is a visual schematic diagram of the detection data provided in one embodiment of this application.

[0012] Figure 3 This is a schematic diagram illustrating the steps for determining cluster centers according to an embodiment of this application.

[0013] Figure 4 This is a schematic diagram of the structure of a charging position identification device provided in an embodiment of this application.

[0014] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0015] The present application will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the embodiments of the present application and are not intended to limit the scope of the present application. Furthermore, it should be noted that, for ease of description, the accompanying drawings only show the parts relevant to the embodiments of the present application, and not all structures. Those skilled in the art, after reading this specification, should be able to deduce that any combination of technical features can constitute an optional implementation method, provided that the technical features do not contradict each other.

[0016] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects, not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, not limited in number; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship. In the description of this application, "multiple" means two or more, and "several" means one or more.

[0017] With the development of robotics technology, the application of intelligent devices in various industries is increasing. For example, in environments such as homes and warehouses, mobile intelligent devices such as robotic vacuum cleaners and robotic dogs are widely used for home cleaning and goods handling. In related technologies, when the battery level of mobile intelligent devices such as robotic vacuum cleaners and robotic dogs drops to a threshold requiring charging, they usually return to fixed charging devices such as charging base stations, charging compartments, and charging piles to charge. They also automatically identify and align with the corresponding charging contacts to form a charging circuit and thus begin charging.

[0018] Currently, smart devices typically use technologies such as infrared guidance, visual guidance, magnetic guidance, or wireless signal strength positioning to accurately identify and connect charging contacts. In the infrared guidance method, the charging base station emits modulated infrared signals, and the smart device uses multiple infrared receiving sensors installed on it to detect signal strength differences or angles for positioning. However, considering the need to install multiple infrared receiving sensors, this places high demands on the structure of the smart device.

[0019] However, in visual guidance, smart devices use cameras to identify visual markings (such as QR codes, specific patterns, etc.) on the charging device. This is greatly affected by lighting conditions. For example, low light or glare can affect the recognition of these markings. Therefore, changes in environmental characteristics can easily lead to visual failure.

[0020] Wireless signal strength-based positioning estimates distance by measuring the strength of Wi-Fi or Bluetooth signals between the smart device and the charging device. However, this method suffers from low positioning accuracy and unstable signal strength due to environmental multipath interference. In other words, the identification and positioning of charging contacts in these technologies are easily affected by device structure and the external environment, making it difficult for smart devices to efficiently complete automatic charging operations.

[0021] To address this issue, this application provides a charging location identification method. This method, applied to smart devices, enables the smart devices to accurately identify charging contacts, facilitating autonomous charging. The smart device includes a multi-point ToF (Time of Flight) sensor. The multi-point ToF sensor uses a dot-matrix transceiver format to generate detection data. It can use signals such as light, ultrasound, and electromagnetic waves as detection signals. Specifically, the multi-point ToF sensor transmits and receives detection signals from multiple points to form a dot-matrix transceiver and generates corresponding detection data. It is conceivable that both the transmitting and receiving ends of the multi-point ToF sensor are in dot-matrix form, such as a 48×32 matrix (the specific matrix size can be set according to actual application requirements). Each point corresponds to a dot-matrix channel, and each dot-matrix channel can feedback the signal reflection intensity at that point. Furthermore, the distance between the target object and the sensor can be determined using the signal transmission time (i.e., the time interval from transmission to reception). Furthermore, the smart device scans the external area using a multi-point ToF sensor to obtain corresponding detection data, and identifies the location of the charging contacts using the charging location identification method in this solution to complete autonomous charging.

[0022] Figure 1 This is a schematic diagram illustrating the steps of a charging position identification method provided in one embodiment of the present application. In one embodiment, a multi-point ToF sensor in the smart device can be disposed on the bottom surface, side surface, or other locations of the device to adapt to the installation position of the charging contacts on the charging device, so as to facilitate scanning of the charging contacts as targets. For example, it can be disposed on the bottom surface of the device to adapt to the charging contacts disposed on the bottom plane of the charging compartment, or disposed on the side surface to adapt to the charging contacts disposed on the side wall of the charging compartment. The smart device then acquires corresponding detection data through the multi-point ToF sensor and analyzes and identifies the location of the charging contacts using this charging position identification method. The specific steps include steps S110-S140: Step S110: In response to receiving the target detection data of the corresponding charging interface area obtained by the multi-point ToF sensor, determine the channel parameter values ​​of the corresponding dot matrix channels in the target detection data.

