A charging pile positioning method, device and robot

Abstract

The application relates to a charging pile positioning method and device and a robot, wherein the charging pile positioning method comprises the following steps: acquiring an initial reference pose of the robot in a map coordinate system and an initial first coordinate of a charging pile in a robot coordinate system at a time t; acquiring an updated reference pose of the robot in the map coordinate system, an updated first coordinate of the charging pile in the robot coordinate system and a pose change amount of the robot from the time t to a time t+1 at the time t+1; taking the initial reference pose, the updated reference pose and the coordinate position of the charging pile in the map coordinate system as variables and taking the pose change amount, the initial first coordinate and the updated first coordinate as constants, constructing an error equation set, and iteratively solving to obtain an optimal solution; and extracting the coordinate position of the charging pile in the map coordinate system from the optimal solution as a target position of the charging pile. Through the application, the problem that the position of the charging pile depends on manual calibration and cannot be automatically updated after the position is changed is solved.

Description

Technical Field

[0001] This application relates to the field of autonomous robot recharging and positioning technology, and in particular to a charging pile positioning method, device and robot. Background Technology

[0002] With the increasing popularity of home service robots, autonomous recharging functionality has become a core necessity. In current mainstream solutions, the location of charging stations typically relies on the following methods:

[0003] (1) Manual teaching method: The user manually pushes the robot to the charging station, triggers the robot to record the current position as the target point for recharging, and writes the coordinates into the map file. This method is cumbersome and requires re-teaching after the charging station is moved.

[0004] (2) Visual marking method: ArUco codes or QR codes are affixed to the charging pile, and the robot uses a camera to recognize the marks to calculate the pose of the charging pile. This method is limited by lighting conditions and camera angle, and fails when the marks are dirty or obstructed.

[0005] (3) Infrared near-field guidance method: The infrared guidance signal is activated only when the robot enters the vicinity of the charging pile, within a range of about 1m. For long distances, navigation still relies on the pre-marked coordinates of the charging pile on the map.

[0006] All of the above solutions share a common drawback: obtaining the location of charging stations relies on manual initialization or pre-calibration. Once the location of the charging station changes, the map coordinates cannot be updated automatically. If the charging station is moved unexpectedly, the return navigation will fail because the target point is invalid, and the user needs to re-execute the calibration process, resulting in a poor user experience.

[0007] Currently, no effective solution has been proposed to address the issue that charging station locations require manual initialization and cannot be automatically updated in related technologies. Summary of the Invention

[0008] This application provides a charging pile positioning method, device, and robot to at least solve the problem in related technologies that the location of charging piles needs to be manually initialized and cannot be automatically updated.

[0009] In a first aspect, embodiments of this application provide a charging pile positioning method, wherein the charging pile is used to charge a robot, the method is applied to the robot, and the method includes:

[0010] At time t, the initial reference pose of the robot in the map coordinate system and the initial first coordinates of the charging pile in the robot coordinate system are obtained.

[0011] At time t+1, the updated reference pose of the robot in the map coordinate system, the updated first coordinate of the charging pile in the robot coordinate system, and the pose change of the robot from time t to time t+1 are obtained.

[0012] An error equation system is constructed using the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and the pose change, the initial first coordinate, and the updated first coordinate as constants.

[0013] The system of error equations is solved iteratively to obtain the optimal solution for the variables;

[0014] The coordinates of the charging pile in the map coordinate system are extracted from the optimal solution, and the extracted coordinates are determined as the target location of the charging pile.

[0015] Secondly, embodiments of this application provide a charging pile positioning device, wherein the charging pile is used to charge a robot, and the device is applied to the robot, the device comprising:

[0016] The acquisition module is used to acquire, at time t, the initial reference pose of the robot in the map coordinate system and the initial first coordinate of the charging pile in the robot coordinate system; at time t+1, the updated reference pose of the robot in the map coordinate system, the updated first coordinate of the charging pile in the robot coordinate system, and the pose change of the robot from time t to time t+1.

[0017] The calculation module is used to construct an error equation system with the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and with the pose change, the initial first coordinate, and the updated first coordinate as constants; and to iteratively solve the error equation system to obtain the optimal solution for the variables.

[0018] The positioning module is used to extract the coordinate position of the charging pile in the map coordinate system from the optimal solution, and determine the extracted coordinate position as the target position of the charging pile.

[0019] Thirdly, embodiments of this application provide a robot that includes a charging pile positioning device as described in the second aspect above; the charging pile positioning device is used to perform the charging pile positioning method as described in the first aspect.

[0020] Compared to related technologies, the charging pile positioning method, device, and robot provided in this application obtain the robot's initial reference pose in the map coordinate system and the initial first coordinates of the charging pile in the robot's coordinate system at time t; at time t+1, obtain the robot's updated reference pose in the map coordinate system, the updated first coordinates of the charging pile in the robot coordinate system, and the change in the robot's pose from time t to time t+1; construct an error equation system using the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and the change in pose, the initial first coordinate, and the updated first coordinate as constants; iteratively solve the error equation system to obtain the optimal solution for the above variables; extract the coordinate position of the charging pile in the map coordinate system from the optimal solution, and determine the extracted coordinate position as the target position of the charging pile. This allows the robot to automatically acquire and dynamically update the charging pile position during operation without any manual operation by the user, solving the problem of charging pile position relying on manual calibration and not being able to automatically update after position change. It achieves zero-manual initialization and dynamic real-time updating of the charging pile position, improving the user experience of the robot's autonomous recharging function.

