CN106055745B - A method of linear CCD carriage simulation model is established based on MATLAB - Google Patents
A method of linear CCD carriage simulation model is established based on MATLAB Download PDFInfo
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Abstract
The present invention relates to a kind of method for establishing linear CCD carriage simulation model based on MATLAB, include the following steps: to establish racing track model；Establish carriage static models；Linear CCD camera shooting head model is established based on carriage static models；In racing track model, three points are determined to obtain the initial posture information of carriage；Carriage kinematics model is established, obtains the carriage pose situation at next moment in the case where posture remains unchanged based on carriage static models；Head model is imaged based on linear CCD, calculates the scanning range of linear CCD camera, and obtains sampled value from the Pixel Information of the racing track picture in the scanning range；Setting proposes line algorithm and control algolithm；Simulation process dynamic demonstration module, the track of Dynamically Announce carriage traveling, the scanning range for beating angle situation and each sampling interval carriage linear CCD camera of front-wheel are set.The modeling method may be implemented to debug on line whenever and wherever possible.
Description
Technical field
The present invention relates to carriage simulation model fields, and in particular to one kind establishes linear CCD carriage based on MATLAB
The method of simulation model.
Background technique
In intelligent vehicle contest, in order to which the control algolithm of Intelligent Optimal vehicle will often carry out multiple experiment, and in reality
Racing track on error and intelligent vehicle posture in intelligent vehicle driving process acquisition it is relatively difficult.Therefore, the ginseng of most of algorithms
Number adjustment will be gathered by examination repeatedly to realize.This method, which exists, to waste time and the shortcomings that resource.
Have in the prior art and intelligent vehicle analogue system is established using LabView virtual instrument technology, but LabView
Data processing, analysis ability it is weaker, be unfavorable for the transplanting and realization of algorithm.Establish the real-time monitoring system of intelligent vehicle, energy
The operation conditions of enough real-time monitoring intelligent vehicles, but more software and hardware resources have been used, increase unnecessary expenditures.Zhou Bin
Et al. (http://www.eepw.com.cn/event/action/Freescale/data06.htm) develop and be based on
The intelligent vehicle analogue system Plastid of LabVIEW virtual instrument technology.System establishes model to racing track and racing car respectively, makes
User can easily designed, designed racing track and racing car as indicated, racing track is designed to various forthrights, detour, slope
Road, by racecar design at various sizes, shape, so that the applicability of system is more extensive.But the system at present can only
For the intelligent vehicle using photosensitive sensors Path Recognition scheme, CCD camera technology is not supported also.Secondly, emulating
In the process, system is to be calculated according to the kinematics model of automobile (vehicle to be reduced to a four-wheel rigid body to handle), not
Consider the influence of its sideslip and road surface friction force.Finally, the problem of calculating speed is also systems face.
Lee wins et al. (foundation for following line intelligent vehicle emulation platform based on MATLAB, chinese scientific papers are online) long and uses
MATLAB software establishes the software emulation platform of hunting intelligent vehicle, takes full advantage of the control system tool box of MATLAB software
The characteristics of can be realized the algorithm of various complexity.But the system is not based on the model of linear CCD, does not account for environment
Interference, and need to draw racing track in MATLAB, it is not available the racing track in other sources；Data collection capacity ratio for analysis
It is less.
Presently, there are intelligent vehicle analogue system be mostly to be emulated for camera, not to the intelligence of linear CCD type
Can vehicle carry out online artificial, therefore can only place debugging, the problems such as debugging can be limited to time, place and light.
Summary of the invention
Linear CCD four-wheel is established based on MATLAB in view of the above-mentioned deficiencies in the prior art, it is an object of the present invention to provide one kind
The method of vehicle simulation model, the modeling method may be implemented to debug on line whenever and wherever possible.