[0023] It is conceivable that when a smart device returns to the charging case, its posture may fail to align with the charging contacts due to obstacles encountered during movement or limitations in the motion algorithm. Therefore, it is necessary to re-identify the charging contacts. It should be noted that the control scheme for the smart device returning to the charging case can refer to the device movement schemes in related technologies, and will not be elaborated upon here.

[0024] Optionally, in some embodiments, the multi-point ToF sensor of the smart device uses an optical signal as the detection signal. For example, a dot-matrix light panel, such as a VCSEL (Vertical-Cavity Surface-Emitting Laser) light source, is used at the transmitting end of the multi-point ToF sensor to reflect the optical signal after detecting the target object. The receiving end of the multi-point ToF sensor also uses a dot-matrix receiver. Therefore, when the detection signal used at the transmitting end of the multi-point ToF sensor is an optical signal, the amount of light reflection received through each dot-matrix channel is determined as the channel parameter value corresponding to each dot-matrix channel. It is conceivable that the number and arrangement of the dots at the receiving end are the same as at the transmitting end, so that the amount of light reflection returned from the target object is received at each dot-matrix point.

[0025] Taking the charging case as an example, when a smart device returns to the charging case, it can scan using a multi-point ToF sensor to obtain corresponding detection data. It's understandable that different materials within the charging case reflect light differently, and the charging contacts, being made of metal, reflect light significantly differently compared to other non-contact areas within the charging case. Therefore, during detection, the smart device determines the currently scanned charging interface area within the charging case by analyzing the detection data. The charging interface area, as the area where charging contacts are located in the charging device, typically has at least two charging contacts, such as those corresponding to the positive and negative terminals. Optionally, in some embodiments, there may be three charging contacts, including those corresponding to the positive and negative terminals, as well as contacts for the ground. Furthermore, the target detection data records channel parameter values ​​corresponding to different dot matrix channels. For example, when the multi-point ToF sensor uses a 48×32 matrix for dot matrix transceiver, the target detection data records the channel parameter values ​​corresponding to 1536 dot matrix channels.

[0026] Furthermore, after determining the target detection data for the corresponding charging interface area, the channel parameter values ​​for different dot matrix channels within the target detection data are determined. Since multi-point ToF sensors employ dot matrix transceivers, different dot matrix channels can be represented by corresponding channel indices, where the channel index indicates the row and column of the dot matrix channel within the entire dot matrix. Therefore, the channel parameter values ​​corresponding to each dot matrix channel can be identified according to the channel index, thereby establishing a first coordinate system associated with the charging interface area. This first coordinate system serves as the coordinate index value for the dot matrix channel within the first coordinate system. It is conceivable that in the first coordinate system, the coordinate index value represents the position of each dot matrix channel using the channel index, and the corresponding channel parameter value is used as the value at that point. Thus, the position of each charging contact in the charging interface area can be determined through the channel index, and the charging contacts within that area can be distinguished from other non-contact areas using the corresponding channel parameter values.

[0027] Step S120: Based on the channel parameter values ​​in the target detection data, determine the position of the target channel and the cluster center corresponding to the target channel in the first coordinate system of the corresponding charging interface area among all the dot matrix channels.

[0028] Smart devices can cluster the determined dot matrix channels to identify target channels, which correspond to charging contacts in the charging interface area. It is conceivable that the charging contacts include several dot matrix channels, and the several dot matrix channels corresponding to the charging contacts are used as target channels. After clustering, all target channels of the corresponding charging contacts can be determined, and the corresponding cluster center is used as the center point of the charging contacts.

[0029] It is conceivable that the horizontal and vertical field of view of a multi-point ToF sensor are fixed, and correspondingly, the detection range of the multi-point ToF sensor (i.e., the FOV (Field of View) range of the multi-point ToF sensor) is also fixed. Moreover, the distance between the multi-point ToF sensor and the detection plane can determine whether the target object covered by the detection range of the multi-point ToF sensor covers the charging contacts. For example, if the distance between the multi-point ToF sensor and the detection plane meets the preset distance, the detection range of the multi-point ToF sensor can completely include all the charging contacts.

