Robot-based pile-setting methods, robots, and storage media

Abstract

This application discloses a robot-to-charge station method, a robot, and a storage medium, relating to the field of robot control technology. The robot-to-charge station method is applied to a robot control system. The robot is equipped with at least one signal receiving device. The method includes: detecting a charging station based on a first observation angle of the signal receiving device; after detecting a charging station, determining an update probability based on the position of the signal receiving device and a second position in the initial probability distribution of the charging station; updating the initial probability distribution of the charging station position based on the update probability to obtain a target probability distribution of the charging station position; determining the maximum probability in the target probability distribution, and identifying the charging station position corresponding to the maximum probability as the target position of the charging station. This application updates the probability of possible charging station positions based on the detected signal, improving the accuracy of charging station position estimation.

Description

Technical Field

[0001] This application relates to the field of robot control technology, and in particular to a robot-based method for setting up stakes, a robot, and a storage medium. Background Technology

[0002] When a robot needs charging, it needs to locate the charging station. Typically, charging stations are equipped with infrared transmitters that continuously or periodically emit infrared signals. The robot is equipped with an infrared receiver that receives these signals. Based on the information provided by the infrared signals, the robot adjusts its position and orientation to ensure accurate docking with the charging station. However, infrared signals only provide discrete signals such as the robot's location, not continuous, precise coordinates or other definitive positional data, making it difficult to reliably and accurately locate the charging station.

[0003] The above content is only used to help understand the technical solution of this application and does not represent an admission that the above content is prior art. Summary of the Invention

[0004] The main objective of this application is to provide a robot-based charging pile positioning method, a robot, and a storage medium, aiming to solve the technical problem of how to improve the accuracy of charging pile location estimation.

[0005] To achieve the above objectives, this application proposes a robot-based method for aligning piles, the robot-based method comprising:

[0006] Based on the first observation angle of the signal receiving device, the charging pile is detected;

[0007] After detecting a charging pile, the updated probability is determined based on the location of the signal receiving device and the second position in the initial probability distribution of the charging pile.

[0008] The initial probability distribution of the charging pile location is updated based on the updated probability to obtain the target probability distribution of the charging pile location;

[0009] Determine the maximum probability in the target probability distribution, and determine the location of the charging pile corresponding to the maximum probability as the target location of the charging pile.

[0010] In one embodiment, the step of detecting the charging pile based on the first observation angle includes:

[0011] Obtain the first location information of the charging pile, and determine the discretization range based on the first location information;

[0012] The coordinates within the discretization range are discretized to obtain discretized coordinate points;

[0013] The discretized coordinate points are input into a preset probability distribution model to obtain the initial probability distribution.

[0014] In one embodiment, the step of determining the updated probability based on the location of the signal receiving device and the second position in the initial probability distribution of the charging pile after detecting the charging pile includes:

[0015] After detecting the signal sent by the charging pile, the second location is traversed;

[0016] Obtain the position vector between the second position and the position of the signal receiving device, and the angle between the position vector and the axis vector of the signal receiving device;

[0017] The update probability is determined based on the included angle.

[0018] In one embodiment, the step of determining the update probability based on the included angle includes:

[0019] Determine whether the second position is within the field of view of the signal receiving device based on the included angle;

[0020] If within the field of view, the update probability is determined based on the distance deviation between the second position and the signal receiving device, and the included angle.

[0021] If the field of view is not within the specified range, the update probability is zero.

[0022] In one embodiment, the step of updating the initial probability distribution of the charging pile location based on the updated probability to obtain the target probability distribution of the charging pile location includes:

[0023] Determine the confidence decay amount;

[0024] The initial probability distribution is updated based on the confidence decay and the update probability to obtain the target probability distribution.

[0025] In one embodiment, after the step of determining the maximum probability in the target probability distribution and determining the location of the charging pile corresponding to the maximum probability as the target location of the charging pile, the following is included:

[0026] Based on the robot's orientation and the target position's orientation, determine whether the robot needs to spin;

[0027] If necessary, the robot's orientation is acquired and adjusted according to the spin angle, and the robot is controlled to travel in an arc to the target position;

[0028] If not required, skip the spin step and control the robot to travel in an arc to the target position.

[0029] In one embodiment, the step of determining whether the robot needs to spin based on the robot's orientation and the target position orientation includes:

[0030] The target orientation of the robot is obtained by acquiring the angle difference between the target position orientation and the direction in which the robot points to the target position;

[0031] If the target orientation is greater than a preset threshold, it is determined that the robot needs to be controlled to spin.

