CN107422730A - The AGV transportation systems of view-based access control model guiding and its driving control method - Google Patents
The AGV transportation systems of view-based access control model guiding and its driving control method Download PDFInfo
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
- G05D1/027—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means comprising intertial navigation means, e.g. azimuth detector
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0268—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means
- G05D1/0274—Control of position or course in two dimensions specially adapted to land vehicles using internal positioning means using mapping information stored in a memory device
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0278—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using satellite positioning signals, e.g. GPS
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Abstract
The invention discloses a kind of AGV transportation systems of view-based access control model guiding and its driving control method, including：D GPS locating module, for obtaining the absolute position of AGV dollies and course information；Visually-perceptible locating module, for identifying the visual beacon thing of the lane line on ground and laying, lane line and visual beacon thing are obtained relative to the spatial relation of vision sensor and the high accuracy positioning information of AGV dollies；Laser radar sensing module, for identifying position, motion state and the shape information of barrier in short range in front of AGV dollies；Data fusion module, for obtaining fused data；Path planning module, for carrying out the positioning of AGV dollies and path planning according to fused data and known map of navigation electronic, and positioning is supplied to vehicle control system with route programming result.Cost of the present invention is low, and precision is high, stable, securely and reliably, the full-automation of harbour container transport can be achieved.
Description
Technical field
The invention belongs to technical field of intelligent traffic, and in particular to a kind of AGV transportation systems of view-based access control model guiding and its
Driving control method.
Background technology
The containerzation of China's port traffic and the maximization of packaging ship, sky is brought to traditional port traffic pattern
Preceding pressure, realize that the full-automation of harbour container transport seems more and more important.AGV (automatical pilot transportation vehicle) system can carry
The conevying efficiency of high harbour container, material resources, manpower and financial resources are saved, therefore showed great advantage.
AGV refers to magnetically or optically wait homing guidance device equipped with electricity, can be travelled along defined guide path, have peace
The transport vehicle of full guard and various transfer functions.AGV guide mode includes the guiding of direct coordinate, electromagnetism guides, tape is led
Draw, the guiding of optical navigation, inertial navigation, GPS (global positioning system) guiding, las er-guidance, visual guidance etc..In practical application
It is middle using it is more be electromagnetism or tape guidance, it pastes tape in embedded underground metal wire or on road surface, allows AGV dollies to travel
On predetermined track, its advantage is that lead is not easily susceptible to pollution and breakage, is easy to control and communicates.Its shortcoming is that path is difficult to
Change extension, has significant limitation, when workload increase, it is necessary to lay new track to pahtfinder hard.Under comparing,
Visual guidance then has considerable flexibility and relatively low cost, and visual apparatus is easy for installation.It is to pass through that it, which guides principle,
Vision system obtains current image information in real time, after software and hardware is handled determine AGV dollies position and with other things
The relative position of body, the dynamical system of dolly is driven to travel.Visual guidance has very high requirement to light and visual beacon, by outer
Boundary's environment has a great influence, so there is also many Research Challenges.
Certain particularity be present in port traffic AGV.The general area in harbour is larger, environment is more complicated, while needs very high
Operating efficiency, so AGV positioning is of crucial importance, it is necessary to realization be accurately positioned.Harbour environment is more special, easily by salt fog
Influence, humidity is larger, and this also brings challenge to AGV positioning and guiding.Harbour AGV needs can be normal in day and night
Work, so needing to consider light problem, the laying of visual beacon thing is especially true, meanwhile, carry out obstacle using laser radar
Analyte detection and avoidance can reach more preferable effect.A kind of safe and reliable AGV system is studied, for realizing that port traffic is automatic
Change, realize that the traditional port traffic pattern of low-cost high-efficiency, change is significant.
Publication No. 106444765A Chinese patent disclose a kind of AGV, view-based access control model AGV air navigation aids and its be
System, the AGV air navigation aids of the view-based access control model include step：1. obtain the picture of ground rail；2. to the reference horizontal line of picture
Gray proces are carried out, obtain reference horizontal line array；3. multiple reference horizontal line arrays are formed into track matrix；4. to orbital moment
Adjacent two rows up and down of battle array carry out XOR processing, obtain rail flanges information；5. processing is digitized to rail flanges information,
Controller as AGV inputs, to realize AGV motion control.The rail obtained using the AGV air navigation aids of the view-based access control model
Road marginal information precision is high, and quick navigation can be achieved.
