CN113340258B - Hough transform-based rotation angle acquisition method, chip and robot - Google Patents
Hough transform-based rotation angle acquisition method, chip and robot Download PDFInfo
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- CN113340258B CN113340258B CN202110575452.2A CN202110575452A CN113340258B CN 113340258 B CN113340258 B CN 113340258B CN 202110575452 A CN202110575452 A CN 202110575452A CN 113340258 B CN113340258 B CN 113340258B
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- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
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- G—PHYSICS
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- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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Abstract
The invention discloses a Hough transform-based method for acquiring a rotation angle, a chip and a robot, wherein the Hough transform-based method for acquiring the rotation angle comprises the following steps of 1, acquiring first frequency statistical information in a reference coordinate mapping space from a global map through Hough transform, acquiring second frequency statistical information in the reference coordinate mapping space from a local map through Hough transform, and setting reference rotation angles suitable for all the reference coordinate mapping spaces; step 2, periodically convolving the second frequency statistic information and the first frequency statistic information by utilizing the trigonometric function of the reference rotation angle to obtain a cross-correlation signal sequence of a straight line of the local map and a straight line corresponding to the global map; and 3, calculating and acquiring a local maximum value from the cross-correlation signal sequence, and setting a rotation angle corresponding to the currently acquired local maximum value as an optimal rotation angle between the local map and the global map.
Description
Technical Field
The invention relates to the technical field of robot map conversion, in particular to a Hough transform-based rotation angle acquisition method, a Hough transform-based rotation angle acquisition chip and a robot.
Background
The SLAM algorithm is the basis for the robot to execute navigation positioning in the grid map, and by executing the SLAM algorithm, the mobile robot builds a map and carries out real-time positioning in a local map which is built immediately. In the prior art, a positioning technology of a robot in a grid map is based on a feature SLAM algorithm, so that the robot depends on extracting features from the grid map, but the grid map features are few, the robot easily loses related feature information, and a map drift error is generated, so that a local map constructed in real time by the robot is not accurately matched with a global map, including a large conversion error between a robot coordinate system on the local map and a global coordinate system on the global map, and the robot cannot accurately and timely identify the self attitude coordinate of the robot, and the position coordinates of objects with many linear features, such as walls, furniture and the like in an indoor environment in a navigation process.
Disclosure of Invention
In order to solve the problem of matching conversion errors between the coordinate system of the local map and the coordinate system on the global map caused by the fact that map feature information is easy to lose, the invention provides the Hough transform-based rotation angle acquisition method, the chip and the robot. The specific technical scheme of the invention is as follows:
step 1, obtaining first frequency statistic information in a reference coordinate mapping space from a global map through Hough transform, obtaining second frequency statistic information in the reference coordinate mapping space from a local map through Hough transform, and setting reference rotation angles suitable for all the reference coordinate mapping spaces; step 2, periodically convolving the second frequency statistical information and the first frequency statistical information by utilizing the trigonometric function of the reference rotation angle to obtain a cross-correlation signal sequence of the straight line of the local map and the straight line corresponding to the global map; step 3, calculating and acquiring a local maximum value from the cross-correlation signal sequence, and setting a rotation angle corresponding to the currently acquired local maximum value as an optimal rotation angle between the local map and the global map; the robot comprises a global map, a local map and a robot, wherein a reference coordinate mapping space corresponding to the global map and a reference coordinate mapping space corresponding to the local map are both used for representing the same environmental area, the local map is built by the robot in real time in the current motion area, and the global map is built by the robot in the same motion area in advance.
According to the technical scheme, reference coordinate mapping spaces with the same size and relative distribution areas are mapped from a global map and a local map respectively through Hough transformation so as to store linear characteristic information in time, loss of map information is avoided, then statistical information related to straight lines is extracted from respective reference coordinate mapping spaces to carry out convolution operation with a rotation angle as a period continuation so as to obtain strength of cross correlation of the rotation angle of the straight line of the local map and the rotation angle of the straight line corresponding to the global map, and matching operation of the straight line of the local map and the straight line of the global map is executed; on the basis, the rotation angle corresponding to the convolution value of the local maximum value is screened to serve as the optimal rotation angle between the local map and the global map, and cross correlation evaluation is only carried out on the distribution frequency characteristics of the corresponding straight line in the reference coordinate mapping space in the specific direction, so that the processing speed of the rotation angle is increased, and the speed of converting the subsequent local map into the global map is further increased.
Further, in the step 1, the method specifically includes: sl1, extracting straight lines in the global map, then converting the straight lines Hough into a corresponding reference coordinate mapping space, and then calculating the sum of squares by using the times of respective extraction of the straight lines at different reference point line distances on the same reference rotation angle to serve as the first frequency statistical information; then, the step S12 is carried out; s12, sequentially calculating the first frequency statistical information on each reference rotation angle according to the step S11 to form a discrete sequence of the square sum of the linear distribution of the global map; s13, extracting straight lines in a local map, then converting the straight lines Hough into a corresponding reference coordinate mapping space, and then calculating the sum of squares by using the times of extraction of the straight lines at different reference point line distances on the same reference rotation angle to serve as the second frequency statistical information; then, the step S14 is carried out; and S14, sequentially calculating the second frequency statistical information on each reference rotation angle according to the step S13 to form a discrete sequence of the square sum of the straight line distribution of the local map.
The technical scheme is equivalent to obtaining the frequency numbers of detected and extracted parallel straight lines in the same map, and then solving the square sum information of the frequency numbers at corresponding positions to describe the frequency condition of the straight lines in all directions in the grid map, so that the robot can identify and position and evaluate the areas such as walls, furniture and the like with linear characteristics.
Further, the straight lines extracted in step S11 and step S13 are all polar coordinate points in the hough transform space, and are a set of straight lines representing a global map or a local map; wherein, different polar coordinate points represent different straight lines, and the same polar coordinate point represents at least one straight line; the polar coordinate points comprise rotation angles and point line distances, the rotation angles are included angles formed by normals of straight lines represented by the polar coordinate points and positive directions of transverse axes of a coordinate system of the map to which the polar coordinate points belong, and the point line distances are geometric vertical distances from an original point of the coordinate system of the map to which the polar coordinate points belong to the straight lines represented by the polar coordinate points. The technical scheme is based on Hough transform, and the straight lines with the same shape in one map space are mapped to points in another coordinate space to complete conversion processing of straight line information, so that the robot mapping positioning algorithm has better robustness to noise or incomplete shapes, and the influence of losing map straight line features in the robot navigation process is reduced.
