CN104035444A - Robot map establishing and storing method - Google Patents

Abstract

The invention discloses a method for constructing and storing a robot map, using an electronic compass and an odometer combined with GPS to realize robot positioning and coordinate calculation. Before creating map data, the robot first runs around the working area along the boundary line to establish map boundary data , and deduce the mapping relationship between the map data and the address of the storage unit, and then the robot runs in the area and establishes the internal map data. The format of the map data is: {X coordinate, Y coordinate, map grid attribute}. In order to facilitate data access, the data is mapped in the storage space according to certain rules.

Description

Robot map construction and storage method

technical field

The invention belongs to the technical field of robots and relates to a method for constructing map information.

Background technique

The mowing paths of most lawn mowing robots currently on the market are random, which leads to a slightly messy lawn after the mower has mowed the grass. At the same time, it takes more time to mow the grass to completely traverse the working area, resulting in The efficiency is low. Although the non-intelligent lawn mower can cut a flat lawn under manual operation, it is time-consuming and laborious. Therefore, the automatic positioning technology is combined with the lawn mower to realize the directional positioning of the lawn mower, and Using map construction technology to realize the robot's autonomous path planning, and finally cut out a smooth and regular lawn.

Contents of the invention

Technical problem: The present invention provides a robot map construction and storage method that realizes the automatic path planning of the mowing robot, can quickly complete the storage and reading of map data, and improves the efficiency of map construction and use.

Technical solution: The robot map construction and storage method of the present invention includes the following steps:

1) Set the base station coordinates as the starting coordinates of the robot (x ₀ , y ₀ ), and set the initial value of the maximum value x _max and the minimum value x _min of the x coordinate in the working area when the robot starts from the base station, The initial value of the maximum value y _max of the y coordinate and the initial value of the minimum value y _min are respectively x _max =x ₀ , x _min =x ₀ , y _max =y ₀ , y _max =y ₀ ;

2) Then the robot starts from the base station and returns to the base station after running along the boundary line of the working area for a week. During the operation, the maximum value x _max and the minimum value x _min of the x coordinate and the maximum value y _max of the y coordinate are continuously updated as follows , the minimum value y _min : at any time i, compare the size relationship between the coordinates (xi _, y _i ) and the last updated x _max , x _min , y _max , y _min , if x _i < x _min then x _min = x _i , otherwise the value of x _min remains unchanged, if x _i > x _max then x _max = x _i , otherwise the value of x _max remains unchanged, if y _i < y _min then y _min = y _i , otherwise y _min The value of remains unchanged, if y _i >y _max then y _max =y _i , otherwise the value of y _max remains unchanged, where (xi _, y _i ) is the coordinates of the robot at time i;

3) According to the x _max , x _min , y _max , and y _min that are finally updated after the robot runs along the boundary line for a week, determine the four coordinate points representing the maximum range of the boundary line as (x _a , y _max ), (x _b , y _min ), (x _max ,y _a ), (x _min ,y _b ), where x _a is the abscissa corresponding to y _max , x _b is the abscissa corresponding to y _min , and y _a is the abscissa corresponding to x _max , y _b is the abscissa corresponding to x _min ;

Then calculate the maximum difference of x coordinates X _max = x _max -x _min and the maximum difference of y coordinates Y _max = y _max - y _min in the working area according to the coordinates of the four characterizing the maximum range of the boundary line;

At the same time, calculate the center coordinates (x _c , y _c ) of the working area, where x _c =[(x _max +x _min )2], y _c =[(y _max +y _min )/2];

4) Calculate the parameter n representing the size of the map according to the following formula: n=[X/2Δ]+1;

Among them, Δ is the side length of the square map grid, and X is the larger value of the maximum difference X _max of x coordinates and the maximum difference Y _max of y coordinates within the maximum range of the working area, that is, when X _max ≥ Y _max , X=X _max , and X _max < Y _max , X = Y _max ;