Publication No. 104792333A Chinese patent discloses a kind of AGV intelligent visions navigation system and processing method,
The AGV intelligent visions navigation system includes image capture mechanism, image procossing mechanism and display structure.The AGV intelligent visions are led
The processing method of boat system includes step：1. scanning two marginal points of guide wire and calculating its coordinate, obtained by fitting a straight line
Obtain the linear equation of guide wire；2. obtain the position deviation and the deviation of directivity between AGV dollies and guide wire using linear equation.
What the AGV intelligent vision navigation system mainly solved is the identification problem of interrupted guide wire and incomplete curve, be compensate for
The defects of traditional magnetic navigation, the change and construction of track can be better achieved.
Notification number is that CN 103019240B Chinese patent discloses a kind of AGV dollies plane positioning navigation system and side
Method, the AGV dolly plane positionings navigation system include AGV dollies, map data base, ultrasonic sensor modules, steering wheel module,
Rotary angle transmitter module and microprocessor module.Wherein map data base is stored in microprocessor module, for providing mesh
Target positional information；Ultrasonic sensor modules are arranged on the front end of AGV dollies and the center in left side, for determining AGV
The distance of dolly front and side simultaneously transfers data to microprocessor module；Steering wheel module and the steering link phase of AGV dollies
Connection, for controlling AGV dollies to turn to；Microprocessor module is used to handle the data received in real time；Rotary angle transmitter module
It is installed on the column tube of AGV dollies, for measuring the corner of AGV dollies.The AGV dolly plane positionings air navigation aid uses
Ultrasonic sensor obtains the range information of dolly front and side, after being matched with existing map data base, using fixed
Position algorithm determines the position of dolly, and pilot trolley advances.The main advantage of this method be without traditional guide rail, and
Ultrasonic ranging cost is low, operating efficiency is high.
Summary, existing AGV location and navigation technologies use electromagnetism or tape guide device mostly, guide AGV dollies
Traveling is on predetermined track, and this method laying track cost is higher, and driving path is single, flexibility is poor, positioning precision is low,
And it is not easy to installation and safeguards and transform.The location and navigation technology of existing view-based access control model guiding also relies on AGV guide rails mostly
Road, the image of track is obtained using visual apparatus, and then is positioned and is navigated, the problem of equally existing very flexible.And make
The problem of being carried out ranging with ultrasonic sensor then existence and stability be poor, accuracy is low.
The present invention realizes the coarse localization of AGV dollies using GPS, realizes being accurately positioned for AGV dollies using vision, breaks away from
A kind of constraint of conventional rails, there is provided the AGV transportation systems that cost is low, flexibility is good, positioning precision is high.
The content of the invention
It is an object of the invention to provide it is a kind of it is more flexible, use cost is low, be easily installed safeguard and transformation view-based access control model
The AGV transportation systems of guiding and its driving control method.
To reach above-mentioned purpose, the present invention adopts the following technical scheme that：
First, a kind of AGV transportation systems of view-based access control model guiding, including：
D GPS locating module, visually-perceptible locating module, laser radar sensing module, data fusion module, path planning mould
Block and vehicle control module；Wherein：
D GPS locating module further comprises GPS submodules, inertial navigation submodule and rotary coding submodule, and rotation is compiled
Numeral module utilizes the rotary encoder on AGV car wheels, obtains rotary coding data；Inertial navigation submodule and
GPS submodules utilize the GPS/INS on AGV dollies, obtain inertial navigation data and gps data respectively；GPS submodules will
Rotary coding data, inertial navigation data and gps data fusion, obtain absolute position and the course information of AGV dollies；
Visually-perceptible locating module, the lane line and cloth on ground are identified using the vision sensor on AGV dollies
If visual beacon thing, pass through the spatial relation that binocular visual positioning obtains lane line and visual beacon thing, utilization space
Resection method realizes the high accuracy positioning of AGV dollies；
Laser radar sensing module, AGV dollies front closely model is identified using the laser radar located at AGV dolly headstocks
Enclose position, motion state and the shape information of interior barrier；
Data fusion module, for the absolute position for obtaining d GPS locating module and course information, visually-perceptible positioning mould
The position for the barrier that the spatial relation and high accuracy positioning information and laser radar sensing module that block obtains obtain,
Motion state and shape information are merged, and obtain fused data；
Path planning module, for carrying out the positioning of AGV dollies and road according to fused data and known map of navigation electronic
Footpath is planned, and positioning is supplied into vehicle control system with route programming result, and driving for AGV dollies is controlled by vehicle control module
Sail state.