Technical solution provided by the present invention are as follows: based on the method that MATLAB establishes linear CCD carriage simulation model, packet
Include following steps:
Step 1: establishing racing track model, by importing the racing track top view of picture format, while Set scale ruler；It is described
Scale bar be picture that width is number of pixels corresponding to racing track width in racing track top view, for actual size to be converted
For Pixel-level size；Set the developed width of racing track；
Step 2: carriage static models are established, the carriage static models include wheel and vehicle body, and front-wheel is used for
It turns to, rear-wheel is used to provide power；Setting vehicle body length, vehicle body is wide, wheel position, wheel is long, wheel is wide, radius of wheel, rear-wheel
Revolving speed；
Step 3: linear CCD camera shooting head model is established based on carriage static models, is taken the photograph linear CCD by fixed link
As head is set to carriage top；Set fixed link size, position, the subtended angle of linear CCD camera, linear CCD camera
The sampling interval of information of looking forward to the prospect and CCD camera；
Step 4: in racing track model, three points are determined to obtain the initial posture information of carriage, including carriage
Initial position, inceptive direction and initial front-wheel beat angle；
Step 5: establishing carriage kinematics model, and the feelings remained unchanged in posture are obtained based on carriage static models
The carriage pose situation at condition next but one moment；
Step 6: head model is imaged based on linear CCD, calculates the scanning range of linear CCD camera, and from the scanning model
Sampled value is obtained in the Pixel Information of racing track picture in enclosing；
Step 7: setting mentions line algorithm, is handled the sampled value that linear CCD camera obtains by mentioning line algorithm,
Obtain the right boundary information and disalignment information of racing track；
Step 8: setting control algolithm controls the next row of carriage by proposing the off-centring information that line algorithm obtains
Into state；
Step 9: setting simulation process dynamic demonstration module imitates the linear CCD carriage that step 1~step 8 obtains
True mode import simulation process dynamic demonstration module, Dynamically Announce carriage traveling track, front-wheel beat angle situation and often
The scanning range of one sampling interval carriage linear CCD camera.
In the above technical solution, it has used a kind of racing track of novelty to import mechanism, it is flat to breach other analogue systems
The limitation that platform racing track needs to draw under designated software and the limitation to call format.The modeling method can import often
See that the racing track picture of picture format is carried out using greatly facilitating the operating process of emulation, improve ease for use.
Above-mentioned modeling method can also be acquired and analyze to emulation data, the four-wheel of acquisition target and present mainstream
Vehicle host computer acquisition target has most of coincidence, therefore is connected analogue system and master system with can be convenient, and makes the system
Practicability increased.Further, it is also possible to the initial posture information of carriage is controlled with the mode of mouse interactive controlling, including
Initial position, inceptive direction and the initial front-wheel of carriage beat angle, can test the travel situations of carriage in a variety of situations.
As an improvement, introduce noise processed in the step six, the noise processed include introduce light intensity coefficient with
Simulate the sampled value under different illumination conditions；Random coefficient is introduced to make sampled value with simulated environment noise and quality of hardware fluctuation
At influence；Breadth coefficient is introduced to simulate the trend that linear CCD camera sampled value is successively decreased from centre to two sides value.It introduces
The stochastic variable of the reasonable interference of simulation actual place and hardware capability fluctuation, closer to truth, make simulation parameter and
Practical tuning parameter narrows the gap as far as possible.
Preferably, it is jpeg, bmp or png that racing track, which overlooks bitmap-format, in the step one；The racing track top view
White is filled with inside interior racing track, outside is filled with grey, and racing track edge uses black.
Linear CCD camera model in the step three are as follows:
In formula, p is vertical range of the mass center away from linear CCD camera ground based scanning line, and b is between fixed link and mass center
Distance, r are radius of wheel, and it is the subtended angle of linear CCD camera that h, which is fixed link height, γ, and w is that linear CCD camera ground is swept
Retouch the width of line.
If the prediction information of given linear CCD camera, the subtended angle of linear CCD camera, fixed link height, bar bottom away from
The distance and radius of wheel at chassis center, that is, can determine the scanning range of linear CCD, for obtaining linear CCD camera
Sampled value.
