CN105184243A - Environment characteristic expression and identification method based on three dimensional grid map - Google Patents

Abstract

The invention discloses an environment characteristic expression and identification method based on a three-dimensional grid map, comprising steps of, for the established three-dimension grid map, performing characteristic analysis on an obstacle in the three-dimension grid map and the circumferential blank space, extracting a grid characteristic expression method which is easy to store and calculate as a basis for environment characteristic identification. The method is applicable to the environment identification of the robot, path planning of the robot and autonomous motion, and supports the game application of the practical environment of the robot and robot cleaning.

Description

A kind of environmental characteristic based on 3 d grid map represents and knowledge method for distinguishing

Technical field

The present invention relates to the discrete orthogonal transform technology, particularly robot such as artificial intelligence, pattern-recognition and Fourier convert, Walsh converts to the three-dimensional environment modeling of complex environment and knowledge method for distinguishing, be applied to Context awareness and the autokinetic movement aspect of robot.

Background technology

Along with industrial machine man-based development in recent years, drive the turn up gradually of service robot industry, Intelligent hardware field simultaneously from 2014 also starts projection, according to the statistics of alliance of international robot, within 2015, service robot sales volume will reach 8,500,000,000 dollars, and keep 20% ~ 30% higher rate of growth, in Intelligent hardware field, according to Ai Rui research, within 2014, global Intelligent hardware installation amount reaches 6,000,000,000, and estimating 2017 will more than 14,000,000,000.

In the behind of market high speed development, problem is obvious equally, the potentiality in market are also excavated out far away on the one hand, on the other hand, robot and Intelligent hardware enter feature modeling and the recognition technology that service industry also also exists some technological difficulties, particularly three-dimensional environment, and such as robot enters in actual home environment, carry out Context awareness and autonomous safely etc., all also have certain technological difficulties at present.

Goal of the invention

Fundamental purpose of the present invention is exactly solve to represent and identification problem based on the environmental characteristic after the environmental modeling of 3 d grid map, it provides a kind of method, make the environmental characteristic based on 3 d grid map, be convenient to store and calculate, thus reach the convenient object identified, for other practical applications provide technical support.Can be, but not limited to be applied in the robot game towards family and robot cleaner aspect.

Technical scheme

The object of the present invention is achieved like this: by relevant device and algorithm, such as three-dimensional laser radar etc., obtain the 3 d grid cartographic information of actual environment, system is represented through environmental characteristic, calculate and store the feature of volume elements in 3 d grid map, after the information setting required target volume elements, by environmental characteristic recognition system, in 3 d grid map, match all required candidate's volume elements.It comprises the following steps:

(1) in environmental characteristic expression system, consider the convenience of calculating, we set one affects distance delta, and namely barrier volume elements is to the coverage of periphery volume elements, and σ can be but be not limited to Euclidean distance, Manhattan (Manhattan) distance etc.Simultaneously also in order to convenience of calculation, volume elements x [δ on influenced all average discrete to eight driftage faces of volume elements x ₀, δ _π/4, δ _pi/2, δ _{3 π/4}, δ _π, δ _{5 π/4}, δ _{3 pi/2s}, δ _{7 π/4}], then each driftage face δ _iin to affect component all discrete to driftage face δ _i[η on eight interior angles of pitch ₀, η _π/12, η _π/4, η _{5 π/12}, η _{7 π/12}, η _{3 π/4}, η _{11 π/12}, η _π], form suffered influence matrix f (x) of volume elements x, and the eigenmatrix of suffered influence matrix f (x) of calculated body element x and characteristic spectrum, provide the computing method of two kinds of eigenmatrixes and characteristic spectrum here,

(2) in environmental characteristic expression system, each element of the influence matrix of each idle volume elements is initialized as 0, analyze the impact of each barrier volume elements on all volume elements in σ distance one by one, such as, in the process analyzed, the yaw angle of the relative volume elements x of barrier volume elements ξ is θ, luffing angle is β, distance is d, d≤σ, then barrier volume elements ξ to the influence function of volume elements x can be but be not limited to f (x _{β, θ, d})=1/d, if θ is just on a certain driftage face of volume elements x, then directly to superpose on this driftage face, if θ is between certain two driftage face, such as θ ∈ (π/4, pi/2), then decompose, f (x according to vector _{β, θ, d}) decompose project to driftage face δ _π/4on vector f _awith driftage face δ _pi/2on vector f _b(two projection vector f _awith f _bequal with Z axis angle, and with f (x _{β, θ, d}) coplanar), by same vector decomposition method more respectively vector f _awith f _bdecomposition projects on adjacent two angle of pitch directions in each driftage face, and after completing all obstructing objects meta analysises, the influence matrix of each volume elements completes as calculated, and is stored in grid, is designated as:

(3) in environmental characteristic expression system, consider the convenience of calculating, we ask for eigenmatrix F (x) of f (x), and are stored in grid:

Method one, ask for F (x) by two-dimensional fourier transform, make transformation operator obtain according to fast two-dimensional Fourier transformation calculations,

Method two, asks for F (x) by Walsh conversion, makes transformation operator calculate according to fast two-dimensional WalshHadama conversion,

8x8 matrix in above-mentioned formula is the WalshHadama transformation matrix of 8 dimensions, different dimensions, and corresponding WalshHadama transformation matrix is not identical, wherein:

$\left\{\begin{array}{c}{H}_1=\left(1\right)\\ H_n=\left(\begin{array}{cc}{H}_{n/2}& H_{n/2}\\ H_{n/2}& -H_{n/2}\end{array}\right),n=2^{\text{m}}\text{,m\∈N}\end{array}\right\}$

(4) in environmental characteristic expression system, consider the convenience of calculating, we ask for the characteristic spectrum P (x) of eigenmatrix F (x), and are stored in grid:

Method one, convert eigenmatrix F (x) obtained according to fast two-dimensional Fourier, Wo Menyou,

By asking modular arithmetic, characteristic spectrum element P (x) [i] [j]=| F (x) [i] [j] |=| F _{i+1, j+1}|, i, j ∈ [0,7]

Method two, convert eigenmatrix F (x) obtained according to fast two-dimensional WalshHadama, Wo Menyou,

$\left\{\begin{array}{c}P\left(x\right)\left[0\right]={\left(F\left(x\right)\right[0\left]\right[0\left]\right)}^2\\ P\left(x\right)\left[r\right]=\underset{i=0}{\overset{2^r-1}{\mathrm{\Σ}}}\underset{j=0}{\overset{2^r-1}{\mathrm{\Σ}}}{\left(F\left(x\right)\right[i\left]\right[j\left]\right)}^2-\underset{k=0}{\overset{r-1}{\mathrm{\Σ}}}P\left(x\right)\left[k\right],r\∈[1,{\log }_2^8]\end{array}\right\}$

(5) in environmental characteristic recognition system, we set threshold value degree ^threshold, and construct the influence matrix of targeted environment volume elements y two-dimentional WalshHadama transform method is used according to above step, ask for characteristic of correspondence spectrum P (y), all volume elements x searched for by 3 d grid map, and the corresponding characteristic spectrum of comparison, remember that the angle between vectorial P (x) and vectorial P (y) is ∠ (P (x), P (y))≤degree ^threshold, calculate if cos is ∠ (P (x), P (y))>=cos (degree ^threshold), just represent that volume elements x is similar to target volume elements y in actual environment, matches the volume elements of one of them candidate,

(6) represent and recognition system through environmental characteristic, we can successfully find out all with environment that is object matching, for subsequent applications provides support.

System used in the present invention is composed as follows: environmental characteristic represents system, environmental characteristic recognition system.These two systems are the software systems according to function setting, and each subsystem concrete function is as follows:

* environmental characteristic represents system: on existing 3 d grid map, analyzes relevant volume elements, calculates and stores influence matrix, eigenmatrix, the characteristic spectrum of volume elements,

* environmental characteristic recognition system: provide the volume elements influence matrix that desired environment is corresponding, the 3 d grid map of existing volume elements feature is searched for and searches, and matches all with volume elements like expectation environment facies.

Accompanying drawing illustrates:

Fig. 1 is the inventive method system for use in carrying composition diagram

Fig. 2 (a) is 3 d grid map, and (b) is impact vector and the decomposition method of volume elements, and (c) is driftage face decomposing schematic representation

Fig. 3 (a) is the driftage face of volume elements and the discretize of the angle of pitch, and (b) is the matrix after discretize

Fig. 4 is the schematic diagram of Yishanmen

Embodiment

Below in conjunction with accompanying drawing, embodiments of the present invention are described.

