JPH02278312A - Device for detecting position of unmanned vehicle - Google Patents

Abstract

PURPOSE:To attain precise measurement by using spatial filters by means of plural sine wave patterns where two groups of spatially different periods are intersected orthogonally with each other, selecting the filter whose output is larger and arithmetic-processing it. CONSTITUTION:The subject device is provided with optical systems 20A and 20B which are provided on a vehicle body 10 and image-pick up patterns on the surface of a travel line, video detection part 30A and 30B which sample the video patterns where the optical systems have picked up at a prescribed period to obtain video pattern signals, and plural filter means 40A and 40B which multiply the video pattern signals of the video detection parts by triangular function setting signals where the periods which have previously been set to be spatially different are intersected orthogonally with each other, and integrate the multiplication signal to obtain triangular pattern signals. Then, an arithmetic processing is executed based on the triangular function pattern signals of the filter means and the larger one out of the outputs of plural filter means 40A and 40B is selected to calculate the moving distance signal of the vehicle body. Thus, a measurement error by the influence of the patterns of the line surface is reduced and highly precise position detection is attained.

Description

DETAILED DESCRIPTION OF THE INVENTION A. Field of Industrial Application The present invention relates to a position detection device for an unmanned vehicle, and more particularly to a position detection device for an unmanned vehicle that detects the running position and running speed of an unmanned vehicle.

B. Summary of the Invention The present invention provides a position detection device for an unmanned vehicle that detects various running states based on detection signals from a detector, in which two sets of spatially different periods are used as part of the detector. Using a spatial filter with a plurality of orthogonal sine wave patterns, the detection signal of the detector is processed by a one-dimensional filter means, and the larger output is selected to determine the two-dimensional position, speed, and traveling direction of the vehicle body. By detecting this, an unmanned vehicle position detection device with high detection accuracy can be obtained.

C1 Conventional technology In the past, when automatically driving unmanned vehicles such as automatic guided vehicles, there were methods in which electromagnetic induction wires and optical reflective tape were laid on the running path to form a travel guide, and encoders and other devices were installed on the upper shaft and measurement wheels. There is a method of installing a tacho generator and measuring the speed and distance traveled by an unmanned vehicle from pulses or analog voltages corresponding to the rotation of the wheels.

Various conventional position detection devices require processing of the running road surface by laying guide wires, reflective tape, etc. on the road surface, which is troublesome and also causes wheel slippage and wheel damage due to unevenness of the road surface, external force, etc. Accurate measurement was not possible due to wear.

Therefore, the road surface pattern is detected by a detector (CO
D line sensor), and the output is manually inputted to an arithmetic processing unit such as a microcomputer through an A/D converter, and the input value and the set value, such as a spatial filter calculated in advance and stored in a memory, etc. An unmanned vehicle position detection device that performs a product-sum calculation with a pattern, detects the travel distance from the output, and calculates the speed by differentiating it.
This is where we look at various proposals.

Problems that D. and I Ming try to solve In the position detection device using the above-mentioned spatial filter,
The pattern of the spatial filter is the curve QIa in Figure 6.
, Since only two orthogonal sine wave patterns as shown in Qlb were used, the frequency components of the spatial filter that is being focused on are reduced in places where the road surface pattern is irregular or suddenly changing, making accurate measurements difficult. There were times when it wasn't possible.

The present invention has been made in view of the above-mentioned problems, and its purpose is to use two sets of spatial filters with a plurality of orthogonal sine wave patterns with spatially different periods, and to select the one with the largest output. An object of the present invention is to provide a position detection device for an unmanned vehicle that can perform highly accurate measurement by performing calculation processing on the vehicle.

61 Means for Solving Problems and Effects An optical system disposed on a vehicle body for photographing a pattern on a running road surface, and an image for obtaining a video pattern signal by sampling the video pattern photographed by the optical system at a predetermined period. a detection unit; and a plurality of units that multiply the video pattern signal of the video detection unit by preset orthogonal trigonometric function setting signals having spatially different periods, and perform an integral operation on the multiplied signal to obtain a trigonometric function pattern signal. A moving distance signal of the vehicle body is calculated by performing arithmetic processing on the basis of a filter means and a trigonometric function pattern signal of the filter means, and selecting a larger one among the outputs of the plurality of filter means.

