CN105116901A - Image-processing-based dual-vehicle intelligent correction system - Google Patents

Abstract

The invention relates to a calibration system, in particular to a dual-vehicle linkage intelligent calibration system based on image processing. It includes a remote control module, an intelligent correction module, a core controller, and a vehicle body, the remote control module, the intelligent correction module, and the vehicle body are respectively connected to the core controller, and the remote control module includes buttons, a remote control control module, and a rocker , wireless module, described button, joystick, wireless module are connected with remote controller control module respectively, and described intelligent correction module comprises front car, camera, image processor, distance measuring module, and described camera one end is connected with front car, and another One end is connected with the image processor, and the ranging module is connected with the image processor. Beneficial effects: flexible operation, high safety factor, the design of the double-vehicle linkage system overcomes the shortcomings of traditional mobile platform vehicles that cannot transport larger objects; through the double-vehicle linkage system, the two vehicles can transport large and heavy objects with the same posture, making up for the single-vehicle Insufficient, improve the transportation efficiency.

Description

A dual-vehicle linkage intelligent correction system based on image processing

technical field

The invention relates to a calibration system, in particular to a dual-vehicle linkage intelligent calibration system based on image processing.

Background technique

Mobile platform vehicles are widely used in aerospace, military, civil, service industries and other fields. When transporting super-long and super-heavy equipment, considering efficiency and cost issues, a double-vehicle linkage method is often used, that is, two vehicles transport goods synchronously.

In the traditional sense, two-vehicle linkage requires two drivers to operate. It is inevitable that the two vehicles will be out of sync when starting, running, and stopping, which will cause changes in the load of the two vehicles and seriously affect the transportation work. may even cause accidents. Using the remote control to control the movement of two cars at the same time seems to be a better solution. However, due to the influence of factors such as ground friction, the two vehicles will still deviate in speed and direction. Therefore, it is necessary to propose an intelligent correction method to synchronize the two vehicles.

Contents of the invention

The present invention aims to solve the above problems, and provides a dual-vehicle linkage intelligent correction system based on image processing. The movement of the two vehicles is controlled through a wireless module, the rear vehicle is loaded with an intelligent correction platform, and the distance between the two vehicles is analyzed through the distance measurement module. Obtain the image of the vehicle in front and process it to obtain the direction of the vehicle in front, obtain the offset [ΔX, ΔY, α], perform PID control, obtain the correction speed [v _x , v _y , w _z ], and realize self-attitude correction. The technical scheme adopted is as follows:

A dual-vehicle linkage intelligent correction system based on image processing, including a remote control module, an intelligent correction module, a core controller, and a vehicle body, the remote control module, the intelligent correction module, and the vehicle body are respectively connected to the core controller, and the The remote controller module includes buttons, a remote controller control module, a rocker, and a wireless module. The buttons, rocker, and wireless module are respectively connected to the remote controller control module. One end of the camera is connected to the front vehicle, the other end is connected to the image processor, and the distance measurement module is connected to the image processor.

The buttons and the rocker are fixed on the remote control panel, the remote control control module and the wireless module are fixed in the remote control panel, the camera, the image processor, and the ranging module are fixed in front of the car body, and the The core controller is installed in the car body.

The remote controller module is connected with the core controller through a wireless module, and the intelligent correction module is connected with the core controller through an image processor.

The remote controller module sends instructions to the core controller through the wireless module to control the movement of the two vehicles.

The camera collects the information of the vehicle in front and sends it to the image processor, and the image processor sends parameter information to the core controller after analysis.

The core controller receives control instructions from the remote controller module and the intelligent correction module, and controls the vehicle body.

The invention has the following advantages: flexible operation, high safety factor, the design of the double-vehicle linkage system overcomes the shortcomings of the traditional mobile platform vehicle that cannot transport larger objects; through the double-vehicle linkage system, the two vehicles can transport large and heavy objects with the same posture , to make up for the lack of bicycles and improve transportation efficiency.