Further, the reference coordinate mapping space is a matrix space belonging to the hough space, the reference rotation angle is the rotation angle of a polar coordinate point of the reference coordinate mapping space, and the reference point line distance is the point line distance of the polar coordinate point of the reference coordinate mapping space, which are adaptively set according to the actual traversal environment of the robot; wherein, the number of rows of the elements arranged in the reference coordinate mapping space is the number of polar coordinate points with the same reference rotation angle but different reference point line distances; the number of columns of the elements arranged in the reference coordinate mapping space is the number of polar coordinate points with the same reference point line distance but different reference rotation angles; the polar coordinate points of the reference coordinate mapping space are all discrete; or the number of columns of the reference coordinate mapping space is the number of polar coordinate points with the same reference rotation angle but different reference point line distances; the number of rows of the reference coordinate mapping space is the number of polar coordinate points with the same reference point line distance but different reference rotation angles; the polar coordinate points of the reference coordinate mapping space are distributed discretely; wherein the element of each row and each column in the reference coordinate mapping space is the number of straight lines represented by polar coordinate points at corresponding positions in the Hough space. According to the technical scheme, a reference coordinate mapping space with the same size and relative distribution area is mapped from a global map and a local map respectively and is used as a parameter space to be detected, wherein the number of polar coordinate points with the same reference rotation angle but different reference point line distances represents the number of parallel straight lines in the corresponding map, and the number of polar coordinate points with the same reference point line distances but different reference rotation angles represents the number of straight lines corresponding to the same point in the map, so that the straight line parameters described by the reference coordinate mapping space are more comprehensive, and more comprehensive straight line segments are covered in the corresponding map area.
Further, in the step 2, the method for obtaining the cross-correlation signal sequence of the straight line of the local map and the straight line corresponding to the global map by periodically convolving the second frequency statistical information and the first frequency statistical information with the trigonometric function of the reference rotation angle specifically includes: setting the number of different reference point linear distances correspondingly existing in polar coordinate points in the reference coordinate mapping space as accumulation times, simultaneously setting the number of the polar coordinate points with the same reference point linear distance but different reference rotation angles in the reference coordinate mapping space as reference offset times, performing discrete convolution on a discrete sequence of the global map linear distribution square sum and a discrete sequence of the local map linear distribution square sum to obtain a cross-correlation signal sequence of a local map linear and a corresponding global map linear under the periodic extension action of different reference rotation angles, realizing the periodic extension and accumulation of second frequency statistic information and first frequency statistic information by using the periodicity of the reference rotation angles, and completing the convolution of the first frequency statistic information and the second frequency statistic information; wherein the trigonometric periodicity of the reference rotation angle is: on the basis of a trigonometric function relational expression in Hough transform, for the same straight line in a global map or a local map, the same reference point line distance corresponds to at least one reference rotation angle; the number of accumulations is greater than 0. According to the technical scheme, the similarity degree of the angle azimuth of the straight line in the local map and the angle azimuth of the straight line in the global map is evaluated in a plurality of discrete angle ranges limited by the reference rotation angle in a convolution operation mode, so that the rotation angle corresponding to the candidate straight line suitable for map matching is provided.
Further, the discrete convolution of the discrete sequence of the global map linear distribution square sum and the discrete sequence of the local map linear distribution square sum specifically includes: after each element in the discrete sequence of the local map linear distribution square sum is subjected to translation operation with the translation variation amount being the corresponding reference rotation angle every time, multiplying the element by the corresponding element of the discrete sequence of the global map linear distribution square sum, and adding the element to obtain a convolution value under the current translation operation, wherein the convolution value is used as a discrete convolution value in the cross-correlation signal sequence; repeating the above steps until the reference rotation angles with the reference offset times are translated along the same direction, and obtaining all discrete convolution values in the cross-correlation signal sequence; or, after each element in the discrete sequence of the global map linear distribution square sum has a translation operation with a translation variation amount being a corresponding reference rotation angle, multiplying the element by a corresponding element in the discrete sequence of the local map linear distribution square sum, and adding the multiplied element to obtain a convolution value under the current translation operation, wherein the convolution value is used as a discrete convolution value in the cross-correlation signal sequence; and repeating the above steps until the reference rotation angles of which the number is the reference offset times are translated along the same direction, so as to obtain all discrete convolution values in the cross-correlation signal sequence.
The technical scheme includes that the periodicity of reference rotation angles in a reference coordinate mapping space relative to the line distance of a reference point is utilized, a mapping discrete sequence of a translated map and each value of the mapping discrete sequence corresponding to the same map to be matched are set to be multiplied pairwise and then added, periodic continuation of the Hough space is completed, the cross correlation of each reference rotation angle between a global map and a local map to be matched is obtained, and the influence of angle offset errors of corresponding straight lines in the two maps for matching is reduced.
Further, the method for obtaining local maxima by computing in the cross-correlation signal sequence specifically includes: and in the reference coordinate mapping space, controlling the cross-correlation signal sequence to execute partial derivative operation along the direction of a variable axis where the reference rotation angle is located, when the first-order difference of the cross-correlation signal sequence is 0 and the second-order difference of the cross-correlation signal sequence is less than 0, obtaining at least one local maximum discrete convolution value from the cross-correlation signal sequence and determining the local maximum discrete convolution value as a local maximum, setting all the local maximum discrete convolution values as the discrete convolution values with the maximum degree of similarity between the straight line of the local map and the straight line of the global map, and simultaneously setting the rotation angles corresponding to all the local maximum discrete convolution values as the optimal rotation angles of the local map relative to the global map respectively, so as to convert the coordinates obtained by real-time calculation of the robot in the local map into the global map. To prevent the algorithm from detecting multiple extremely adjacent 'false' straight lines to generate misjudgment; furthermore, if the local maxima present in the cross-correlated signal sequence are sufficiently high, only a fraction of the time is required to search, thereby substantially reducing computation time and providing high performance efficiency.