Further, vision sensor includes tri- cameras of A, B, C, and camera A is located at AGV dolly headstocks center, camera B
AGV dolly homonymies are located at camera C, wherein, camera B is located at car forequarter, and camera C is located at car side rear portion.
2nd, the driving control method of the AGV transportation systems of above-mentioned view-based access control model guiding, including：
Step 1, the combined calibrating model of laser radar and vision sensor is established, the Coordinate Conversion obtained between the two is closed
System；
Step 2, the absolute location information and course information of AGV dollies are obtained using d GPS locating module, utilizes visually-perceptible
Locating module obtains the locus of visual beacon thing and the high accuracy positioning information of AGV dollies, and mould is perceived using laser radar
The position of block acquisition barrier, speed, course information；
Step 3, d GPS locating module, visually-perceptible locating module, laser radar sensing module are obtained using RANSAC methods
All data taken are merged, and obtain the depth perception of high accuracy depth information and scene；Utilize the front truck and barrier of acquisition
Hinder the speed and course information of thing, judge the movement tendency of front truck and barrier, form the perception of dynamic scene；
Step 4, location information d GPS locating module and visually-perceptible locating module obtained and existing navigation map
Match somebody with somebody, realize the positioning of AGV dollies；Transitable global path is planned according to road net data, according to visually-perceptible locating module and
The local environment data that laser radar sensing module obtains, with reference to dynamic scene information, establish the driving behavior scene of AGV dollies
Model, the movement locus of AGV dollies is predicted using Quick Extended random tree method, generate preferable local path curve, realized dynamic
State path planning；
Step 5, vehicle control module provides decision support according to active path planning for AGV dolly driving behaviors.
Further, using visually-perceptible locating module obtain visual beacon thing locus and AGV dollies it is high-precision
Location information is spent, is specially：
1. the two images of same visual beacon thing are obtained using two vision sensors positioned at diverse location, it is described
Vision sensor is camera；
2. vision sensor is demarcated using Zhang Zhengyou plane reference methods；
3. feature point extraction is carried out to two images using Scale invariant features transform method；
4. carrying out measuring similarity to the characteristic point of two images using Euclidean distance, match point is obtained；
5. utilize the depth information of the same point caused disparity computation point in two images；
6. using spatial point known to picpointed coordinate and three-dimensional coordinate, utilization space resection method calculates AGV dollies
Position coordinates.
Further, using the position of laser radar sensing module acquisition barrier, speed, course information, it is specially：
1. utilize the laser radar data in front of laser radar collection AGV dollies；
2. barrier point in laser radar data is clustered using neighbour's domain method and rule-based classification algorithm；
3. setting the characteristic parameter of barrier cluster, the type of barrier is determined using the correlation analysis of confidential interval,
Specially：
Each cluster subset is described using three area metrics, barycenter polar coordinates, confidential interval characteristic parameters, gathered
The area metrics of class subset, distance range of the subset in the horizontal direction with vehicle heading is represented, and using polar coordinates
The scope of all obstacle object points represented；All obstacle object points is polar equal in the barycenter polar coordinates subset of cluster subset
Value represents；The confidential interval of barrier is the average and mean square deviation by clustering subset, is asked for by standardized normal distribution；Put
After believing section, by data correlation valuation functions, barrier cluster the being associated property analysis to adjacent moment, obstacle is determined
The motion state of thing；
4. determining the position of barrier, speed, course information to same barrier progress coordinate transformation, it is specially：
Using laser radar point as the origin of coordinates, coordinate system is established by the longitudinal axis of AGV dollies travel direction, in the sampling period,
The distance and deflection angle moved according to AGV dollies, the barrier center-of-mass coordinate of t is converted under t-1 moment coordinate systems
Coordinate, according under t-1 moment coordinate systems, the position relationship of same barrier at different moments, that is, obtain the speed of the barrier with
Course.
Existing AGV location and navigation technologies use electromagnetism or tape guide device mostly, and guiding AGV dolly travelings are predetermined
Track on, this method laying track cost it is higher, driving path is single, flexibility is poor, and be not easy to installation safeguard and change
Make.The location and navigation technology of existing view-based access control model guiding also depends on AGV guide rails mostly, and rail is obtained using visual apparatus
The image in road, and then positioned and navigated.And using ultrasonic sensor progress ranging, then existence and stability is poor, accuracy is low
The problem of.