[0032] In one embodiment, after the step of detecting the charging pile based on the first observation angle of the signal receiving device, the method further includes:

[0033] When no charging pile is detected at the first observation angle, the first observation angle is adjusted.

[0034] The charging pile is detected based on the adjusted first observation angle;

[0035] If the charging pile is still not detected, repeat the steps of angle adjustment and charging pile detection until the preset detection time threshold is reached.

[0036] In addition, to achieve the above objectives, this application also proposes a robot comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the robot-pile method as described above.

[0037] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the robot-pile-alignment method described above.

[0038] This application provides a robot-based method for locating charging piles. By setting an observation angle, the robot uses a signal receiving device to search for signals emitted by charging piles within a specific range. Upon detecting a charging pile signal, the robot updates the initial probability of the possible locations of the charging piles based on its own position, dynamically adjusting the probability of each possible location. After completing the probability update, the location with the highest probability is identified as the target location of the charging pile.

[0039] In this application, by setting an observation angle, detection is targeted within an angular range that may contain charging piles, avoiding aimless blind searches and providing information on the potential locations of charging piles for subsequent precise positioning. The initial probability distribution is formed by discretizing the location of the charging pile and assigning a probability value to each discretized location unit. The probability of the charging pile's possible location is updated based on the detected signals, and the updated probability distribution more accurately reflects the actual location of the charging pile. This application transforms the determination of the charging pile's location from vague regional judgment to precise location positioning, improving the accuracy of charging pile location estimation. Attached Figure Description

[0040] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0042] Figure 1 This is a flowchart illustrating the robot-based pile-setting method of this application in Embodiment 1.

[0043] Figure 2 This is a schematic diagram showing the positions of the infrared sensors installed on the robot and the charging pile, as provided in Embodiment 1 of the robot-to-pile method of this application.

[0044] Figure 3 This is a flowchart illustrating Embodiment 2 of the robot-based pile-setting method of this application;

[0045] Figure 4 This is a flowchart illustrating Embodiment 3 of the robot-based pile-setting method of this application;

[0046] Figure 5 This is a schematic diagram of the field of view of the signal receiving device provided in Embodiment 3 of the robot-based pile-setting method of this application;

[0047] Figure 6 This is a flowchart illustrating Embodiment 4 of the robot-based pile-setting method of this application;

[0048] Figure 7 This is a schematic diagram of the robot's motion trajectory provided in Embodiment 4 of the robot-to-pile method of this application;

[0049] Figure 8 This is a flowchart illustrating Embodiment 5 of the robot-based pile-setting method of this application;

[0050] Figure 9 This is a schematic diagram of the hardware operating environment involved in the robot-to-pile method in the embodiments of this application.

[0051] The purpose, features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0052] It should be understood that the specific embodiments described herein are merely used to explain the technical solutions of the present application and are not intended to limit the present application.

[0053] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0054] The main solution of this application embodiment is as follows: Based on the first observation angle of the signal receiving device, a charging pile is detected; after the charging pile is detected, an update probability is determined according to the position of the signal receiving device and the second position in the initial probability distribution of the charging pile; the initial probability distribution of the charging pile position is updated according to the update probability to obtain the target probability distribution of the charging pile position; the maximum probability in the target probability distribution is determined, and the charging pile position corresponding to the maximum probability is determined as the target position of the charging pile.

[0055] When a robot needs charging, it needs to locate the charging station. Typically, charging stations are equipped with infrared transmitters that continuously or periodically emit infrared signals. The robot is equipped with an infrared receiver that receives these signals. Based on the information provided by the infrared signals, the robot adjusts its position and orientation to ensure accurate docking with the charging station. However, infrared signals only provide discrete signals such as the robot's location, not continuous, precise coordinates or other definitive positional data, making it difficult to reliably and accurately locate the charging station.

[0056] To address the aforementioned issues, this application provides a robot-based charging station positioning method. By setting an observation angle, the robot uses a signal receiving device to search for signals emitted by charging stations within a specific range. Upon detecting a charging station signal, the robot updates the initial probabilities of possible charging station locations based on its own position, dynamically adjusting the probability of each possible location. After completing the probability update, the location with the highest probability is identified as the target location of the charging station.