A chip is used for storing a program, and the program is the acquisition method and is used for calculating and acquiring a cross-correlation signal sequence of a straight line of a local map and a straight line corresponding to a global map, then calculating and acquiring a local maximum value from the cross-correlation signal sequence, and setting a rotation angle corresponding to the local maximum value as an optimal rotation angle of the local map relative to the global map. According to the technical scheme, a straight line to be detected in a map is mapped into a polar coordinate point of a Hough space through an equation of Hough transformation, similarity evaluation of the map-associated straight line is carried out by using a statistical result of frequency numbers of the straight lines in the same direction extracted from the same polar coordinate point, and finally the robot is guaranteed to be capable of outputting reasonable optimal rotation angle parameters of a local map in a mode of solving a local maximum value.
The robot is provided with the chip and is used for acquiring the optimal rotation angle between the local map and the global map according to the cross correlation between the straight line of the local map constructed immediately and the straight line corresponding to the global map constructed in advance. The robot evaluates the cross correlation of the distribution frequency characteristics of the corresponding straight line in the reference coordinate mapping space in a specific direction, accelerates the processing speed of obtaining the optimal rotation angle, and further accelerates the subsequent positioning speed of the robot in a global map.
Further, the robot is also provided with a laser sensor for acquiring two-dimensional laser point cloud from a laser map constructed by scanning, and then linear features of the two-dimensional laser point cloud are extracted by utilizing Hough transform. The accuracy of the robot in recognizing straight lines in the map environment is improved.
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Fig. 1 is a schematic flow chart of an embodiment of the invention, which discloses a method for acquiring a rotation angle based on hough transform.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application, and the appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. One of ordinary skill in the art will explicitly or implicitly appreciate that the embodiments described herein can be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application pertains. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The terms "comprises," "comprising," "including," "has," "having," and any variations thereof, as referred to herein, are intended to cover non-exclusive inclusions, such as: a process, method, system, article, or apparatus that comprises a list of steps or modules is not limited to only those steps or elements but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus. Reference herein to the terms "first," "second," and "third" are merely used to distinguish between similar objects and not necessarily to represent a particular ordering for the objects.
Fig. 1 is a flowchart of a method for acquiring a rotation angle based on hough transform according to an embodiment of the present invention, where the method specifically includes the following steps:
s1, acquiring first frequency statistic information in a reference coordinate mapping space from a global map through Hough transformation, acquiring second frequency statistic information in the reference coordinate mapping space from a local map through Hough transformation, and setting reference rotation angles suitable for all the reference coordinate mapping spaces; then, the process proceeds to step S2. The second frequency statistical information and the first frequency statistical information both reflect the number of occurrences of a straight line in a specific direction in the corresponding hough space. The robot comprises a global map, a local map and a robot, wherein a reference coordinate mapping space corresponding to the global map and a reference coordinate mapping space corresponding to the local map are both used for representing the same environmental area, the local map is built by the robot in real time in the current motion area, and the global map is built by the robot in the same motion area in advance.
It should be noted that, in this embodiment, the core idea of hough transform is to map a point set (two-dimensionally) belonging to a certain graphic in a map onto a point (which may be a high-dimensional point), where the point records the number of points in the point set, the point is a parameter of the graphic to be searched, and the range of the parameter is called a parameter space, i.e., the reference coordinate mapping space. The hough transform not only can identify whether a graph needing to be detected exists in a map constructed by scanning, but also can locate the graph (including position, angle and the like). When this feature sought to be extracted is located within a set of points and can be described mathematically, a search can be made by hough transform.
The hough transform is a method of detecting straight lines and various geometric figures in a binary image, and the present embodiment focuses on the detection of straight lines in a grid map since it is considered that many linear features exist in walls inside a building.
The equation forms of the straight line have intercept, truncated, general, point-diagonal, etc., but these forms all have "singular" cases where one intercept is 0, the slope is 0, and c =0 (c is usually divided to the left of the equation, reducing the search by one parameterCord), and some other forms of parameter space are not closed, such as a truncated slope k, ranging from 0 to infinity. In order to simplify the quantization search, the present embodiment adopts a straight line representation type containing polar coordinate parameters, which is abbreviated as polar coordinate type, in hough transform as follows:
it is noted that this polar equation is not a polar equation, as it is also expressed in cartesian coordinates.
Wherein the angle
The included angle formed by the normal line of the converted straight line and the positive direction of the x axis and the distance between the line lines
Two parameters of the hough transform of the straight line are formed for the geometric perpendicular distance from the origin of the map coordinate system to the converted straight line, and are related by the polar equation. If angle
And distance between points and lines
When the values are constant, any point on the straight line can be expressed by using the polar coordinate formula.
If N points are assumed, if the robot needs to detect the straight line where the robot is located during positioning, a specific angle needs to be found
And distance between points and lines
. Each point can be passed through an infinite number of straight lines, here set to n (typically n = 180), and then Nn numbers can be found
For the Nn
When counting at
Is equal to a certain value
At a plurality of points
Is approximately equal to
That is to say the points are all in a straight line
The above.
In this embodiment, each straight line of the contour of the wall and the furniture represented by the map and a pair of parameters may be used
Associating the pair of parameters
The two-dimensional plane is defined as Hough space for the set of two-dimensional straight lines, so that Hough transformation can detect and acquire the output vectors of the straight lines. Each straight line is composed of polar coordinates with two elements
Express, same polar coordinate
Multiple coincident straight lines may be represented.
Specifically, the transformation is achieved by quantizing the hough space into an accumulator unit. This embodiment angles
And distance between points and lines
Set to notional polar coordinates, but accumulator space is in abscissa
And ordinate
The rectangle of (2) is drawn. In the hough space of the present embodiment, each polar coordinate point is regarded as a result of one extraction of a straight line of the grid map.