The present invention realizes the coarse localization of AGV dollies using GPS, and being accurately positioned for AGV dollies is realized using binocular vision,
Barrier closely is detected using laser radar and carries out avoidance, can break away from the constraint of traditional AGV guide rails, is avoided multiple
The laying of miscellaneous track, route have more flexibility.The installation and maintenance of sighting device (for example, camera) are also more convenient,
And cost is low, meanwhile, the present invention also has at a relatively high positioning precision and detection of obstacles ability.
Compared to the prior art, the present invention has following features：
(1) coarse positioning of AGV dollies is realized using GPS.GPS location precision height, good reliability, it is not easy by environmental factor
Influence, round-the-clock, round-the-clock, multidimensional Continuous Observation can be carried out, and the track guiding that need not navigate, traditional AGV tracks can be broken away from.
GPS location precision need to only reach meter level in the present invention, and the GPS device of meter accuracy is cheap, thus escapable cost.
(2) fine positioning of AGV dollies is realized using binocular vision.Binocular visual positioning need to only install two phases on AGV
Machine, cost is low, convenient for installation and maintenance, and has optimal flexibility, can avoid the laying of complicated railroad tracks.Binocular vision simultaneously
Positioning uses photogrammetric general principle, and principle is simple, easily realizes, and have higher positioning precision.
(3) identify barrier closely using laser radar and carry out avoidance processing.Laser radar has very accurate
Range capability, high angle, distance, velocity resolution can be obtained；And its strong antijamming capability, reliability is high, very suitable
Close detection barrier.
Compared to the prior art, the invention has the advantages that and beneficial effect：
(1) cost is low, and the GPS device and vision sensor cost of meter accuracy are than relatively low；
(2) precision is high, and binocular stereo vision localization method can reach high positioning precision；
(3) it is stable, safe and reliable, the full-automation of harbour container transport can be achieved；
(4) it is more flexible, port traffic operating efficiency can be improved, obtains more preferable economic benefit.
Brief description of the drawings
Fig. 1 is the structured flowchart of AGV transportation systems of the present invention；
Fig. 2 is the structured flowchart of d GPS locating module；
Fig. 3 is the driving control method flow chart of AGV transportation systems of the present invention；
Fig. 4 is the flow chart of the localization method of d GPS locating module；
Fig. 5 is the flow chart of the localization method of visually-perceptible locating module；
Fig. 6 is the flow chart of laser radar sensing module.
Embodiment
The specific embodiment of the invention will be described further below.
In the present embodiment, existing AGV dollies are reequiped, i.e. additional equipment.The AGV dollies vehicle is conducted oneself with dignity 9.5 tons, preceding
6.8 tons of axle maximum load capacity, 6.8 tons of rear axle maximum load capacity, 363 tons, long 15m, wide 3.1m, high 2.4m of payload ratings,
Wheel diameter 4.2m.AGV dollies refiting scheme includes additional equipment and electrical design.
The equipment installed additional on AGV dollies mainly include laser radar, GPS/INS, camera, computer (PC), controller and
Power module, wherein, GPS, computer and controller are installed in the canyon of AGV dollies；Laser radar is installed on
Position high the AGV dolly headstocks liftoff 2.1m in center, for identifying that barrier, the delimitation vehicle body of AGV dollies closely are guarded against
Area and reduction blind area.Gps antenna is placed in headstock, for vehicle location and course-angle mensurement.Color camera includes A, B, C tri-
Individual, camera A is installed at the AGV dolly headstocks liftoff 2m in center, and camera B is installed on car and leaned to one side forward position, camera C installations
Leaned to one side rearward position in car, camera B and camera C are located at AGV dolly homonymies.Three cameras are used for during AGV dollies traveling
Identify visual beacon thing.Computer is used to handle perception data and carries out path planning, and controller issues for performing computer
To the control instruction of vehicle, power module is used for laser radar, GPS/INS, camera, computer (PC), controller power supply.