[0021] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0022] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0023] Figure 1 A flowchart of Embodiment 1 of the charging pile positioning method provided in this application;

[0024] Figure 2 A flowchart of Embodiment 2 of the charging pile positioning method provided in this application;

[0025] Figure 3 A flowchart of Embodiment 3 of the charging pile positioning method provided in this application;

[0026] Figure 4 A flowchart of Embodiment 4 of the charging pile positioning method provided in this application;

[0027] Figure 5 A flowchart of Embodiment 5 of the charging pile positioning method provided in this application;

[0028] Figure 6 This is a structural block diagram of the charging pile positioning device provided in this application. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this application clearer, the application is described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the application. All other embodiments obtained by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application. Furthermore, it is understood that although the efforts made in such a development process may be complex and lengthy, for those skilled in the art related to the content disclosed in this application, modifications to design, manufacturing, or production based on the technical content disclosed in this application are merely conventional technical means and should not be construed as insufficient disclosure of the content of this application.

[0030] In this application, the reference to "embodiment" means that a specific feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0031] Unless otherwise defined, the technical or scientific terms used in this application shall have the ordinary meaning understood by one of ordinary skill in the art to which this application pertains. The terms “a,” “an,” “an,” “the,” and similar words used in this application do not indicate quantity limitation and may indicate singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units not listed, or may include other steps or units inherent to these processes, methods, products, or devices. The terms “connected,” “linked,” “coupled,” and similar words used in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. “Multiple” used in this application means two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. The terms “first,” “second,” “third,” etc., used in this application are merely to distinguish similar objects and do not represent a specific ordering of the objects.

[0032] This embodiment provides a method for locating a charging station, which is used to charge a robot. This method is applied to the aforementioned robot. Figure 1 For a flowchart of Embodiment 1 of the charging pile positioning method provided in this application, please refer to [link / reference]. Figure 1 The process includes the following steps:

[0033] Step S110: At time t, obtain the initial reference pose of the robot in the map coordinate system and the initial first coordinate of the charging pile in the robot coordinate system.

[0034] Among them, the initial reference pose This refers to the robot's pose information relative to the map coordinate system at time t, which can be estimated in real time by the SLAM (Simultaneous Localization and Mapping) module on the robot. The SLAM module mentioned above refers to the simultaneous localization and mapping module, which can be visual SLAM, laser SLAM, or other modules that can realize the robot's simultaneous localization and mapping functions; no limitation is made here.

[0035] Specifically, at time t, the robot's initial reference pose in the map coordinate system is obtained. ,in, For the robot in map coordinate system The axis coordinates are estimated and output in real time by the SLAM module; For the robot in map coordinate system The axis coordinates are estimated and output in real time by the SLAM module; The robot's facing angle, i.e., the angle between the robot's front and the map coordinate system. The included angle in the positive direction of the axis is estimated and output in real time by the SLAM module.

[0036] Understandably, the robot and the charging station can interact wirelessly, such as via Bluetooth, Wi-Fi, or infrared communication. The robot can determine the relative position of the charging station by receiving signals from it, thus obtaining the initial coordinates of the charging station in the robot's coordinate system. In one possible implementation, the aforementioned initial first coordinates... It can be a two-dimensional coordinate vector, representing the position of the charging pile in the robot coordinate system. The origin of the robot coordinate system is located at the center of the robot chassis, the x-axis points directly in front of the robot, and the y-axis points to the left side of the robot.

[0037] Figure 2 For a flowchart of Embodiment 2 of the charging pile positioning method provided in this application, please refer to [link / reference]. Figure 2In one possible implementation, the method for determining the initial first coordinates includes:

[0038] Step S201: Receive the first signal emitted by the charging pile, and calculate the azimuth angle of the charging pile relative to the robot based on the signal strength distribution characteristics of the first signal.

[0039] The first signal mentioned above is an infrared signal.

[0040] In detail, an infrared receiver array can be installed on the robot. For example, a five-channel infrared receiver array R0~R4 can be installed on the front side of the robot's chassis. The receivers are arranged horizontally at equal intervals with their optical axes parallel and facing forward, and are used to receive infrared signals emitted from the charging pile. Correspondingly, a five-channel infrared transmitter array S0~S4 is installed on the front of the charging pile. The transmitters are arranged horizontally at equal intervals with their optical axes parallel and facing forward, corresponding one-to-one with the receivers on the robot side.