The straight line extraction method related in the embodiment is that all straight lines in a corresponding map are subjected to Hough transformation into polar coordinate points in Hough space, and the polar coordinate points are used for representing a set of straight lines of a global map or a local map; wherein, different polar coordinate points represent different straight lines, and the same polar coordinate point represents at least one straight line; the polar coordinate points comprise rotation angles and point line distances, the rotation angles are included angles formed by normals of straight lines represented by the polar coordinate points and positive directions of transverse axes of a coordinate system of the map to which the polar coordinate points belong, and the point line distances are geometric vertical distances from an original point of the coordinate system of the map to which the polar coordinate points belong to the straight lines represented by the polar coordinate points. If the hough transform is repeated to the same polar coordinate point, a new vote is cast for the corresponding polar coordinate point in the accumulator space, namely, a count is added, all points are calculated in such a way, and the vote number of some points is a local maximum (namely, a peak value) inevitably. The embodiment maps straight lines with the same shape in one map space to points in another coordinate space based on Hough transformation for voting statistics, and forms peak values to complete the transformation processing of straight line information, thereby converting the problem of detecting the straight line characteristics of the environment into the problem of statistical peak values. By introducing probability peak value statistics, the robot mapping positioning algorithm has better robustness to noise or incomplete shapes, and the influence of losing map straight line features in the robot navigation process is reduced. It should be noted that, in the conventional hough transform straight line detection algorithm, the peak generated in the accumulator space represents strong evidence of the corresponding straight line in the image.
The accuracy of the alignment of the detected and original image lines is obviously not perfect, depending on the quantization of the accumulator array. (note also that many image edges have several detection lines because there are several nearby hough space peaks with similar line parameter values, and techniques exist to control this effect, but are not used here to illustrate standard hough transforms).
Note that, according to the above, a little generalization is performed, that is, generalized hough transform is performed. The generalized Hough transform can process a graph with an arbitrary shape, not finding an equation which can represent the arbitrary graph, but describing a graph in the form of a table, storing coordinates of edge points of the graph in a table, and determining the graph, so that no matter the graph is a straight line (actually a line segment), a circle, an ellipse or a geometric graph with other shapes, the graph can be processed by the same method, except that the graph at this time is customized and is real, the mode represented by an algebraic equation is continuous and abstract, the equation of the circle is only one, but the customized circle is infinite, and only a user thinks that the graph is sufficiently round. The application of generalized Hough transform provides a foundation for edge-extending exploration, the prior art can only simply perform repeated traversal on unknown points, and a large number of repeated routes exist at the moment, so that the efficiency is low. Meanwhile, the generalized Hough transform is not limited to a straight line structure, and the detection process of the generalized Hough transform can be completely changed according to actual conditions (such as curve of a specific radian or geometric structure information of an ellipse) in different environments so as to achieve the purpose of adaptation. The present embodiment focuses on the detection of straight lines in a grid map, since it is considered that there are many linear features in the walls of the building interior.
To accelerate the detection speed, the present embodiment uses a Discrete Hough Transform (DHT) from which DHT is derived
Dividing a line number in space to be a preset line numberAnd the row number is a matrix HS with a preset row number, and the matrix HS is defined as the reference coordinate mapping space and belongs to a matrix space in the Hough space.
The reference coordinate mapping space (parameter space) is not continuous, but is an array space composed of rectangular cells (accumulation cells) one by one, and each rectangular cell stores a corresponding rectangular cell
Frequency statistics (cumulative result of the number of times of occurrence of conversion). In this embodiment, the reference rotation angle is a rotation angle of a polar coordinate point of the reference coordinate mapping space, and the reference point line distance is the point line distance of the polar coordinate point of the reference coordinate mapping space, which are adaptively set according to an actual traversal environment of the robot; when the rotation angle is set to be 0, there are infinite cases in the corresponding matched dot line distances in the same grid map; when the dot-line pitch is set to 0, there are infinite cases in which the rotation angles correspondingly matched within the same grid map exist. Therefore, in order to create an effective reference coordinate mapping space in the Hough space, the maximum value of the reference rotation angle is set to
A minimum value of the reference rotation angle is set to 1; the maximum value of the reference point line distance is set as
The minimum value of the reference point line distance is set to be 1; extracting the straight lines on the wall in the grid map (the global map and the local map) as much as possible, and visually displaying the occurrence frequency of the straight lines in a specific direction on the grid map for reflecting the distribution position characteristics of the straight lines in the grid map by combining the statistical information and the polar coordinate information of the reference coordinate mapping space. Specifically, the number of rows of the elements arranged in the reference coordinate mapping space is the number of polar coordinate points with the same reference rotation angle but different reference point line distances, that is, the preset number of rows is equivalent to extracting from the mapThe number of parallel lines removed, in some embodiments, is preferably set to
In particular, the reference point line distance in the reference coordinate mapping space constitutes an arithmetic progression with a first term of 1 and a tolerance of 1. The number of columns of the elements arranged in the reference coordinate mapping space is the number of polar coordinate points with the same reference point line distance but different reference rotation angles, i.e. the preset number of columns, which is equivalent to the number of crossed straight lines extracted from the map, and is preferably set in some embodiments
In particular, the reference rotation angle in the reference coordinate mapping space constitutes an arithmetic progression with a first term of 1 and a tolerance of 1; the polar coordinate points of the reference coordinate mapping space are all discrete.
Preferably, the number of columns in the reference coordinate mapping space may also be the number of polar coordinate points with the same reference rotation angle but different reference point line distances, which is equal to the preset number of rows; the number of rows of the reference coordinate mapping space is the number of polar coordinate points with the same reference point linear distance but different reference rotation angles, and is equal to the preset number of columns; in this embodiment, the polar coordinate points arranged in the reference coordinate mapping space are all discretely distributed.
In the foregoing embodiment, the element of each row and each column in the reference coordinate mapping space is the number of straight lines represented by the polar coordinate point at the corresponding position in the hough space. It should be noted that the coordinate system to which the polar coordinate points in the hough space belong is not a standard polar coordinate system, but a cartesian coordinate system. In the embodiment, a reference coordinate mapping space with the same size and relative distribution area is mapped from the global map and the local map respectively and is used as a parameter space to be detected, wherein the number of polar coordinate points with the same reference rotation angle but different reference point line distances represents the number of parallel straight lines in the corresponding map, and the number of polar coordinate points with the same reference point line distances but different reference rotation angles represents the number of straight lines with the same common point in the corresponding map, so that the straight line parameters described by the reference coordinate mapping space are more comprehensive, and more comprehensive straight line segments are covered in the corresponding map area.
