CN104035444A - Robot map establishing and storing method - Google Patents

Abstract

The invention discloses a robot map establishing and storing method. The method comprises the steps that an electronic compass and a speedometer are used for achieving positioning and coordinate calculation of a robot combined with a GPS, before map data are established, the robot operates a circle around a working area along a boundary first, map boundary data are established, the mapping relation of the map data and the address of a storage unit is calculated, then the robot operates in the area, and then internal map data are established. The format of the map data is {X coordinate, Y coordinate and map grid attributes}, and in order to facilitate data storage, the data are mapped into storage space according to a certain rule.

Description

Robot map structuring storage means

Technical field

The invention belongs to Robotics field, relate to a kind of method that builds cartographic information.

Background technology

The mowing path of most of grass-removing robots is in the market all random, therefore the lawn that causes mower to remove after grass shows slightly in disorder, mow to realize simultaneously and need to spend the more time to the traversal completely of perform region, cause efficiency lower, although but not intellectual mower can cut out smooth lawn under artificial operation, but relatively waste time and energy, therefore automatic positioning technology is combined to realize the orientation location of mower with mower, and use map structuring technology to realize the autonomous path planning of robot, finally cut out the lawn of smooth rule.

Summary of the invention

Technical matters: the invention provides a kind of automatic path planning of realizing grass-removing robot, can complete fast map datum storage and read, improve the robot map structuring storage means of the efficiency of map structuring and use.

Technical scheme: robot of the present invention map structuring and storage means, comprise the following steps:

1) base station coordinates is made as to the origin coordinates (x of robot ₀, y ₀), and while setting robot from base station, the maximal value x of x coordinate in perform region _maxinitial value, minimum value x _mininitial value, the maximal value y of y coordinate _maxinitial value, minimum value y _mininitial value be respectively x _max=x ₀, x _min=x ₀, y _max=y ₀, y _max=y ₀;

2) then robot, from base station, returns to base station after moving one week along the boundary line of perform region, in operational process, constantly updates in the following manner the maximal value x of x coordinate _max, minimum value x _min, the maximal value y of y coordinate _max, minimum value y _min: at any i, constantly distinguish reduced coordinates (x _i, y _i) and the last x upgrading _max, x _min, y _max, y _minmagnitude relationship, if x _i< x _minx _min=x _i, otherwise x _minvalue remain unchanged, if x _i> x _maxx _max=x _i, otherwise x _maxvalue remain unchanged, if y _i< y _miny _min=y _i, otherwise y _minvalue remain unchanged, if y _i> y _maxy _max=y _i, otherwise y _maxvalue remain unchanged, wherein, (x _i, y _i) be the coordinate of i robot during the moment;

3) according to the Robot boundary line operation x that after a week, final updated obtains _max, x _min, y _max, y _min, determine that four coordinate points that characterize boundary line maximum magnitude are respectively (x _a, y _max), (x _b, y _min), (x _max, y _a), (x _min, y _b), x wherein _afor y _maxcorresponding horizontal ordinate, x _bfor y _mincorresponding horizontal ordinate, y _afor x _maxcorresponding horizontal ordinate, y _bfor x _mincorresponding horizontal ordinate;

Then according to these four coordinates that characterize boundary line maximum magnitude, calculate x coordinate maximum difference X in perform region _max=x _max-x _minwith y coordinate maximum difference Y _max=y _max-y _min;

Calculate the centre coordinate (x of perform region simultaneously _c, y _c), wherein, x _c=[(x _max+ x _min) 2], y _c=[(y _max+ y _min)/2];

4) according to following formula, calculate the parameter n:n=[X/2 Δ that characterizes map size]+1;

Wherein Δ is the length of side of square map grid, and X is x coordinate maximum difference X in the maximum magnitude of perform region _maxwith y coordinate maximum difference Y _maxhigher value, work as X _max>=Y _maxtime, X=X _max, and X _max< Y _maxtime, X=Y _max;

5) according to the parameter n that characterizes map size, realize the mapping of map datum and memory unit address, concrete grammar is: by the data of all map grids according to { x _i, y _i, map grid attribute } form be stored in storage unit, wherein each map raster data takies storage unit space size for m byte, map center coordinate (x _c, y _c) being stored in the start address of storage unit, this start address is k with the side-play amount of lowest address in storage unit, k>=0, other coordinates (x _i, y _i) memory location this coordinate of trying to achieve according to following formula and the side-play amount of lowest address determine:

M(2n+1)m+Nm+k；

Wherein, M, N are determined by following methods:

L ₁＝(x _i-x _c)/Δ，L ₂＝(y _i-y _c)/Δ；

Work as L ₁during >0, M=2|L ₁|, work as L ₁during <0, M=2|L ₁|-1;

Work as L ₂during >0, N=2|L ₂|, work as L ₂during <0, N=2|L ₂|-1.