[0041] It is understandable that when the robot is directly facing the charging station, the charging station's five infrared transmitters and the robot's five infrared receivers form a one-to-one optical path. When the robot shifts laterally or angularly relative to the charging station, the signal strength distribution of each channel changes accordingly: when the robot and charging station are directly facing each other, the signal in the middle channel of the robot's infrared receiver array is the strongest, with symmetrical attenuation on both sides, exhibiting a single-peak bell-shaped distribution; when the robot and charging station shift laterally, the signal peak channel shifts; when there is angular deflection between the robot and charging station, the left and right channels of the robot's receiver array show asymmetrical differences. The azimuth angle of the charging station relative to the robot can be calculated by collecting the real-time signal strength values ​​of the five channels and using the centroid algorithm. , can be represented as:

[0042] ;

[0043] in, Let be the received signal strength value of the i-th channel of the robot's receiving array; Let be the position offset of the i-th channel relative to the center. , The distance between adjacent receiving tubes; This is a scaling factor used to convert positional offset into angle, and can be set according to actual needs; in one possible implementation, It can be set to 6° / unit.

[0044] Optionally, the number of infrared transmitting and receiving arrays is not limited to 5 channels. In other embodiments, it can also be set to 3 channels or as needed, and there is no limitation here.

[0045] Step S202: Receive the second signal emitted by the charging pile and calculate the relative distance between the charging pile and the robot based on the second signal.

[0046] The second signal mentioned above is a Time of Flight (TOF) ranging signal.

[0047] A first Time-of-Flight (TOF) ranging module can be installed on the robot, and a second TOF ranging module can be installed on the charging station. A TOF ranging module is a sensor module that calculates distance by measuring the time of flight between signal transmission and reception. The robot receives a second signal from the second TOF ranging module on the charging station and calculates the first distance from the robot to the charging station based on the signal's time of flight. Simultaneously, the charging station receives a third signal from the first TOF ranging module on the robot. This third signal is also a time-of-flight signal, and the second distance from the charging station to the robot is calculated based on the signal's time of flight. Subsequently, the charging station will connect via wireless communication methods (such as Bluetooth, Wi-Fi, or infrared communication). Feedback is sent to the robot; then, the robot calculates the first distance. With the second distance If the distance deviation is less than a preset deviation threshold (e.g., 5cm), then the first distance... Second distance The average value is used as the relative distance If the distance deviation is greater than or equal to the preset threshold, the measurement is determined to be abnormal, the data is discarded, and the measurement is restarted at the next moment.

[0048] By employing the above steps, and by averaging the measurements between two TOF modules and setting a deviation threshold, the measurement noise of a single TOF module can be effectively suppressed, thereby improving the robustness and accuracy of distance measurement.

[0049] As an alternative implementation, if only one side of the charging pile or robot is equipped with a TOF ranging module, the system can also operate in a degraded manner, using only the distance measured by the TOF on one side as the relative distance d. This method has a lower cost, but its accuracy is also lower than that of the two-sided mutual measurement method.

[0050] Step S203: Determine the initial first coordinates based on the azimuth and relative distance.

[0051] In detail, based on the azimuth angle calculated above... Given the relative distance d, we obtain the initial first coordinates of the charging pile in the robot coordinate system, which can be expressed as:

[0052] ;

[0053] in, This represents the distance component of the charging station in the direction directly in front of the robot. This is the distance component of the charging pile in the lateral direction of the robot. The physical meaning of this parameter is the position vector of the charging pile relative to the robot's coordinate system, which is used for coordinate transformation and error equation construction in subsequent steps.

[0054] Through steps S201 to S203, the azimuth angle of the charging pile relative to the robot is calculated by receiving the signal intensity distribution through an infrared array. This, combined with the relative distance between the charging pile and the robot obtained from the TOF ranging module, enables a single observation of the charging pile's position relative to the robot, providing fundamental observation data for subsequent multi-moment joint optimization. Furthermore, this method is independent of ambient lighting and exhibits stronger robustness compared to visual marking schemes.

[0055] Step S120: At time t+1, obtain the updated reference pose of the robot in the map coordinate system, the updated first coordinate of the charging pile in the robot coordinate system, and the change in the robot's pose from time t to time t+1.

[0056] Wherein, the pose change is the odometry measurement value of the robot from time t to time t+1, used to characterize the robot's relative motion during this time period, and can be expressed as:

[0057] ;

[0058] Among them, the odometer refers to the module that uses wheel encoders, vision or laser sensors to measure the relative displacement and attitude changes of the robot; The displacement of the robot along the forward direction from time t to time t+1 is measured and output by a wheel encoder or a vision / laser odometry. The displacement of the robot in the lateral direction from time t to time t+1 is measured and output by a wheel encoder or a vision / laser odometry. This parameter represents the change in the robot's orientation angle from time t to time t+1, measured and output by a wheel encoder or a visual / laser odometry. The physical significance of this parameter lies in the fact that the robot's onboard odometry provides short-term, high-precision relative motion information, constraining the robot's pose change range from time t to time t+1 and effectively suppressing the cumulative drift in SLAM pose estimation.

[0059] Specifically, at time t+1, the robot's updated reference pose in the map coordinate system is obtained through the SLAM module. The updated first coordinates of the charging pile in the robot coordinate system are obtained in the same manner as in steps S201~S203. And obtain pose change through odometry ;in, Let x be the robot's x-axis coordinate in the map coordinate system at time t+1. Let y be the robot's y-axis coordinate in the map coordinate system at time t+1. Let be the robot's orientation angle at time t+1; Let t+1 be the distance component of the charging pile in the direction directly in front of the robot. Let t+1 be the distance component of the charging pile in the lateral direction of the robot.