Description of drawings

Figure 1: A schematic diagram of the control principle of a dual-vehicle linkage intelligent correction system based on image processing;

Figure 2: A control schematic diagram of a dual-vehicle linkage intelligent correction system based on image processing;

Figure 3: Schematic diagram of the structure of a remote control for a dual-vehicle linkage intelligent correction system based on image processing;

Figure 4: Schematic diagram of the structure of a mobile platform vehicle for a dual-vehicle linkage intelligent correction system based on image processing;

Figure 5: A flowchart of the correction principle of a dual-vehicle linkage intelligent correction system based on image processing;

Figure 6: A schematic diagram of the calibration target of a dual-vehicle linkage intelligent correction system based on image processing;

Figure 7: A schematic diagram of the correction scene of a dual-vehicle linkage intelligent correction system based on image processing;

Figure 8: A schematic diagram of the determination of the rear vehicle offset angle of a dual-vehicle linkage intelligent correction system based on image processing;

Figure 9: PID control diagram of a dual-vehicle linkage intelligent correction system based on image processing;

Symbol Description:

1. Remote control module, 11. Button, 12. Remote control control module, 13. Joystick, 14. Wireless module, 2. Intelligent correction module, 21. Front car, 22. Camera, 23. Image processor, 24. Ranging module, 3. Core controller, 4. Vehicle body.

Detailed ways

Below in conjunction with accompanying drawing and example the present invention will be further described:

As shown in Figures 1-4, the present invention is a dual-vehicle linkage intelligent correction system based on image processing, including a remote control module (1), an intelligent correction module (2), a core controller (3), and a vehicle body (4) , the remote controller module (1), the intelligent correction module (2), and the car body (4) are connected to the core controller (3) respectively, and the remote controller module (1) includes buttons (11), a remote controller control module (12), rocking bar (13), wireless module (14), described button (11), rocking bar (13), wireless module (14) are connected with remote controller control module (12) respectively, and described intelligent correction module (2) comprising front car (21), camera (22), image processor (23), ranging module (24), described camera (22) one end is connected with front car (21), and the other end is connected with image processor (23) connected, the distance measuring module (24) is connected with the image processor (23).

Described button (11), rocking bar (13) are fixed on the remote control panel, and described remote control control module (12), wireless module (14) are fixed in the remote control panel, and described camera (22), image processing The device (23) and the ranging module (24) are fixed in front of the car body (4), and the core controller (3) is installed in the car body (4).

The remote controller module (1) is connected to the core controller (3) through a wireless module (14), and the intelligent correction module (2) is connected to the core controller (3) through an image processor (23).

The remote controller module (1) sends instructions to the core controller (3) through the wireless module (14) to control the movement of the two vehicles.

The camera (22) collects the information of the vehicle in front (21), and sends it to the image processor (23), and the image processor (23) sends parameter information to the core controller (3) after analysis.

The core controller (3) receives control instructions from the remote controller module (1) and the intelligent correction module (2), and controls the vehicle body (4).

a. Correction principle of dual-vehicle linkage intelligent correction system

As shown in Fig. 5, it is necessary to make the front and rear vehicles transport cargo in the same direction, with a distance of D ₀ and relatively static, but the rear vehicle has an offset angle α and a distance offset. Therefore, a correction method in which the rear vehicle is intelligently corrected through image processing is adopted. Among them, the calibration image is the black frame shown in Figure 6, which is pasted behind the front car. The length of the upper side of the black frame is L; the length of the left and right sides is R. After the initialization of the car body (4) is completed, image data collection starts. Scan left and right from the initial position of the horizontal centerline of the image, extract the abscissa values of the left and right edges, then scan up and down from the vertical centerline as the initial position, extract the ordinate values of the upper and lower edges, and obtain the ordinate, thereby determining the graph and obtaining the length of the left and right sides of the graph and margin information, save the data as standard parameters. According to the focal length formula of the imaging law, when there is an offset between the rear vehicle and the front vehicle (21), the left and right side lengths and side distances of the collected graphics will change. The offset information of the rear vehicle at this time is calculated and converted into a vehicle body control amount, and the core controller (3) fine-tunes the rear vehicle body (4).

The focal length formulas (1) and (2) are the important theoretical basis of the intelligent correction system:

F=v×D/V(1)

F=h×D/H(2)

In the formula, F is the focal length of the lens; V is the longitudinal dimension of the subject; H is the transverse dimension of the subject; D is the distance between the lens and the subject; v is the longitudinal dimension of the photosensitive original; h is the photosensitive The horizontal size of the original.

