CN109955253B - Method for robot to find charging seat position - Google Patents
Method for robot to find charging seat position Download PDFInfo
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- CN109955253B CN109955253B CN201910255108.8A CN201910255108A CN109955253B CN 109955253 B CN109955253 B CN 109955253B CN 201910255108 A CN201910255108 A CN 201910255108A CN 109955253 B CN109955253 B CN 109955253B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J9/00—Programme-controlled manipulators
- B25J9/16—Programme controls
- B25J9/1656—Programme controls characterised by programming, planning systems for manipulators
- B25J9/1664—Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning
Abstract
The invention discloses a method for searching a charging seat position by a robot. In the method, the robot selects the position point of the current path and the detected corresponding guide signal to match with the distribution points and the corresponding distribution signals in the signal quantization distribution diagram prestored by the robot, selects two paths with the highest matching degree from the distribution points, and then calculates the position of the charging seat in the current walking path of the robot according to the position of the charging seat corresponding to the path in the quantization signal distribution diagram, so that the robot can quickly and accurately return to the seat.
Description
Technical Field
The invention relates to the field of intelligent robots, in particular to a method for searching a charging seat position by a robot.
Background
At present, intelligent robot that can carry out autonomous movement, for example cleaning robot, security protection robot and accompany robot etc. all have the function of automatic seat charging of returning. If the robot does not start to walk from the charging seat, or the position of the charging seat is changed in the process of walking of the robot, the robot is difficult to find the charging seat. When the robot enters the returning mode, the robot starts to continuously detect the guide signal sent by the charging seat in the process of searching the charging seat, and only when the guide signal is detected, the robot can return to the seat according to the guide of the guide signal. Since the seat returning method needs to search for the pilot signal for a long time, the seat returning efficiency is low.
Disclosure of Invention
The invention provides a method for searching a charging seat position by a robot, which can improve the efficiency of searching the charging seat by the robot. The specific technical scheme of the invention is as follows:
a method for searching the position of a charging seat by a robot comprises the following steps: step S1, the robot randomly selects a first position point in the path based on the current walking path, acquires a first detection signal detected when the robot is at the first position point, and then enters step S2; step S2, the robot acquires a first distribution point in a signal quantization distribution map of the charging dock, where a distribution signal of the first distribution point in the signal quantization distribution map is a first distribution signal, and the first distribution signal is the same as the signal information contained in the first detection signal, and then proceeds to step S3; step S3, the robot randomly selects a second position point in the path based on the current walking path, acquires a second detection signal detected when the robot is at the second position point, and then enters step S4; step S4, the robot acquires a second distribution point in the signal quantization distribution map, where a distribution signal corresponding to the second distribution point in the signal quantization distribution map is a second distribution signal, the second distribution signal is the same as the signal information contained in the second detection signal, and a linear distance between the second distribution point and the first distribution point is equal to a linear distance between the second position point and the first position point, and then the process proceeds to step S5; step S5, the robot selects different verification position points based on the current walking path, acquires the verification detection signals detected when the robot is at the verification position points, and then enters step S6; step S6, acquiring, by a robot, verification distribution points in the signal quantization distribution map, where distribution signals corresponding to the verification distribution points in the signal quantization distribution map are verification distribution signals, and a positional relationship between the verification distribution points and the first distribution points and the second distribution points is the same as a positional relationship between the verification position points and the first position points and the second position points, and then entering step S7; step S7, the robot judges whether the signal information contained in the verification distribution signal and the verification detection signal is the same, if so, the robot carries out cumulative adding points, if not, the robot does not carry out cumulative adding points, and then the robot enters step S8; step S8, the robot judges whether the selected verification position points reach the preset number, if so, the step S9 is carried out, otherwise, the step S5 is returned; step S9, the robot determines the final accumulated score and judges whether the number of times of determining the score reaches the preset number, if so, the step S10 is executed, otherwise, the step S1 is executed again; step S10, the robot compares the score of the last cumulative score determined each time, and obtains the position of the charging seat corresponding to the current walking path based on the position of the charging seat determined by the distribution point in the signal quantization distribution map corresponding to the time with the highest score.