[0057] In this application, by setting an observation angle, detection is targeted within an angular range that may contain charging piles, avoiding aimless blind searches and providing information on the potential locations of charging piles for subsequent precise positioning. The initial probability distribution is formed by discretizing the location of the charging pile and assigning a probability value to each discretized location unit. The probability of the charging pile's possible location is updated based on the detected signals, and the updated probability distribution more accurately reflects the actual location of the charging pile. This application transforms the determination of the charging pile's location from vague regional judgment to precise location positioning, improving the accuracy of charging pile location estimation.

[0058] It should be noted that the executing entity in this embodiment can be a computing service device with network communication and program execution functions, such as a robot, unmanned vehicle, server, server cluster, etc., or an electronic device or apparatus capable of realizing the above functions. The following description uses a robot as an example to illustrate this embodiment and the subsequent embodiments.

[0059] Based on this, embodiments of this application provide a robot-based stake-aligning method, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the robot-based pile-setting method of this application.

[0060] In this embodiment, the robot-to-pile method is applied to a robot control system. The robot is equipped with at least one signal receiving device, and the method includes steps S100 to S400:

[0061] Step S100: Based on the first observation angle of the signal receiving device, the charging pile is detected.

[0062] In this embodiment, the charging pile is equipped with at least one signal transmitting device, and the robot's charging contacts are equipped with at least one signal receiving device. The signal transmitting and receiving devices can be infrared lights, lidar, Bluetooth devices, etc. The signal receiving device can scan the surrounding environment at a certain angle and receive signals within the corresponding range. When the robot needs charging, it detects whether a signal from the charging pile is received within a first observation angle range. If a signal of a specific frequency or intensity is received, it is considered that a charging pile has been detected, indicating that a charging pile exists near the robot's current location. Path planning can then be performed, controlling the robot to move to the charging pile location for docking. After successful docking, the charging operation begins.

[0063] In this embodiment, please refer to Figure 2The aforementioned signal receiving device is an infrared sensor. The charging station is equipped with four infrared emitting lights S1, S2, S3, and S4, which emit infrared signals at different angles. Charging contacts are located behind the robot, and two infrared receiving lights R1 and R2 are positioned at the contact points. R1 and R2 may receive signals from the transmitters S1, S2, S3, and S4, respectively. The four infrared emitting lights on the charging station create different signal distributions in space. When the infrared receiving sensors R1 and R2 on the robot receive these signals, they can infer the robot's position based on the signal source and intensity. Multiple emitting lights provide more positioning reference points. Compared to a single emitting light, four emitting lights can emit signals from different directions, covering a larger spatial area, allowing the robot to receive signals from different positions, thereby improving positioning accuracy and reliability. By combining the signal information from multiple emitting lights, the robot's position coordinates can be calculated more accurately, reducing positioning errors.

[0064] Step S200: After detecting the charging pile, determine the update probability based on the location of the signal receiving device and the second position in the initial probability distribution of the charging pile.

[0065] In this embodiment, after detecting a charging pile, the initial probability distribution of the charging pile's location is obtained. The position of the signal receiving device on the robot can be determined based on the robot's own positioning system or based on the signal strength and angle of the received infrared signal. If R1 receives the signal from S1, indicating that the probability of the robot being in the direction corresponding to the charging pile S1 will increase, the increased probability (i.e., the updated probability) is determined based on the position of the signal receiving device and the second position in the initial probability distribution of the charging pile.

[0066] In this embodiment, the signals received by R1 and R2 are processed separately, and the initial probability distribution of the charging pile is updated twice consecutively. The first update, based on the signal received by R1, can initially narrow down the range of possible charging pile locations. The second update, based on the signal received by R2 and combined with the result of the first update, can further narrow down the range, making the final estimated charging pile location more accurate. By receiving and processing the signals twice consecutively, the uncertainty of the charging pile location can be gradually reduced, making the probability distribution more concentrated near the actual location.

[0067] Step S300: Update the initial probability distribution of the charging pile location according to the updated probability to obtain the target probability distribution of the charging pile location.

[0068] Step S400: Determine the maximum probability in the target probability distribution, and determine the location of the charging pile corresponding to the maximum probability as the target location of the charging pile.