[0060] Step S130: Using the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and the pose change, the initial first coordinate, and the updated first coordinate as constants, construct an error equation system.

[0061] Among them, the coordinates of the charging pile in the map coordinate system This refers to the location of the charging station to be determined.

[0062] Understandably, this application employs a graph-based SLAM backend optimization approach, treating the robot's pose and landmark positions as variables, and sensor observations and odometry measurements as constraints. The optimal variable values ​​are found by minimizing the sum of squared errors across all constraints. In this application, sensor observation refers to the initial and updated first coordinates of the charging pile relative to the robot, acquired through an infrared receiver array and a TOF ranging module; this can also be termed IR-TOF observation. Odometry measurement refers to the pose change acquired through a wheel encoder or a visual / laser odometry system. In subsequent discussions, these will be referred to as IR-TOF observation constraints and odometry constraints, respectively. Therefore, in this application, a system of error equations containing odometry constraints and two IR-TOF observation constraints can be constructed and solved to obtain the optimal charging pile position.

[0063] Specifically, in this application, the initial reference pose is used. Update reference pose and the coordinates of the charging station in the map coordinate system. As variables, and in terms of pose change Initial first coordinate and updating the first coordinates As constants, construct a system of error equations.

[0064] Step S140: Iteratively solve the above error equation system to obtain the optimal solution for the above variables.

[0065] Specifically, the error equation set constructed in step S130 can be solved iteratively using the nonlinear least squares method to obtain the set of variables that minimizes the total objective function value. This set of variables includes the optimized initial reference pose, the optimized updated reference pose, and the optimal coordinate position of the charging pile in the map coordinate system.

[0066] Step S150: Extract the coordinates of the charging pile in the map coordinate system from the above optimal solution, and determine the extracted coordinates as the target location of the charging pile.

[0067] Specifically, the coordinates corresponding to the charging pile location are extracted from the optimal solution obtained through iterative solving. The component is the target location of the charging station in the map coordinate system.

[0068] Through steps S110 to S150, by acquiring robot pose and charging pile observation data at two different times, and combining the odometer measurement information between the two times, a joint error equation system is constructed and iteratively solved to finally obtain the optimal position estimate of the charging pile in the map coordinate system. This method treats the charging pile position as an optimization variable and solves it simultaneously with the robot pose, making full use of multi-source information constraints, effectively suppressing the influence of single observation noise and robot positioning errors, and achieving high-precision automatic acquisition of the charging pile position. Furthermore, this method can initialize and dynamically update the charging pile position without any manual operation by the user, solving the problem of charging pile position relying on manual calibration and not being able to automatically update after position changes, thus improving the user experience of the robot's autonomous recharging function.

[0069] Figure 3 For a flowchart of Embodiment 3 of the charging pile positioning method provided in this application, please refer to [link / reference]. Figure 3 In one possible implementation, the above-mentioned system of error equations is constructed using the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and the pose change, the initial first coordinate, and the updated first coordinate as constants. The system includes:

[0070] Step S301: Based on the initial reference pose and the updated reference pose, determine the predicted relative motion, and based on the deviation between the predicted relative motion and the pose change, determine the pose error equation.

[0071] In detail, the pose error equation can be expressed as:

[0072] ;

[0073] in, , which is the displacement along the direction directly in front of the robot predicted based on the reference pose and the updated reference pose;

[0074] , which is the lateral displacement predicted based on the reference pose and the updated reference pose;

[0075] , which is the change in orientation angle predicted based on the reference pose and the updated reference pose;

[0076] , , The relative motion directly measured by the odometer;

[0077] The physical meaning of this equation is: to constrain the deviation between the predicted relative motion calculated from the robot's pose variables and the actual odometry measurement, thereby using the short-term accurate measurement of the odometry as a constraint on the trajectory shape.

[0078] Step S302: Based on the initial reference pose and coordinate position, determine the first distance component of the charging pile relative to the robot, and determine the first observation error equation based on the deviation between the first distance component and the first coordinate.

[0079] Wherein, the first distance component is based on the initial reference pose. and the coordinates of the charging station The predicted position vector of the charging pile in the robot coordinate system.

[0080] In detail, at time t, the first observation error equation can be expressed as:

[0081]

[0082] in:

[0083] , which is the distance component of the charging pile in the direction directly in front of the robot, predicted based on the initial reference pose and the coordinate position of the charging pile.

[0084] , which is the distance component of the charging pile in the lateral direction of the robot, predicted based on the initial reference pose and the coordinate position of the charging pile;

[0085] Let be the component of the initial first coordinate at time t in the direction directly in front of the robot;

[0086] Let be the component of the initial first coordinate at time t in the lateral direction of the robot;

[0087] The physical meaning of this equation is: constraining the deviation between the predicted relative coordinates of the robot's initial reference pose as seen from the charging pile's coordinate position at time t and the actual measurement values ​​obtained through the infrared transmitter / receiver array and the TOF module, thereby establishing a spatial constraint relationship between the robot's pose and the charging pile's position.