[0030] Figure 2 This is a visualization diagram of the detection data provided in an embodiment of this application. Because the amount of light signal reflected by the charging contact and non-contact areas 101 is different, the corresponding dot matrix channels of the charging contact and the corresponding dot matrix channels of the non-contact areas 101 correspond to different channel parameter values, exhibiting significant differences. Therefore, corresponding detection data is obtained within the detection range of the multi-point ToF sensor, such as... Figure 2As shown, each square in the figure represents a dot matrix channel, and the corresponding grayscale value represents the corresponding channel parameter value. For example, taking a grayscale value of 255 to represent white, the grayscale value of the target channel corresponding to the charging contact is lower than the grayscale value of the dot matrix channel corresponding to the non-contact area 101, making the target channel's color darker. It is conceivable that by mapping the channel parameter values ​​to the range of 0~255, the channel parameters corresponding to the dot matrix channel can be converted into grayscale values. Optionally, in some embodiments, further grayscale binarization can be performed to more clearly distinguish the charging contact and the non-contact area 101. In this regard, the channel index corresponding to each dot matrix channel can be used as the coordinate of that dot matrix channel. Then, based on the clustering area 102 formed by the target channels corresponding to each charging contact, the cluster center 201 of that area is calculated as the center point of the charging contact. That is, after determining the coordinates of each vertex of the clustering area 102, the coordinates of the cluster center 201 are calculated according to the coordinates of each vertex, thereby determining the position of the cluster center 201.

[0031] Step S130: Based on the mapping origin and cluster center of the multi-point ToF sensor in the first coordinate system, determine the offset angle of the cluster center relative to the multi-point ToF sensor.

[0032] Reference Figure 2 In the acquired detection data, the mapping origin 202 corresponds to a dot matrix channel on it. This can be understood as the mapping origin 202 corresponding to the center point of the multi-point ToF sensor. The line connecting this center point and the mapping origin 202 is perpendicular to the detection plane. The distance between these two points corresponds to the distance between the charging interface area and the multi-point ToF sensor. Furthermore, when the distance between the multi-point ToF sensor and the charging interface area meets a preset distance, the FOV range of the multi-point ToF sensor can cover all charging contacts, thus making the dot matrix channels at the edges correspond to the edges of the FOV range. Therefore, the offset angle of the cluster center 201 relative to the multi-point ToF sensor can be determined according to the offset distance of each cluster center 201 relative to the mapping origin 202.

[0033] For example, the offset angle includes a first deflection angle corresponding to the horizontal direction and a second deflection angle corresponding to the vertical direction, such as in Figure 2The horizontal direction corresponds to the horizontal direction, while the vertical direction corresponds to the vertical direction. Furthermore, in the two-dimensional plane of the first coordinate system corresponding to the charging interface area, the vertical direction (corresponding to the Y-axis) is perpendicular to the horizontal direction (corresponding to the X-axis). Optionally, in one embodiment, the offset angle of the cluster center relative to the multi-point ToF sensor can be determined by the offset of each dot matrix channel. Specifically, based on the FOV range of the multi-point ToF sensor, the offset corresponding to each dot matrix channel in the first and second coordinate directions is determined. It is understood that, given a fixed multi-point ToF sensor, the horizontal and vertical field of view angles of the multi-point ToF sensor are fixed, its FOV range is fixed, and the number and arrangement of the dot matrix channels are fixed. Therefore, the offset corresponding to each dot matrix channel in the first coordinate direction can be calculated according to the range of the horizontal field of view angle and the number of dot matrix channels in the first coordinate direction, and the offset corresponding to each dot matrix channel in the second coordinate direction can be calculated according to the range of the vertical field of view angle and the number of dot matrix channels in the second coordinate direction. Here, the first coordinate direction and the second coordinate direction are different coordinate axis directions on the first coordinate system. For example, the first coordinate direction corresponds to the X-axis direction of the first coordinate system, and the second coordinate direction corresponds to the Y-axis direction of the first coordinate system. Therefore, the offset of a single dot matrix channel in the first coordinate direction and the second coordinate direction can be determined, and this offset is the offset of the corresponding angle.

[0034] Furthermore, the difference between the coordinate index value of the cluster center and the mapping origin in the first coordinate direction is determined, and the first deflection angle is determined based on the offset corresponding to each lattice channel in the first coordinate direction. Similarly, the difference between the coordinate index value of the cluster center and the mapping origin in the second coordinate direction is determined, and the second deflection angle is determined based on the offset corresponding to each lattice channel in the second coordinate direction. It can be understood that by calculating the difference between the cluster center and the mapping origin in the first and second coordinate directions—that is, the difference between their coordinate index values—the number of lattice channels between the two points in the first and second coordinate directions can be determined. Then, by calculating the offset in the corresponding direction, the first and second deflection angles can be determined. The corresponding calculation formulas are as follows:

[0035]

[0036] Where, θ h Let θ be the first deflection angle. v The second deflection angle is (row, col), where (row, col) is the coordinate index of the cluster center. row center col ) represents the coordinate index value of the mapping origin, per rowper is the offset corresponding to each dot matrix channel in the first coordinate direction. col This represents the offset of each dot matrix channel in the second coordinate direction. Therefore, this scheme determines the offset angle of the cluster center relative to the multi-point ToF sensor by calculating the offset of each dot matrix channel in different directions. This helps to transform the charging contacts to the coordinate system corresponding to the multi-point ToF sensor, thereby achieving accurate positioning of the charging contacts and improving the accuracy of identification.