Further, the signal quantization distribution diagram of the charging seat is formed by the following steps: the robot determines a preset range based on the position of a charging seat, and the preset range is rasterized to form a plurality of grid units; and traversing the preset range by the robot, carrying out signal coding according to a preset coding form based on the guide signal sent by the charging seat detected in the traversing process to form a distribution signal, and correspondingly recording the distribution signal and the grid unit corresponding to the current position to form the signal quantization distribution map.
Further, the preset range is a square area of 2 meters by 2 meters, and the charging seat is located in the middle of one side of the square area; the grid cell is a square virtual cell of 0.1 meter by 0.1 meter; the square area is divided into 400 of the square virtual cells.
Further, the robot traverses the preset range, and performs signal coding according to a preset coding form based on the guiding signal sent by the charging seat detected in the traversing process to form a distribution signal, specifically including the following steps: the robot starts from the position of the charging seat and walks within the preset range by a Chinese character 'gong' type track; the robot detects the guide signal sent by the charging seat while walking, and analyzes the condition of detecting the guide signal; when the robot detects the first guiding signal, the value of the first data bit is 1, otherwise, the value of the first data bit is 0; when the robot detects the second guiding signal, the value of the second data bit is 1, otherwise, the value of the second data bit is 0; by analogy, when the robot detects the Nth guiding signal, the numerical value of the Nth data bit is 1, otherwise, the numerical value of the Nth data bit is 0; wherein N is a number greater than or equal to 4 and less than or equal to 8; the robot arranges the first data bit to the Nth data bit according to the sequence from the low bit to the high bit to form a binary number group, and then converts the binary number group into a hexadecimal number value to form the distribution signal.
Further, the preset number is greater than 100.
Further, the preset number of times is more than 50.
Further, the step S10 of obtaining the position of the charging seat corresponding to the current walking path based on the position of the charging seat determined by the distribution point in the signal quantization distribution map corresponding to the time with the highest score specifically includes the following steps: the robot determines a signal quantization distribution diagram corresponding to the time with the highest score as a reference diagram; the robot determines the orientation parameters of the charging seat relative to the first distribution point and the second distribution point in the reference image; the robot determines the position parameters of the first position point and the second position point corresponding to the time with the highest score; and the robot calculates the position of the charging seat in the current walking path according to the position parameters and the orientation parameters.
Drawings
Fig. 1 is a schematic signal distribution diagram of a charging cradle according to an embodiment of the present invention.
Fig. 2 is a flowchart illustrating a method for finding a charging seat position by a robot according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a current walking path of the robot according to the embodiment of the present invention.
Fig. 4 is a schematic diagram of a signal quantization distribution diagram of a charging dock according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be described in detail below with reference to the accompanying drawings in the embodiments of the present invention. It should be understood that the following specific examples are illustrative only and are not intended to limit the invention. In the following description, specific details are given to provide a thorough understanding of the embodiments. However, it will be understood by those of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits may be shown in block diagrams in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, structures and techniques may not be shown in detail in order not to obscure the embodiments.
A method for searching a charging seat position by a robot is a cleaning intelligent robot such as a sweeping robot, a mopping robot, a polishing robot or a waxing robot. In the walking process, the intelligent robots can determine and record the positions and the directions of the robots in real time by means of sensors such as driving wheel code discs, gyroscopes, cameras and laser radars of the robots, so that the robots can move and navigate independently and purposefully. The robot can detect the guide signal sent by the charging seat in real time while walking. The guiding signal is the signal that the charging seat sent is used for guiding the robot to return the seat, quantity and mounted position according to the infrared emission sensor that sets up in the charging seat, can divide into different signal types to the guiding signal, for example, the intermediate signal that the infrared emission sensor that is located the middle of the charging seat front side sent, the left signal that the infrared emission sensor that is located the charging seat front side left side sent, the right signal that the infrared emission sensor that is located the charging seat front side right sent, the guardrail signal that the infrared emission sensor that is located the charging seat both sides sent, of course, can also divide into far-end signal, middle part signal and near-end signal according to the regional far and near of signal