[0088] Step S303: Based on the updated reference pose and coordinate position, determine the second distance component of the charging pile relative to the robot, and based on the deviation between the second distance component and the updated first coordinate, determine the second observation error equation.

[0089] The second distance component is based on the updated reference pose. and the coordinates of the charging station The predicted position vector of the charging pile in the robot coordinate system.

[0090] In detail, at time t+1, the second observation error equation can be expressed as:

[0091]

[0092] in: , which is the distance component of the charging pile in the direction directly in front of the robot, predicted based on the updated reference pose and the coordinate position of the charging pile.

[0093] , which is the distance component of the charging pile in the lateral direction of the robot, predicted based on the updated reference pose and the coordinate position of the charging pile;

[0094] The component of the first coordinate in the direction directly in front of the robot is updated at time t+1;

[0095] The component of the first coordinate in the lateral direction of the robot is updated at time t+1;

[0096] The physical meaning of this equation is: to constrain the deviation between the predicted relative coordinates of the charging pile position coordinates from the robot's updated reference pose at time t+1 and the actual measurement values ​​obtained by the infrared transmitter / receiver array and the TOF module, thereby constraining the charging pile position from a new perspective.

[0097] Step S304: Determine the set of error equations based on the pose error equation, the first observation error equation, and the second observation error equation.

[0098] In detail, the pose error equation First observation error equation and the second observation error equation These equations, when combined, form a complete set of error equations. This set of equations contains three sub-constraints: first, the consistency constraint between the robot's pose change and the odometer measurement; second, the spatial consistency constraint between the observation at time t and the robot's pose and the charging pile's position; and third, the spatial consistency constraint between the observation at time t+1 and the robot's pose and the charging pile's position.

[0099] Through the steps S301 to S304 above, by constructing a set of error equations that include odometer constraints and observation constraints at two different times, the problem of determining the location of the charging pile is transformed into a multi-constraint joint optimization problem, laying the foundation for subsequent solution of the optimal charging pile location through nonlinear least squares.

[0100] Figure 4 For the flowchart of Embodiment 4 of the charging pile positioning method provided in this application, please refer to [link / reference]. Figure 4 In one possible implementation, the above iterative solution of the error equation system yields the optimal solution for the variables, including:

[0101] Step S401: Based on the initial first coordinates and the initial reference pose, calculate the second coordinates of the charging pile in the map coordinate system through coordinate transformation.

[0102] In detail, based on the initial reference pose and initial first coordinates By transforming the coordinates, the second coordinates of the charging pile in the map coordinate system are calculated. , can be represented as:

[0103] ;

[0104] Or equivalent:

[0105] ;

[0106] ;

[0107] in, Let t be the estimated initial location of the charging station in the map coordinate system at time t. This is a rotation matrix used to align the robot's coordinate system with the map's coordinate system. This second coordinate... It can be used as the initial value for subsequent iterations. Although there is error in a single observation, it is close enough to the true value as the starting point for optimization iteration, which helps to accelerate the convergence speed of the overall objective function.

[0108] Step S402: Construct the overall objective function based on the pose error equation, the first observation error equation, and the second observation error equation.

[0109] In detail, the overall objective function S can be constructed by squaring the error components of the pose error equation and all observation error equations, multiplying them by their respective weights, and then summing them up. This objective function can be expressed as:

[0110]

[0111] in:

[0112] , , The odometer measures the distances at the odometer. , , The directional weights can be determined based on the noise variance of the odometer sensor;

[0113] The weights for the observations of the infrared array and the TOF ranging module can be determined based on the noise variance of the infrared array sensor and the TOF module sensor.

[0114] Step S403: Using the initial reference pose, the updated reference pose, and the current values ​​of the second coordinates as initial values, the nonlinear least squares method is used to iteratively adjust the values ​​of all variables until the overall objective function converges.

[0115] In detail, with reference pose Update reference pose Second coordinate Using the initial values, a nonlinear least squares method is employed to iteratively adjust the values ​​of all variables to be optimized until the overall objective function converges, yielding the optimal solution. The convergence condition can be that the decrease in the overall objective function is less than a preset convergence threshold, or that the number of iterations reaches its maximum limit.

[0116] Furthermore, the nonlinear least squares method can be solved using the Gauss-Newton method or the Levenberg-Marquardt method. When using the Gauss-Newton method for iterative solution, the iterative update formula can be expressed as:

[0117]

[0118] in:

[0119] , is a vector consisting of all variables to be optimized;

[0120] This is the Jacobian matrix for all error components with respect to all variables;

[0121] This is a weighted diagonal matrix;

[0122] The error vector is formed by stacking all error components.

[0123] Step S404: The value of the variable when the overall objective function converges is determined as the optimal solution.

[0124] In detail, through the above iterative solution, the optimal solution can be expressed as:

[0125] ;

[0126] in, The optimized robot pose at time t; The optimized robot pose at time t+1; This shows the optimized location of the charging station in the map coordinate system. The physical meaning is the optimal location estimate of the charging pile obtained by integrating the odometer constraint and the two observation constraints.