Carriage kinematics model in the step five are as follows:
In formula, α is the angle that carriage turns in a sampling interval, and β is mass center-hind axle-turning radius auxiliary angle,
θ is that front-wheel beats angle；W is that vehicle body is wide, and L is vehicle body length；Δ t is sampling interval duration；R is radius of wheel；ω is rear wheel rotation speed.
It is the asymmetric one-dimensional small window filtering algorithm for becoming sash length that line algorithm is mentioned in the step seven；
Binaryzation is carried out to sampled value as threshold value according to the mean value of sampled value first, is then repeatedly filtered using one-dimensional small window
Wave algorithm filters out the fluctuation in binarization result, whether loses line using the fluctuation analytical judgment to processing result, finally
Obtain the right boundary information and disalignment information of racing track.
Control algolithm is according to proposing disalignment information that line algorithm obtains multiplied by for controlling in the step eight
The K of algorithmpCoefficient beats the input quantity at angle as front-wheel next time to control the next travel condition of carriage.
Compared with the existing technology, the beneficial effects of the present invention are embodied in:
(1) present invention imports mechanism using a kind of racing track of novelty, breaches other Simulation System Platform racing track needs
The limitation drawn under designated software and the limitation to call format.The racing track picture that common picture format can be imported carries out
It uses, greatly facilitates the operating process of emulation, improve ease for use.
(2) modeling method of the invention can be acquired and analyze to emulation data, acquisition target and present mainstream
Carriage host computer acquisition target has most of coincidence, therefore is connected analogue system and master system with can be convenient, and makes this
The practicability of system is increased.
(3) present invention controls the initial posture information of carriage with the mode of mouse interactive controlling, first including carriage
Beginning position, inceptive direction and initial front-wheel beat angle, the travel situations of carriage in a variety of situations can be tested.
(4) closer invention introduces the stochastic variable of the reasonable interference of simulation actual place and hardware capability fluctuation
In truth, simulation parameter and practical tuning parameter is made to narrow the gap as far as possible.
Detailed description of the invention
Fig. 1 is the flow chart for establishing linear CCD carriage simulation model in embodiment 1 based on MATLAB；
Fig. 2 is the racing track top view that picture format is imported in embodiment 1；
Fig. 3 is linear CCD camera illustraton of model in embodiment 1；
Fig. 4 is that carriage determines the initial pose hum pattern after three points in embodiment 1；
Fig. 5 is carriage kinematics model figure in embodiment 1；
Fig. 6 is the linear CCD sampled value for showing as 3 dimension forms at all moment simulated in embodiment 1；
Fig. 7 is the schematic diagram of the asymmetric one-dimensional small window filtering algorithm for becoming sash length in embodiment 1；
Fig. 8 is the schematic diagram for proposing the judgement of line algorithm and losing the entropy operation of line embedded in embodiment 1；
Fig. 9 is the dynamic demonstration graph in embodiment 1 in carriage simulation process；
The racing track top view of picture format is imported in Figure 10 embodiment 2；
Figure 11 is the dynamic demonstration graph in embodiment 2 in carriage simulation process；
Figure 12 is the linear CCD sampled value for showing as 3 dimension forms at all moment simulated in embodiment 2.
Specific embodiment
Present invention will be further explained below with reference to the attached drawings and examples.
Embodiment 1
Based on the method that MATLAB establishes linear CCD carriage simulation model, specific process is as shown in Figure 1:
Step 1: establishing racing track model, by importing the racing track top view of picture format, such as Fig. 2, in racing track top view
White is filled with inside racing track, outside is filled with grey, and racing track edge uses black；Set scale ruler simultaneously, scale bar are wide
Degree is the picture of number of pixels corresponding to racing track width in racing track top view, for actual size to be scaled Pixel-level ruler
It is very little；Set the developed width of racing track；
Step 2: establishing carriage static models, and carriage static models include wheel and vehicle body, and front-wheel is used to turn to,
Rear-wheel is used to provide power；Setting vehicle body length, vehicle body is wide, wheel position, wheel is long, wheel is wide, radius of wheel, rear wheel rotation speed；
Step 3: linear CCD camera shooting head model is established based on carriage static models, is taken the photograph linear CCD by fixed link
As head is set to carriage top；Set fixed link size, position, the subtended angle of linear CCD camera, linear CCD camera
The sampling interval of information of looking forward to the prospect and CCD camera, as shown in figure 3, linear CCD images head model are as follows:
In formula, p is vertical range of the mass center away from linear CCD camera ground based scanning line, and b is between fixed link and mass center
Distance, r are radius of wheel, and it is the subtended angle of linear CCD camera that h, which is fixed link height, γ, and w is that linear CCD camera ground is swept
Retouch the width of line.