distribution, etc. In addition, the robot body is provided with a plurality of infrared receiving sensors which can receive the guide signals sent by the infrared transmitting sensor of the charging seat, and the infrared receiving sensors are respectively arranged at different directions of the robot body. This embodiment the infrared receiving sensor setting of robot is at the top of robot to an dustcoat circle bubble structure, so can be convenient for the all-round receipt guide signal of robot, improve the accuracy that the robot judges self position. Each infrared receiving sensor can be provided with a code, and the code value can be freely set, so that the robot can more accurately know which guide signals are positioned in which direction of the robot, and the robot can be conveniently positioned. As shown in fig. 1, the guiding signals sent by the charging dock C of this embodiment include a middle signal F3, a left signal F4, a right signal F2, and a guard rail signal F1. The guardrail signal F1 is a signal distributed in an area surrounded by a front arc of the charging seat C. The signal distributed in the area defined by the two downward extending oblique lines in the middle in front of the charging dock C is the middle signal F3. The signal distributed in the area defined by the two downward extending oblique lines at the leftmost position in front of the charging dock C is the left signal F4. The signal distributed in the area defined by the two downward extending oblique lines at the rightmost side in front of the charging dock C is the right signal F2. As shown in fig. 2, the method for finding the position of the charging seat by the robot specifically includes the following steps:
in step S1, as shown in fig. 3, the circle in the figure indicates the robot 10, the indicated arcuate path indicates the current path traveled by the robot, and the arrow indicates the traveling direction of the robot. First, the robot 10 randomly selects a first position point P1 in the path based on the current walking path, and acquires a first detection signal detected by the robot at the first position point P1, where the first detection signal includes a guardrail signal, a left signal, and a middle signal sent by a charging dock, that is, when the robot 10 walks to the first position point P1, the guardrail signal, the left signal, and the middle signal sent by the charging dock are detected at the same time. The process then proceeds to step S2.
In step S2, the robot acquires a first distribution point p1 in the signal quantization profile of the charging dock. Fig. 4 is a schematic diagram of a signal quantization profile, which is a 20 × 20 grid cell array, each small square representing a grid cell with a side of 0.1 meter, and when the center point of the robot is located at a certain grid cell, the position of the robot is located at the grid cell. Each grid cell is marked with a hexadecimal numerical value, and the numerical value represents the situation of the guiding signal sent by the charging seat and detected when the robot is at the position of the corresponding grid cell. The signal quantification profile is stored in the robot memory and the robot continuously updates the values in the squares based on its motion and signal detection. Of course, normally, the values in the squares should be fixed, but if the type of the charging base is changed or a sensor in the charging base is damaged, the signal sent by the charging base will change, and the corresponding values in the signal quantization profile will need to be updated and adjusted. In fig. 4, the distribution signal corresponding to the first distribution point p1 in the signal quantization distribution map is a first distribution signal, and its hexadecimal value is B (corresponding to a binary value 1011). The first distribution signal corresponding to the acquired first distribution point p1 is the same as the signal information included in the first detection signal, that is, includes a guard rail signal, a left signal and a middle signal. The process then proceeds to step S3.
In step S3, as shown in fig. 3, the robot 10 randomly selects a second position point P2 in the path based on the current walking path, and acquires a second detection signal detected by the robot at the second position point P2, where the second detection signal only includes a right signal. Then, the process proceeds to step S4.
In step S4, as shown in fig. 4, the robot obtains a second distribution point p2 in the signal quantization distribution map, where a distribution signal corresponding to the second distribution point in the signal quantization distribution map is a second distribution signal, and its hexadecimal value is 4 (corresponding to a binary value of 0100). The second distribution signal and the second detection signal contain the same signal information, and both contain only the right signal, and the straight-line distance P2P1 between the second distribution point and the first distribution point is equal to the straight-line distance P2P1 between the second position point and the first position point. Wherein, the straight line distance between the distribution points is the straight line length from the central point of the grid unit corresponding to one distribution point to the central point of the grid unit corresponding to the other distribution point. The process then proceeds to step S5.
In step S5, as shown in fig. 3, the robot selects a different verification position point P3 based on the current walking path, and the P3 point may be any point except the P1 point and the P2 point in the bow-shaped path. A verification detection signal detected by the robot at the verification position point P3 is acquired, the verification detection signal including only the intermediate signal. The process then proceeds to step S6.