The inventive method overall system architecture used can with reference to figure 1, and it is made up of two subsystems, specifically comprises following steps:

The first step

First, environmental characteristic represents system, definition distance is Euclidean distance, setting affects distance delta=4, namely barrier volume elements only affects the volume elements within peripheral distance 4, as the 3 d grid map that Fig. 2 (a) is environment, the impact vector of Fig. 2 (b) barrier volume elements and decomposition method:

f(x _β，θ，d)＝f ₁+f ₂

=f ₁+ f ₃+ f ₄(f ₃with f ₄f ₂component on two adjacent driftage faces)

=f ' ₃+ f ' ₄+ f ₃+ f ₄(f ₁by f ₃with f ₄the long ratio of mould resolve into f ' ₃with f ' ₄)

＝(f′ ₃+f ₃)+(f′ ₄+f ₄)

=f _a+ f _b(f _awith f _bequal with Z axis angle)

Go off course on faces and eight angles of pitch to eight discrete for the impact of volume elements by Fig. 3 (a) Suo Shi, the matrix after discrete is as shown in Fig. 3 (b).

Secondly, environmental characteristic recognition system, setting degree ^threshold=5 °.

Second step

Environmental characteristic represents system, the element f of the influence matrix of each volume elements of initialization _ij=0, i, j ∈ [1,8], each volume elements one by one in scanning three-dimensional grating map, on each barrier volume elements total calculation on the impact of periphery volume elements.

Such as, as shown in Figure 4, barrier volume elements (1,1,1) affects f (x to volume elements (2,1,1) _{pi/2, π, 1})=1, affects the driftage face of discretize to volume elements (2,1,1) with on the angle of pitch to this, easily knows f (x _{pi/2, π, 1}) just at driftage face δ _πon, and at angle of pitch η _{5 π/12}with η _{7 π/12}between, so the mode of decomposing by vector, only need f (x _{pi/2, π, 1}) project to angle of pitch η _{5 π/12}with η _{7 π/12}upper, know f (x by Fig. 2 and Fig. 3 _{pi/2, π, 1}) decompose later obtaining:

$\left\{\begin{array}{c}{f}_{45}=f_{45}+\frac{f\left(x_{\mathrm{\π}/2,\mathrm{\π},1}\right)}{2\cos \mathrm{\π}/12}=0+0.5176=0.5176\\ f_{55}=f_{55}+\frac{f\left(x_{\mathrm{\π}/2,\mathrm{\π},1}\right)}{2\cos \mathrm{\π}/12}=0+0.5176=0.5176\end{array}\right\}.$

In like manner, barrier volume elements (1,2,1) is to the impact of volume elements (2,1,1) discrete to driftage face δ _{3 π/4}on angle of pitch η _{5 π/12}with η _{7 π/12}on, after decomposition:

$\left\{\begin{array}{c}{f}_{44}=f_{44}+\frac{f\left(x_{\mathrm{\π}/2,3\mathrm{\π}/4,\sqrt{2}}\right)}{2\cos \mathrm{\π}/12}=0+0.3660=0.3660\\ f_{54}=f_{54}+\frac{f\left(x_{\mathrm{\π}/2,3\mathrm{\π}/4,\sqrt{2}}\right)}{2\cos \mathrm{\π}/12}=0+0.3660=0.3660\end{array}\right\}$

Barrier volume elements (1,3,1) is to the impact of volume elements (2,1,1) discrete to driftage face δ _{3 π/4}with driftage face δ _pi/2be respectively after upper:

$\left\{\begin{array}{c}{f}_a=\frac{\sqrt{2}}{5}=0.2828\\ f_b=\frac{1}{5}=0.2000\end{array}\right\},$ Again f _awith f _bproject to the angle of pitch η on affiliated driftage face _{5 π/12}with η _{7 π/12}on, after decomposition:

$\left\{\begin{array}{c}{f}_{44}=f_{44}+\frac{f\left(x_{\mathrm{\π}/2,3\mathrm{\π}/4,\sqrt{2}}\right)}{2\cos \mathrm{\π}/12}=0.3660+0.1464=0.5124\\ f_{54}=f_{54}+\frac{f\left(x_{\mathrm{\π}/2,3\mathrm{\π}/4,\sqrt{2}}\right)}{2\cos \mathrm{\π}/12}=0.3660+0.1464=0.5124\\ f_{43}=f_{43}+\frac{f\left(x_{\mathrm{\π}/\mathrm{2,3}\mathrm{\π}/4,\sqrt{2}}\right)}{2\cos \mathrm{\π}/12}=0+0.1035=0.1035\\ f_{53}=f_{53}+\frac{f\left(x_{\mathrm{\π}/\mathrm{2,3}\mathrm{\π}/4,\sqrt{2}}\right)}{2\cos \mathrm{\π}/12}=0+0.1035=0.1035\end{array}\right\}$

Barrier volume elements (1,1,2) is to the impact of volume elements (2,1,1) discrete to driftage face δ _πon angle of pitch η _π/4on, after decomposition: $f_{35}=f_{35}+f\left(x_{\mathrm{\π}/4,\mathrm{\π},\sqrt{2}}\right)=0+1/\sqrt{2}=0.7071.$

Barrier volume elements (1,2,2) is to the impact of volume elements (2,1,1) discrete to driftage face δ _{3 π/4}on angle of pitch η _π/4with η _{5 π/12}on, after decomposition:

$\left\{\begin{array}{c}{f}_{34}=f_{34}+f_{34}^{\′}=0+0.3999=0.3999\\ f_{44}=f_{44}+f_{44}^{\′}=0.5124+0.1952=0.7076\end{array}\right\}$

Barrier volume elements (1,3,2) is to the impact of volume elements (2,1,1) discrete to driftage face δ _{3 π/4}with driftage face δ _pi/2be respectively (coordinate in each driftage face represents, does not consider directivity) after upper:

$\left\{\begin{array}{c}{f}_a=\frac{1}{6}\left(\begin{array}{c}\sqrt{2}\\ \frac{\sqrt{2}}{1+\sqrt{2}}\end{array}\right)\\ f_b=\frac{1}{6}\left(\begin{array}{c}1\\ \frac{1}{1+\sqrt{2}}\end{array}\right)\end{array}\right\},$ Again f _awith f _bproject to the angle of pitch η on affiliated driftage face _{5 π/12}with η _π/4on, as follows:

$f_b=\frac{1}{6}\left(\begin{array}{c}1\\ \frac{1}{1+\sqrt{2}}\end{array}\right)=a{\left(\begin{array}{c}1\\ 1\end{array}\right)}_{\mathrm{\η\π}/4}+b{\left(\begin{array}{c}1\\ \cot 5\mathrm{\π}/12\end{array}\right)}_{\mathrm{\η}5\mathrm{\π}/12},$ ? $\left(\begin{array}{c}a\\ b\end{array}\right)=\left(\begin{array}{c}\frac{0.1998}{6}\\ \frac{0.8002}{6}\end{array}\right),$ After decomposition:

$\left\{\begin{array}{c}{f}_{34}=f_{34}+\left|\sqrt{2}a{\left(\begin{array}{c}1\\ 1\end{array}\right)}_{\mathrm{\η\π}/4}\right|=0.3999+0.0666=0.4665\\ f_{44}=f_{44}+\left|\sqrt{2}b{\left(\begin{array}{c}1\\ \cot 5\mathrm{\π}/12\end{array}\right)}_{\mathrm{\η}5\mathrm{\π}/12}\right|=0.7076+0.1953=0.9029\\ f_{33}=f_{33}+\left|a{\left(\begin{array}{c}1\\ 1\end{array}\right)}_{\mathrm{\η\π}/4}\right|=0+0.0471=0.0471\\ f_{43}=f_{43}+\left|b{\left(\begin{array}{c}1\\ \cot 5\mathrm{\π}/12\end{array}\right)}_{\mathrm{\η}5\mathrm{\π}/12}\right|=0.1035+0.1381=0.2416\end{array}\right\}$

Barrier volume elements (1,1,3) is to the impact of volume elements (2,1,1) discrete to driftage face δ _πon angle of pitch η _{5 π/12}with η _π/4after upper:

$\left\{\begin{array}{c}{f}_{25}=0.2828\\ f_{35}=0.1793\end{array}\right\}$

Barrier volume elements (1,2,3) is to the impact of volume elements (2,1,1) discrete to driftage face δ _{3 π/4}on angle of pitch η _π/4with η _π/12on, after decomposition:

$\left\{\begin{array}{c}{f}_{24}=0.1381\\ f_{34}=0.7493\end{array}\right\}$

Barrier volume elements (1,3,3) is to the impact of volume elements (2,1,1) discrete to driftage face δ _{3 π/4}with driftage face δ _pi/2be respectively after upper:

$\left\{\begin{array}{c}{f}_a=\frac{1}{9}\left(\begin{array}{c}\sqrt{2}\\ \frac{2\sqrt{2}}{1+\sqrt{2}}\end{array}\right)\\ f_b=\frac{1}{9}\left(\begin{array}{c}1\\ \frac{2}{1+\sqrt{2}}\end{array}\right)\end{array}\right\},$ Again f _awith f _bproject to the angle of pitch η on affiliated driftage face _{5 π/12}with η _π/4on, as follows:

$f_b=\frac{1}{9}\left(\begin{array}{c}1\\ \frac{2}{1+\sqrt{2}}\end{array}\right)=a{\left(\begin{array}{c}1\\ 1\end{array}\right)}_{\mathrm{\η\π}/4}+b{\left(\begin{array}{c}1\\ \cot 5\mathrm{\π}/12\end{array}\right)}_{\mathrm{\η}5\mathrm{\π}/12},$ ? $\left(\begin{array}{c}a\\ b\end{array}\right)=\left(\begin{array}{c}\frac{0.8284}{9}\\ \frac{0.1716}{9}\end{array}\right),$ After decomposition:

$\left\{\begin{array}{c}{f}_{34}=f_{34}+\left|\sqrt{2}a{\left(\begin{array}{c}1\\ 1\end{array}\right)}_{\mathrm{\η\π}/4}\right|=0.7493+0.1841=0.9334\\ f_{44}=f_{44}+\left|\sqrt{2}b{\left(\begin{array}{c}1\\ \cot 5\mathrm{\π}/12\end{array}\right)}_{\mathrm{\η}5\mathrm{\π}/12}\right|=0.9029+0.0278=0.9307\\ f_{33}=f_{33}+\left|a{\left(\begin{array}{c}1\\ 1\end{array}\right)}_{\mathrm{\η\π}/4}\right|=0.0471+0.1302=0.1773\\ f_{43}=f_{43}+\left|b{\left(\begin{array}{c}1\\ \cot 5\mathrm{\π}/12\end{array}\right)}_{\mathrm{\η}5\mathrm{\π}/12}\right|=0.2416+0.0197=0.2613\end{array}\right\}$

To sum up, the influence matrix suffered by volume elements (2,1,1)

$\left(\begin{array}{cccccccc}0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0.1381& 0.2828& 0& 0& 0\\ 0& 0& 0.1773& 0.9334& 0.1793& 0& 0& 0\\ 0& 0& 0.2613& 0.9307& 0.5176& 0& 0& 0\\ 0& 0& 0.1035& 0.5124& 0.5176& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\end{array}\right)$

3rd step

The eigenmatrix F (2,1,1) of the influence matrix f (2,1,1) of volume elements (2,1,1) is obtained, Wo Menyou according to Fast W alshHadama conversion:

$F\left(\mathrm{2,1,1}\right)=\left(\begin{array}{cccccccc}0.0712& -0.0074& -0.0244& 0.0542& 0.0244& -0.0542& -0.0712& 0.0074\\ 0.0046& -0.0072& -0.0078& 0.0040& 0.0078& -0.0040& -0.0046& 0.0072\\ -0.0226& 0.0153& 0.0258& -0.0121& -0.0258& 0.0121& 0.0226& -0.0153\\ 0.0177& 0.0061& 0.0002& 0.0118& -0.0002& -0.0118& -0.0177& -0.0061\\ 0.0357& -0.0108& -0.0213& 0.0253& 0.0213& -0.0253& -0.0357& 0.0108\\ -0.0308& -0.0106& -0.0047& -0.0250& 0.0047& 0.0250& 0.0308& 0.0106\\ -0.0580& 0.0119& 0.0289& -0.0411& -0.0289& 0.0411& 0.0580& -0.0119\\ -0.0177& 0.0027& 0.0033& -0.0171& -0.0033& 0.0171& 0.0177& -0.0027\end{array}\right)$

