JPH0821730A - Two-dimensional position sensor - Google Patents

Abstract

PURPOSE:To measure a two-dimensional position by computing a travel in the orthogonal direction and the angle of rotation in a plane by spatial-filter arithmetic operation from the two-dimensional image data of an object to be measured. CONSTITUTION:The image pick-up signal of an object to be measured 1 picked up by a two-dimensional CCD 2 is converted 6 into a digital signal through a read circuit 3, and input to a spatial-filter arithmetic operation section 5 as an image data. The digital signal is stored in an image memory 7, and input to spatial filters 8, 9, 10 respectively in the arithmetic operation section 5. Outputs Fs, Fc passing through the filters 8, 9 are input to phase rotary arithmetic operation sections 11, 12 together with previous values, and alphaDELTA, betaDELTA are arithmetically operated. A moving vector DELTA=(DELTAx, DELTAy) is obtained by a moving- vector arithmetic operation section 13, to which alphaDELTA, betaDELTA are input, and travels in the two orthogonal directions are arithmetically operated by an integrator 14. An output Fw from the filter 10 is input to a phase rotary arithmetic operation section 15 together with a previous value and the angle of rotation theta is acquired, and the angle of rotation phi in a plane containing the orthogonal directions is computed by an integrator 16.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a distance measuring device using a spatial filter, which is improved to detect a two-dimensional position.

[0002]

2. Description of the Related Art Conventionally, in the automatic traveling of an automatic guided vehicle or the like, a traveling guide is formed by laying an electromagnetic induction wire or an optical reflecting tape on a traveling path, or an encoder or a tachogenerator is attached to an axle or a measuring wheel. There is a method of measuring the speed and moving distance of an unmanned vehicle from a pulse or an analog voltage according to the rotation of a wheel.

However, these methods require the work of laying a reflective tape or the like on the road surface, and the work must be carried out every time the traveling road is changed, and the work is complicated, and the road surface irregularities, slips due to external force, and the like. Accurate measurement could not be performed due to wheel wear. Therefore, as a method of measuring the movement distance without contact from the outside and without contact,
Distance measuring methods using spatial filters have been developed.

The distance measuring method using this spatial filter is performed by the apparatus configuration shown in FIG. That is, as shown in the figure, the reflected light from the road surface 01 is detected by the one-dimensional line sensor (CCD) 03 through the optical system 02, sampled at a predetermined cycle, and converted into an electric signal. The optical system 02 and the line sensor 03 are attached to the bottom surface of the vehicle body (not shown). The line sensor 03 is formed by temporarily arranging optical conversion elements along the traveling direction, and sequentially outputs signals according to light and dark.

The output signal P from the line sensor 03 passes through the read circuit 04, is converted into CCD data of a digital signal by the A / D converter 06, and then is spatial filter calculation unit 05.
Is input to The spatial filter calculation unit 05 integrates this output signal within a predetermined range to extract an arbitrary frequency component from the reflected light composed of optically random frequencies, and based on the spatiotemporal change, the phase space is calculated. At, the vector corresponding to the moving distance is obtained.

That is, the CCD data D _i (i = 1,2, ... N) from the line sensor 03 consisting of N pixels is the weighting function S _i (i = 1,1).
2, ... N), and products of equal subscripts are sequentially added N times to perform a product-sum operation to obtain a product-sum value b _n .

Next, when the weighting function C _i (i = 1,2, ... N) is read, the subscript is added between the CCD data D _i (i = 1,2, ... N). equal is the product-sum operation is performed by the product of one is added successively n times, Sekiwachi a _n is obtained. Further, since the product sum values a _n and b _n are obtained for each sampling, the product sum value of the previous sampling is set to a _n−1 and b _n−1, and the product sum value of the current sampling is a _n and b _n. I will decide. In this way, the phase difference Δφ between the previous sampling and the current sampling is calculated by the phase difference calculation unit 07 as the following equation.

[0008]

[Equation 1]

Here, the moving distance x ₀ and the phase difference Δφ are in a proportional relationship, and the proportional constant is the filter pitch p (=
Since the ratio is (L / n) and 2π, the moving distance x ₀ and the velocity V are obtained as follows.

[0010]

[Equation 2]

However, the phase difference during one sampling is within one rotation. Therefore, after that, the phase difference Δφ is summed up by the accumulator 08, and (p
/ 2π) is integrated to obtain the moving distance x ₀ and the velocity V, respectively.