[0069] In this embodiment, the probabilities in the initial probability distribution are updated based on the obtained update probabilities. The estimated probability at the current moment is obtained by subtracting the confidence decay from the probability in the initial probability distribution and adding the calculated update probability. Since the latest update probabilities are continuously obtained at different times, after obtaining the latest update probability, the probability corresponding to the possible location of the charging pile is updated based on the probability of the previous moment and the latest update probability until the condition for stopping updates is met. The probability update formula is: P t+1 =P t -P C +P; where P t+1 It is the estimated probability at the current moment, P. t This represents the probability from the previous moment. PC is an algorithm parameter representing the decay of confidence in the charging station's location over time. P is the updated probability calculated at the current moment. This means that as time progresses, the probability from the previous moment will decrease due to the decay of confidence, and will be adjusted based on the new calculation result (updated probability) at the current moment. After stopping probability updates and obtaining the target probability distribution, the position with the highest probability is found within the target probability distribution. The position corresponding to the highest probability is determined as the target location of the charging station. The probability P found in the target probability distribution... x,y The maximum value is used as the target position.

[0070] The formula for calculating the target position p2 is as follows:

[0071] In this embodiment, the condition for stopping updates can be that after several consecutive updates, the estimated probability P at the current time is... t+1 If the change is within a preset range, the probability is considered to have stabilized, and updates can be stopped. Another condition for stopping updates is that the number of updates reaches a preset limit. Yet another condition is that the maximum probability in the probability distribution exceeds a preset probability threshold; in this case, the confidence level of the charging station location determined based on the current probability distribution is considered high enough, and updates can be stopped.

[0072] When a robot needs charging, it needs to locate the charging station. Typically, charging stations are equipped with infrared transmitters that continuously or periodically emit infrared signals. The robot is equipped with an infrared receiver that receives these signals. Based on the information provided by the infrared signals, the robot adjusts its position and orientation to ensure accurate docking with the charging station. However, infrared signals only provide discrete signals such as the robot's location, not continuous, precise coordinates or other definitive positional data, making it difficult to reliably and accurately locate the charging station.

[0073] Based on the first embodiment of this application, in the second embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Steps S01 to S03 may be included before step S100:

[0074] Step S01: Obtain the first location information of the charging pile, and determine the discretization range based on the first location information.

[0075] Step S02: Discretize the coordinates within the discretization range to obtain discretized coordinate points.

[0076] Step S03: Input the discretized coordinate points into a preset probability distribution model to obtain the initial probability distribution.

[0077] In this embodiment, the recorded charging station locations are obtained. Where C represents the charging station coordinate system and m represents the map coordinate system. It is a 3x3 rotation matrix used to describe the rotation of the charging pile coordinate system relative to the map coordinate system; This is a 3x1 translation matrix used to describe the translation of the charging pile coordinate system relative to the map coordinate system. The charging pile coordinate system is a local coordinate system established with the charging pile as its origin. In this system, the charging pile's position is fixed at the origin (0, 0, 0), and other points are located based on their positions relative to the charging pile. The map coordinate system is a global, unified coordinate system used to locate all points on the map. In this system, each point has a unique, fixed position. By converting the charging pile's position from the charging pile coordinate system to the map coordinate system, the charging pile's location can be associated and matched with other geographic features (such as roads, buildings, etc.), thus providing more accurate and intuitive location information.

[0078] In this embodiment, the coordinate points around the charging pile location are discretized, forming a grid or lattice to simulate the distribution of charging demand around the charging pile. The discretization range can be determined by a pre-set fixed radius. A fixed radius is set with the charging pile location as the center, and all coordinate points within this radius are discretized. Alternatively, the area where the charging pile is located can be divided into a series of grids (such as square, rectangular, or hexagonal grids), with the grid containing the charging pile and its adjacent grids serving as the discretization range. During discretization, a step size (or resolution) is determined, dividing continuous coordinate values ​​into discrete intervals. The coordinate value is divided by the step size and rounded down, mapping each continuous coordinate value to its corresponding discrete interval. A unique index value is assigned to each discrete interval, representing each coordinate value with a simple integer index. For example, if the step size is 0.5, the coordinate value 2.3 will be mapped to the discrete interval 4 (2.3 / 0.5 = 4.6, rounded down to 4).

[0079] For example, with a step size of 0.05, the discretized coordinates are x = (-1, -0.95, -0.90, ..., 0, 0.0, 0.1, ... 1) and y = (-1, -0.95, -0.90, ..., 0, 0.05, 0.1, ... 1).