4th step

Obtain the characteristic spectrum P (2,1,1) of volume elements (2,1,1) according to Fast W alshHadama conversion, by previous step eigenmatrix F (2,1,1) we have:

P(2，1，1)＝[0.0051，0.0001，0.0057，0.0325]

5th step

In environmental characteristic recognition system, such as we are interested in Yishanmen, and we want the place found on 3 d grid map near door, first, construct the influence matrix of this fitting of door environment, as follows:

$f\left(\mathrm{door}\right)=\left(\begin{array}{cccccccc}0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0.1& 0.2& 0& 0& 0\\ 0& 0& 0.1& 1.0& 0.1& 0& 0& 0\\ 0& 0& 0.2& 1.0& 0.5& 0& 0& 0\\ 0& 0& 0.1& 0.5& 0.5& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\end{array}\right),$ In like manner we have:

P(door)＝[0.0045，0.0003，0.0064，0.0336]

6th step

By environmental characteristic recognition system, search for whole 3 d grid map, search all volume elements matched with P (door), such as we compare P (2,1,1) and P (door)

cos∠(P(2，1，1)，P(door))＝0.999625≥cos(degree ^threshold)＝0.996195

In like manner, we are interested in another Yishanmen, and we want the place found on 3 d grid map near door, and the influence matrix of environment is as follows:

$f^{\′}\left(\mathrm{door}\right)=\left(\begin{array}{cccccccc}0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\\ 0& 0& 0& 0& 0& 0.1& 0.2& 0\\ 0& 0& 0& 0& 0.1& 1.0& 0.1& 0\\ 0& 0& 0& 0& 0.2& 1.0& 0.5& 0\\ 0& 0& 0& 0& 0.1& 0.5& 0.5& 0\\ 0& 0& 0& 0& 0& 0& 0& 0\end{array}\right)$ We have equally:

P′(door)＝[0.0045，0.0003，0.0064，0.0336]

To sum up, we can see that the characteristic spectrum P (door) of f (door) and f ' (door) and P ' (door) are identical, also be similar in actual environment, represented and recognition system by our environmental characteristic, these " door " environment all can be matched, this has just absolutely proved our system, for similar environment, there is rotational invariance, in the process of environmental characteristic identification, just greatly reduce exhaustive comparison number of times, the efficiency of whole method is high, the time complexity of whole method and the size of grating map are linear.

Claims (6)

1. the environmental characteristic based on 3 d grid map represents and knowledge method for distinguishing, 3 d grid map in the method is as given a definition: by abstract for environment space be the grid space under three-dimensional cartesian coordinate system O:xyz, the complete or collected works in space are that each element in Ω, Ω is called volume elements, use c _{x, y, z}represent, (x, y, z) be the three-dimensional coordinate of this volume elements, each volume elements is a length of side is the square of λ, and every bar limit of square is all parallel with solid axes, occupy with or without object according to actual environment, determine or probability meaning is determined the duty ratio value of corresponding volume elements, the map formed based on this is called 3 d grid map, and λ is called the resolution of 3 d grid map.This method is the 3 d grid cartographic representation by setting up actual environment, for the impact analysis of barrier volume elements to the idle volume elements of periphery, extract the feature of volume elements, as the expression of actual environment feature, by aspect ratio to the identifying purpose reaching environment, it comprises the following steps:

(1) by relevant equipment and algorithm, as three-dimensional laser radar, binocular vision sensor and other algorithms etc., the 3 d grid map corresponding with actual environment is set up,

(2) on grating map, analyze the impact of each barrier volume elements on the idle volume elements of periphery one by one, as follows:

The impact of barrier volume elements on volume elements x is denoted as f (x _{β, θ, d}), β ∈ [0, π] represent the angle of pitch (Z-direction of 3 d grid map is as 0 degree of initial direction) of the relative volume elements x of barrier volume elements, θ ∈ [0,2 π) represent the crab angle (X-direction of 3 d grid map is as 0 degree of initial direction) of the relative volume elements x of barrier volume elements, d represents the distance of the relative volume elements x of barrier volume elements, according to β, the incremental order of θ, the impact suffered by volume elements x is designated as:

(3) discretize of f (x).