[0012]

In the above-described distance measuring device using a spatial filter, a device has been developed which corrects a measurement error by performing a plurality of spatial filter calculations on one pattern data (actually, the actual measurement). 2-70
643). In such a distance measuring device, the velocity can be detected from the temporal change of the specific spatial frequency component included in the pattern of the object to be measured.

However, even such a distance measuring device cannot measure a two-dimensional position because it measures a one-dimensional distance. The present invention has been made in view of the above conventional technique, and an object of the present invention is to provide a two-dimensional position detecting device that can measure a two-dimensional position by utilizing a spatial filter calculation. Still another object of the present invention is to reduce the error due to the contrast of the image data captured in the spatial filter calculation.

[0014]

The structure of the present invention which achieves such an object is a two-dimensional image pickup device for two-dimensionally picking up a moving measuring object, and an image pickup signal from the two-dimensional image pickup device is converted from an analog signal to a digital signal. Regarding an A / D converter for converting into a signal and two-dimensional image data which is a digital signal converted by the A / D converter, regarding two orthogonal directions and a rotation direction in a plane including these orthogonal directions. A spatial filter calculation unit that extracts an arbitrary frequency component by a spatial filter calculation and calculates a moving distance in the two orthogonal directions and a rotation angle in the plane is provided.

Further, the spatial filter calculation unit is arranged to
A differentiation circuit for differentiating the digital signal converted by the / D converter and a binarization circuit for binarizing the image pickup signal differentiated by the differentiation circuit may be provided.

[0016]

[Action]

(1) Parallel movement A spatial filter operation unit in which f (u + v) as image data f (x, y) which is an image pickup signal picked up by a two-dimensional image pickup device has a weighting function Ws (v) represented by the following equation After passing, its output Fs (u) becomes:

[0017]

(Equation 3)

When the object to be measured is two-dimensionally moved in parallel, its movement vector is Δ =, as shown in FIG.
If (Δx, Δy), the image data f (u + Δ +
v) output Fs (u +
Δ) can be expressed as follows.

[0019]

[Equation 4] Here, when q = v + Δ, it is transformed into the following equation.

[0020]

(Equation 5) Therefore, the following equation is derived.

[0021]

(Equation 6) Similarly, the output Fc of the spatial filter calculator having the weighting function Wc expressed by the following equation is expressed by the following equation.

[0022]

(Equation 7) Therefore, the movement vector v will be calculated by the following equation.

[0023]

(Equation 8)

(2) Rotational movement A spatial filter in which f (u + r) as image data f (x, y) which is an image pickup signal picked up by a two-dimensional image pickup device has a weighting function Wr (v) represented by the following equation. The output Fw (u) after passing through the calculation unit is as follows.

[0025]

[Equation 9] However, r = (l, ρ) is a vector represented by polar coordinates with u as the origin. Here, when the object to be measured rotates in a two-dimensional plane, assuming that angle is θ as shown in FIG. 2, the output Fwr (u) obtained by passing the image data g (u + r) through the spatial filter calculation unit is as follows. Can be expressed as

[0026]

[Equation 10] However, g (u + r) is a pattern obtained by rotating θ with respect to f (u + r) about the origin u.

Therefore, the following equation is derived. g (u + r) = f (u + p) p = (l,?) = (l,?-?) From this, the rotation angle? Is obtained as follows.

[0028]

[Equation 11]

Further, as shown in FIG. 3, when the object to be measured moves with rotation, if there is a particularly bright portion in the image data, the influence is large and the error becomes large. Therefore, in the present invention, if there is such an influence, it is advisable to perform differential processing and binarization processing to correct the unevenness of the brightness of the image.

[0030]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The present invention will be described in detail below with reference to the embodiments shown in the drawings. 4 and 5 show an embodiment of the present invention. FIG. 4 shows a concrete device configuration of the present embodiment, and FIG. 5 shows a functional block diagram thereof.
As shown in FIG. 4, the measurement target 1 is assumed to move in the direction shown in the figure, and a two-dimensional CCD camera 2 for capturing an image of the moving measurement target 1 is provided.

An image pickup signal picked up by the two-dimensional CCD 2 is input to the CPU board 4 via the read circuit 3. The CPU board 4 includes an A / D converter 4a and a buffer R
It is composed of an AM 4b, a ROM 4c and a DSP (digital signal processor) 4d, and mainly functions as the spatial filter operation section 5 shown in FIG. That is, the image pickup signal picked up by the two-dimensional CCD 2 passes through the readout circuit 3, is converted from an analog signal to a digital signal by the A / D converter 6, and is then input to the spatial filter calculation section 5 as image data.