In step S6, as shown in fig. 4, the robot acquires a verification distribution point p3 in the signal quantization distribution map, and the distribution signal corresponding to the verification distribution point p3 in the signal quantization distribution map is a verification distribution signal. The positional relationship between the verification distribution point P3 and the first and second distribution points P1 and P2 is the same as the positional relationship between the verification position point P3 and the first and second position points P1 and P2, i.e., the triangle formed by P1P2P3 is congruent with the triangle formed by P1P2P 3. The process then proceeds to step S7.
In step S7, the robot determines whether the signal information included in the verification distribution signal and the verification detection signal is the same, and if both signals include only the intermediate signal, the robot performs cumulative addition. If the types of the signals included in the two signals are different, for example, the verification detection signal only includes the middle signal, and the verification distribution signal includes the right signal, the signal information included in the two signals is different, and the cumulative addition is not performed. The signal information refers to the type of the pilot signal, and the type of the pilot signal in this embodiment includes a guard rail signal, a left signal, a right signal, and a middle signal. The process then proceeds to step S8.
In step S8, after the robot completes the determination of one verification position point, it is determined whether the selected verification position points reach the preset number, if so, it indicates that the matching verification of the currently walking path and the corresponding path in the signal quantization distribution map by the robot is sufficient, and it may consider to change a path in the signal quantization distribution map for matching verification, and then step S9 is performed. The preset number can be set according to specific design requirements, and preferably, can be set to 200 or 300. If the selected verification position points do not reach the preset number, which indicates that the path data acquired by the robot for matching is insufficient and sufficient verification cannot be performed, the method returns to step S5 to continue to select other verification position points for verification.
In step S9, the robot determines the score of the last accumulated point, completes the path verification of this time, and determines whether the number of times of determining the score reaches the preset number of times, if so, it indicates that the robot has performed sufficient path verification many times, and the accuracy of the verification result is high, and may go to step S10 to determine the position of the charging dock. Otherwise, returning to step S1, the verification of the next path is started. The preset times can be set according to specific design requirements, and preferably, can be set to 100 times or 200 times.
In step S10, the robot compares the scores of the last cumulative scores determined each time to obtain a primary matching verification result with the highest score, and in the result, the path corresponding to the distribution point in the signal quantization distribution map of the robot highly coincides with the path the robot currently walks. And the position of the charging dock is known in the signal quantification profile relative to the orientation of the profile point in the path. Therefore, the position of the charging seat corresponding to the current walking path can be calculated according to the relation of congruent triangles based on the position of the charging seat determined by the distribution point in the signal quantization distribution diagram corresponding to the time with the highest score.
The robot described in this embodiment can accurately determine the position of the charging seat by way of path matching in the signal quantization distribution diagram of the charging seat, thereby providing effective reference data for the subsequent robot returning, and improving the robot returning efficiency.
In one embodiment, the signal quantization profile of the charging dock is formed by: first, as shown in fig. 4, the robot determines a preset range based on the position of the charging seat 20, the shape and size of the preset range may be set according to specific design requirements, and may be set to be rectangular, square or elliptical, and the like, and set to be 2 square meters, 3 square meters or 4 square meters, and the like. The area surrounded by the outermost rectangular frame in fig. 4 is used as the preset range in the present embodiment. The robot grids the preset range to form a plurality of grid units, the grid units are virtual grids with certain lengths and widths, and the lengths and the widths can be the same or different, but each grid unit is required to be the same, such as small grids which can be set to 0.1 meter by 0.1 meter, small long grids which can be set to 0.1 meter by 0.15 meter, small grids which can be set to 0.15 meter by 0.15 meter, and the like. The small squares shown in fig. 4 are grid cells described in this embodiment. Then, the robot traverses the preset range in a track form of a Chinese character 'gong', wherein the traversal refers to the robot walks once through on the surface of the preset range. The cleaning robot traverses a certain area, namely the cleaning robot finishes cleaning the floor of the area. The robot detects the guiding signal sent by the charging seat 20 while walking, and performs signal coding according to a preset coding form based on the guiding signal sent by the charging seat 20 detected in the traversal process to form a distribution signal. The preset coding form may be set according to specific design requirements, for example, an octal coding form or a hexadecimal coding form is adopted. The formed distribution signal may represent the condition of the guiding signal detected by the robot. Finally, the robot records the distribution signal in correspondence with the grid cell corresponding to the current position to form the signal quantization distribution map, and the position of the robot relative to the charging stand 20 at a certain grid cell and the condition of the guide signal detectable at the position can be known through the signal quantization distribution map. In the method of this embodiment, an area in a certain range in front of the charging stand is rasterized, and a guidance signal detected by the robot is quantized and encoded to form an indirect correspondence between the position of the charging stand and the guidance signal, so as to provide an accurate reference basis for a subsequent robot to determine the position of the charging stand.
