CN116312014B - Intelligent navigation method for parking lot - Google Patents
Intelligent navigation method for parking lot Download PDFInfo
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- CN116312014B CN116312014B CN202310401072.6A CN202310401072A CN116312014B CN 116312014 B CN116312014 B CN 116312014B CN 202310401072 A CN202310401072 A CN 202310401072A CN 116312014 B CN116312014 B CN 116312014B
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- 238000004891 communication Methods 0.000 claims description 12
- 238000010276 construction Methods 0.000 claims description 12
- 238000012545 processing Methods 0.000 claims description 12
- 238000013178 mathematical model Methods 0.000 claims description 11
- 238000004364 calculation method Methods 0.000 claims description 8
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Classifications
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096805—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route
- G08G1/096811—Systems involving transmission of navigation instructions to the vehicle where the transmitted instructions are used to compute a route where the route is computed offboard
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096877—Systems involving transmission of navigation instructions to the vehicle where the input to the navigation device is provided by a suitable I/O arrangement
- G08G1/096883—Systems involving transmission of navigation instructions to the vehicle where the input to the navigation device is provided by a suitable I/O arrangement where input information is obtained using a mobile device, e.g. a mobile phone, a PDA
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/14—Traffic control systems for road vehicles indicating individual free spaces in parking areas
- G08G1/141—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces
- G08G1/144—Traffic control systems for road vehicles indicating individual free spaces in parking areas with means giving the indication of available parking spaces on portable or mobile units, e.g. personal digital assistant [PDA]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/60—Electric or hybrid propulsion means for production processes
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Abstract
The invention discloses an intelligent navigation method for a parking lot, which belongs to the technical field of three-dimensional parking lots and comprises the steps of establishing an AGV car navigation system and an AGV car monitoring system, identifying outline marks and subtitle marks projected by projection lamps on an AGV transport car, identifying the running state of the AGV transport car according to the outline marks, calculating value scores of avoidance vehicles by adopting a greedy algorithm, judging which vehicles avoid, solving the technical problems that the actual monitoring feedback of the AGV transport car is realized through a third party camera monitoring system, changing a traditional single-way lane into a double-way lane, and simultaneously carrying out translational avoidance scheduling on the AGV transport car according to the monitoring feedback.
Description
Technical Field
The invention belongs to the technical field of three-dimensional parking lots, and particularly relates to an intelligent navigation method for a parking lot.
Background
At present, parking is realized by adopting an AGV transport vehicle auxiliary parking mode, after a user downloads a parking application through a mobile phone end, the AGV transport vehicle can automatically bear the vehicle to reach a parking space in an access garage of the three-dimensional parking lot, and the AGV transport vehicle generally carries out scheduling and navigation through an AGV vehicle navigation system in the three-dimensional parking lot.
The AGV transporter in the three-dimensional parking lot generally adopts a vehicle tray to carry vehicles, that is, a user parks the vehicles in one vehicle tray in the access garage, and then the AGV transporter automatically travels below the vehicle tray to jack up the vehicle tray to carry the vehicles for movement.
The prior art has the following defects:
1. At present, a transport channel of an AGV transport vehicle is divided into two lanes, and the traveling direction of the AGV transport vehicle in the lanes is regulated in a one-way lane mode in the prior art, so that the actual transport efficiency is lower.
2. At present, the travel route and the travel state of the AGV transport vehicle are monitored in real time by adopting feedback data of sensors of the AGV transport vehicle, and a third party monitoring system does not monitor and feed back the actual running state of the AGV transport vehicle, so that the AGV transport vehicle cannot be monitored intuitively and accurately in real time.
Disclosure of Invention
The invention aims to provide an intelligent navigation method for a parking lot, which solves the technical problems that the actual monitoring feedback of an AGV transport vehicle is realized through a third party camera monitoring system, a traditional single-lane is changed into a double-lane, and meanwhile, the AGV transport vehicle is subjected to translational avoidance scheduling according to the monitoring feedback.