[0080] In this embodiment, based on the charging pile location T and the discretized coordinate points, a probability distribution p = P for the charging pile is constructed. x，y Here, x and y represent the offset position relative to the charging pile. The preset probability distribution model can be Gaussian, binomial, Poisson, or uniform, etc. For example, the probability of each point is initialized as a Gaussian distribution, where σ1 is an algorithm parameter representing the degree of dispersion of the distribution. In a Gaussian distribution, the greater the distance from the initial charging pile, the lower the probability. Using the discretized coordinate point data as input, the mean μ and standard deviation σ of the Gaussian distribution are estimated based on the distribution of the discrete coordinate points. The mean represents the center position P of the data. 0,0 =1, and the standard deviation σ reflects the dispersion of the data. The probability density function formula of the Gaussian distribution is used. Calculate the probability density value corresponding to each discrete coordinate point, and combine the discrete coordinate points and their corresponding probability density values ​​to form the initial probability distribution of the charging pile.

[0081] In this embodiment, by discretizing the estimation of the charging pile location, the originally complex continuous spatial positioning problem is simplified to a selection problem among a finite number of grids, reducing the complexity and difficulty of positioning. The method of recording grid positions by probability can fully utilize the observation information provided by infrared signals, and gradually approximate the true location of the charging pile through multiple observations and probability updates. Compared with traditional positioning methods based on fuzzy region information, this significantly improves the accuracy and stability of positioning.

[0082] Based on the first embodiment of this application, in the third embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 4 Step S200 may include steps S210 to S230:

[0083] Step S210: After detecting the signal sent by the charging pile, traverse the second location.

[0084] In this embodiment, when the infrared receiver on the robot receives an infrared signal emitted by the charging pile, it indicates that a charging pile exists nearby. The robot can then be controlled to move towards the charging pile, engage with it, and begin charging. After detecting the presence of a charging pile, all possible second positions p(x, y) of the charging pile are obtained from a preset initial probability distribution.

[0085] Step S220: Obtain the position vector between the second position and the position of the signal receiving device, and the angle between the position vector and the axis vector of the signal receiving device.

[0086] Step S230: Determine the update probability based on the included angle.

[0087] In this embodiment, the signal receiving device r is acquired. i The position is denoted by 'i', where 'i' represents the index of the signal receiving device. To transform the signal receiving device's position from the map coordinate system to the charging pile coordinate system, a rotation operation is first performed. A rotation matrix is ​​used to rotate the signal receiving device's coordinates so that its orientation aligns with the charging pile coordinate system. Then, a translation operation is performed. A translation vector is added to the rotated coordinates to move them to the correct position in the charging pile coordinate system. The transformed position of the signal receiving device is T. C i Its corresponding rotation matrix and translation matrix are Rotation matrix It is a 3×3 matrix used to describe the rotation of the signal receiving device in three-dimensional space, using trigonometric functions to represent the rotation angles of the coordinate axes. Translation matrix It is a 3×1 column vector used to describe the translation of the signal receiving device in three-dimensional space.

[0088] In this embodiment, the robot's current location is first obtained. Location of signal receiving device Where m represents the map coordinate system, b represents the robot, and r i This represents the receiving device, where 'i' represents the index of the receiving device. Please refer to [reference needed]. Figure 5 AC represents the central axis of the signal receiving device, and AC represents the vector V. AC , AB and AD represent the FOV (Field of View) of the signal receiving device. Next, the possible locations p(x, y) of the charging pile in the preset initial probability distribution are obtained. Finally, the updated probability is determined based on the difference between the possible locations of the charging pile and the actual distances from the signal receiving device.

[0089] In this embodiment, the update probability is determined based on the angle between the second position and the central axis, and the distance deviation between the second position and the signal receiving device. The possible positions p, p = [x, y] of the charging pile in the initial probability distribution are traversed sequentially. Vector V is calculated. Ap Vector V Ap With V AC The included angle β and the distance deviation r between them δ Vector V Ap This represents the vector pointing from the location of the signal receiving device to the possible location of the charging pile. The included angle β measures the degree of deviation of the possible location of the charging pile from the central axis of the receiving sensor. Distance deviation r δ This represents the distance difference between the actual location and the estimated location of the charging station. If r δ If the value of r is small, the actual location of the charging station is closer to the estimated location. δ If the value is large, the actual location of the charging station will differ significantly from the estimated location.