AGV transportation systems of the present invention, its workflow are：1. AGV dollies receive the control instruction of controller transmission, fortune
Row arrives gantry crane；2. AGV dollies are run at AGV companions in gantry crane load after container；3. container is placed on AGV by AGV dollies
Wait suspension bridge that container is put into a heap at companion.The present invention realizes AGV dollies and gantry crane rail by visually-perceptible locating module
The relative positioning in road, gantry crane and AGV companions, and AGV dollies are accurately positioned.Therefore need in gantry crane, AGV companions and ground cloth
If vision recognition mark, auxiliary AGV dollies carry out vision positioning, and the present invention is in surface deployment lane line, in gantry crane and AGV companions
Upper laying "+" word mark.
See Fig. 1, the AGV transportation systems of view-based access control model guiding of the present invention include：D GPS locating module, visually-perceptible positioning mould
Block, laser radar sensing module, data fusion module, path planning module and vehicle control module.Wherein, d GPS locating module
Absolute fix is carried out to AGV dollies using GPS, recycles inexpensive inertial navigation system and odometer to carry out dead reckoning, and
Obtain the course information of vehicle.Visually-perceptible locating module is using the lane line on vision sensor identification ground and lays manually
Visual beacon thing, obtain lane line and visual beacon thing relative to camera spatial relation and AGV dollies it is high-precision
Spend positional information.Laser radar sensing module obtains the laser scanning data in front of AGV dollies using laser radar, by processing
The barrier in AGV dolly short ranges is identified afterwards.D GPS locating module, visually-perceptible locating module, laser radar perceive mould
Block is connected with data fusion module, and output of the data fusion module to these three modules carries out autotelic fusion, and will
Data after fusion are supplied to path planning module and vehicle control module.Path planning module navigation through electronic known to
Figure carries out the positioning of AGV dollies and path planning, and positioning is supplied into vehicle control system with route programming result, by vehicle control
The driving condition of system control AGV dollies processed.
D GPS locating module is used to realize the absolute fix during AGV dollies traveling, and d GPS locating module further comprises
GPS submodules, inertial navigation submodule and rotary coding submodule, are shown in Fig. 2.GPS submodules, for receiving gps satellite signal,
And by gps data and inertial navigation data, rotary coding data fusion, obtain absolute position and the course information of AGV dollies.It is used
Property d navigation submodule, for receiving the data of inertial navigation system, and be input in GPS submodules and GPS location data, rotation
Encoder data merges.In practical application, easily there is dropout situation in GPS, and inertial navigation submodule can be used to believe in GPS
Data under number loss situation calculate.Rotary coding submodule, the mileage information of vehicle is obtained using rotary encoder, and is inputted
Merged into GPS submodules with GPS location data, inertial navigation data, and can obtain the course angle of vehicle.Rotary encoder is pacified
Loaded on wheel, the mileage number of vehicle is calculated in the number of turns rotated in vehicular motion by calculating vehicle.
Visually-perceptible locating module using vision sensor obtain visual beacon thing locus and AGV dollies it is high-precision
Spend location information.In this specific implementation, vision sensor includes three color cameras, is designated as camera A, camera B and camera respectively
C.Camera A is installed at the AGV dolly vehicle fronts liftoff 2m in center, and camera B is installed on the forward position in AGV dollies side,
Camera C is installed on AGV dollies side rearward position, and its investigative range is 40 °, is gathered during being travelled for AGV dollies
Lane line and the visual beacon thing manually laid.Track of the visually-perceptible locating module using binocular visual positioning method to collection
Line and visual beacon thing are handled, calculate lane line and visual beacon thing relative visual sensor spatial relation and
The high precision position information of AGV dollies.Binocular visual positioning method is specially：For the two of the same object of two camera shootings
Width image, the characteristic point of image is extracted using Scale invariant features transform (SIFT) method and matched, obtains match point；Utilize
The calibrating parameters of epipolar-line constraint relation and camera between match point solve the space coordinates of the point；Utilization space resection
Method calculates the position coordinates of camera；It is final calculate the spatial relation of lane line and visual beacon thing with respect to camera and
The high precision position coordinate of AGV dollies.When visual beacon thing is equal to 4 meters with respect to the distance of AGV dollies, vehicle control system control
AGV dollies processed stop.
Laser radar sensing module utilizes the identification of laser radar AGV dolly front obstacles.Laser radar is installed on AGV
Dolly headstock center is liftoff high 2.1m position, its detection range is 80m, and detection angle is 190 °, for gathering AGV dollies
Laser radar data in short range.Laser radar data is clustered, the characteristic parameter of analysis cluster barrier, really
Determine the type of barrier, final position, motion state and the shape information for obtaining barrier.Vehicle control module is according to barrier
Position, motion state and shape information, take avoidance measure, such as slow down, turn, parking, avoid colliding.