Step 4: in racing track model, three points are determined to obtain the initial posture information of carriage, including carriage
Initial position, inceptive direction and initial front-wheel beat angle；As shown in figure 4, clicking carriage in racing track top view with mouse first
Location point, a position coordinates (x can be obtained at this time1,y1), second location point (x is then put again2,y2), (x2,y2) and
(x1,y1) inceptive direction of carriage can be determined altogether, then put third location point (x3,y3), (x3,y3) and (x1,y1) close
Get up to determine that the initial steering engine of carriage beats angle.It can after thering is initial position, inceptive direction and initial steering engine to beat angle
To determine next position and the posture of carriage according to the carriage kinematics model in step 5.
Step 5: establishing carriage kinematics model, and the feelings remained unchanged in posture are obtained based on carriage static models
The carriage pose situation at condition next but one moment；As shown in figure 5, carriage kinematics model are as follows:
In formula, α is the angle that carriage turns in a sampling interval, and β is mass center-hind axle-turning radius auxiliary angle,
θ is that front-wheel beats angle.W is that vehicle body is wide, and L is vehicle body length；Δ t is sampling interval duration；R is radius of wheel；ω is rear wheel rotation speed.
Step 6: head model is imaged based on linear CCD, calculates the scanning range of linear CCD camera, and from the scanning model
Sampled value is obtained in the Pixel Information of racing track picture in enclosing；Noise processed is introduced, the noise processed includes introducing light intensity
Coefficient is to simulate the sampled value under different illumination conditions；Random coefficient is introduced with simulated environment noise and quality of hardware fluctuation to adopting
It is influenced caused by sample value；Breadth coefficient is introduced to simulate the trend that linear CCD camera sampled value is successively decreased from centre to two sides value.
The simulation of ambient light and hardware condition fluctuation is as shown in Figure 6: the sampling of practical CCD can not be highly desirable, i.e., white
Color corresponding 255, black corresponding 0, therefore in order to simulate actual effect, it introduces light intensity coefficient and sampled value is integrally carried out on multiple
Increase and reduction, introduce random coefficient, carried out on the basis of ideal sampled value plus a random sequence.After these processing
It was found that random sequence fluctuation is more violent, therefore carry out a step smoothing techniques again, i.e., since third point, each point
Numerical value is all the average value of the first two point and data itself.It is found by actual experiment, the sampling of linear CCD is from center to two sides
Data have the tendency that reduction, therefore have also multiplied the quadratic function that Open Side Down to treated sampled value, to realize
The effect for forcing down two side datas, after these processing, the CCD sampled value emulated and practical CCD sampling are very close.
Step 7: setting mentions line algorithm, is handled the sampled value that linear CCD camera obtains by mentioning line algorithm,
Obtain the right boundary information and disalignment information of racing track；The line algorithm that mentions is the one-dimensional of asymmetric change sash length
Small window filtering algorithm；
The principle of small window filtering algorithm is that, when the two sides sash number of small window is consistent, small window central region is assigned
Value is the data of small window two sides sash.The small window filtering algorithm two sides sash length of measured length is symmetrically immutable, therefore for area
The noise of domain edge cannot effectively filter out.And the small window filtering algorithm of elongated degree is guaranteeing the constant feelings of small window sash total length
Under condition, can not it be required symmetrical with the length of the small window in dynamic mapping two sides.The noise gone out in this way for edges of regions can be filtered effectively
It removes.As shown in fig. 7, black represents 1, white represents 0, and wherein the edge place of black region band has the noise of white, if
It the use of small window central region is 3, the small window filtering algorithm of measured length that the small every fan length of window sash is 4 can not effectively filter out this
The noise at place, because the sash number in left side is inconsistent.