As an example, in the step S1, the following steps are specifically performed:
sl1, extracting straight lines in the global map, hough transforming the currently extracted straight lines into the corresponding reference coordinate mapping space, and then calculating the sum of squares by using the times of respective extraction of the straight lines with different reference point line distances on the same reference rotation angle, namely when the reference rotation angle is used
Is equal to a certain value
When the line distance at the reference point is 1 to
The method comprises the steps of taking straight lines with the same reference point line distance as a statistical unit, counting the times of Hough transform of each straight line to a corresponding position in a reference coordinate mapping space one by one, squaring the times of appearance of the straight lines with the same reference point line distance of the same reference rotation angle at the same polar coordinate point position of the Hough space correspondingly mapped by a global map, and finally accumulating and summing the square values of the appearance times of the straight lines with different reference point line distances of the same reference rotation angle to obtain first frequency statistical information in the reference coordinate mapping space, wherein the straight lines with different reference point line distances on the same reference rotation angle are equivalent to parallel straight lines in the global map. And then proceeds to step S12.
S12, sequentially calculating the first frequency statistical information on each reference rotation angle according to the step S11 to form a discrete sequence of the global map linear distribution square sum, wherein the number of elements in the discrete sequence of the global map linear distribution square sum is the preset column number and corresponds to the discrete sequenceIs 1 to
And belongs to a discrete angle value, which in some embodiments may be a series of arithmetic numbers with a first term of 1 and a tolerance of 1.
S13, extracting straight lines in the local map, then converting the straight lines Hough into a corresponding reference coordinate mapping space, and then calculating the sum of squares by using the times of respective extraction of the straight lines of different reference point line distances on the same reference rotation angle to be used as the second frequency statistical information, wherein the straight lines of different reference point line distances on the same reference rotation angle are equivalent to parallel straight lines in the local map; then, the step S14 is carried out; when the reference rotation angle is reached
Is equal to a certain value
When the line distance at the reference point is 1 to
The method comprises the steps of taking straight lines with the same reference point line distance as a statistical unit, counting the times of Hough transform of each straight line to a corresponding position in a reference coordinate mapping space one by one, squaring the times of appearance of the straight lines with the same reference point line distance of the same reference rotation angle at the same polar coordinate point position of the Hough space correspondingly mapped by a local map, and finally accumulating and summing the square values of the appearance times of the straight lines with different reference point line distances of the same reference rotation angle, wherein the sum value is used as first frequency statistical information, namely second frequency statistical information in the reference coordinate mapping space is obtained from the local map through Hough transform. And then proceeds to step S14.
And S14, sequentially calculating the second frequency statistical information on each reference rotation angle according to the step S13 to form a discrete sequence of the square sum of the straight line distribution of the local map. In which the local map is distributed in a discrete sequence of sums of squares of straight linesThe number of the elements is the preset column number, and the corresponding discrete reference rotation angle is 1 to
And belongs to discrete angle values, and in some embodiments may be an arithmetic series with a first term of 1 and a tolerance of 1.
The steps S11 to S14 are equivalent to obtaining the frequency counts of detected and extracted parallel straight lines in the same map, but not obtaining the frequency counts of detected and extracted straight lines crossing at different angular orientations in the same map, accumulating the quantized information with the reference rotation angle as an independent variable in the corresponding reference coordinate mapping space to form straight lines, and then summing the squares of the obtained frequency counts to describe the frequency situation of the straight lines in each direction appearing in the grid map by using the information, so as to realize that the robot identifies and positions and evaluates the areas such as walls and furniture with linear characteristics.
S2, periodically convolving the second frequency statistic information and the first frequency statistic information by utilizing the trigonometric function of the reference rotation angle to obtain a cross-correlation signal sequence of a straight line of the local map and a straight line corresponding to the global map; then, the process proceeds to step S3. Taking the line distance of the reference point as an independent variable, keeping a discrete sequence of the linear distribution square sum of the local map unchanged, translating the discrete sequence of the linear distribution square sum of the global map by using the reference rotation angle, multiplying the translated discrete sequence of the linear distribution square sum of the global map and the discrete sequence of the linear distribution square sum of the local map by each other respectively, and adding the multiplied discrete sequences; or taking the line distance of the reference point as an independent variable, keeping the discrete sequence of the linear distribution square sum of the global map unchanged, translating the discrete sequence of the linear distribution square sum of the local map by using the reference rotation angle, multiplying the translated discrete sequence of the linear distribution square sum of the local map and the discrete sequence of the linear distribution square sum of the global map in pairs respectively, and adding the multiplied discrete sequences; the cross correlation between the discrete sequence of the local map linear distribution square sum and the discrete sequence of the global map linear distribution square sum can be reflected as the similarity degree of the delay of each corresponding reference rotation angle, the discrete sequence of the local map linear distribution square sum is regarded as the hough space signal of the local map, and the discrete sequence of the global map linear distribution square sum is regarded as the hough space signal of the global map. When the cross-correlation signal of the discrete sequence of the local map linear distribution square sum and the discrete sequence of the global map linear distribution square sum is obtained, since the trigonometric function of the reference rotation angle has periodicity, the hough space signal should be periodically extended.
As an embodiment, in step S2, the method for periodically convolving the second frequency statistics information and the first frequency statistics information by using the trigonometric function of the reference rotation angle to obtain the cross-correlation signal sequence of the straight line of the local map and the straight line corresponding to the global map specifically includes: setting the number of different reference point line distances corresponding to polar coordinate points in the reference coordinate mapping space as an accumulation number, wherein the accumulation number is greater than 0, and is preferably set to be greater than or equal to 1 in the reference coordinate mapping space; when the reference point line distance in the reference coordinate mapping space forms an arithmetic progression with a first term of 1 and a tolerance of 1, the accumulated times are
It can be set as an argument in the convolution process; meanwhile, the number of polar coordinate points with the same reference point line distance but different reference rotation angles in the reference coordinate mapping space is set as the reference offset frequency, and the reference offset frequency is used for judging whether all sequences are calculated; then carrying out discrete convolution on the discrete sequence of the global map linear distribution square sum and the discrete sequence of the local map linear distribution square sum to obtain a cross-correlation signal sequence of the local map linear and the corresponding linear of the global map under the periodic continuation action of different reference rotation angles, realizing the periodic continuation and accumulation of the second frequency statistic information and the first frequency statistic information by utilizing the periodicity of the reference rotation angles, and finishing the convolution of the first frequency statistic information and the second frequency statistic information; wherein the trigonometric periodicity of the reference rotation angle is: based on trigonometric relations in the Hough transform, this is done for the same straight line within the global map or the local mapAnd when the line distance of the same reference point is used as a result of a trigonometric function, at least one reference rotation angle exists in angles obtained by an inverse trigonometric function, and the difference value of the reference rotation angles is a multiple of 360 degrees. The embodiment evaluates the similarity degree of the angular orientations of the straight lines in the local map and the straight lines in the global map in a plurality of discrete angular ranges defined by the reference rotation angle through a convolution operation so as to provide the rotation angle suitable for map matching.