[0127] Through steps S401 to S404, initial values ​​for iteration are obtained through coordinate transformation, a weighted overall objective function is constructed, and iteratively solved using the nonlinear least squares method to finally obtain the optimized charging pile location. In this process, the odometry constraint provides short-term accurate constraints on the robot's relative motion, and the two-observation constraint provides spatial constraints on the charging pile's position relative to the robot. The combined effect of these three constraints makes the estimation accuracy of the charging pile location significantly better than the result of direct calculation from a single observation.

[0128] In some implementations, after obtaining the target location of the charging pile at the current moment through joint optimization, the above method further includes:

[0129] The target location is stored in the robot's map metadata file for recharge navigation.

[0130] Among them, the robot's map metadata file refers to the file that stores map-related metadata (such as map_meta.json), which is used to record information about key target points in the map, including the location coordinates of charging piles.

[0131] Specifically, in step S150, the target location of the charging pile is determined. Then, the target location can be... This information is written to the corresponding storage fields in the map metadata file, such as the `dock_pose` field. When the robot triggers recharging navigation, it can directly read the latest charging station location from this map metadata file. As a navigation target point, the robot is controlled to move to the vicinity of the target point, and then switches to near-field guidance mode (such as infrared precision alignment) to complete docking and charging with the charging station. Since the above steps S110 to S150 are executed in each positioning cycle and the charging station position in the map file is continuously updated, the robot can automatically detect and update the charging station position even if the charging station is accidentally moved, without the need for manual recalibration by the user.

[0132] Through the above steps, by continuously storing the target location obtained from each joint optimization in the map metadata file, the dynamic real-time update of the charging pile location is realized, ensuring that the return navigation target always points to the current actual location of the charging pile, effectively solving the problem of the return navigation target becoming invalid after the charging pile location changes in the prior art.

[0133] Furthermore, during the robot's recharging and navigation process, the target location determined in step S150 above can be used for autonomous recharging and navigation and precise docking. Figure 5 For the flowchart of Embodiment 5 of the charging pile positioning method provided in this application, please refer to [link / reference]. Figure 5 The robot's recharging navigation specifically includes the following steps:

[0134] Step S501: When the robot triggers the recharging condition, the target location of the charging pile is read from the map metadata file as the navigation target point.

[0135] The recharging conditions can be that the robot's battery level is lower than a preset battery threshold (e.g., 20%) and it is not currently charging.

[0136] In detail, the robot reads the target locations of charging stations, which were determined and stored through steps S110 to S150 above, from the map metadata file. The target location is the optimal location estimate of the charging pile in the map coordinate system after joint optimization based on multi-time observations.

[0137] Furthermore, the navigation process can be divided into three stages: coarse navigation, infrared reversing docking, and fine docking. Coarse navigation refers to the robot moving from its current position to the charging station (i.e., the target location). The process of the robot moving from the standby area to the charging pile; infrared reversing docking refers to the process of the robot slowly reversing from the standby area with its rear facing the charging pile, so that the robot enters the near field range of the charging pile; fine docking refers to the process of the robot making fine adjustments to its posture within the near field range and completing the physical docking with the charging pile.

[0138] Step S502: Control the robot to navigate to the standby area near the charging station.

[0139] Specifically, the robot uses the target location of the charging pile as its navigation target point and employs a navigation framework to perform global path planning and local control, driving the robot to move to a standby area near the charging pile. The standby area refers to the region located in the direction the charging pile faces and within a preset distance from the center of the charging pile (e.g., 0.4 meters to 1.2 meters). When the robot arrives at the standby area, its orientation is either the same as or opposite to the direction from the standby area to the charging pile, ensuring that the robot's rear or front is aligned with the charging pile.

[0140] In one possible implementation, the robot docks in a reverse docking direction, meaning the robot approaches the charging station with its rear facing the charging station.

[0141] During the coarse navigation phase, the robot continuously receives infrared signals and Time-of-Flight (TOF) ranging signals from the charging station and calculates the azimuth and distance of the charging station relative to the robot in real time. The coarse navigation phase ends when all of the following conditions are met:

[0142] (1) The distance between the robot and the charging station is within a preset range, such as between 0.4 meters and 1.2 meters;

[0143] (2) The azimuth offset of the robot relative to the charging pile is less than the preset threshold, and the infrared signal strength is sufficient to calculate the effective azimuth angle;

[0144] (3) The robot is aligned with the charging station, that is, the azimuth offset is stable within the preset range and continues for the preset duration;

[0145] (4) The deviation between the robot’s heading and the charging pile’s orientation is less than a preset angle, such as 8°.

[0146] If the takeover conditions are not met after the coarse navigation reaches the standby area, the robot enters a rotation search mode. The robot rotates and adjusts in place until the infrared signal is valid and the takeover conditions are met. Furthermore, a rotation search timeout mechanism can be set. If the rotation search time exceeds a preset rotation threshold (e.g., 16 seconds) and no valid signal is found, the recharging process is deemed to have failed and the recharging process is exited.

[0147] Step S503: Control the robot to perform infrared reversing docking.

[0148] After the initial navigation phase, the robot was positioned in the standby area near the charging station and met the takeover requirements. At this point, the robot entered the infrared reversing docking phase, slowly reversing with its rear facing the charging station.