The dual-vehicle linkage intelligent correction system uses a 1/4CCD zoom lens, which can zoom up to 27 times, and the image resolution is 720*576. Simultaneously by the laser ranging module (24), we can obtain the distance D between the two vehicles; through image acquisition, we can obtain: the long pixel number M on the _left side of the target imaging, the long pixel number M on the _right side of the target imaging, the long pixel number N on the target imaging side, The target center point is offset by pixel value Q. Taking the front vehicle (21) as a reference, when the rear vehicle deviates, intelligent correction of the vehicle body (4) is carried out according to these data.

The schematic diagram of the calibration scene of the dual-vehicle linkage intelligent calibration system is shown in Figure 7. At this time, the rear vehicle has a deflection angle α, a left-right offset ΔX, and a front-rear offset ΔY.

b. Determination of vehicle body offset

1) Measure the rear vehicle offset angle α

According to the imaging law of the length of the upper side, the target image is equivalently replaced by an object parallel to the rear vehicle, with a length of L _X and a distance of D _X , as shown in Figure 8. From the triangle sine and cosine theorem, it is deduced that:

${\mathrm{<span\; class="notranslate">\; L</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}<span\; class="notranslate">\; =</span>\frac{\mathrm{<span\; class="notranslate">\; 4</span>}{{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; L</span>}\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; the\; s</span>}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}{\mathrm{<span\; class="notranslate">\; 4</span>}{{\mathrm{<span\; class="notranslate">\; D.</span>}}_{\mathrm{<span\; class="notranslate">\; x</span>}}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}<span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; L</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}{\mathrm{<span\; class="notranslate">\; sin</span>}}^{\mathrm{<span\; class="notranslate">\; 2</span>}}\mathrm{<span\; class="notranslate">\; \&alpha;</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

Substituting formula (3) into focal length formula (2), we get

In the formula, hup is the length of the _upper side of the imaging; α is the offset angle of the rear vehicle; L is the length of the upper side of the target;

From the long imaging law on the left, bring it into the focal length formula (1), we get

In the formula, v _left is the left length of the imaging;

From the long imaging law on the right, bring it into the focal length formula (1), we get

In the formula, v _right is the length of the right side of the imaging;

Divide formula (5) and formula (6) to get

In the formula, M _left is the number of long pixels on the left side of the target image; M _right is the number of long pixels on the right side of the target image;

Combining formula (4) and formula (7), eliminate D _X ; push out:

The camera sensor is 1/4CCD, the sensor imaging size h: 3.2mm; v: 2.4mm, the corresponding resolution is 720*576, according to the proportional relationship:

In the formula: N is the number of pixels on the upper side of the image; it can be deduced that the rotation angle at this time is:

2) Measure the left and right offset of the center ΔX

Shift the center point of the target image left and right, bring it into the focal length formula (2), and get

In the formula, ΔX is the left and right offset distance; z _image is the offset distance _of the imaging center; D1 is the current distance between the two vehicles measured by the laser ranging module;

Convert the proportional relationship to: Bring into formula (8), push left and right offset:

3) Measure the front and rear offset ΔY

The distance D measured by the ranging module (24 ₎ and the standard distance D make _a difference to obtain the front and rear offsets:

ΔY=D ₁ cosα-D ₀ (12)

c. PID control

In order to respond quickly and accurately, PID control is performed on the three control variables of the mobile platform vehicle [v _x , _vy , w _z ] according to the left and right offset ΔX, front and rear offset ΔY, and deflection angle α.

$\mathrm{<span\; class="notranslate">\; c</span>}\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; no</span>}\mathrm{<span\; class="notranslate">\; t</span>}\mathrm{<span\; class="notranslate">\; r</span>}\mathrm{<span\; class="notranslate">\; o</span>}\mathrm{<span\; class="notranslate">\; l</span>}<span\; class="notranslate">\; =</span>{\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}}<span\; class="notranslate">\; \&times;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; +</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span>{\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}}<span\; class="notranslate">\; \&times;</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; +</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; \&times;</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 1</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; +</span>{\mathrm{<span\; class="notranslate">\; K</span>}}_{\mathrm{<span\; class="notranslate">\; p</span>}}<span\; class="notranslate">\; \&times;</span>\frac{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; d</span>}}}{{\mathrm{<span\; class="notranslate">\; T</span>}}_{\mathrm{<span\; class="notranslate">\; the\; s</span>}}}<span\; class="notranslate">\; \&times;</span>\mathrm{<span\; class="notranslate">\; e</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; k</span>}<span\; class="notranslate">\; -</span>\mathrm{<span\; class="notranslate">\; 2</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 13</span>}<span\; class="notranslate">\; )</span>$

In the formula: K _p is the proportional coefficient; T _i is the integral coefficient; T _d is the differential coefficient; T _s is the sampling period; e(k) is the attitude deviation at time k.