As an embodiment, as shown in fig. 4, the predetermined range is a square area of 2 meters by 2 meters surrounded by the outermost frame in the figure. The charging seat 20 is located at the middle position of one side of the square area, and the signal transmission direction of the charging seat 20 faces to the opposite other side. The grid cell is a square virtual cell of 0.1 meter by 0.1 meter. The square area may be divided into 400 of the square virtual cells. Each grid cell corresponds to the situation where the guiding signal collected by the robot at the position of the grid cell is recorded, for example, the grid cell located in the middle records hexadecimal values 9 and 8, the grid cell located at the left side of the charging stand (i.e., the left side of the drawing) records hexadecimal values 0 and 2, the grid cell located at the right side of the charging stand (i.e., the right side of the drawing) records hexadecimal values 0 and 4, and so on. In the embodiment, the area range of 4 square meters in front of the charging seat is divided into 400 grid units, and the signal distribution condition of the charging seat on each grid unit is correspondingly marked, so that the robot can more accurately find the position of the charging seat through the distribution diagram.
As one embodiment, the method includes the steps of traversing the preset range by the robot, encoding signals according to a preset encoding form based on the detected guiding signal sent by the charging dock in the traversing process, and forming a distribution signal, and specifically includes the following steps: first, the robot travels within the preset range with a zigzag track from the position of the charging stand. As shown in fig. 4, the robot starts to move forward from the position of the charging stand 20, and after moving forward for a distance of 2 meters, turns left, and traverses the area on the right side of the charging stand (i.e., the right side of fig. 4) in a zigzag manner, and then travels to the area on the left side of the charging stand to traverse. Of course, the robot may traverse the left area of the charging stand first and then traverse the right area of the charging stand. The number of times the robot traverses the entire preset range may be a plurality of times, preferably 2 or 3 times. Through repeated traversal for many times, the accuracy of detecting the charging seat signal distribution by the robot can be improved, and the accuracy of the constructed signal quantization distribution diagram is ensured. Then, the robot detects the guidance signal from the charging stand while walking, and analyzes the detected guidance signal. When the robot detects the first guiding signal, which is a guard rail signal in this embodiment, the value of the first data bit is 1, otherwise, the value of the first data bit is 0. When the robot detects the second pilot signal, which is a left signal in this embodiment, the value of the second data bit is 1, otherwise, the value of the second data bit is 0. When the robot detects the third pilot signal, which is a right signal in this embodiment, the value of the third data bit is 1, otherwise, the value of the third data bit is 0. When the robot detects the fourth pilot signal, which is an intermediate signal in this embodiment, the value of the fourth data bit is 1, otherwise, the value of the fourth data bit is 0. The charging base described in this embodiment has only four kinds of guiding signals, and can be represented by one byte (four bits), each bit represents one data bit, that is, 4 bits represent the situation that the robot receives 4 kinds of signals at the current position. Then, the robot arranges the first data bit to the fourth data bit in the sequence from the low bit to the high bit to form a binary number group, and then converts the binary number group into a hexadecimal number value to form the distribution signal. In fig. 4, a grid cell of hexadecimal number 0 (i.e., binary 0000) is marked to indicate that the robot does not detect any pilot signal. The grid cell labeled hexadecimal number 1 (i.e., binary 0001) indicates that the robot only detected the guardrail signal. The grid cell labeled hexadecimal number 2 (i.e., binary 0010) indicates that the robot only detected the left signal. The grid cell labeled hexadecimal number 3 (i.e., binary 0011) indicates that the robot detects both the guardrail signal and the left signal. The grid cell labeled hexadecimal number 4 (i.e., binary 0100) indicates that the robot only detected the right signal. The grid cell labeled hexadecimal number 5 (i.e., binary 0101) indicates that the robot detects both the guardrail signal and the right signal. The grid cell labeled hexadecimal number 8 (i.e., binary 1000) indicates that the robot only detected the intermediate signal. The grid cell labeled hexadecimal number 9 (i.e., binary 1001) indicates that the robot detects both the mid signal and the guard rail signal. The grid cell labeled hexadecimal number a (i.e., binary 1010) indicates that the robot detects both the middle and left signals. The grid cell labeled hexadecimal number B (i.e., binary 1011) indicates that the robot detects the middle signal, the left signal, and the guard rail signal simultaneously. The grid cell labeled hexadecimal number C (i.e., binary 1100) indicates that the robot detects both the middle and right signals. The grid cell labeled hexadecimal number D (i.e., binary 1101) indicates that the robot detects the middle signal, the right signal, and the guard rail signal simultaneously.