[0149] In detail, the robot acquires the azimuth offset and distance information of the charging pile relative to the robot in real time at a preset frequency (e.g., 50Hz). The linear velocity and angular velocity of the robot can be calculated by a proportional-integral-derivative controller. The linear velocity can be set to a preset reversing speed (e.g., -0.1m / s to -0.3m / s), with negative values ​​indicating backward movement. The angular velocity can be calculated by the angle loop proportional-integral-derivative controller based on the azimuth offset and is used to adjust the robot's heading so that the rear of the robot is always aligned with the direction of the charging pile.

[0150] When the robot detects that it has reached the charging station, for example, when the robot is at a very close distance (within 5cm to 15cm) directly in front of the charging station and the azimuth angle deviation is close to zero, it can be determined that the reversing docking is complete and enter the fine docking stage.

[0151] If the infrared signal is lost continuously for more than the preset number of frames (e.g., 6 frames, about 300 milliseconds) during the reversing process, or if the azimuth angle offset continues to exceed the preset range, the reversing docking is determined to have failed, and the process returns to step S502 to re-execute coarse navigation.

[0152] Step S504: Control the robot to perform precise docking.

[0153] After the reverse docking is completed, the robot is very close to the charging station (usually within 0.1 to 0.25 meters), at which point it enters the fine docking stage. Unlike the coarse navigation stage, which uses the global pose in the map coordinate system, the fine docking stage directly uses real-time observation data in the robot coordinate system, namely the azimuth and distance information of the charging station relative to the robot, to eliminate the impact of cumulative drift in the SLAM map coordinate system on docking accuracy.

[0154] In detail, the robot continuously acquires the precise position of the charging pile in the robot's coordinate system. A proportional controller can be used to fine-tune the robot's pose so that the rear of the robot is precisely aligned with the charging pile, ultimately completing the physical docking between the robot and the charging pile.

[0155] Through steps S501 to S504, the target location of the charging pile determined in step S150 is used as the target point for recharging navigation. The robot is controlled to sequentially perform coarse navigation to the standby area, infrared reversing docking, and fine docking, ultimately completing autonomous recharging. The coarse navigation stage uses the global target location in the map coordinate system, while the fine docking stage switches to real-time IR-TOF observation in the robot coordinate system for closed-loop control. This ensures the feasibility of long-distance navigation and eliminates the impact of SLAM accumulated drift on the final docking accuracy, achieving a complete closed loop from long-distance positioning to close-range precise docking.

[0156] Furthermore, in this application, the infrared array achieves hardware reuse in the charging pile positioning and precise docking processes. On one hand, during the robot's SLAM mapping or localization mode, the robot uses a 5-channel infrared receiver array to receive infrared signals emitted by the charging pile. It calculates the azimuth angle of the charging pile relative to the robot through multi-channel signal strength distribution, and combines this with distance information obtained from TOF ranging to achieve automatic detection and dynamic updating of the charging pile's location in the SLAM map. On the other hand, in the precise docking stage, the same infrared array continues to be used to detect the azimuth angle offset in real time, driving the robot to complete precise alignment and docking via the controller. Both stages share the exact same infrared transceiver hardware, only employing different processing logic at the backend signal processing and control strategy level based on the current task. Through this reuse method, there is no need to configure separate sensor systems for charging pile positioning and precise docking, reducing the number of sensors, lowering hardware material costs and assembly complexity; simultaneously, it avoids data association and coordinate alignment issues between different sensors, simplifying the system software architecture and improving overall system reliability. In addition, infrared signals are unaffected by ambient light conditions, allowing stable operation in both bright and dark environments, further enhancing the environmental adaptability of the recharge system.

[0157] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0158] This embodiment also provides a charging pile positioning device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as described above. As used below, the terms "module," "unit," "subunit," etc., can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0159] Figure 6 This is a structural block diagram of the charging pile positioning device provided in this application. The charging pile is used to charge a robot, and the device is applied to a robot, such as... Figure 6 As shown, the device includes:

[0160] The acquisition module 10 is used to acquire the initial reference pose of the robot in the map coordinate system and the initial first coordinate of the charging pile in the robot coordinate system at time t; and to acquire the updated reference pose of the robot in the map coordinate system, the updated first coordinate of the charging pile in the robot coordinate system, and the change in pose of the robot from time t to time t+1 at time t+1.

[0161] The calculation module 20 is used to construct an error equation system with the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and the pose change, the initial first coordinate, and the updated first coordinate as constants; and to iteratively solve the error equation system to obtain the optimal solution for the variables.

[0162] The positioning module 30 is used to extract the coordinate position of the charging pile in the map coordinate system from the optimal solution, and to determine the extracted coordinate position as the target position of the charging pile.

[0163] It should be noted that the above modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above modules can reside in the same processor; or the above modules can be located in different processors in any combination. Specific examples in this embodiment can be found in the examples described in the above embodiments and optional implementations, and will not be repeated in this embodiment.

[0164] This embodiment also provides a robot that includes the above-described charging pile positioning device; the charging pile positioning device is used to perform the steps in any of the above method embodiments.