[0037] Step S140: Based on the offset angle and the distance value of the multi-point ToF sensor relative to the charging interface area, determine the coordinate value of the cluster center in the second coordinate system of the corresponding multi-point ToF sensor.

[0038] The distance between the multi-point ToF sensor and the charging interface area can be determined using the acquired detection data. Optionally, in some embodiments, after the smart device moves to the charging compartment and determines the charging interface area, it uses the time interval from transmission to reception of the light signal from the multi-point ToF sensor to determine the time of flight of the light signal. Then, combining the propagation speed and time of flight of the light signal, it determines the distance between the multi-point ToF sensor and the charging interface area. Furthermore, after determining the offset angle, based on the distance between the multi-point ToF sensor and the charging interface area, the determined cluster center is subjected to coordinate transformation to convert the cluster center from the first coordinate system to the corresponding coordinate values ​​in the second coordinate system. This allows the position of the cluster center (i.e., the center point of the charging contact) relative to the multi-point ToF sensor to be determined in the same coordinate system. For example, the distance in the second coordinate system can be calculated using trigonometric functions to generate the corresponding coordinate values. Alternatively, the coordinate offset distance corresponding to the current offset angle can be determined based on the coordinate offset amount corresponding to each degree in different coordinate directions to generate the corresponding coordinate values.

[0039] As can be seen from the above scheme, this scheme is based on a multi-point ToF sensor and determines the position of the charging contacts relative to the multi-point ToF sensor by sensing and receiving the reflected signal intensity of the charging contacts in the charging interface area. The implementation cost of the scheme is low, and the multi-point ToF sensor can transmit and receive signals independently without being affected by the environment. This allows the scheme to accurately and efficiently identify the charging position, improves the identification efficiency of the scheme, and helps the device to achieve automatic charging operation efficiently.

[0040] Optionally, when the smart device determines the movement distance based on the third coordinate system, the coordinate values ​​of the cluster center are converted into target coordinate values ​​according to the mapping relationship between the second and third coordinate systems, so that the smart device can determine the movement distance. Here, the third coordinate system is the coordinate system of the corresponding smart device. For example, the coordinate system of the real world can be used as the coordinate system of the smart device. Therefore, when performing movement control, the smart device can determine its own position, destination position, movement direction, and movement distance according to the third coordinate system. It is understood that the second and third coordinate systems use different reference points. Therefore, after determining the position of the charging contact relative to the multi-point ToF sensor, another coordinate transformation is required. For example, the mapping relationship between the second and third coordinate systems can be pre-stored in the smart device so that after determining the coordinate values ​​of the cluster center (i.e., the coordinates in the second coordinate system), the coordinate transformation is performed to obtain the target coordinate values, so that the smart device can determine the movement distance, move and connect to the charging contact to complete the charging operation. In this way, through coordinate transformation, this solution can apply the position of the charging contact to the coordinate system referenced during actual movement, which helps improve the accuracy of the charging position identification, facilitating subsequent charging operations.

[0041] It should be noted that when the smart device uses the second coordinate system as the reference coordinate system for the movement distance, the coordinate values ​​of the cluster center in the second coordinate system of the corresponding multi-point ToF sensor are determined. That is, the smart device can perform movement control according to the determined coordinate values. Moreover, the control scheme for the smart device to move the device and connect to the charging contact after determining the charging contact can refer to the device movement scheme in related technologies. This scheme will not be elaborated further.

[0042] In one embodiment, the smart device can cluster based on the channel parameter values ​​of the dot matrix channels to determine the dot matrix channels of the charging contacts in the corresponding charging interface area, i.e., the target channels. That is, through clustering, all target channels corresponding to the same charging contact can be clustered into corresponding cluster regions, such as... Figure 3 As shown, Figure 3 This is a schematic diagram illustrating the steps for determining cluster centers according to an embodiment of this application. After determining the channel parameter values ​​of each lattice channel, the lattice channels are clustered accordingly. The specific steps are as follows: Step S210: Based on the channel parameter values ​​corresponding to each dot matrix channel, cluster all dot matrix channels to determine the clustering region including the target channel.

[0043] Step S220: Determine the coordinate index value of each target channel in the first coordinate system according to the arrangement of the dot matrix channels.

[0044] Step S230: Based on the coordinate index value of the target channel, determine the coordinate index value of the cluster center in each cluster region as the position of the cluster center in the first coordinate system of the corresponding charging interface region.