[0090] Vector V Ap The calculation formula is:

[0091] The formula for calculating the included angle β is β = atan²(v Ap [1], v Ap [0])-atan2(v AC [1], v AC [0]).

[0092] Among them, atan2(V Ap [1], V Ap [0]) represents vector V Ap The angle between the x-axis and the positive x-axis, atan2(V) AC [1], V AC[0]) represents vector V AC The angle between the x-axis and the positive x-axis is subtracted from the two angles to obtain the vector V. Ap With V AC The included angle β between them.

[0093] Distance deviation r δ The calculation formula is:

[0094] Among them, ||V Ap ||2 represents the distance between the potential location of the charging station and the signal receiving device. It is the distance between the actual location of the charging pile and the signal receiving device.

[0095] In this embodiment, after obtaining the included angle β, the included angle β is compared with the field of view angle of the signal receiving device. When β > α / 2, it indicates that the second position exceeds the field of view angle corresponding to the signal receiving device, and the signal received by the signal receiving device may be inaccurate or very weak, and cannot be effectively used to determine the location of the charging pile. The update probability corresponding to the position outside this range is set to 0 to avoid interference from unreliable positions on the overall position estimation and save computational resources. When β ≤ α / 2, the charging pile may be located at... Figure 5 The position of the shaded area is determined by the distance deviation between the second position and the signal receiving device, as well as the included angle, taking into account the degree of deviation of the second position from the charging contact and the difference in distance.

[0096] The formula for calculating the update probability is:

[0097] Where L represents the update weight, This represents the degree of dispersion of the distribution of the update probability. For example, L = 0.1, σ 2 =0.2.

[0098] Based on the first embodiment of this application, in the fourth embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 6 Step S400 may be followed by steps S500 to S700:

[0099] Step S500: Determine whether the robot needs to spin based on the robot's orientation and the target position orientation.

[0100] Step S600: If necessary, obtain and adjust the robot's orientation according to the spin angle, and control the robot to travel in an arc to the target position.

[0101] Step S700: If not required, skip the spin step and control the robot to travel in an arc to the target position.

[0102] In this embodiment, after determining the orientation θ3 of the target location p2 of the charging pile, the vector V3 corresponding to θ3, the robot's current position p1 = [x1, y1], its orientation θ1, and the vector V1 corresponding to θ1, the vector V1 pointing from the robot to the target location of the charging pile is calculated. p1p2 Vector V p1p2 The corresponding angle is θ4. Where V p1p2 =p2-p1, θ4=atan2(V p1p2 [1], V p1p2 [0]), θ4 is the angle between the vector from robot position p1 to target position p2 and the positive direction of the X-axis. The robot's trajectory towards the charging station is determined based on the orientation and vector corresponding to the target position, and the robot's current position. The robot's trajectory can take several forms. One form is to first rotate to align the robot and the target charging station's orientation, then move in a straight line to the target position. Another form is to first rotate and then move along an arc to the target position.

[0103] In this embodiment, the movement towards the charging station is transformed into a combination of two movements: stationary spinning and arc-shaped travel. Please refer to... Figure 7 The starting position is p1, and the ending position is p2. First, based on the angular difference between the target position of the charging pile and the robot's orientation, it is determined whether to control the robot to perform a self-spinning maneuver, with the angular difference θ. diff The formula for calculating θ is: diff =θ1 - (2(θ4 - θ3). If this angle difference is greater than the preset threshold, it means that the robot's current orientation differs significantly from the direction it needs to face the charging station. It cannot accurately reach the charging station by traveling in an arc and needs to first spin to adjust its orientation. If the angle difference is less than or equal to the preset threshold, it means that the robot can directly reach the charging station at a suitable angle by traveling in an arc, without needing to spin in place. The robot can be directly controlled to reach the target location of the charging station by traveling in an arc. For example, the preset threshold is 0.1.

[0104] When controlling the robot to spin, adjust the robot's orientation from V1 to V2, where the angle between V1 and V2 is θ. diff When determining the direction of spin, at θ diff When θ > 0, rotate clockwise; when θ < 0, rotate clockwise. diffWhen the value is less than 0, counter-clockwise rotation is used. When controlling the robot to reach the target location of the charging station by traveling in an arc, first, determine the straight-line distance *l* between the robot's current position and the target position, the curvature *C* of the arc motion, and the angular velocity *W* of the arc motion. Then, control the robot to move from p1 to p2 using the angular velocity *W*, curvature *C*, and the set angular velocity *V*.