Specifically, the discrete convolution of the discrete sequence of the global map straight line distribution square sum and the discrete sequence of the local map straight line distribution square sum specifically includes:
setting the number of different reference point line distances corresponding to the polar coordinate points in the reference coordinate mapping space as an accumulation frequency, wherein the accumulation frequency is greater than or equal to 1 and is set as an independent variable in the convolution process; and simultaneously setting the number of polar coordinate points with the same reference point line distance but different reference rotation angles in the reference coordinate mapping space as reference offset times for judging whether all the sequences are calculated, wherein the reference offset times can be 0.
Keeping the discrete sequence of the global map linear distribution square sum unchanged, directly multiplying the discrete sequence of the local map linear distribution square sum by each element of the discrete sequence of the global map linear distribution square sum in pairs at the same reference point line distance, and then adding the multiplication result to serve as a first discrete convolution value in the cross-correlation signal sequence, and regarding each element in the discrete sequence of the local map linear distribution square sum as a translation operation of a corresponding reference rotation angle each time, wherein the translation operation in the embodiment is a translation in the same direction, and the reference rotation angle under the first translation operation is 0. Then, after each element in the discrete sequence of the local map linear distribution square sum is subjected to translation operation with a translation variation amount (offset amplitude) corresponding to a reference rotation angle, multiplying the element by a corresponding element in the discrete sequence of the global map linear distribution square sum, and adding the element to obtain a convolution value under the current translation operation, wherein the convolution value is used as a discrete convolution value in the cross-correlation signal sequence, the discrete sequence of the local map linear distribution square sum is moved to the left or right by the offset amplitude of a corresponding reference rotation angle according to the translation sequence represented by the current reference offset frequency, the offset amplitude of a reference rotation angle is equal to an interval of an independent variable, and is multiplied by each element in the discrete sequence of the global map linear distribution square sum under the same independent variable, and then adding the element to obtain a convolution value under the current translation operation; and repeating the above steps until the reference rotation angles of which the number is the reference offset times are translated (traversed) in the same direction, so as to obtain all discrete convolution values in the cross-correlation signal sequence.
As another discrete convolution implementation, the discrete sequence of the local map straight line distribution square sum is kept unchanged, the discrete sequence of the global map straight line distribution square sum is multiplied by each element of the discrete sequence of the local map straight line distribution square sum in pairs at the same reference point line distance and then added, as a first discrete convolution value in the cross-correlation signal sequence, it is regarded that each element in the discrete sequence of the global map straight line distribution square sum has a translation operation of a corresponding reference rotation angle each time, the translation operation in this embodiment is a translation in the same direction, and the reference rotation angle under the first translation operation is 0. Then, after each element in the discrete sequence of the global map linear distribution square sum has a translation operation with a translation variation being a corresponding reference rotation angle, multiplying and adding the element by the corresponding element in the discrete sequence of the local map linear distribution square sum to obtain a convolution value under the current translation operation, wherein the discrete sequence of the global map linear distribution square sum is moved leftwards or rightwards by a corresponding offset amplitude of a reference rotation angle according to a translation sequence represented by the current reference offset times, the offset amplitude of one reference rotation angle is equal to an interval of an argument, and multiplying and adding the element by two in the discrete sequence of the local map linear distribution square sum under the same argument to obtain a convolution value under the current translation operation; and repeating the above steps until the reference rotation angles of which the number is the reference offset times are translated (traversed) in the same direction, so as to obtain all discrete convolution values in the cross-correlation signal sequence.
In the embodiment of the discrete convolution, the periodicity of the reference rotation angle in the reference coordinate mapping space relative to the line distance of the reference point is utilized, the mapping discrete sequence of the translated map and each value in the mapping discrete sequence corresponding to the same map to be matched are set to be multiplied by each other and then added, the periodic continuation of the Hough space is completed, the cross correlation of each reference rotation angle between the global map and the local map to be matched is obtained, and the influence of the angle offset error of the corresponding straight line in the two maps for matching is reduced.
And S3, calculating and acquiring a local maximum value from the discrete convolution values in the cross-correlation signal sequence, and setting a rotation angle corresponding to the currently acquired local maximum value as an optimal rotation angle between the local map and the global map. The cross-correlation signal sequence is a result of cross-correlation operation based on the reference rotation angle, so that a plurality of local maximum values may exist in the same reference rotation angle, that is, one or more local maximum values exist, and the local maximum values are used as candidates of the rotation angle parameter required for map rotation matching.
Specifically, the method for obtaining local maxima by computing in a cross-correlation signal sequence specifically includes: in the reference coordinate mapping space, controlling the cross-correlation signal sequence to execute a partial derivative operation along the direction of a variable axis where the reference rotation angle is located, executing the partial derivative operation on the cross-correlation signal sequence, when the first-order difference of the cross-correlation signal sequence is 0 and the second-order difference of the cross-correlation signal sequence is less than 0, obtaining at least one locally maximum discrete convolution value from the cross-correlation signal sequence and determining the discrete convolution value as a local maximum value, setting all the local maximum values as the discrete convolution values with the maximum degree of similarity of the straight lines of the local map and the global map, and setting the rotation angles corresponding to all the local maximum values as the optimal rotation angles of the local map relative to the global map respectively.