[0045] Understandably, because the amount of light signal reflected by charging contacts and non-contact areas differs, the channel parameter values ​​fed back in the target detection data also differ. To address this, the channel parameter values ​​corresponding to each dot matrix channel can be identified to distinguish between dot matrix channels corresponding to different charging contacts and those corresponding to non-contact areas, thereby determining clustered regions that include target channels. It can be conceivable that the clustered regions, as virtual regions defined on the detection plane, correspond to the charging contacts and are associated with several target channels in the target detection data, as detailed in [reference needed]. Figure 2 As shown. Furthermore, the number of clustered regions corresponds to the number of charging contacts. For example, in a scenario with two charging contacts, two clustered regions are determined. Moreover, the arrangement of the dot matrix channels corresponds to a dot matrix layout, i.e., arranged in rows and columns. The channel index corresponding to each dot matrix channel can be mapped to the coordinate values ​​in the first coordinate system to determine the corresponding coordinate index value, and from this, the coordinate index value of the target channel is determined. Furthermore, after the coordinate index values ​​of each target channel are determined, for the same clustered region, the coordinate index value of the target channel at the region vertex can also be determined. Then, based on the coordinate index value corresponding to the target channel at the region vertex, the coordinate index value of the cluster center of that clustered region is calculated.

[0046] Optionally, in determining the clustering region, a preset channel threshold can be used to differentiate and filter the dot matrix channels. This preset channel threshold is related to the reflection intensity value of the charging contact. Specifically, in the target detection data fed back by a multi-point ToF sensor using light signals as detection signals, the channel parameter value of each dot matrix channel corresponds to the light reflection amount. The preset channel threshold is then used to determine the light reflection amount of the light signal corresponding to the charging contact. The preset channel threshold is then compared with the corresponding channel parameter value of each dot matrix channel to determine the dot matrix channel as the target channel. This involves traversing all dot matrix channels, comparing their corresponding channel parameter values ​​with the preset channel threshold, and selecting dot matrix channels with channel parameter values ​​greater than or equal to the preset channel threshold as target channels. Furthermore, once the target channels are determined, adjacent target channels are clustered to determine clustering regions corresponding to different charging contacts. This means merging all adjacent dot matrix channels belonging to the same charging contact into one clustering region, and this clustering region corresponds to the same charging contact. This allows for the filtering of clustering regions corresponding to different charging contacts from the target detection data.

[0047] Optionally, during clustering, the process can involve taking the first dot matrix channel with a parameter value greater than or equal to a preset channel threshold as the initial cluster center during the traversal of all dot matrix channels. The channel parameter values ​​of the dot matrix channels adjacent to the initial cluster center are then compared to merge the dot matrix channels with channel parameter values ​​greater than or equal to the preset channel threshold to form an initial cluster region. This comparison and merging operation is then repeated outward to continuously expand the range of the initial cluster region and continuously determine the cluster center until it is expanded to all dot matrix channels corresponding to the charging contact, thereby finally obtaining the cluster region corresponding to the entire charging contact.

[0048] Therefore, this method uses clustering processing to receive the intensity of the light reflection signal from the charging contact, thereby determining the clustering region of the corresponding charging contact. This makes the identification and positioning of the charging location more accurate and helps to improve the accuracy of the solution.

[0049] In one embodiment, during the coordinate transformation process, the coordinates of the cluster centers in the second coordinate system can be calculated using trigonometric functions. Specifically, taking the offset angle, which includes a first deflection angle and a second deflection angle, as an example, the intelligent device first determines the first deflection angle corresponding to the horizontal direction and the second deflection angle corresponding to the vertical direction, such as the first deflection angle θ determined with reference to the above embodiment. h and the second deflection angle θ v To obtain the first deflection angle θ of the cluster center in the X-axis direction. h and the second deflection angle θ in the Y-axis direction v .

[0050] Furthermore, based on the first deflection angle and the distance value, the product of the tangent function corresponding to the first deflection angle and the distance value is determined to determine the coordinates of the cluster center in the X-axis direction of the second coordinate system; based on the second deflection angle and the distance value, the product of the tangent function corresponding to the second deflection angle and the distance value is determined to determine the coordinates of the cluster center in the Y-axis direction of the second coordinate system. It can be understood that two right triangles can be constructed using the multi-point ToF sensor, the mapping origin, and the two components of the cluster center in the X-axis and Y-axis directions of the second coordinate system. In these right triangles, the distance between the multi-point ToF sensor and the mapping origin is equivalent to the distance between the multi-point ToF sensor and the detection plane. Moreover, with the first and second deflection angles determined, i.e., the right-angled sides and one included angle (not a right angle) of the right triangle are determined, the two distance components in the X-axis and Y-axis directions of the second coordinate system can be calculated using the tangent function, as shown in the following formula:

[0051]

[0052] Among them, X c Y represents the distance component of the cluster centers along the X-axis. c Let h be the distance component of the cluster center along the Y-axis, and h be the distance value. It can be inferred that the aforementioned distance components correspond to the coordinate distances between the cluster center and the multi-point ToF sensor on the X-axis and Y-axis in the second coordinate system. Therefore, the coordinate values ​​of the cluster center on the X-axis and Y-axis can be determined based on the coordinates of the multi-point ToF sensor in the second coordinate system and the aforementioned coordinate distances. Furthermore, the smart device also determines the coordinate value of the cluster center along the Z-axis in the second coordinate system based on the distance value. It can be inferred that the coordinate distance between the cluster center and the multi-point ToF sensor on the Z-axis is the aforementioned distance value, i.e., Z... c =h, similarly, the coordinates of the cluster center on the Z-axis can be determined based on the coordinates of the multi-point ToF sensor in the second coordinate system and the distance to that coordinate. For example, in the charging interface area located directly below the multi-point ToF sensor of the smart device and containing two such sensors... Figure 2 The charging contacts shown are located in a scenario where they are all at the origin of the mapping. If the multi-point ToF sensor is the origin of the second coordinate system, and the coordinate distances of the cluster center corresponding to the charging contact on the left to the X, Y, and Z axes are respectively X... c Y c Z c Then the coordinates of the cluster center in the second coordinate system are (-X). c -Y c -Z c Therefore, this solution determines the charging location by using multi-point ToF sensors to identify the charging contacts and performing coordinate transformation. This solution can easily and quickly identify the charging location, which helps improve detection efficiency.

[0053] Figure 4 The figure shows a schematic diagram of a charging position identification device provided in an embodiment of this application. This device is applied to a smart device and is used to execute the charging position identification method provided in the above embodiment. It also has the functional modules for executing the method and the beneficial effects. The smart device includes a multi-point ToF sensor. The data transmission and reception format of the multi-point ToF sensor is a dot matrix transmission and reception for generating detection data. As shown in the figure, the charging position identification device includes a data detection module 301, a channel determination module 302, an angle detection module 303, and a coordinate transformation module 304.

[0054] The data detection module 301 is configured to determine the channel parameter values ​​of different dot matrix channels in the target detection data in response to receiving target detection data of the corresponding charging interface area obtained by the multi-point ToF sensor. The channel determination module 302 is configured to determine the position of the target channel and the cluster center corresponding to the target channel in the first coordinate system of the corresponding charging interface area based on the channel parameter values ​​in the target detection data. The target channel corresponds to the charging contact in the charging interface area, and the cluster center corresponds to the center point of the charging contact. The angle detection module 303 is configured to determine the offset angle of the cluster center relative to the multi-point ToF sensor based on the mapping origin and cluster center of the multi-point ToF sensor in the first coordinate system. The coordinate transformation module 304 is configured to determine the coordinates of the cluster center in the second coordinate system of the corresponding multi-point ToF sensor based on the offset angle and the distance value of the multi-point ToF sensor relative to the charging interface area.

[0055] Based on the above embodiments, the data detection module 301 is specifically configured as follows: When the detection signal used at the transmitter of a multi-point ToF sensor is an optical signal, the amount of light reflection received through each dot matrix channel is determined as the channel parameter value corresponding to each dot matrix channel.

[0056] Based on the above embodiments, the channel determination module 302 is specifically configured as follows: Based on the channel parameter values ​​corresponding to each dot matrix channel, all dot matrix channels are clustered to determine the clustering region that includes the target channel; Based on the arrangement of the dot matrix channels, determine the coordinate index value of each target channel in the first coordinate system; Based on the coordinate index value of the target channel, the coordinate index value of the cluster center in each cluster region is determined as the position of the cluster center in the first coordinate system of the corresponding charging interface region.

[0057] Based on the above embodiments, the channel determination module 302 is further configured as follows: By comparing the preset channel threshold with the channel parameter values ​​corresponding to each dot matrix channel, the dot matrix channel to be used as the target channel is determined. The preset channel threshold is related to the reflection intensity value of the charging contact. Once the target channel is determined, adjacent target channels are clustered to identify cluster regions corresponding to different charging contacts.