5) Realize the mapping between the map data and the address of the storage unit according to the parameter n representing the size of the map. The specific method is: store the data of all map grids in the storage unit in the format of {xi _, y _i , map grid attribute} , where each map raster data occupies a storage unit with a size of m bytes, the coordinates of the map center (x _c , y _c ) are stored in the starting address of the storage unit, and the offset between the starting address and the minimum address in the storage unit The displacement is k, k≥0, and the storage location of other coordinates ( _xi , y _i ) is determined according to the offset between the coordinate and the minimum address obtained from the following formula:

M(2n+1)m+Nm+k;

Among them, M and N are determined by the following methods:

L ₁ =(x _i -x _c )/Δ, L ₂ =(y _i -y _c )/Δ;

When L ₁ >0, M=2|L ₁ |, when L ₁ <0, M=2|L ₁ |-1;

When L ₂ >0, N=2|L ₂ |, and when L ₂ <0, N=2|L ₂ |−1.

In the preferred solution of the method of the present invention, the map grid attribute in step 5) is composed of various elements related to the robot map, including attributes used to characterize the environment in the map grid and whether the robot passes through the map grid Attributes.

The method of this system can complete the creation and storage of the robot map, so as to realize the autonomous positioning and navigation of the robot. When creating the map data, the robot first runs around the working area, calculates the data of the map boundary according to the coordinate values calculated by the sensor, and Generate the mapping relationship between the map data and the address of the storage unit, and then the robot establishes the internal map data in the boundary area, and updates the map attributes in the data storage; after the map coordinates are established, the robot runs according to the map, and the robot reads the current coordinates after positioning And the data of the adjacent four coordinates, according to the forward direction and the grid characteristics of the adjacent coordinates to judge the next action and running direction of the robot. When the working voltage of the robot is insufficient, the robot automatically stores the current coordinates and heading and returns to the base station for charging. After charging, read the coordinates and heading recorded last time, and automatically plan the optimal path to reach the coordinate position, and then continue to work. In the method of the present invention, the robot constructs the map data through the positioning and navigation sensor, and maps the map data with the address of the storage unit one by one, so as to facilitate the storage and reading of a large amount of map data.

Beneficial effect: compared with the prior art, the present invention has the following advantages:

The present invention can well realize the construction and storage of map data. In this method, the map data of the robot is in the form of a grid, and the attributes of the grid map can be used to describe the map environment well. In view of the large amount of data of the grid map , when building a map, the robot starts from the base station and runs around the boundary line. During the operation, the current coordinates are continuously calculated. After running for a week, four important characteristic coordinate points representing the size of the map are obtained, which are the maximum and maximum abscissa coordinates of the map and The two smallest points, as well as the two points with the largest and smallest vertical coordinates, and then independently generate the map data and storage unit address mapping relationship according to these four characteristic coordinate points, and closely combine the map data with the storage unit through the establishment of address mapping , not only can realize the fast reading and storage of map data, but also adopt the method of parameter adjustment to make the method applicable under different map sizes, so that the robot can run in any working environment.

After the map data is established by this method, the map data is unique, that is, the content of the storage unit corresponds to the coordinates of the entire environment map. When the robot needs to call the map during operation, it only needs to calculate the current coordinates corresponding to the coordinates in the map. The map data can be quickly read through parameters, which can ensure that the robot has a clear understanding of the environmental map.

Description of drawings

Figure 1 is a schematic diagram of a grid map; the map is represented in the form of a grid, and the numbers in each grid point represent the attributes in the grid;

Figure 2 is a diagram of running along the boundary; the size and parameters of the map are determined in this way;

FIG. 3 is a storage unit address mapping diagram; showing the mapping relationship between map data and storage unit addresses.

Detailed ways

The technical solution of the present invention will be further described in detail below.