The driving control method of the present invention is shown in Fig. 3, including step：
1. establishing the combined calibrating model of laser radar and camera, coordinate transformation relation between the two is obtained.Laser thunder
Up to distance and angle information of the packet containing target, the positional information of scanning element can be obtained by calculating.Utilize laser radar pair
Special scaling board is scanned, and scan data is handled to obtain the particular location of radar data point, by radar data point
Matched with the corresponding image pixel point shot by camera, obtain a series of match points.For these matching double points, profit
Relativeness between the two is asked for parameter fitness method, the demarcation of laser radar and camera is realized, obtains between the two
Position orientation relation.
2. obtaining the positional information and course information of AGV dollies using d GPS locating module, visually-perceptible locating module is utilized
The spatial positional information of visual beacon thing and the high accuracy positioning information of AGV dollies are obtained, is obtained using laser radar sensing module
Take the position of barrier, speed, course information.
3. the data of all acquisitions are merged using RANSAC methods, to obtain high accuracy depth information and scene
Depth perception.Using the front truck of acquisition and the speed of barrier and course information, the movement tendency of judgement front truck and barrier,
Form the perception of dynamic scene.
4. the location information that d GPS locating module and visually-perceptible locating module are obtained matches with existing navigation map,
The positioning of AGV dollies is realized, and transitable global path is planned according to road net data.According to visually-perceptible locating module and swash
The local environment data that optical radar sensing module obtains, with reference to dynamic scene information, establish the driving row such as lane change, avoidance of vehicle
For model of place, the movement locus of vehicle is predicted using the random tree algorithm of Quick Extended (RRT), it is bent to generate preferable local path
Line, realize active path planning.
5. determining the final driving behavior of AGV dollies by vehicle control module, decision support is provided for driving behavior.
See Fig. 4, the localization method of d GPS locating module includes：1. obtain GPS location data using GPS；2. utilize
Inertial navigation system obtains inertial navigation data；3. obtain rotary coding data using rotary encoder；4. using extending karr
Graceful wave filter merges to GPS location information, inertial navigation data and vehicle mileage information, obtains the position of AGV dollies
And course information.
See Fig. 5, the localization method of visually-perceptible locating module includes：
1. IMAQ：The two images of same visual beacon thing are obtained using two cameras positioned at diverse location.
2. camera calibration：Camera is demarcated using Zhang Zhengyou plane reference methods.Zhang plane references method utilizes plane
Template carries out the demarcation of camera inside and outside parameter, obtains several template images that camera is shot from different perspectives first, then utilizes
Corresponding relation between the point on point and image in template forms mapping matrix, and camera internal parameter is constructed by mapping matrix
Two constraintss, solve inner parameter using linear solution, finally utilize inner parameter and mapping matrix to solve outside join
Number, realizes camera calibration.
3. feature extraction：SIFT feature extraction is carried out to two images.SIFT algorithms pass through the different scale in image
Some are spatially found not because of the characteristic point of the changes such as illumination, affine transformation, and calculates its direction, to generate characteristic vector.It is first
Image pyramid is established first with Gaussian kernel, to ensure the validity of detection characteristic point, builds difference of Gaussian (DOG) pyramid；
Extremum extracting is carried out in DOG pyramids and is accurately positioned extreme point, obtains stable local feature region.Then characteristic point is utilized
The gradient direction distribution characteristic of neighborhood territory pixel is each characteristic point assigned direction, SIFT operators is had rotational invariance.Finally
8 × 8 windows centered on characteristic point are taken, the gradient orientation histogram in 8 directions are calculated in every 4 × 4 window, then each
Characteristic point can form the characteristic vector of one 128 dimension, it is normalized to eliminate the influence of illumination.
4. Stereo matching：Using Euclidean distance to step 3. in obtain two images SIFT feature vector carry out it is similar
Degree measurement, finds out the characteristic point in the another piece image nearest with the Euclidean distance of the characteristic point in piece image.First to one
Some characteristic point in width image, its Euclidean distance with the characteristic point of another piece image is calculated, find out preceding the two of distance minimum
Individual characteristic point.Then closest distance and the ratio of secondary adjacency are calculated, if the ratio is less than proportion threshold value set in advance,
Then the match is successful, otherwise as erroneous matching.