[0105] The formula for calculating the straight-line distance l is: The formula for calculating the curvature C of an arc motion is: C = 2*sin(θ₄-θ₁) / l, and the angular velocity W = V*C.

[0106] Based on the first embodiment of this application, in the fifth embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description and will not be repeated hereafter. Based on this, the following steps may be included after step S100:

[0107] When no charging pile is detected at the first observation angle, the first observation angle is adjusted.

[0108] The charging pile is detected based on the adjusted first observation angle.

[0109] If the charging pile is still not detected, repeat the steps of angle adjustment and charging pile detection until the preset detection time threshold is reached.

[0110] In this embodiment, charging pile detection is performed based on a first observation angle of the signal receiving device. For example, the range of the first observation angle of the signal receiving device is from θ... start1 to θ start2 Within this angular range, the system detects whether there is a signal from a charging station. If a charging station signal is detected, the detection process stops, and relevant information about the charging station (such as direction and location) is recorded. If no charging station is detected at the initial observation angle, the observation angle needs to be adjusted. Each adjustment increment is Δθ, and the angle is adjusted in either a counter-clockwise or clockwise direction.

[0111] In this embodiment, the charging pile detection is performed again based on the adjusted observation angle. If a charging pile signal is detected, the detection process is stopped and relevant information is recorded. If no charging pile is detected at the adjusted angle, the angle adjustment and charging pile detection steps are repeated until a preset detection time threshold is reached. After reaching the preset time threshold, if the robot fails to find a charging pile within a certain angle range around its current position after a long period of searching, the robot's position is adjusted. Once the robot moves to the new position, the charging pile detection is performed again using the method described above.

[0112] In this embodiment, by continuously adjusting the observation angle, the search range can be expanded, thereby increasing the probability of detecting charging piles. Setting a detection time threshold can avoid indefinite angle adjustments and detection operations, improving work efficiency.

[0113] Based on the first embodiment of this application, in the sixth embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 8 The above-mentioned robot-based stake-setting method includes the following steps:

[0114] First, the potential locations of charging stations are discretized, dividing the continuous space where charging stations might appear into discrete location units for subsequent probability calculations and location determination. Second, the robot's signal receiving device detects the charging station at its current location. If a charging station is detected, the previously discretized probability distribution of the charging station's location is updated based on information such as the angle at which it is observed. This adjusts the probability of the charging station appearing at each location according to the observation results, more accurately reflecting its possible location. Finally, the location with the highest probability in the updated probability distribution is selected as the moving target, and the robot is moved towards this target location to align with the charging station.

[0115] By discretizing the location of charging piles and using discrete grid positions to record the probability of possible locations, the observation information provided by the signal can be fully utilized. Through multiple observations and probability updates, the accuracy of the determined true location of the charging pile is improved, and the computational complexity and implementation difficulty of positioning are reduced.

[0116] This application provides a robot, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the robot staking method of Embodiment 1 described above.

[0117] The following is for reference. Figure 9The diagram illustrates a structural schematic suitable for implementing embodiments of the present application. The robot may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes based on a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for robot operation. The processing device 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the robot to communicate wirelessly or wiredly with other devices to exchange data. Although control devices with various systems are shown in the figure, it should be understood that it is not required to implement or possess all the systems shown. More or fewer systems can be implemented alternatively.

[0118] In particular, according to the embodiments disclosed in the present application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments disclosed in the present application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program comprising program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0119] The robot provided in this application, employing the robot-to-charge station method described in the above embodiments, can solve the technical problem of how to improve the accuracy of charging station location estimation. Compared with the prior art, the beneficial effects of the robot provided in this application are the same as those of the robot-to-charge station method provided in the above embodiments, and other technical features of the robot are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0120] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0121] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

[0122] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the robot staking method in the above embodiments.

[0123] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0124] The aforementioned computer-readable storage medium may be included in the robot or may exist independently without being assembled into the robot. The aforementioned computer-readable storage medium carries one or more programs that, when executed by the robot, cause the robot to: detect a charging pile based on a first observation angle of the signal receiving device; after detecting a charging pile, determine an update probability based on the position of the signal receiving device and a second position in the initial probability distribution of the charging pile; update the initial probability distribution of the charging pile position according to the update probability to obtain a target probability distribution of the charging pile position; determine the maximum probability in the target probability distribution, and determine the charging pile position corresponding to the maximum probability as the target position of the charging pile.