In this embodiment, when the first order difference is found to be 0, at a corresponding polar coordinate point in the reference coordinate mapping space, the change rate of the cross-correlation signal sequence in the coordinate axis (variable axis) direction to which the reference rotation angle corresponding to the polar coordinate point belongs (or the directional derivative of the coordinate axis (variable axis) direction to which the reference rotation angle belongs) is 0, a local maximum value or a local minimum value may be obtained, at this time, the second order difference is continuously found, when the second order difference (or the second order directional derivative of the coordinate axis (variable axis) to which the reference rotation angle belongs) is less than 0, the cross-correlation signal sequence grows slowest in the coordinate axis (variable axis) direction to which the reference rotation angle of the corresponding polar coordinate point belongs, and a local maximum value is obtained, at this time, the second order difference smaller than 0 of the cross-correlation signal sequence does not only one corresponding polar coordinate point but not only one maximum value point in the reference coordinate mapping space, so that a local maximum value is finally obtained. Thereby preventing the algorithm from detecting a plurality of extremely adjacent 'false' straight lines to generate misjudgment; furthermore, if the local maxima present in the cross-correlated signal sequence are sufficiently high, only a fraction of the time is required to search, thereby substantially reducing computation time and providing high performance efficiency.
In the embodiment, a reference coordinate mapping space with the same size and relative distribution area is mapped from the global map and the local map through hough transformation to store linear characteristic information in time, so as to avoid loss of map information, then statistical information associated with straight lines is extracted from respective reference coordinate mapping spaces to perform convolution operation with a rotation angle as a period extension, so as to obtain strength of cross correlation of the rotation angle of the straight line reflecting the local map and the rotation angle of the straight line corresponding to the global map, and the matching operation of the straight line of the local map and the straight line of the global map is executed; on the basis, the rotation angle corresponding to the convolution value of the local maximum value is screened to serve as the optimal rotation angle between the local map and the global map, and cross correlation evaluation is only carried out on the distribution frequency characteristics of the corresponding straight line in the reference coordinate mapping space in the specific direction, so that the processing speed of the rotation angle is increased, and the speed of converting the subsequent local map into the global map is further increased.
A chip is used for storing a program, and the program is the acquisition method and is used for calculating and acquiring a cross-correlation signal sequence of a straight line of a local map and a straight line corresponding to a global map, then calculating and acquiring a local maximum value from the cross-correlation signal sequence, and setting a rotation angle corresponding to the local maximum value as an optimal rotation angle of the local map relative to the global map. According to the technical scheme, a straight line to be detected in a map is mapped into a polar coordinate point of a Hough space through an equation of Hough transformation, similarity evaluation of the map-associated straight line is carried out by using a statistical result of frequency numbers of the straight lines in the same direction extracted from the same polar coordinate point, and finally the robot is guaranteed to be capable of outputting reasonable optimal rotation angle parameters of a local map in a mode of solving a local maximum value.
The robot is provided with the chip and is used for acquiring the optimal rotation angle between the local map and the global map according to the cross correlation between the straight line of the local map constructed immediately and the straight line corresponding to the global map constructed in advance. The robot evaluates the cross correlation of the distribution frequency characteristics of the corresponding straight line in the reference coordinate mapping space in a specific direction, accelerates the processing speed of obtaining the optimal rotation angle, and further accelerates the subsequent positioning speed of the robot in a global map.
Preferably, the robot is further provided with a laser sensor for acquiring two-dimensional laser point clouds from a laser map constructed by scanning, and then linear features of the two-dimensional laser point clouds are extracted by using hough transform. The accuracy of the robot in recognizing straight lines in the map environment is improved.
But the embodiment protects the situation that the detection is not only carried out by the laser radar. Feature information for constructing a map and information characterizing straight line features may also be collected using a vision camera mounted in front of the robot.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by hardware related to instructions of a computer program, which may be stored in a non-volatile computer readable storage medium, and when executed, may include the processes of the embodiments of the methods as described above. References to memory, storage, databases, or other media used in the embodiments provided herein can include non-volatile and/or volatile memory. The non-volatile memory may include read only memory ROM, programmable memory PROM, electrically programmable memory EPROM, electrically erasable programmable memory EEPROM or flash memory. Volatile memory can include random access memory, RAM, or external cache memory.
The features of the above embodiments may be arbitrarily combined, and for the sake of brevity, all possible combinations of the above embodiments are not described, but should be considered as within the scope of the present specification as long as there is no contradiction between the combinations of the features.
The above embodiments only express a few embodiments of the present invention, and the description thereof is specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application.
Claims (10)
1. The method for acquiring the rotation angle based on the Hough transform is characterized by comprising the following steps of:
step 1, acquiring first frequency statistic information in a reference coordinate mapping space from a global map through Hough transformation, acquiring second frequency statistic information in the reference coordinate mapping space from a local map through Hough transformation, and setting reference rotation angles suitable for all the reference coordinate mapping spaces; extracting a straight line in the global map, then converting the straight line Hough into a corresponding reference coordinate mapping space, and then calculating the square sum by using the times of extraction of the straight lines of different reference point line distances on the same reference rotation angle to be used as the first frequency statistical information; extracting a straight line in the local map, then converting the straight line Hough into a corresponding reference coordinate mapping space, and then calculating the square sum by using the times of extraction of the straight lines of different reference point line distances on the same reference rotation angle to be used as the second frequency statistical information;
step 2, periodically convolving the second frequency statistic information and the first frequency statistic information by utilizing the trigonometric function of the reference rotation angle to obtain a cross-correlation signal sequence of a straight line of the local map and a straight line corresponding to the global map;
step 3, calculating and acquiring a local maximum value from the cross-correlation signal sequence, and setting a rotation angle corresponding to the currently acquired local maximum value as an optimal rotation angle between the local map and the global map;
the robot comprises a global map, a local map and a robot, wherein a reference coordinate mapping space corresponding to the global map and a reference coordinate mapping space corresponding to the local map are both used for representing the same environmental area, the local map is built by the robot in real time in the current motion area, and the global map is built by the robot in the same motion area in advance.
2. The obtaining method according to claim 1, wherein in the step 1, specifically comprising:
sl1, extracting straight lines in the global map, then converting the straight lines Hough into a corresponding reference coordinate mapping space, and then calculating the sum of squares by using the respective extracted times of the straight lines at different reference point line distances on the same reference rotation angle to serve as the first frequency statistical information; then, the step S12 is carried out;
s12, sequentially calculating the first frequency statistical information on each reference rotation angle according to the step S11 to form a discrete sequence of the square sum of the linear distribution of the global map;
s13, extracting straight lines in a local map, then converting the straight lines Hough into a corresponding reference coordinate mapping space, and then calculating the sum of squares by using the times of extraction of the straight lines at different reference point line distances on the same reference rotation angle to serve as the second frequency statistical information; then, the step S14 is carried out;
and S14, sequentially calculating the second frequency statistical information on each reference rotation angle according to the step S13 to form a discrete sequence of the square sum of the straight line distribution of the local map.