[0165] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0166] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0167] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0168] Those skilled in the art should understand that the technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments have been described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0169] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for locating a charging pile, characterized in that, The charging station is used to charge the robot, and the method is applied to the robot, the method comprising: At time t, the initial reference pose of the robot in the map coordinate system and the initial first coordinates of the charging pile in the robot coordinate system are obtained. At time t+1, the updated reference pose of the robot in the map coordinate system, the updated first coordinate of the charging pile in the robot coordinate system, and the pose change of the robot from time t to time t+1 are obtained. An error equation system is constructed using the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and the pose change, the initial first coordinate, and the updated first coordinate as constants. The system of error equations is solved iteratively to obtain the optimal solution for the variables; The coordinates of the charging pile in the map coordinate system are extracted from the optimal solution, and the extracted coordinates are determined as the target location of the charging pile.

2. The charging pile positioning method according to claim 1, characterized in that, Using the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and the pose change, the initial first coordinate, and the updated first coordinate as constants, a system of error equations is constructed, including: Based on the initial reference pose and the updated reference pose, the predicted relative motion is determined, and based on the deviation between the predicted relative motion and the pose change, the pose error equation is determined. Based on the initial reference pose and the coordinate position, a first distance component of the charging pile relative to the robot is determined, and a first observation error equation is determined based on the deviation between the first distance component and the first coordinate. Based on the updated reference pose and the coordinate position, a second distance component of the charging pile relative to the robot is determined, and a second observation error equation is determined based on the deviation between the second distance component and the updated first coordinate. The set of error equations is determined based on the pose error equation, the first observation error equation, and the second observation error equation.

3. The charging pile positioning method according to claim 2, characterized in that, The iterative solution of the error equation system to obtain the optimal solution for the variable includes: Based on the initial first coordinates and the initial reference pose, the second coordinates of the charging pile in the map coordinate system are calculated through coordinate transformation; Based on the pose error equation, the first observation error equation, and the second observation error equation, a total objective function is constructed. Using the initial reference pose, the updated reference pose, and the current value of the second coordinate as initial values, the nonlinear least squares method is used to iteratively adjust the values ​​of all variables until the overall objective function converges; The value of the variable when the overall objective function converges is determined as the optimal solution.

4. The charging pile positioning method according to claim 1, characterized in that, The method for determining the initial first coordinate includes: The robot receives a first signal emitted by the charging pile and calculates the azimuth angle of the charging pile relative to the robot based on the signal strength distribution characteristics of the first signal; the first signal is an infrared signal. The robot receives a second signal emitted by the charging pile and calculates the relative distance between the charging pile and the robot based on the second signal; the second signal is a time-of-flight ranging signal. The initial first coordinates are determined based on the azimuth angle and the relative distance.

5. The charging pile positioning method according to claim 4, characterized in that, The first signal is transmitted by the multi-transmitter array on the charging pile and received by the multi-receiver array on the robot, and the received signal strength value of each channel of the multi-receiver array is obtained. The calculation of the azimuth angle includes: The azimuth angle is determined based on the received signal strength value of each channel and the offset of each channel relative to the preset center position of the multi-channel receiver array.

6. The charging pile positioning method according to claim 4, characterized in that, The calculation of the relative distance based on the second signal includes: Receive the second signal emitted by the second ranging module on the charging pile, and calculate the first distance from the charging pile to the robot based on the second signal; The robot receives a third signal from a first ranging module mounted on the robot via the charging station, and calculates a second distance from the robot to the charging station based on the third signal; the third signal is a time-of-flight signal. Calculate the distance deviation between the first distance and the second distance; If the distance deviation is less than a preset threshold, the average of the first distance and the second distance is taken as the relative distance; If the distance deviation is greater than or equal to the preset threshold, the step of receiving the second signal emitted by the second ranging module on the charging pile is repeated.

7. The charging pile positioning method according to claim 1, characterized in that, The method further includes: The target location is stored in the robot's map metadata file for recharge navigation.

8. The charging pile positioning method according to claim 5, characterized in that, The multi-channel transmitter array is a 5-channel infrared transmitter array; the multi-channel receiver array is a 5-channel infrared receiver array.

9. A charging pile positioning device, characterized in that, The charging station is used to charge the robot, and the device is applied to the robot, comprising: The acquisition module is used to acquire, at time t, the initial reference pose of the robot in the map coordinate system and the initial first coordinate of the charging pile in the robot coordinate system; at time t+1, the updated reference pose of the robot in the map coordinate system, the updated first coordinate of the charging pile in the robot coordinate system, and the pose change of the robot from time t to time t+1. The calculation module is used to construct an error equation system with the initial reference pose, the updated reference pose, and the coordinate position of the charging pile in the map coordinate system as variables, and with the pose change, the initial first coordinate, and the updated first coordinate as constants; and to iteratively solve the error equation system to obtain the optimal solution for the variables. The positioning module is used to extract the coordinate position of the charging pile in the map coordinate system from the optimal solution, and determine the extracted coordinate position as the target position of the charging pile.

10. A robot, characterized in that, The robot includes a charging pile positioning device as described in claim 9; the charging pile positioning device is used to perform the charging pile positioning method as described in any one of claims 1 to 8.

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