F. EXAMPLE An example of the present invention will be described below with reference to FIGS. 1 to 5.

FIG. 2 is a block diagram of a position detection device for an unmanned vehicle according to an embodiment of the present invention, in which 10 is the vehicle body of the unmanned vehicle, 12 is the running wheel, and 2OA is the traveling axis of the unmanned vehicle at the bottom 11 of the vehicle body 10. A first optical system disposed at one side end of the constant surface section 11 with respect to the center (X axis), 20B is the first optical system 2OA
The other side end (Y
This is a second optical system disposed on the optical axis (on the axis). 30A is the first
The first image detecting section 40A which inputs the image signal of the optical system 2OA is a first spatial filter which receives the image detection signal of the first image detecting section 30A as input. The first optical system 20A, the first image detection section 30A, and the first spatial filter 40A constitute a first detection section 60A. Similarly, 20B is a second optical system, 30B is a second image detection section, and 40B is a second spatial filter. These constitute the second detection section 60B. 50 calculates the moving distance and speed of the unmanned vehicle by performing arithmetic processing based on the filter output signals of the first spatial filter 40A and the second spatial filter 40B.

The first detection section 60A and the second detection section 60B are composed of substantially the same components as shown in FIG.

That is, as shown in the first column, the first. The second video detection units 30A and 30B are connected to the licensor 31. It is composed of a readout circuit 32 and an analog/digital converter (A/D converter) 33. 1st. Second spatial filter 40
A, 40B are multiplication parts 41a, 41b, pattern setting part 4
2a, 42b, and integral calculation sections 43a, 43b. As the arithmetic processing unit 50, a microcomputer (hereinafter abbreviated as microcomputer) 51 is used.

The pattern of the spatial filter is the curve Q l in Figure 3.
As shown in aI Q+b and Q2a, Q2b, 2
A combination of sine wave patterns and cosine wave patterns is used. Each set is two orthogonal patterns, 2
The cycles of the sets of patterns are made to be different.

That is, the setting pattern of the pattern setting section 42ilL in the first spatial filter 40A is sin pattern 1.
(Q, , ), and the setting pattern of the pattern setting section 42b of the first spatial filter 40A is COS pattern 1 (Q
l! , ). Further, the setting pattern of the pattern setting section 42a of the second spatial filter 40B is sin pattern 2.
(L,), the setting pattern of the pattern setting section 42b is eO
s pattern 2 (C, b).

Next, the operation of the position detection device having the above configuration will be explained.

The video signals of the optical systems 20A and 20B are the first and second ones, respectively.
Detected by the video detection units 30A and 30B of the first. It is input to second spatial filters 40A and 40B. Spatial filters 40A and 40B detect specific spatial frequency components from optically random patterns on the road surface and examine their temporal behavior.

Schematically, as shown in FIG. 1, a pattern of a road surface 80 is detected by an image detection unit 30A (
30B) and its output is detected by the spatial filter 40
Enter A (40B).

In the spatial filter, a sum-of-products operation is performed using human input values and a pre-calculated and pre-set setting pattern. Here, a cosine wave pattern is used instead of a sine wave pattern. The setting pattern has data for a period determined by the number of elements and pitch of the licensor 31 of the video detection section 30A (30B). The output of the spatial filter is processed by the arithmetic processing unit 50 to calculate the travel distance of the car, and this travel distance is differentiated with respect to time to determine the speed.

More specifically, as shown in FIG. 1, a video signal of the road surface 80 is input to the video detection section 30A (30B) via the optical system 2OA (20B). Video detection unit 30A (30
In B), the licensor 31 detects the video, the successive circuit 32 reads out the video detection signal, A/D converts the video detection signal, and sends the spatial filter 40A (4, OB
).

In the spatial filter 4/OA (40B), a multiplication section 41a multiplies the video detection signal from the video detection section 30A (30B) and a sine wave pattern setting signal from the pattern setting section 42a, and a multiplication section 41b performs video detection. The signal is multiplied by the cosine wave pattern setting signal of the pattern setting section 42b. Further, the multiplication signal of the first multiplication section 41a is integrated by the integral calculation section 43a and outputs the integral signal 52a (S2a), and the multiplication signal of the multiplication section 41b is integrated by the second integration calculation section 43b, and the integral Signal 5lb (S2b)
Output. The microcomputer 51 is the first spatial filter 40A.
Performs predetermined arithmetic processing using the outputs Sla and Slb and the outputs S2a and S2b of the second spatial filter 40B as input,
Calculate the distance traveled by the unmanned vehicle, i.e. its position and speed.

That is, 1st. Second spatial filter 40A.