Of course, if the guiding signal of the charging dock also includes other types of signals, such as a left middle signal, a right middle signal, a left deflection signal, a right deflection signal, etc., the robot can add one more byte to represent, that is, 8 bits represent the situation that the robot receives 8 types of signals at the current position. The number of data bits used can be set according to the type number of the boot signal of the charging dock, and is generally set to a value greater than or equal to 4 and less than or equal to 8.
The embodiment adopts the form of data bits to mark different types of signal detection conditions, can realize the storage of a large amount of data by using the minimum storage capacity, saves the storage capacity, and can improve the processing speed of the data, so that the robot can calculate the position of the charging seat more quickly.
As one embodiment, the preset number is greater than 100, that is, when the robot performs verification of one path, only 100 verification points are extracted from the path to be verified, which is a relatively suitable value, so that a relatively good verification effect can be achieved. If the number is too large, more calculation resources and data processing time need to be consumed, and if the number is too small, an accurate verification effect cannot be achieved.
In one embodiment, the preset number is greater than 50, that is, the robot only performs matching between the path in the signal quantization distribution map and the current walking path of the robot 50 times, which is a relatively proper value, and a relatively good matching result can be achieved. If the times are too many, more operation resources and data processing time need to be consumed, and if the times are too few, an accurate matching effect cannot be achieved.
As one embodiment, the step S10 of obtaining the position of the charging seat corresponding to the current walking path based on the position of the charging seat determined by the distribution point in the signal quantization distribution map corresponding to the time with the highest score specifically includes the following steps: firstly, the robot determines the signal quantization distribution graph corresponding to the time with the highest score as a reference graph, and the reference graph already forms the track of the matched reference path. Then, since the coordinates of the grid cells in the reference map are known, as are the distribution of the reference path in these grid cells, the robot can determine the orientation parameters of the charging dock in the reference map with respect to the first distribution point and the second distribution point in the reference path. Then, the robot determines the position parameters of the first position point and the second position point corresponding to the time with the highest score, that is, determines the coordinates and directions of the robot at the first position point and the second position point, which are located based on sensors such as a gyroscope and a code wheel of a driving wheel, in the actual walking process of the robot on the current path. Finally, the robot calculates the position parameters of the charging seat relative to the two position points and in the current walking path by the position parameters of the first position point and the second position point according to a triangle formed by the orientation parameters of the three position points, namely the first distribution point, the second distribution point and the position point of the charging seat in the reference picture in an congruent triangle mode, so that the robot can accurately find the position of the charging seat and can quickly navigate back to the seat.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. Which when executed performs steps comprising the method embodiments described above. Finally, it should be noted that: the above embodiments are only used for illustrating the technical solution of the present invention, but not for limiting the same, and the embodiments may be combined with each other; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. A method for searching a charging seat position by a robot is characterized by comprising the following steps:
step S1, the robot randomly selects a first position point in the path based on the current walking path, acquires a first detection signal detected when the robot is at the first position point, and then enters step S2;
step S2, the robot acquires a first distribution point in a signal quantization distribution map of the charging dock, where a distribution signal of the first distribution point in the signal quantization distribution map is a first distribution signal, and the first distribution signal is the same as the signal information contained in the first detection signal, and then proceeds to step S3;
step S3, the robot randomly selects a second position point in the path based on the current walking path, acquires a second detection signal detected when the robot is at the second position point, and then enters step S4;
step S4, the robot acquires a second distribution point in the signal quantization distribution map, where a distribution signal corresponding to the second distribution point in the signal quantization distribution map is a second distribution signal, the second distribution signal is the same as the signal information contained in the second detection signal, and a linear distance between the second distribution point and the first distribution point is equal to a linear distance between the second position point and the first position point, and then the process proceeds to step S5;