5. depth recovery：Using same point, caused parallax calculates the point by vision range finding principle in two images
Depth information.Epipolar geom etry relation be present from the image of the same target of different points of view shooting, i.e. the matching of step 4. middle acquisition
Epipolar-line constraint be present between point, the relation that can be established between match point by the constraint.Utilization space a little in two images
Picpointed coordinate and camera inside and outside parameter, according to camera imaging model, build the equation group being made up of four linear equations, should
Equation group draws unique solution using the world coordinates of the point as unknown number, using least square method, and the as point is in world coordinates
Three-dimensional coordinate under system.
6. AGV dolly high accuracy positionings：Using step 5. in obtained a number of picpointed coordinate and three-dimensional coordinate
The spatial point known, utilization space resection method calculate the position coordinates of AGV dollies.
In the present invention, the handling process of laser radar sensing module is shown in Fig. 6, further comprises：
1. utilize the laser radar data in front of laser radar collection AGV dollies.By with the range data of polar coordinate representation
Be converted to rectangular co-ordinate information, i.e. obstacle object point and the distance x and obstacle object point distance AGV dollies of AGV dollies in the horizontal direction
The distance y in front.
2. barrier point in laser radar data is clustered using neighbour's domain method and rule-based classification algorithm.In laser
Radar sampling moment t, if two continuous obstacle object points are equal with distance difference Δ x, the Δ y of vehicle heading in the horizontal direction
Less than threshold value set in advance, then the two barrier points are classified as one kind, and so on, set until the number of obstacle object point is more than
Fixed threshold value, then these obstacle object points are same class barrier.In this way, complete the cluster of all obstacle object points.
3. the characteristic parameter of setting cluster barrier, the type of barrier is determined using the correlation analysis of confidential interval.
After carrying out space clustering to barrier point, to each cluster subset using area metrics, barycenter polar coordinates, confidential interval three
Characteristic parameter describes.The area metrics of subset are clustered, represent the subset in the horizontal direction with vehicle heading apart from model
Enclose, and the scope of all obstacle object points using polar coordinate representation.Subset barycenter polar coordinates are clustered, with all obstacles in subset
Polar average of object point represents.The confidential interval of barrier, by clustering the average and mean square deviation of subset, by standard normal
Confidential interval is asked in distribution.After obtaining confidential interval, by data correlation valuation functions, the barrier of adjacent moment is clustered
Being associated property is analyzed, and determines the motion state of barrier.So as to can determine that the barrier is the obstacle with vehicle geo-stationary
Thing, different barriers is still fallen within, or be the barrier being kept in motion.
4. the position of barrier, speed, course information are determined to same barrier progress coordinate transformation.With laser radar point
For the origin of coordinates, coordinate system is established using AGV dolly travel directions as the longitudinal axis.In sampling period T, moved according to AGV dollies
Distance and deflection angle, are converted into the coordinate under t-1 moment coordinate systems by the barrier center-of-mass coordinate of t, are sat according to the t-1 moment
Under mark system, the position relationship of same barrier at different moments, you can obtain speed and the course of the barrier.
Claims (5)
1. the AGV transportation systems of view-based access control model guiding, it is characterized in that, including：
D GPS locating module, visually-perceptible locating module, laser radar sensing module, data fusion module, path planning module and
Vehicle control module；Wherein：
D GPS locating module further comprises GPS submodules, inertial navigation submodule and rotary coding submodule, rotary coding
Module utilizes the rotary encoder on AGV car wheels, obtains rotary coding data；Inertial navigation submodule and GPS
Module utilizes the GPS/INS on AGV dollies, obtains inertial navigation data and gps data respectively；GPS submodules will rotate
Coded data, inertial navigation data and gps data fusion, obtain absolute position and the course information of AGV dollies；
Visually-perceptible locating module, lane line and the laying on ground are identified using the vision sensor on the AGV dollies
Visual beacon thing, the spatial relation of lane line and visual beacon thing, utilization space rear are obtained by binocular visual positioning
Intersection realizes the high accuracy positioning of AGV dollies；
Laser radar sensing module, identified using located at the laser radar of AGV dolly headstocks in front of AGV dollies in short range
Position, motion state and the shape information of barrier；
Data fusion module, obtained for the absolute position for obtaining d GPS locating module and course information, visually-perceptible locating module
The position for the barrier that the spatial relation and high accuracy positioning information and laser radar sensing module obtained obtains, motion
State and shape information are merged, and obtain fused data；
Path planning module, advised for carrying out the positioning of AGV dollies according to fused data and known map of navigation electronic with path
Draw, and positioning is supplied to vehicle control system with route programming result, the driving shape of AGV dollies is controlled by vehicle control module
State.