[0058] Based on the above embodiments, the offset angle includes a first deflection angle corresponding to the horizontal direction and a second deflection angle corresponding to the vertical direction. The angle detection module 303 is specifically configured as follows: Based on the FOV range of the multi-point ToF sensor, the offset of each dot matrix channel is determined in the first coordinate direction and the second coordinate direction. The first coordinate direction and the second coordinate direction are different coordinate axis directions in the first coordinate system. Determine the difference between the coordinate index value of the cluster center and the mapping origin in the first coordinate direction, and determine the first deflection angle based on the offset corresponding to each lattice channel in the first coordinate direction; The difference between the coordinate index value of the cluster center and the mapping origin in the second coordinate direction is determined, and the second deflection angle is determined based on the offset corresponding to each lattice channel in the second coordinate direction.

[0059] Based on the above embodiments, the coordinate transformation module 304 is specifically configured as follows: Determine the first deflection angle in the horizontal direction and the second deflection angle in the vertical direction within the offset angle; Based on the first deflection angle and the distance value, the product of the function value corresponding to the tangent function of the first deflection angle and the distance value is determined, so as to determine the coordinate value of the cluster center in the X-axis direction in the second coordinate system; Based on the second deflection angle and the distance value, the product of the function value corresponding to the tangent function of the second deflection angle and the distance value is determined, so as to determine the coordinate value of the cluster center in the Y-axis direction in the second coordinate system; Based on the distance value, the coordinates of the cluster center in the Z-axis direction in the second coordinate system are determined.

[0060] Based on the above embodiments, the device further includes a coordinate re-transformation module, which is configured as follows: When the intelligent device determines the moving distance based on the third coordinate system, the coordinate values ​​of the cluster center are converted into target coordinate values ​​according to the mapping relationship between the second and third coordinate systems, so that the intelligent device can determine the moving distance.

[0061] It is worth noting that in the embodiments of the above-mentioned device, the modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each module are only for easy differentiation and are not used to limit the protection scope of the embodiments of this application.

[0062] Figure 5This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The device is used to execute the charging position identification method provided in the above embodiment and has corresponding functional modules and beneficial effects for executing the method. It is conceivable that this electronic device can be a robotic vacuum cleaner, a robot dog, or other intelligent device. As shown in the figure, the device includes a processor 401, a memory 402, an input device 403, and an output device 404. The number of processors 401 can be one or more; the figure shows one processor 401 as an example. The processor 401, memory 402, input device 403, and output device 404 can be connected via a bus or other means; the figure shows a connection via a bus as an example. The memory 402, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the charging position identification method in the embodiments of this application. The processor 401 executes various corresponding functional applications and data processing by running the software programs, instructions, and modules stored in the memory 402, thereby realizing the above-mentioned charging position identification method.

[0063] The memory 402 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a given function; the data storage area may store data recorded or created during use. Furthermore, the memory 402 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory 402 may further include memory remotely located relative to the processor 401, which can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0064] The input device 403 can be used to input corresponding digital or character information to the processor 401, and to generate key signal inputs related to the user settings and function control of the device; the output device 404 can be used to send or display key signal outputs related to the user settings and function control of the device.

[0065] This application also provides a storage medium storing computer-executable instructions, which, when executed by a processor, are used to perform related operations in the charging position identification method provided in any embodiment of this application.

[0066] Computer-readable storage media include both permanent and non-permanent, removable and non-removable media, and information storage can be achieved by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0067] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0068] Note that the above description is merely a preferred embodiment and the technical principles employed in this application. Those skilled in the art will understand that this application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments. Many other equivalent embodiments may be included without departing from the concept of this application, and the scope of this application is determined by the scope of the appended claims.

Claims

1. A charging location identification method, characterized in that, The method is applied to smart devices, which include multi-point ToF sensors. The data transmission and reception format of the multi-point ToF sensors is a dot-matrix transmission and reception format for generating detection data. The charging position identification method includes: In response to receiving target detection data of the corresponding charging interface area obtained by the multi-point ToF sensor, the channel parameter values ​​of the corresponding dot matrix channels in the target detection data are determined; Based on the channel parameter values ​​in the target detection data, the position of the target channel and the cluster center corresponding to the target channel in the first coordinate system corresponding to the charging interface area is determined among all the dot matrix channels. The target channel corresponds to the charging contact in the charging interface area, and the cluster center corresponds to the center point of the charging contact. Based on the origin of the multi-point ToF sensor in the first coordinate system and the cluster center, the offset angle of the cluster center relative to the multi-point ToF sensor is determined. Based on the offset angle and the distance value of the multi-point ToF sensor relative to the charging interface area, the coordinate value of the cluster center in the second coordinate system corresponding to the multi-point ToF sensor is determined.

2. The charging location identification method according to claim 1, characterized in that, The step of responding to receiving target detection data for the corresponding charging interface area acquired by the multi-point ToF sensor, and determining channel parameter values ​​for different dot matrix channels in the target detection data, includes: When the detection signal used at the transmitting end of the multi-point ToF sensor is an optical signal, the amount of light reflection received through each dot matrix channel is determined as the channel parameter value corresponding to each dot matrix channel.