In the preferred version of the inventive method, step 5) the map grid attribute in is comprised of the multiple element relevant to robot map, comprises for characterizing the attribute of the environment in map grid and characterizing the attribute whether robot passes through this map grid.

The method of native system can complete establishment and the storage of robot map, thereby realize the autonomous location navigation of robot, when creating map datum, robot is first around perform region operation one circle, the coordinate figure calculating according to sensor calculates the data of map boundary line, and generate the mapping relations of map datum and memory unit address, then robot sets up internal map data in borderline region, and upgrades the map attribute in data-carrier store; After map reference is set up, robot moves according to map, robot is by reading the data of current coordinate and adjacent four coordinates after locating, according to the lattice characteristic of working direction and adjacent coordinates, judge next step action and the traffic direction of robot, when robot operating voltage is not enough, base station charging is also returned in the current coordinate of robot autostore and course, complete coordinate and the course of after charging, reading last registration, and automatically plan that optimal path arrives coordinate position, then works on.In the inventive method, robot constructs map datum by location navigation sensor, and map datum and memory unit address are shone upon one by one, the storage of convenient diagram data in large quantities with read.

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

The present invention can realize structure and the storage of map datum well, in the method, robot map datum is grid, use the attribute of grating map can describe well map environment, in view of the larger reason of the data volume of grating map, when setting up map, robot is from base station, along moving around boundary line, in operational process, constantly calculate current coordinate, in operation, after one week, obtain four key character coordinate points that characterize map size, be respectively two minimum and maximum points of map horizontal ordinate, and two minimum and maximum points of ordinate, then according to autonomous map datum and the memory unit address mapping relations of generating of these four characteristic coordinates points, map datum and storage unit are combined closely in the foundation of shining upon by address, not only can realize reading fast and storing of map datum, the mode that simultaneously adopts parameter to regulate can make the method all can be suitable under different map sizes, robot can be moved under any working environment.

By the method, set up after map datum, map datum has uniqueness, the content that is storage unit is corresponding one by one with whole environmental map coordinate, while needing invocation map in robot operational process, only need to calculate current coordinate can read map datum fast corresponding to the parameter in mapping graph, can guarantee that there is a cognition very clearly in robot to environmental map.

Accompanying drawing explanation

Fig. 1 is grating map schematic diagram; Map is represented to the attribute in this grid of the digitized representation in each lattice point by the form of grid;

Fig. 2 is along border service chart; By which, determine size and the parameter of map;

Fig. 3 is memory unit address mapping graph; The mapping relations that represent map datum and memory unit address.

Embodiment

Below technical solution of the present invention is further elaborated.

In the inventive method, described robot is mainly grass-removing robot, it is a kind of four-wheeled mobile robot, rear two-wheeled is differential gear, can realize the motion of robot any direction, robot is by lithium battery power supply, utonomous working in certain regional extent, this region is artificially drawn a circle to approve by boundary line, can have any shape and size, boundary line is electrified wire, in wire, be connected with specific sideband signal, this sideband signal is sent by the base station of charging, base station can provide to robot the source of charging simultaneously, when robot electric weight is not enough, can automatically along boundary line, return to base station charging, after being full of electricity, automatically go out base station work, robot receives the electromagnetic signal of sending boundary line and comes inside or the outside of recognition machine people in boundary line by being arranged on the inductive coil of robot interior.Meanwhile, this robot can also identify outer barrie thing by Hall element, and when robot is lifted or run into barrier, Hall element can send signal, thereby realizes the environment identification of robot.

When setting up map, robot can use electronic compass, odometer, GPS to realize autonomous location navigation, by electronic compass, measure course angle, then in conjunction with odometer dead reckoning, go out the relative coordinate of robot, according to the coordinate of GPS, carry out absolute fix and error concealment again, finally obtain the coordinate (x of any time of robot _k, y _k).Concrete projectional technique is as follows:

Grass-removing robot can be thought the operation at certain two dimensional surface when operation, builds a local plane right-angle coordinate, and establishing x is the due east direction of part plan rectangular coordinate system, and y is the direct north of part plan rectangular coordinate system.If grass-removing robot initial time t ₀position R ₀coordinate is (x ₀, y ₀), course angle is θ ₀, according to t ₁-t ₀range ability in time period and course angle can be extrapolated t ₁coordinate position constantly.