If but using the small window filtering algorithm of elongated degree, can be realized by the length of the small window sash of dynamic mapping left
Side and right-hand side sash number are consistent, and just can effectively filter out the noise of small window central region.It is every successfully filter out after, it is next
The position of secondary small window can move the distance of right-hand side sash length, and the left-hand side sash of new small window can be sentenced without solid colour
It is disconnected.
It is embedded to mention line algorithm also using to the entropy operation for judging to lose line, for the CCD sampled value collected,
Define the confusion degree that an entropy is used to evaluate this group of data.Entropy is the transition times of this group of data digital, if certain group data
Entropy is greater than some threshold value, and intelligent vehicle loses line phenomenon when can be determined that this group of data of acquisition substantially.As shown in figure 8, first
The entropy of group data is 13, and the entropy of second group of data is 1, it is seen that first group of than second group data is more chaotic.
Step 8: setting control algolithm controls the next row of carriage by proposing the off-centring information that line algorithm obtains
Into state；The control algolithm is according to proposing disalignment information that line algorithm obtains multiplied by the K for control algolithmpSystem
Number beats the input quantity at angle as front-wheel next time to control the next travel condition of carriage.
Step 9: setting simulation process dynamic demonstration module imitates the linear CCD carriage that step 1~step 8 obtains
True mode import simulation process dynamic demonstration module, Dynamically Announce carriage traveling track, front-wheel beat angle situation and often
The scanning range of one sampling interval carriage linear CCD camera, as shown in Figure 9.Dynamic demonstration can choose real-time sight
It sees, also can choose directly observation result.Carriage voluntarily stops after returning within some distance of initial position, then may be used
The collected data of institute in emulation are analyzed and be handled, modify initial parameter, propose line algorithm and control algolithm etc..It can
The picture in dynamic demonstration is saved and is synthesized cardon with selection, convenient for the exchange of other members and share, more
Intuitively, vividly.
Embodiment 2
Concrete operations are same as Example 1, and difference is that the racing track top view imported in step 1 is different, such as Figure 10
It is shown；Final dynamic demonstration is as shown in figure 11, and all moment simulated show as the linear CCD sampled value of 3 dimension forms
As shown in figure 12.Actual racing track is not easy to be designed to equidistant helix form, but is easy to draw equidistant spiral shell in software
Spin line, when carriage along equidistant helix racing track when driving because radius of curvature constantly changes, this makes it possible to be apparent
Find out that excessively curved performance of the intelligent vehicle under which kind of radius of curvature is relatively good, which kind of is poor, when it is possible that crimping
Or the case where out-of-bounds, control algolithm can be targetedly adjusted according to this.The obtained data of emulation can be carried out analysis and
Processing, can obtain the collected boundary information of CCD and offset, the trend and situation of change of curve be observed, to some data
Point is adjusted.
For the control algolithm in embodiment, the scalability of this modeling method is very big, and control algolithm is not limited to PID,
It can be arbitrary form, as long as it is identical with the return value of plug-in to meet return value, mention line algorithm also similarly, the present invention
In mention line and control algolithm and can be specified by user oneself.