[0125] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0126] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0127] The modules described in the embodiments of the present application may be implemented in software or hardware, wherein the name of a module does not necessarily limit the unit itself.

[0128] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described robot-to-charge pile method, thereby solving the technical problem of how to improve the accuracy of charging pile location estimation. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the robot-to-charge pile method provided in the above embodiments, and will not be repeated here.

[0129] The above description is only part of the embodiments of the present application and does not limit the patent scope of the present application. All equivalent structural transformations made by using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect application in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A robot-based method for aligning piles, characterized in that, Applied to a robot control system, wherein the robot is equipped with at least one signal receiving device, the method includes: Based on the first observation angle of the signal receiving device, the charging pile is detected; After detecting a charging pile, an update probability is determined based on the location of the signal receiving device and the second position in the initial probability distribution of the charging pile; the formula for calculating the update probability is: Where L is the update weight, β represents the degree of dispersion of the update probability distribution; β is the angle between the central axis vector of the signal receiving device and the position vector between the second position and the position of the signal receiving device. This represents the distance difference between the actual location and the estimated location of the charging station. The initial probability distribution of the charging pile location is updated based on the updated probability to obtain the target probability distribution of the charging pile location; Determine the maximum probability in the target probability distribution, and determine the location of the charging pile corresponding to the maximum probability as the target location of the charging pile.

2. The robot-based stake-aligning method as described in claim 1, characterized in that, Prior to the step of detecting the charging pile based on the first observation angle, the following steps are included: Obtain the first location information of the charging pile, and determine the discretization range based on the first location information; The coordinates within the discretization range are discretized to obtain discretized coordinate points; The discretized coordinate points are input into a preset probability distribution model to obtain the initial probability distribution.

3. The robot-based stake-aligning method as described in claim 1, characterized in that, The step of determining the updated probability based on the location of the signal receiving device and the second position in the initial probability distribution of the charging pile after detecting the charging pile includes: After detecting the signal sent by the charging pile, the second location is traversed; Obtain the position vector between the second position and the position of the signal receiving device, and the angle between the position vector and the axis vector of the signal receiving device; The update probability is determined based on the included angle.

4. The robot-based stake-aligning method as described in claim 3, characterized in that, The step of determining the update probability based on the included angle includes: Determine whether the second position is within the field of view of the signal receiving device based on the included angle; If within the field of view, the update probability is determined based on the distance deviation between the second position and the signal receiving device, and the included angle. If the field of view is not within the specified range, the update probability is zero.

5. The robot-based stake-aligning method as described in claim 1, characterized in that, The step of updating the initial probability distribution of the charging pile location based on the updated probability to obtain the target probability distribution of the charging pile location includes: Determine the confidence decay amount; The initial probability distribution is updated based on the confidence decay and the update probability to obtain the target probability distribution.

6. The robot-based stake-aligning method as described in claim 1, characterized in that, After the step of determining the maximum probability in the target probability distribution and determining the location of the charging pile corresponding to the maximum probability as the target location of the charging pile, the following is included: Based on the robot's orientation and the target position's orientation, determine whether the robot needs to spin; If necessary, the robot's orientation is acquired and adjusted according to the spin angle, and the robot is controlled to travel in an arc to the target position; If not required, skip the spin step and control the robot to travel in an arc to the target position.

7. The robot-based stake-aligning method as described in claim 6, characterized in that, The step of determining whether the robot needs to spin based on the robot's orientation and the target position orientation includes: The target orientation of the robot is obtained by acquiring the angle difference between the target position orientation and the direction in which the robot points to the target position; If the target orientation is greater than a preset threshold, it is determined that the robot needs to be controlled to spin.

8. The robot-based stake-aligning method as described in claim 1, characterized in that, Following the step of detecting the charging pile based on the first observation angle of the signal receiving device, the method further includes: When no charging pile is detected at the first observation angle, the first observation angle is adjusted. The charging pile is detected based on the adjusted first observation angle; If the charging pile is still not detected, repeat the steps of angle adjustment and charging pile detection until the preset detection time threshold is reached.

9. A robot, characterized in that, The robot includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the robot-to-pile method as described in any one of claims 1 to 8.

10. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the robot staking method as described in any one of claims 1 to 8.

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