First, on the impact suffered by volume elements x, angularly θ is discrete to [δ in limited driftage face ₁, δ ₂..., δ _s], s ∈ N, each driftage face δ represents a half-plane being border with the Z-direction at volume elements x place, and secondly, in each driftage face δ, angularly β is discrete to [η on the limited angle of pitch ₁, η ₂..., η _n], n ∈ N, such as:

Certain barrier volume elements is on the impact of volume elements x work as δ _i≤ θ _k≤ δ _i+1, i ∈ [1, s-1], k ∈ [1, s], then decompose by vector and project to driftage face δ _iwith driftage face δ _i+1on, and then respectively driftage face δ _iwith driftage face δ _i+1interior component, decomposes by vector respectively and projects to η _jwith η _j+1on two angles of pitch, after discretize,

(4) according to the influenced f (x) of volume elements x, its eigenmatrix F (x) is extracted,

be a kind of conversion, can be but be not limited to two-dimensional fourier transform, two-dimensional walsh transform etc.,

(5) according to eigenmatrix F (x) of volume elements x, the characteristic spectrum P (x) that it has rotational invariance is calculated,

Here rotational invariance is definition like this:

Matrix f (x) is n × s rank, f (x) [i] [j], and i ∈ [1, n], j ∈ [1, s] represent the element of the i-th row jth row in vector f (x),

Each element of matrix f (x) circulates and moves down r ∈ N and walk, and the recycle l ∈ N that moves to right walks, and is designated as f _rl(x),

F (x) if [i] [j]=f _rl(x) [(i+r) %n] [(j+l) %s],

Then matrix f (x) and matrix f _rlx () characteristic of correspondence spectrum is identical, be rotational invariance.

(6) characteristic spectrum comparison,

Influence matrix f (y) the characteristic of correspondence spectrum that influence matrix f (x) characteristic of correspondence of volume elements x is composed as P (x), volume elements y is P (y), and we define a threshold angle degree ^thresholdif, angle ∠ (P (x), P (y))≤degree between vectorial P (x) and vectorial P (y) ^threshold, or cos ∠ (P (x), P (y))>=cos (degree ^threshold), be similar with regard to representing matrix f (x) to f (y), namely volume elements x and volume elements y are similar in actual environment, utilize vector operation rule, and we can calculate:

$\cos \&angle;(P\left(x\right),P\left(y\right))=\frac{<P\left(x\right),P\left(y\right)>}{\left|P\left(x\right)\right|\&CenterDot;\left|P\left(y\right)\right|},$ With cos (degree ^threshold) relatively after, we both can draw similarity,

(7) by characteristic spectrum comparison, we can find out the volume elements x similar to target volume elements y, so just reach the object of Context awareness.

2. a kind of environmental characteristic based on 3 d grid map represents and knowledge method for distinguishing as claimed in claim 1, it is characterized in that, the impact of barrier volume elements on the idle volume elements of periphery is quantized, and the variable of this quantization function can be but be not limited to angle, apart from isostructure expression formula.

3. a kind of environmental characteristic based on 3 d grid map represents and knowledge method for distinguishing as claimed in claim 1, it is characterized in that, discretize or non-discretize can be considered when applying, element number after discretize can be limited also can be unlimited, can evenly or non-uniform discrete, element within discrete segment can be added on the discrete direction of both sides by vector decomposition, also can decompose by other modes.

4. a kind of environmental characteristic based on 3 d grid map represents and knowledge method for distinguishing as claimed in claim 1, it is characterized in that, in order to convenience of calculation asks for eigenmatrix the influence matrix of volume elements by conversion, can not certainly do any conversion and directly participate in computing with influence matrix, conversion here can be but be not limited to Fourier conversion, Walsh conversion etc.

5. a kind of environmental characteristic based on 3 d grid map represents and knowledge method for distinguishing as claimed in claim 1, it is characterized in that, in order to convenience of calculation passes through the eigenmatrix of volume elements the characteristic spectrum that rotational invariance is asked in conversion, can not certainly do any conversion and directly participate in computing with eigenmatrix, conversion here can be but be not limited to the power spectrum etc. of the spectral magnitude of Fourier conversion, Walsh conversion.

6. a kind of environmental characteristic based on 3 d grid map represents and knowledge method for distinguishing as claimed in claim 1, it is characterized in that, finds similar volume elements by the characteristic spectrum comparison of volume elements, and its comparison method can be but be not limited to the direction cosine of vector.