The spatial filter calculation unit 5 multiplies the input image data by three weighting functions which are spatial filters, calculates the sum of products and calculates the phase rotation, and calculates the two orthogonal directions and these directions. The moving distance and the rotation angle in the rotation direction of the included plane are calculated and obtained. That is,
The image data input to the spatial filter calculation unit 5 is stored in the image memory 7 and then input to the spatial filters 8, 9 and 10, respectively. Here, the image data at time mT is h _m (v). However, T is a sampling interval. The output Fs _m passed through the spatial filter 8 is expressed by the following equation.

[0033]

(Equation 12) Output Fc _m passing through the spatial filter 9 is represented by the following formula.

[0034]

(Equation 13) The outputs Fs _m and Fc _m from the spatial filters 8 and 9 together with the previous values Fs _m-1 and Fc _m-1 are respectively included in the phase rotation calculation unit 1.
1 and 12 are input, and αΔ and βΔ are calculated according to the following equations.

[0035]

[Equation 14] Further, αΔ and β obtained by the phase rotation calculation units 11 and 12
Δ is input to the movement vector calculation unit 13, and the movement vector Δ = (Δx, Δy) is obtained by the following equation.

[0036]

(Equation 15) After that, the movement vector is input to the integrator 14, and the movement distance is obtained by the following equation. Meanwhile _{x m = x m-1 +} Δx y m = y m-1 + Δy, the output Fw _m which has passed through the spatial filter 10, represented by the following formula.

[0037]

[Equation 16] The output Fw _m from the spatial filter 10 is input to the phase rotation calculation unit 15 together with the previous value Fw _m-1 , and the rotation angle θ is calculated by the following equation.
Is required.

[0038]

[Equation 17] Subsequently, the rotation angle θ is input to the integrator 16, and the rotation angle Φ _m is obtained as shown in the following expression. _{Φ m = Φ m-1 +} θ Thus, in the spatial filter calculating unit 5, so that the two-dimensional position x _m, y _m and the rotation angle [Phi _m is obtained.

Next, another embodiment of the present invention will be described with reference to FIGS. In this embodiment, a differential processing circuit 17 and a binarization processing circuit 18 are added so as not to be affected by the unevenness of the brightness of the target image, and the other configurations are similar to those of the above-described embodiments. . Therefore, according to the present embodiment, the deviation of the image is corrected when passing through the differentiation processing circuit 17 and the binarization processing circuit 18, so that even if there is a bright point, the movement vector is It does not become larger than the actual movement, and an accurate movement vector can always be measured.

[0040]

As described above in detail with reference to the embodiments, according to the present invention, it is possible to measure a two-dimensional position by using the spatial filter operation and to perform the spatial filter operation. It is possible to reduce the error due to the brightness of the captured image data.

[Brief description of drawings]

FIG. 1 is a principle diagram of parallel movement measurement according to the present invention.

FIG. 2 is a principle diagram of rotation measurement according to the present invention.

FIG. 3 is an explanatory diagram showing the contrast of image data.

FIG. 4 is a device configuration diagram of an embodiment of the present invention.

FIG. 5 is a block diagram of an embodiment of the present invention.

FIG. 6 is a device configuration diagram of another embodiment of the present invention.

FIG. 7 is a block diagram of another embodiment of the present invention.

FIG. 8 is a block diagram showing a conventional technique.

[Explanation of symbols]

 1 Measurement Target 2 Two-dimensional CCD 3 Readout Circuit 4 CPU Board 5 Spatial Filter Calculation Unit 6 A / D Converter 7 Image Memory 8, 9, 10 Spatial Filter 11, 12, 15 Phase Difference Calculation Unit 13 Movement Vector Calculation Unit 14, 16 integrator

Claims (2)

[Claims] 1. A two-dimensional imaging device for two-dimensionally imaging a moving measurement object, an A / D converter for converting an imaging signal from the two-dimensional imaging device from an analog signal to a digital signal, and an A / D conversion. With respect to two-dimensional image data which is a digital signal converted by a filter, with respect to two orthogonal directions and a rotation direction in a plane including these orthogonal directions, an arbitrary frequency component is extracted by a spatial filter operation, A two-dimensional position detecting device, comprising: a moving distance in two orthogonal directions and a spatial filter calculating unit that calculates a rotation angle in the plane. 2. The spatial filter calculation unit is configured to perform the A / D conversion.
The two-dimensional position according to claim 1, further comprising: a differentiating circuit that differentiates the digital signal converted by the converter, and a binarizing circuit that binarizes the image pickup signal differentiated by the differentiating circuit. Detection device.