Claims (7)
1. a kind of method for establishing linear CCD carriage simulation model based on MATLAB, includes the following steps:
Step 1: establishing racing track model, by importing the racing track top view of picture format, while Set scale ruler；The ratio
Example ruler is the picture that width is number of pixels corresponding to racing track width in racing track top view, for actual size to be scaled picture
Plain grade size；Set the developed width of racing track；
Step 2: establishing carriage static models, and the carriage static models include wheel and vehicle body, and front-wheel is for turning
To rear-wheel is used to provide power；Setting vehicle body length, vehicle body is wide, wheel position, wheel is long, wheel is wide, radius of wheel, rear rotation
Speed；
Step 3: linear CCD camera shooting head model is established based on carriage static models, by fixed link by linear CCD camera
It is set to carriage top；Set the prediction of fixed link size, position, the subtended angle of linear CCD camera, linear CCD camera
The sampling interval of information and CCD camera；
Step 4: in racing track model, three points are determined to obtain the initial posture information of carriage, including the initial of carriage
Position, inceptive direction and initial front-wheel beat angle；
Step 5: establishing carriage kinematics model, is obtained based on carriage static models in the case where posture remains unchanged
The carriage pose situation at next moment；
Step 6: head model is imaged based on linear CCD, calculates the scanning range of linear CCD camera, and out of this scanning range
Racing track picture Pixel Information in obtain sampled value；
Step 7: setting mentions line algorithm, handles the sampled value that linear CCD camera obtains by mentioning line algorithm, obtains
The right boundary information and disalignment information of racing track；
Step 8: setting control algolithm controls the next traveling shape of carriage by proposing the off-centring information that line algorithm obtains
State；
Step 9: setting simulation process dynamic demonstration module, the linear CCD carriage that step 1~step 8 is obtained emulate mould
Type import simulation process dynamic demonstration module, Dynamically Announce carriage traveling track, front-wheel beat angle situation and each
The scanning range of sampling interval carriage linear CCD camera.
2. the method according to claim 1 for establishing linear CCD carriage simulation model based on MATLAB, feature exist
In introducing noise processed in the step six, the noise processed includes introducing light intensity coefficient to simulate different illumination items
Sampled value under part；Introduce random coefficient is influenced caused by sampled value with simulated environment noise and quality of hardware fluctuation；It introduces
Breadth coefficient is to simulate the trend that linear CCD camera sampled value is successively decreased from centre to two sides value.
3. the method according to claim 1 for establishing linear CCD carriage simulation model based on MATLAB, feature exist
In it is jpeg, bmp or png that racing track, which overlooks bitmap-format, in the step one；It is filled out inside racing track in the racing track top view
It fills for white, outside is filled with grey, and racing track edge uses black.
4. the method according to claim 1 for establishing linear CCD carriage simulation model based on MATLAB, feature exist
In linear CCD camera model in the step three are as follows:
In formula, p is vertical range of the mass center away from linear CCD camera ground based scanning line, b be between fixed link and mass center away from
It is radius of wheel from, r, it is the subtended angle of linear CCD camera that h, which is fixed link height, γ, and w is linear CCD camera ground based scanning
The width of line.
5. the method according to claim 1 for establishing linear CCD carriage simulation model based on MATLAB, feature exist
In carriage kinematics model in the step five are as follows:
In formula, α is the angle that carriage turns in a sampling interval, and β is mass center-hind axle-turning radius auxiliary angle, and θ is
Front-wheel beats angle；W is that vehicle body is wide, and L is vehicle body length；Δ t is sampling interval duration；R is radius of wheel；ω is rear wheel rotation speed.
6. the method according to claim 1 for establishing linear CCD carriage simulation model based on MATLAB, feature exist
In mentioning line algorithm in the step seven is the asymmetric one-dimensional small window filtering algorithm for becoming sash length；
Binaryzation is carried out to sampled value as threshold value according to the mean value of sampled value first, is then repeatedly calculated using one-dimensional small window filtering
Method filters out the fluctuation in binarization result, whether loses line using the fluctuation analytical judgment to processing result, finally obtains
The right boundary information and disalignment information of racing track.
7. the method according to claim 1 for establishing linear CCD carriage simulation model based on MATLAB, feature exist
In control algolithm is according to proposing disalignment information that line algorithm obtains multiplied by for control algolithm in the step eight
KpCoefficient beats the input quantity at angle as front-wheel next time to control the next travel condition of carriage.
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| CN102662402A (en) * | 2012-06-05 | 2012-09-12 | 北京理工大学 | Intelligent camera tracking car model for racing tracks |
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