If R ₀and R ₁between distance be S ₀, the odometer in Gai Liangyou robot measures, and works as t ₁-t ₀within enough hour, think that robot does rectilinear motion, therefore can obtain R ₁coordinate be:

x ₁＝x ₀+S ₀?cos?θ ₀

y ₁＝y ₀+S ₀?sin?θ ₀

According to above formula recursion, can obtain R ₂coordinate be:

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 recursion, can extrapolate any time t _kposition R _kcoordinate be:

$x_k=x_0+\underset{i=0}{\overset{k-1}{\mathrm{\&Sigma;}}}{S}_i\cos {\mathrm{\&theta;}}_i$

$y_k=y_0+\underset{i=0}{\overset{k-1}{\mathrm{\&Sigma;}}}{S}_i\sin {\mathrm{\&theta;}}_i$

Base station coordinates is made as to the origin coordinates (x of robot ₀, y ₀), and while setting robot from base station, the maximal value x of x coordinate in perform region _maxinitial value, minimum value x _mininitial value, the maximal value y of y coordinate _maxinitial value, minimum value y _mininitial value be respectively x _max=x ₀, x _min=x ₀, y _max=y ₀, y _max=y ₀; Then robot is from base station, returns to base station after moving one week along the boundary line of perform region, in operational process, constantly updates in the following manner the maximal value x of x coordinate _max, minimum value x _min, the maximal value y of y coordinate _max, minimum value y _min:

At any i, constantly distinguish reduced coordinates (x _i, y _i) and the last x upgrading _max, x _min, y _max, y _minmagnitude relationship, if x _i< x _minx _min=x _i, otherwise x _minvalue remain unchanged, if x _i> x _maxx _max=x _i, otherwise x _maxvalue remain unchanged, if y _i< y _miny _min=y _i, otherwise y _minvalue remain unchanged, if y _i> y _maxy _max=y _i, otherwise y _maxvalue remain unchanged, wherein, (x _i, y _i) be the coordinate of i robot during the moment; According to the Robot boundary line operation x that after a week, final updated obtains _max, x _min, y _max, y _min, determine that four coordinate points that characterize boundary line maximum magnitude are respectively (x _a, y _max), (x _b, y _min), (x _max, y _a), (x _min, y _b), x wherein _afor y _maxcorresponding horizontal ordinate, x _bfor y _mincorresponding horizontal ordinate, y _afor x _maxcorresponding horizontal ordinate, y _bfor x _mincorresponding horizontal ordinate; Then according to these four coordinates that characterize boundary line maximum magnitude, calculate x coordinate maximum difference X in perform region _max=x _max-x _minwith y coordinate maximum difference Y _max=y _max-y _min; Calculate the centre coordinate (x of perform region simultaneously _c, y _c), wherein, x _c=[(x _max+ x _min) 2], y _c=[(y _max+ y _min) 2]; Then according to following formula, calculate the parameter n:n=[X/2 Δ that characterizes map size]+1; Map grid in this method is square grid, be that the length of each map grid is with wide all identical, whole environmental map is divided into a plurality of adjacent square grid squares, and the length of side of square map grid is Δ, and X is x coordinate maximum difference X in the maximum magnitude of perform region _maxwith y coordinate maximum difference Y _maxhigher value, work as X _max>=Y _maxtime, X=X _max, and X _max< Y _maxtime, X=Y _max; According to the parameter n that characterizes map size, realize the mapping of map datum and memory unit address, concrete grammar is: by the data of all map grids according to { x _i, y _imap grid attribute } form be stored in storage unit, each map raster data takies storage unit space size for m byte, wherein map grid attribute can be comprised of the multiple element relevant to robot map, comprise for characterizing the attribute of the environment in map grid, for example use numeral 0,1,2 ... form represent that respectively there are the foreign objects such as trees, boundary line, charging base station this map grid inside; Also comprise and characterize the attribute whether robot passes through this map grid, for realizing the map traversal of robot, map center coordinate (x _c, y _c) being stored in the start address of storage unit, this start address is k with the side-play amount of lowest address in storage unit, k>=0, other coordinates (x _i, y _i) memory location this coordinate of trying to achieve according to following formula and the side-play amount of lowest address determine:

M(2n+1)m+Nm+k；

Wherein, M, N are determined by following methods:

L ₁＝(x _i-x _c)/Δ，L ₂＝(y _i-y _c)/Δ；

Work as L ₁during >0, M=2|L ₁|, work as L ₁during <0, M=2|L ₁|-1;

Work as L ₂during >0, N=2|L ₂|, work as L ₂during <0, N=2|L ₂|-1.

Then grass-removing robot is constantly updated the map grid attribute in map datum corresponding coordinate, and data relevant to attribute under arbitrary coordinate are deposited in corresponding storage unit fast, realizes the foundation of whole map.