In the method of the present invention, the robot is mainly a mowing robot, which is a four-wheeled robot, and the rear two wheels are differential wheels, which can realize the movement of the robot in any direction. The robot is powered by a lithium battery. Work autonomously within the range. The area is artificially delineated by the boundary line, which can be of any shape and size. The boundary line is an electrified wire, and there is a specific boundary signal in the wire. The boundary signal is sent by the charging base station, and the base station can provide charging for the robot. When the power of the robot is low, it will automatically return to the base station along the boundary line to charge, and it will automatically go out of the base station to work after it is fully charged. The robot will recognize that the robot is inside the boundary line by receiving the electromagnetic signal sent by the boundary line through the induction coil installed inside the robot. or external. At the same time, the robot can also identify external obstacles through the Hall sensor. When the robot is lifted or encounters an obstacle, the Hall sensor will send a signal, thereby realizing the environment recognition of the robot.

When building a map, the robot can use the electronic compass, odometer, and GPS to realize autonomous positioning and navigation, measure the heading angle through the electronic compass, and then calculate the relative coordinates of the robot based on the odometer dead position, and then perform absolute positioning and error based on the GPS coordinates Eliminate, and finally get the coordinates (x _k , y _k ) of the robot at any time. The specific calculation method is as follows:

The mowing robot can be regarded as running on a certain two-dimensional plane during operation, and constructs a local plane Cartesian coordinate system. Let x be the due east direction of the local plane Cartesian coordinate system, and y be the true north of the local plane Cartesian coordinate system. direction. Let the coordinates of the position R ₀ of the lawn mowing robot at the initial time t ₀ be (x ₀ , y ₀ ), and the heading angle be θ ₀ . According to the running distance and heading angle during the time period t ₁ -t ₀ , the position at the time t ₁ can be calculated. coordinate location.

Let the distance between R ₀ and R ₁ be S ₀ , which is measured by the odometer on the robot. When t ₁ -t ₀ is small enough, the robot is considered to be moving in a straight line, so the coordinates of R ₁ can be obtained as:

x ₁ ＝x ₀ +S ₀ cos θ ₀

y ₁ ＝y ₀ +S ₀ sin θ ₀

According to the above formula recursion, the coordinates of _R2 can be obtained as:

x ₂ ＝x ₁ +S ₁ cos θ ₁ ＝x ₀ +S ₀ cos θ ₀ +S ₁ cos θ ₁

y ₂ =y ₁ +S ₁ sin θ ₁ =y ₀ +S ₀ sin θ ₀ +S ₁ sin θ ₁

According to this rule, the coordinates of the position R _k at any time t _k can be deduced as:

${\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; x</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; cos</span>}{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}$

${\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; k</span>}}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; the\; y</span>}}_{\mathrm{<span\; class="notranslate">\; 0</span>}}<span\; class="notranslate">\; +</span>\underset{\mathrm{<span\; class="notranslate">\; i</span>}<span\; class="notranslate">\; =</span>\mathrm{<span\; class="notranslate">\; 0</span>}}{\overset{\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; \&Sigma;</span>}}}{\mathrm{<span\; class="notranslate">\; S</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}\mathrm{<span\; class="notranslate">\; sin</span>}{\mathrm{<span\; class="notranslate">\; \&theta;</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}$

Set the coordinates of the base station as the initial coordinates of the robot (x ₀ , y ₀ ), and set the initial value of the maximum value x _max of the x coordinate, the initial value of the minimum value x _min , and the y coordinate of the robot when it starts from the base station. The initial value of the maximum value y _max and the initial value of the minimum value y _min are respectively x _max = x ₀ , x _min = x ₀ , y _max = y ₀ , y _max = y ₀ ; then the robot starts from the base station, along The boundary line of the working area returns to the base station after a week of operation. During the operation, the maximum value x _max and minimum value x _min of the x coordinate, and the maximum value y _max and minimum value y _min of the y coordinate are continuously updated as follows:

At any time i, compare the relationship between the coordinates ( _xi , y _i ) and the last updated x _max , x _min , y _max , and y _min . If x _i < x _min , then x _min = x _i , otherwise x _min The value remains unchanged, if x _i > x _max then x _max = x _i , otherwise the value of x _max remains unchanged, if y _i < y _min then y _min = y _i , otherwise the value of y _min remains unchanged, If y _i > y _max , then y _max = y _i , otherwise the value of y _max remains unchanged, where ( _xi , y _i ) is the coordinates of the robot at time i; according to the final update obtained after the robot runs along the boundary line for one week x _max , x _min , y _max , y _min , the four coordinate points to determine the maximum range of the boundary line are (x _a ,y _max ), (x _b ,y _min ), (x _max ,y _a ), ( x _min ,y _b ), where x _a is the abscissa corresponding to y _max , x _b is the abscissa corresponding to y _min , y _a is the abscissa corresponding to x _max , y _b is the abscissa corresponding to x _min ; then according to These four coordinates representing the maximum range of the boundary line calculate the maximum difference of x coordinates X _max = x _max -x _min and the maximum difference of y coordinates Y _max = y _max -y _min in the working area; at the same time, calculate the center of the working area Coordinates (x _c , y _c ), where, x _c =[(x _max +x _min )2], y _c =[(y _max +y _min )2]; then calculate the parameters representing the size of the map according to the following formula n: n=[X/2Δ]+1; the map grid in this method is a square grid, that is, the length and width of each map grid are the same, and the entire environmental map is divided into multiple adjacent square grids Grid square, the side length of the square map grid is Δ, X is the larger value of the maximum difference X _max of x coordinates and the maximum difference Y _max of y coordinates within the maximum range of the working area, that is, when X _max ≥ Y _max , X =X _max , and when X _max <Y _max , X=Y _max ; realize the mapping between map _data and storage unit addresses according to the parameter n representing the size of the map. y _i , the format of the map raster attribute} is stored in the storage unit, and each map raster data occupies a storage unit space of m bytes, where the map raster attribute can be composed of various elements related to the robot map, including It is used to characterize the attributes of the environment in the map grid, such as using numbers 0, 1, 2... to indicate that there are trees, boundary lines, charging base stations and other foreign objects inside the map grid; it also includes whether the robot passes through this The attribute of the map grid, which is used to realize the map traversal of the robot, The coordinates of the center of the map (x _c , y _c ) are stored in the starting address of the storage unit, and the offset between the starting address and the minimum address in the storage unit is k, k≥0, other coordinates (xi , y _{i )} The storage location of is determined according to the offset between the coordinate and the minimum address obtained by the following formula:

M(2n+1)m+Nm+k;

Among them, M and N are determined by the following methods:

L ₁ =(x _i -x _c )/Δ, L ₂ =(y _i -y _c )/Δ;

When L ₁ >0, M=2|L ₁ |, when L ₁ <0, M=2|L ₁ |-1;

When L ₂ >0, N=2|L ₂ |, and when L ₂ <0, N=2|L ₂ |−1.

Then the mowing robot continuously updates the map grid attributes in the corresponding coordinates of the map data, and quickly stores the data related to the attributes at any coordinates into the corresponding storage unit to realize the establishment of the entire map.

After the map is established, the mowing robot also calculates the current coordinate position according to the electronic compass, odometer and GPS data when it is running. When the robot runs to the coordinates (x _k , y _k ), it only needs to calculate the map at this time Corresponding parameter i and j in can get the storage unit address corresponding thereto, then read out the content representing the map attribute of m bytes behind the address, and read directly from the corresponding map storage unit at the same time The 4 coordinates adjacent to the coordinates, and then according to the grid properties of the coordinates combined with the program algorithm to realize the control of its own motion state, during the operation, the information measured by the Hall sensor and the boundary sensor is used to judge whether the constructed map is correct. If found Update the stored map data when the current map is different from the stored map.