After several tests, the parameters K _p , T _i , and T _d are adjusted according to experience, so that the intelligent correction system can respond accurately and quickly. Determine the size of [v _x , v _y , w _z ] according to the size of the control amount, so that the rear vehicle can correct its own attitude. The control process is shown in Figure 9.

When the present invention is in use, first turn on the power switches of the two vehicle bodies (4) and the remote controller, and when transporting larger goods, place the two transport vehicles front and back, and control the synchronous movement of the two vehicles through the remote controller module (1). Due to the influence of factors such as friction, the two vehicles have a small error, and the rear vehicle can obtain the distance parameters of the two vehicles through the distance measuring module (24), and the direction parameters of the front vehicle can be obtained by image processing through the camera (22) and the image processor (23). , the core controller (3) conducts its own posture adjustment after analyzing, so that the two vehicles remain relatively still, and the linkage between the two vehicles is realized.

Its intelligent correction process is as follows:

First, the image processor (23) analyzes the left and right length changes of the vehicle in front to measure the offset angle α of the rear vehicle at the current moment;

Then, analyze the front vehicle (21) center point offset ΔX;

Finally, according to the distance deviation ΔY of the two vehicles measured by the ranging module (24);

According to the deviation value [ΔX, ΔY, α], the velocity [v _x , v _y , w _z ] of the control car body (4) is obtained through PID control, so that the rear car can be calibrated to keep the attitude of the two cars consistent.

Preferably, the car body (4) adopts mecanum wheels, and the omnidirectional motion equipment of mecanum wheel technology can realize motion modes such as forward movement, lateral movement, oblique movement, rotation and combinations thereof.

Preferably, the movement of the car body (4) is controlled by the zigbee wireless module (14), and the operation is flexible.

Preferably, the speed control amount is optimized through the PID algorithm, so that the following vehicle can quickly and accurately perform intelligent correction.

Preferably, a two-vehicle linkage system based on image processing is adopted, and the image processor (23) is used to realize that the postures of the two vehicles are consistent, and the large cargo is transported after being relatively stationary, thereby reducing transportation costs.

The present invention has been described above by way of examples, but the present invention is not limited to the above specific embodiments, and any changes or modifications made based on the present invention fall within the scope of protection of the present invention.

Claims (5)

1. A dual-vehicle linkage intelligent correction system based on image processing, characterized in that: comprising a remote controller module (1), an intelligent correction module (2), a core controller (3), a car body (4), the remote control The device module (1), the intelligent correction module (2), and the car body (4) are connected to the core controller (3) respectively, and the remote controller module (1) includes a button (11), a remote controller control module (12), Rocking bar (13), wireless module (14), described button (11), rocking bar (13), wireless module (14) are connected with remote controller control module (12) respectively, and described intelligent correction module (2) comprises Front car (21), camera (22), image processor (23), ranging module (24), described camera (22) one end is connected with front car (21), and the other end is connected with image processor (23) , the ranging module (24) is connected with the image processor (23). 2. A kind of two-vehicle linkage intelligent correction system based on image processing according to claim 1, is characterized in that: said remote controller module (1) is connected with core controller (3) by wireless module (14), so The intelligent correction module (2) is connected with the core controller (3) through the image processor (23). 3. A kind of image processing-based dual-vehicle linkage intelligent correction system according to claim 1, characterized in that: the remote control module (1) sends instructions to the core controller (3) through the wireless module (14) to control Two-car movement. 4. A kind of two-vehicle linkage intelligent correction system based on image processing according to claim 1, characterized in that: the camera (22) collects the information of the vehicle in front (21), and sends it to the image processor (23), The image processor (23) sends parameter information to the core controller (3) after analysis. 5. A kind of image processing-based dual-vehicle linkage intelligent correction system according to claim 1, characterized in that: the core controller (3) receives information from the remote control module (1) and the intelligent correction module (2) control instructions, and control the car body (4).