After map is set up, during grass-removing robot operation, according to electronic compass, odometer and gps data, extrapolate current place coordinate position equally, when robot runs to coordinate (x _k, y _k) while locating, only need calculate the memory unit address that parameter i corresponding in mapping graph now and j can obtain answering in contrast, then read the content that represents map attribute of m byte behind this address, from corresponding map storage unit, directly read again 4 coordinates adjacent with this coordinate simultaneously, then according to the grid attribute of coordinate, in conjunction with programmed algorithm, realizing displacement state controls, the information of measuring by Hall element and border sensor in operational process judges that whether the map of structure is correct, if find to upgrade when the map of current map and storage is different the map datum of storage.

Below be only the preferred embodiment of the present invention; be noted that for those skilled in the art; under the premise without departing from the principles of the invention; can also make the some improvement that can expect and be equal to replacement; these improve the claims in the present invention and are equal to the technical scheme after replacement, all fall into protection scope of the present invention.

Claims (2)

1.Yi Zhong robot map structuring storage means, is characterized in that, the method comprises the following steps:

1) base station coordinates is made as to the origin coordinates (x of robot ₀, y ₀), and while setting robot from base station, the maximal value x of x coordinate in perform region _maxinitial value, minimum value x _mininitial value, the maximal value y of y coordinate _maxinitial value, minimum value y _mininitial value be respectively x _max=x ₀, x _min=x ₀, y _max=y ₀, y _max=y ₀;

2) then robot, from base station, returns to base station after moving one week along the boundary line of perform region, in operational process, constantly updates in the following manner the maximal value x of x coordinate _max, minimum value x _min, the maximal value y of y coordinate _max, minimum value y _min:

At any i, constantly distinguish reduced coordinates (x _i, y _i) and the last x upgrading _max, x _min, y _max, y _minmagnitude relationship, if x _i< x _minx _min=x _i, otherwise x _minvalue remain unchanged, if x _i> x _maxx _max=x _i, otherwise x _maxvalue remain unchanged, if y _i< y _miny _min=y _i, otherwise y _minvalue remain unchanged, if y _i> y _maxy _max=y _i, otherwise y _maxvalue remain unchanged, wherein, (x _i, y _i) be the coordinate of i robot during the moment;

3) according to the Robot boundary line operation x that after a week, final updated obtains _max, x _min, y _max, y _min, determine that four coordinate points that characterize boundary line maximum magnitude are respectively (x _a, y _max), (x _b, y _min), (x _max, y _a), (x _min, y _b), x wherein _afor y _maxcorresponding horizontal ordinate, x _bfor y _mincorresponding horizontal ordinate, y _afor x _maxcorresponding horizontal ordinate, y _bfor x _mincorresponding horizontal ordinate;

Then according to these four coordinates that characterize boundary line maximum magnitude, calculate x coordinate maximum difference X in perform region _max=x _max-x _minwith y coordinate maximum difference Y _max=y _max-y _min;

Calculate the centre coordinate (x of perform region simultaneously _c, y _c), wherein, x _c=[(x _max+ x _min) 2], y _c=[(y _max+ y _min) 2];

4) according to following formula, calculate the parameter n that characterizes map size:

n＝[X/2Δ]+1；

Wherein Δ is the length of side of square map grid, and X is x coordinate maximum difference X in the maximum magnitude of perform region _maxwith y coordinate maximum difference Y _maxhigher value, work as X _max>=Y _maxtime, X=X _max, and X _max< Y _maxtime, X=Y _max;

5) according to the parameter n that characterizes map size, realize the mapping of map datum and memory unit address, concrete grammar is:

By the data of all map grids according to { x _i, y _i, map grid attribute } form be stored in storage unit, wherein each map raster data takies storage unit space size for m byte, map center coordinate (x _c, y _c) being stored in the start address of storage unit, this start address is k with the side-play amount of lowest address in storage unit, k>=0, other coordinates (x _i, y _i) memory location this coordinate of trying to achieve according to following formula and the side-play amount of lowest address determine:

M(2n+1)m+Nm+k；

Wherein, M, N are determined by following methods:

L ₁＝(x _i-x _c)/Δ，L ₂＝(y _i-y _c)/Δ；

Work as L ₁during >0, M=2|L ₁|, work as L ₁during <0, M=2|L ₁|-1;

Work as L ₂during >0, N=2|L ₂|, work as L ₂during <0, N=2|L ₂|-1.

2. robot according to claim 1 map structuring storage means, it is characterized in that, described step 5) the map grid attribute in is comprised of the multiple element relevant to robot map, comprises for characterizing the attribute of the environment in map grid and characterizing the attribute whether robot passes through this map grid.