3. The charging location identification method according to claim 1, characterized in that, The step of determining the position of the target channel and its corresponding cluster center in the first coordinate system of the charging interface region based on the channel parameter values ​​in the target detection data includes: Based on the channel parameter values ​​corresponding to each dot matrix channel, all dot matrix channels are clustered to determine the clustering region that includes the target channel; Based on the arrangement of the dot matrix channels, determine the coordinate index value of each target channel in the first coordinate system; Based on the coordinate index value of the target channel, the coordinate index value of the cluster center in each cluster region is determined as the position of the cluster center in the first coordinate system corresponding to the charging interface region.

4. The charging location identification method according to claim 3, characterized in that, The step of clustering all dot matrix channels based on the channel parameter values ​​corresponding to each dot matrix channel to determine the clustering region including the target channel includes: By comparing the preset channel threshold with the channel parameter values ​​corresponding to each dot matrix channel, the dot matrix channel to be used as the target channel is determined. The preset channel threshold is related to the reflection intensity value of the charging contact. Once the target channel is determined, adjacent target channels are clustered to determine cluster regions corresponding to different charging contacts.

5. The charging location identification method according to claim 1 or 3, characterized in that, The offset angle includes a first deflection angle corresponding to the horizontal direction and a second deflection angle corresponding to the vertical direction; Based on the origin of the multi-point ToF sensor in the first coordinate system and the cluster center, the offset angle of the cluster center relative to the multi-point ToF sensor is determined, including: Based on the FOV range of the multi-point ToF sensor, the offset of each dot matrix channel is determined in the first coordinate direction and the second coordinate direction, where the first coordinate direction and the second coordinate direction are different coordinate axis directions on the first coordinate system. The difference between the coordinate index value of the cluster center and the mapping origin in the first coordinate direction is determined, and the first deflection angle is determined based on the offset corresponding to each lattice channel in the first coordinate direction. The difference between the coordinate index value of the cluster center and the mapping origin in the second coordinate direction is determined, and the second deflection angle is determined based on the offset corresponding to each lattice channel in the second coordinate direction.

6. The charging location identification method according to claim 1, characterized in that, Determining the coordinates of the cluster center in the second coordinate system corresponding to the multi-point ToF sensor based on the offset angle and the distance value of the multi-point ToF sensor relative to the charging interface area includes: Determine the first deflection angle corresponding to the horizontal direction and the second deflection angle corresponding to the vertical direction in the offset angle; Based on the first deflection angle and the distance value, the product of the function value corresponding to the tangent function of the first deflection angle and the distance value is determined, so as to determine the coordinate value of the cluster center in the X-axis direction in the second coordinate system; Based on the second deflection angle and the distance value, the product of the function value corresponding to the tangent function of the second deflection angle and the distance value is determined, so as to determine the coordinate value of the cluster center in the Y-axis direction in the second coordinate system; Based on the distance value, the coordinates of the cluster center in the Z-axis direction in the second coordinate system are determined.

7. The charging location identification method according to claim 1, characterized in that, Also includes: When the intelligent device determines the moving distance based on the third coordinate system, the coordinate values ​​of the cluster center are converted into target coordinate values ​​according to the mapping relationship between the second coordinate system and the third coordinate system, so that the intelligent device can determine the moving distance.

8. A charging location identification device, characterized in that, The device is applied to smart devices, including multi-point ToF sensors. The data transmission and reception of the multi-point ToF sensors is in the form of dot-matrix transmission and reception for generating detection data. The charging position identification device includes: The data detection module is configured to, in response to receiving target detection data of the corresponding charging interface area obtained by the multi-point ToF sensor, determine the channel parameter values ​​of different dot matrix channels in the target detection data; The channel determination module is configured to determine the position of the target channel and the cluster center corresponding to the target channel in the first coordinate system of the charging interface area based on the channel parameter values ​​in the target detection data. The target channel corresponds to the charging contact in the charging interface area, and the cluster center corresponds to the center point of the charging contact. An angle detection module is configured to determine the offset angle of the cluster center relative to the multi-point ToF sensor based on the mapping origin of the multi-point ToF sensor in the first coordinate system and the cluster center. The coordinate transformation module is configured to determine the coordinates of the cluster center in the second coordinate system corresponding to the multi-point ToF sensor based on the offset angle and the distance value of the multi-point ToF sensor relative to the charging interface area.

9. An electronic device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the charging location identification method as described in any one of claims 1-7.

10. A storage medium for storing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a processor, are used to perform the charging position identification method as described in any one of claims 1-7.

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