The above are only preferred embodiments of the present invention, and it should be pointed out that for those of ordinary skill in the art, without departing from the principle of the present invention, some conceivable improvements and equivalent replacements can also be made, which are essential to the present invention. The technical solutions after the claims are improved and replaced by equivalents all fall into the protection scope of the present invention.

Claims (2)

1. A robot map builds storage method, is characterized in that, the method comprises the following steps: 1) Set the base station coordinates as the starting coordinates of the robot (x ₀ , y ₀ ), and set the initial value of the maximum value x _max and the minimum value x _min of the x coordinate in the working area when the robot starts from the base station, The initial value of the maximum value y _max of the y coordinate and the initial value of the minimum value y _min are respectively x _max =x ₀ , x _min =x ₀ , y _max =y ₀ , y _max =y ₀ ; 2) Then the robot starts from the base station and returns to the base station after running along the boundary line of the working area for a week. During the operation, the maximum value x _max and the minimum value x _min of the x coordinate and the maximum value y _max of the y coordinate are continuously updated as follows , minimum value y _min : At any time i, compare the relationship between the coordinates ( _xi , y _i ) and the last updated x _max , x _min , y _max , and y _min . If x _i < x _min , then x _min = x _i , otherwise x _min The value remains unchanged, if x _i > x _max then x _max = x _i , otherwise the value of x _max remains unchanged, if y _i < y _min then y _min = y _i , otherwise the value of y _min remains unchanged, If y _i > y _max , then y _max = y _i , otherwise the value of y _max remains unchanged, where ( _xi , y _i ) is the coordinates of the robot at time i; 3) According to the x _max , x _min , y _max , and y _min that are finally updated after the robot runs along the boundary line for a week, determine the four coordinate points representing the maximum range of the boundary line as (x _a , y _max ), (x _b , y _min ), (x _max ,y _a ), (x _min ,y _b ), where x _a is the abscissa corresponding to y _max , x _b is the abscissa corresponding to y _min , and y _a is the abscissa corresponding to x _max , y _b is the abscissa corresponding to x _min ; Then calculate the maximum difference of x coordinates X _max = x _max -x _min and the maximum difference of y coordinates Y _max = y _max - y _min in the working area according to the coordinates of the four characterizing the maximum range of the boundary line; At the same time, calculate the center coordinates (x _c , y _c ) of the working area, where x _c =[(x _max +x _min )2], y _c =[(y _max +y _min )2]; 4) Calculate the parameter n representing the size of the map according to the following formula: n=[X/2Δ]+1; Among them, Δ is the side length of the square map grid, and X is the larger value of the maximum difference X _max of x coordinates and the maximum difference Y _max of y coordinates within the maximum range of the working area, that is, when X _max ≥ Y _max , X=X _max , and X _max < Y _max , X = Y _max ; 5) Realize the mapping between the map data and the address of the storage unit according to the parameter n representing the size of the map, the specific method is: Store all the map grid data in the storage unit in the format of { _xi , y _i , map grid attribute}, where each map grid data occupies a storage unit size of m bytes, and the map center coordinates (x _c , y _c ) are stored in the starting address of the storage unit, the offset between the starting address and the minimum address in the storage unit is k, k≥0, and the storage positions of other coordinates (xi _, y _i ) are according to the following Determine the offset between the coordinate and the minimum address obtained by the formula: M(2n+1)m+Nm+k; Among them, M and N are determined by the following methods: L ₁ =(x _i -x _c )/Δ, L ₂ =(y _i -y _c )/Δ; When L ₁ >0, M=2|L ₁ |, when L ₁ <0, M=2|L ₁ |-1; When L ₂ >0, N=2|L ₂ |, and when L ₂ <0, N=2|L ₂ |−1. 2. The robot map construction storage method according to claim 1, characterized in that, the map grid attribute in the step 5) is composed of a variety of elements related to the robot map, including elements used to characterize the map grid An attribute of the environment and an attribute that characterizes whether the robot has passed through this map grid.