40B calculates Δφ corresponding to the moving distance from the previous sampling time for each set as follows.

Here, San is the spatial filter calculation result (sin pattern).

Sbo is the spatial filter calculation result (cos pattern).

5an-++ 5bn-+ is the previous value of San and Sbn.

The spatial filter 40A (40B) calculates equation (1) for each set to obtain △φ1△φ2. Also 1 microcomputer 5
1 is the size A of the calculation results of the spatial filters 40A and 40B
1. A2 is calculated for each set using the following formula.

A = J San'+Sbn' -==-(2)
Next, A1. A t is compared, the larger △φ is found, and it is set as △φ again.

By integrating this Δφ, the moving distance φn is determined.

φ0−φ. −2+△φ ・・・・・・(4) However, φ,
-1 is the previous φ1.

Figures 4 and 5 show the above-mentioned operation flow.
The figure shows the calculation flow of the spatial filter 40A (40B).

As shown in FIG. 4, the licensor (C
OD) is A/D converted and input to the spatial filter 40A. In the spatial filter 4OA, block B2
As shown in a, the window function data l is sine m (sin)
Read the pattern l and use this sine wave pattern l and COD
A product-sum operation of the outputs is performed to obtain a signal Sla (block B3 a).

Next, as shown in block B4a, a cosine wave (COS) pattern l is read as window function data 2, and a product-sum operation is performed on this cosine wave pattern l and the COD output to generate a signal Slb.
(block B4 a).

Further, in the second calculation filter 40B, block B
2b, a sine wave (sin wave) is used as the window function data 3.
) Load pattern 2 and combine this sine wave pattern 2 with Sl
A product-sum operation of b is executed (block B3 b). next,
As shown in block B4b, a cosine wave (COS) pattern 2 is read as window function data 2, and a product-sum operation of this cosine wave pattern 2 and the COD output is performed (block B5
b). Then, as shown in block B6b, the operation of block B1a=B5b is repeated a COD number of times, for example, 2048 times.

As shown in FIG. 5, the microcomputer 51 calculates Δφ1 based on the above-mentioned equation (1) (block B7).
. Also, in block B8, based on equation (1), △φ
, calculate. Next, A1 is calculated based on equation (2) (block B9), and A is calculated in block Bll. Furthermore, the sizes of A1 and A are compared in block Bll, and if A1≧A2, Δφ1 is selected (block B12), and if A I<A t, Δφ is selected. After that, the moving distance φ is calculated in block BI4 based on equation (3).

G1 Effects of the Invention The present invention uses spatial filters with two sets of orthogonal sine wave patterns with spatially different periods, and selects the one with the larger output at that time to calculate the travel distance. Therefore, measurement errors due to the influence of road surface patterns are minimized, and highly accurate position detection is possible.

[Brief explanation of drawings]

Fig. 1 is a block diagram of a position detection device according to the present invention, Fig. 2 is a block diagram showing a case where a detection processing section according to an embodiment of the present invention is applied to an unmanned vehicle, and Fig. 3 is a block diagram of a position detection device according to the present embodiment. Trigonometric function pattern diagram of the spatial filter of the device, 4th
5 is a calculation flow diagram of the spatial filter, FIG. 5 is a calculation flow diagram of the calculation processing section, and FIG. 6 is a trigonometric function pattern diagram of the spatial filter of a conventional position detection device. 10...Vehicle body, 11...Bottom part of vehicle body, 2OA...1st
optical system, 20B: second optical system, 30A: first image detection section, 30B: second image detection section, 40A:
- First spatial filter, 40B... second spatial filter, 50... arithmetic processing section, 51... microcomputer, 60A... first detection section, 60B... second detection section. Fig. 1 Position detection device of the embodiment Fig. 5 φ (traveling distance) calculation algorithm

Claims (1)

[Claims] (1) An optical system disposed on the vehicle body that photographs the pattern of the road surface, an image detection section that samples the image pattern photographed by the optical system at a predetermined period to obtain a video pattern signal, and the image detection section. a plurality of filter means for multiplying the video pattern signal of the part by orthogonal trigonometric function setting signals having preset spatially different periods and performing an integral operation on the multiplied signal to obtain a trigonometric function pattern signal; An unmanned vehicle characterized by comprising an arithmetic processing unit that performs arithmetic processing based on the trigonometric function pattern signal and selects a larger output from among the outputs of the plurality of filter means to calculate a moving distance signal of the vehicle body. Position detection device.