step S5, the robot selects different verification position points based on the current walking path, acquires the verification detection signals detected when the robot is at the verification position points, and then enters step S6;
step S6, acquiring, by a robot, verification distribution points in the signal quantization distribution map, where distribution signals corresponding to the verification distribution points in the signal quantization distribution map are verification distribution signals, and a positional relationship between the verification distribution points and the first distribution points and the second distribution points is the same as a positional relationship between the verification position points and the first position points and the second position points, and then entering step S7;
step S7, the robot judges whether the signal information contained in the verification distribution signal and the verification detection signal is the same, if so, the robot carries out cumulative adding points, if not, the robot does not carry out cumulative adding points, and then the robot enters step S8;
step S8, the robot judges whether the selected verification position points reach the preset number, if so, the step S9 is carried out, otherwise, the step S5 is returned;
step S9, the robot determines the final accumulated score and judges whether the number of times of determining the score reaches the preset number, if so, the step S10 is executed, otherwise, the step S1 is executed again;
step S10, the robot compares the score of the last cumulative score determined each time, and obtains the position of the charging seat corresponding to the current walking path based on the position of the charging seat determined by the distribution point in the signal quantization distribution map corresponding to the time with the highest score.
2. The method of claim 1, wherein the signal quantization profile of the cradle is formed by:
the robot determines a preset range based on the position of a charging seat, and the preset range is rasterized to form a plurality of grid units;
and traversing the preset range by the robot, carrying out signal coding according to a preset coding form based on the guide signal sent by the charging seat detected in the traversing process to form a distribution signal, and correspondingly recording the distribution signal and the grid unit corresponding to the current position to form the signal quantization distribution map.
3. The method of claim 2, wherein:
the preset range is a square area of 2 meters by 2 meters, and the charging seat is positioned in the middle of one side of the square area; the grid cell is a square virtual cell of 0.1 meter by 0.1 meter; the square area is divided into 400 of the square virtual cells.
4. The method according to claim 2, wherein the step of the robot traversing the preset range, based on the detected guiding signal sent by the charging dock in the traversing process, performing signal coding according to a preset coding form to form a distribution signal includes the following steps:
the robot starts from the position of the charging seat and walks within the preset range by a Chinese character 'gong' type track;
the robot detects the guide signal sent by the charging seat while walking, and analyzes the condition of detecting the guide signal; when the robot detects the first guiding signal, the value of the first data bit is 1, otherwise, the value of the first data bit is 0; when the robot detects the second guiding signal, the value of the second data bit is 1, otherwise, the value of the second data bit is 0; by analogy, when the robot detects the Nth guiding signal, the numerical value of the Nth data bit is 1, otherwise, the numerical value of the Nth data bit is 0; wherein N is a number greater than or equal to 4 and less than or equal to 8;
the robot arranges the first data bit to the Nth data bit according to the sequence from the low bit to the high bit to form a binary number group, and then converts the binary number group into a hexadecimal number value to form the distribution signal.
5. The method of claim 1, wherein the predetermined number is greater than 100.
6. The method of claim 1, wherein the predetermined number of times is greater than 50 times.
7. The method according to any one of claims 1 to 6, wherein the step S10 of obtaining the position of the charging seat corresponding to the current walking path based on the position of the charging seat determined by the distribution point in the signal quantization profile corresponding to the time with the highest score value includes the following steps:
the robot determines a signal quantization distribution diagram corresponding to the time with the highest score as a reference diagram;
the robot determines the orientation parameters of the charging seat relative to the first distribution point and the second distribution point in the reference image;
the robot determines the position parameters of the first position point and the second position point corresponding to the time with the highest score;
and the robot calculates the position of the charging seat in the current walking path according to the position parameters and the orientation parameters.
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