2. the AGV transportation systems of view-based access control model guiding as claimed in claim 1, it is characterized in that：
Described vision sensor includes tri- cameras of A, B, C, and camera A is located at AGV dolly headstocks center, camera B and camera C
Located at AGV dolly homonymies, wherein, camera B is located at car forequarter, and camera C is located at car side rear portion.
3. the driving control method of the AGV transportation systems of the view-based access control model guiding described in claim 1, it is characterized in that, including：
Step 1, the combined calibrating model of laser radar and vision sensor is established, obtains coordinate transformation relation between the two；
Step 2, the absolute location information and course information of AGV dollies are obtained using d GPS locating module, is positioned using visually-perceptible
Module obtains the locus of visual beacon thing and the high accuracy positioning information of AGV dollies, is obtained using laser radar sensing module
Take the position of barrier, speed, course information；
Step 3, d GPS locating module, visually-perceptible locating module, laser radar sensing module are obtained using RANSAC methods
All data are merged, and obtain the depth perception of high accuracy depth information and scene；Utilize the front truck and barrier of acquisition
Speed and course information, judge the movement tendency of front truck and barrier, form the perception of dynamic scene；
Step 4, the location information that d GPS locating module and visually-perceptible locating module obtain is matched with existing navigation map,
Realize the positioning of AGV dollies；Transitable global path is planned according to road net data, according to visually-perceptible locating module and laser
The local environment data that radar sensing module obtains, with reference to dynamic scene information, establish the driving behavior scene mould of AGV dollies
Type, the movement locus of AGV dollies is predicted using Quick Extended random tree method, generate preferable local path curve, realize dynamic
Path planning；
Step 5, vehicle control module provides decision support according to active path planning for AGV dolly driving behaviors.
4. the driving control method of the AGV transportation systems of view-based access control model guiding as claimed in claim 3, it is characterized in that：
The described spatial relation that visual beacon thing relative visual sensor is obtained using visually-perceptible locating module, specifically
For：
1. the two images of same visual beacon thing, described vision are obtained using two vision sensors positioned at diverse location
Sensor is camera；
2. vision sensor is demarcated using Zhang Zhengyou plane reference methods；
3. feature point extraction is carried out to two images using Scale invariant features transform method；
4. carrying out measuring similarity to the characteristic point of two images using Euclidean distance, match point is obtained；
5. utilize the depth information of the same point caused disparity computation point in two images；
6. using spatial point known to picpointed coordinate and three-dimensional coordinate, utilization space resection method calculates the position of AGV dollies
Put coordinate.
5. the driving control method of the AGV transportation systems of view-based access control model guiding as claimed in claim 3, it is characterized in that：
Using the position of laser radar sensing module acquisition barrier, speed, course information, it is specially：
1. utilize the laser radar data in front of laser radar collection AGV dollies；
2. barrier point in laser radar data is clustered using neighbour's domain method and rule-based classification algorithm；
3. setting the characteristic parameter of barrier cluster, the type of barrier is determined using the correlation analysis of confidential interval, specifically
For：
Each cluster subset is described using three area metrics, barycenter polar coordinates, confidential interval characteristic parameters, cluster
The area metrics of collection, distance range of the subset in the horizontal direction with vehicle heading is represented, and using polar coordinate representation
All obstacle object points scope；Cluster polar average table of all obstacle object points in the barycenter polar coordinates subset of subset
Show；The confidential interval of barrier is the average and mean square deviation by clustering subset, is asked for by standardized normal distribution；Obtain confidence area
Between after, by data correlation valuation functions, barrier cluster the being associated property analysis to adjacent moment, determine barrier
Motion state；
4. determining the position of barrier, speed, course information to same barrier progress coordinate transformation, it is specially：
Using laser radar point as the origin of coordinates, coordinate system is established by the longitudinal axis of AGV dollies travel direction, in the sampling period, according to
The distance and deflection angle of AGV dollies movement, the coordinate under t-1 moment coordinate systems is converted into by the barrier center-of-mass coordinate of t,
According under t-1 moment coordinate systems, the position relationship of same barrier at different moments, that is, speed and the course of the barrier are obtained.
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