3. The acquisition method according to claim 2, wherein the straight lines extracted in step S11 and step S13 are both polar coordinate points in hough transform space, and are a set of straight lines representing a global map or a local map;
wherein, different polar coordinate points represent different straight lines, and the same polar coordinate point represents at least one straight line;
the polar coordinate points comprise rotation angles and point line distances, the rotation angles are included angles formed by normals of straight lines represented by the polar coordinate points and positive directions of transverse axes of a coordinate system of the map to which the polar coordinate points belong, and the point line distances are geometric vertical distances from an original point of the coordinate system of the map to which the polar coordinate points belong to the straight lines represented by the polar coordinate points.
4. The acquisition method according to claim 3, wherein the reference coordinate mapping space is a matrix space belonging to the Hough space, the reference rotation angle is the rotation angle of a polar coordinate point of the reference coordinate mapping space, and the reference point line distance is the point line distance of a polar coordinate point of the reference coordinate mapping space, which are all adaptively set according to an actual robot traversal environment;
wherein, the number of rows of the elements arranged in the reference coordinate mapping space is the number of polar coordinate points with the same reference rotation angle but different reference point line distances; the number of columns of the elements arranged in the reference coordinate mapping space is the number of polar coordinate points with the same reference point line distance but different reference rotation angles; the polar coordinate points of the reference coordinate mapping space are all discrete;
or the number of columns of the reference coordinate mapping space is the number of polar coordinate points with the same reference rotation angle but different reference point line distances; the number of lines of the reference coordinate mapping space is the number of polar coordinate points with the same reference point line distance but different reference rotation angles; the polar coordinate points of the reference coordinate mapping space are distributed discretely;
wherein the element of each row and each column in the reference coordinate mapping space is the number of straight lines represented by polar coordinate points at corresponding positions in the Hough space.
5. The method according to claim 4, wherein in the step 2, the method for obtaining the cross-correlation signal sequence of the local map straight line and the global map straight line by periodically convolving the second frequency statistics information and the first frequency statistics information with the trigonometric function of the reference rotation angle specifically includes:
setting the number of different reference point linear distances correspondingly existing in polar coordinate points in the reference coordinate mapping space as accumulation times, simultaneously setting the number of the polar coordinate points with the same reference point linear distance but different reference rotation angles in the reference coordinate mapping space as reference offset times, performing discrete convolution on a discrete sequence of the global map linear distribution square sum and a discrete sequence of the local map linear distribution square sum to obtain a cross-correlation signal sequence of a local map linear and a corresponding global map linear under the periodic extension action of different reference rotation angles, realizing the periodic extension and accumulation of second frequency statistic information and first frequency statistic information by using the periodicity of the reference rotation angles, and completing the convolution of the first frequency statistic information and the second frequency statistic information;
wherein the trigonometric periodicity of the reference rotation angle is: on the basis of a trigonometric function relational expression in Hough transform, for the same straight line in a global map or a local map, the same reference point line distance corresponds to at least one reference rotation angle; the number of accumulations is greater than 0.
6. The obtaining method according to claim 5, wherein the discrete convolution of the discrete sequence of the global map straight line distribution square sum and the discrete sequence of the local map straight line distribution square sum specifically includes:
after each element in the discrete sequence of the local map linear distribution square sum is subjected to translation operation with the translation variation amount being the corresponding reference rotation angle every time, multiplying the element by the corresponding element of the discrete sequence of the global map linear distribution square sum, and adding the element to obtain a convolution value under the current translation operation, wherein the convolution value is used as a discrete convolution value in the cross-correlation signal sequence; repeating the above steps until the reference rotation angles with the reference offset times are translated along the same direction, and obtaining all discrete convolution values in the cross-correlation signal sequence;
or after each element in the discrete sequence of the global map linear distribution square sum has a translation operation with a translation variation being a corresponding reference rotation angle, multiplying the element by a corresponding element in the discrete sequence of the local map linear distribution square sum, and adding the multiplied element to obtain a convolution value under the current translation operation, wherein the convolution value is used as a discrete convolution value in the cross-correlation signal sequence; and repeating the above steps until the reference rotation angles of which the number is the reference offset times are translated along the same direction, so as to obtain all discrete convolution values in the cross-correlation signal sequence.
7. The method of claim 6, wherein the step of computing local maxima from within the cross-correlation signal sequence comprises:
and in the reference coordinate mapping space, controlling the cross-correlation signal sequence to execute partial derivative operation along the direction of a variable axis where the reference rotation angle is located, when the first-order difference of the cross-correlation signal sequence is 0 and the second-order difference of the cross-correlation signal sequence is less than 0, obtaining at least one local maximum discrete convolution value from the cross-correlation signal sequence and determining the local maximum discrete convolution value as a local maximum, setting all the local maximum discrete convolution values as the discrete convolution values with the maximum degree of similarity between the straight line of the local map and the straight line of the global map, and simultaneously setting the rotation angles corresponding to all the local maximum discrete convolution values as the optimal rotation angles of the local map relative to the global map respectively, so as to convert the coordinates obtained by real-time calculation of the robot in the local map into the global map.
8. A chip for storing a program, the program being the acquisition method of any one of claims 1 to 7, for calculating and acquiring a cross-correlation signal sequence of a straight line of a local map and a straight line corresponding to a global map, calculating and acquiring a local maximum value from within the cross-correlation signal sequence, and setting a rotation angle corresponding to the local maximum value as an optimum rotation angle of the local map with respect to the global map.
9. A robot, characterized in that it is equipped with a chip according to claim 8 for obtaining the optimum rotation angle between a local map and a global map based on the cross-correlation of the straight line of the local map constructed on the fly and the straight line corresponding to the global map constructed in advance.
10. The robot of claim 9, further comprising a laser sensor, configured to obtain a two-dimensional laser point cloud from the laser map constructed by scanning, and extract a linear feature of the two-dimensional laser point cloud by using hough transform.
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