In order to achieve the above purpose, the invention adopts the following technical scheme:
An intelligent navigation method for a parking lot specifically comprises the following steps:
step 1: the method comprises the steps that an AGV navigation system and an AGV monitoring system are established, the AGV navigation system is used for providing scheduling information and navigation route data for AGV transport vehicles in a parking lot, the scheduling information comprises parking list numbers and vehicle access information, the AGV transport vehicles send speed data of the AGV transport vehicles to the AGV navigation system in the process of traveling, the AGV monitoring system comprises a plurality of monitoring cameras, a monitoring data acquisition server, a picture processing server and a model construction server, the monitoring cameras are deployed on a traffic channel of the AGV transport vehicles, and the monitoring data acquisition server is used for acquiring real-time traffic channel monitoring images shot by all the monitoring cameras through data lines;
each monitoring camera is preset with a unique identification serial number;
The vehicle access information is used for marking and representing a vehicle storage event or a vehicle taking event;
step 2: in the traveling process of the AGV, a contour mark for representing the contour of the AGV and a caption mark for representing a parking list number are projected on the ground through a projection lamp;
Step 3: when the AGV transport vehicle moves in the shooting range of any monitoring camera, the monitoring camera sends the shot traveling image of the AGV transport vehicle to a monitoring data acquisition server, and the monitoring data acquisition server sends the traveling image and the identification serial number of the monitoring camera shooting the traveling image to a picture processing server;
step 4: the picture processing server analyzes the travelling image through an image recognition technology and recognizes a contour mark and a caption mark;
The picture processing server marks the outline mark in the travelling image to obtain a mark image, and meanwhile, a parking list number is obtained according to the identification of the caption mark, and a mapping list among the parking list number, the mark image and the identification serial number is established;
Step 5: the model construction server constructs a mathematical model of the traffic channel in a world coordinate system, wherein the mathematical model is established by dividing the traffic channel into a left lane and a right lane according to the width of the traffic channel, and a safety interval is set between the left lane and the right lane;
the model construction server presets a translation threshold in a mathematical model of the traffic channel;
step 6: the model building server acquires speed data of the AGV from the AGV navigation system through the Internet;
the model building server calls the mark image, coordinates of the mark image are overlapped into a world coordinate system, and whether the AGV is located in a left lane or a right lane is judged according to the position of the outline mark:
if the AGV is in the left lane or the right lane, the AGV transport vehicle normally passes, the step 11 is executed, and if not, the step 7 is executed;
step 7: judging whether the position of the profile mark exceeds a translation threshold value: step 8 is executed; if not, executing the step 9;
step 8: judging the lane where the AGV is located:
if the position of the contour mark is the left lane, judging whether the position of the contour mark exceeds the maximum translation amount of left translation of the left lane according to the translation amount threshold value: if yes, the AGV carries out right translation; if not, executing the step 9;
if the position of the contour mark is the right lane, judging whether the position of the contour mark exceeds the maximum translation amount of right lane translation according to the translation amount threshold value: if yes, the AGV carries out left translation; if not, executing the step 9;
Step 9: judging whether a vehicle arrives or not: if not, the AGV transport vehicle normally passes, and the step 11 is executed; if yes, executing step 10;
step 10: the model construction server takes vehicle access information, parking unit number and vehicle speed as value conditions, calculates the priority values of two AGV transport vehicles in a left lane and a right lane through a greedy algorithm, and the AGV transport vehicles with low priority values translate and avoid the AGV transport vehicles with high priority values;
Step 11: and (5) ending.
Preferably, the AGV car navigation system comprises a navigation communication server and a scheduling server, wherein the AGV transport car is communicated with the navigation communication server through a wireless network, the navigation communication server is communicated with the scheduling server through a network cable, the scheduling server is used for acquiring a parking application sent by a user from a mobile phone through a mobile network, generating a parking single number according to the parking application, simultaneously marking a parking event corresponding to the parking single number as a car parking or car taking, generating vehicle access information, and the navigation communication server is used for drawing a navigation route of the AGV transport car according to the vehicle access information and the parking single number, sending the navigation route to the AGV transport car, and meanwhile, sending speed data sent by the AGV transport car through the mobile phone.
Preferably, the projection lamp is arranged at the front car light of the AGV transport vehicle, and when the projection lamp projects the outline mark, the adjustment angle of the projection lamp is calculated by adopting the following method:
Setting theta z as the rotation angle of the projection lamp on the vertical plane, setting theta y as the rotation angle of the projection lamp on the horizontal plane, and calculating theta z and theta y according to a trigonometric function formula:
tanθz＝d÷h；
tanθy＝w÷d；
Wherein d is the horizontal distance between the cursor projected by the projection lamp and the front lamp where the projection lamp is positioned, h is the height of the front lamp where the projection lamp is positioned from the ground, and w is the minimum distance between the front lamp where the projection lamp is positioned and the contour edge of the AGV;
The projection lamp performs an angle adjustment according to the rotation angle θ z and the rotation angle θ y, thereby projecting the outline marker on the ground.
Preferably, the outline mark is a preset geometric pattern light spot, and the subtitle mark is a digital light spot representing a parking list number.
Preferably, in executing step 10, the greedy algorithm is specifically calculated using the following formula:
Score(car(i))＝w1×value(access(i))+w2×value(number(i))+w3×value(V(i))；
Wherein Score represents a greedy Score, i represents a parking order number, car (i) represents a number of an AGV transport dispatched by an order of the parking order number i, value (access(i)) represents a Score of an access event of the order of the parking order number i, value (number(i)) represents a single number Score of the order of the parking order number i, value (V(i)) represents a speed Score of the AGV transport dispatched by the order of the parking order number i, and w 1、w2 and w 3 are weight values.
Preferably, the score of the access event is a fixed preset value, the access event comprises a parking event and a picking event, and the score of the parking event is smaller than the score of the picking event.
Preferably, in calculating the single number score, the calculation is performed by the following formula:
Wherein i represents a parking bill number, maxNUM represents the maximum number value in all the issued parking bill numbers, va (number) represents the maximum score assigned by the bill number score in a greedy algorithm;
In calculating the vehicle speed score, the calculation is performed by the following formula:
Where velocity (i) represents the actual speed of the AGV transport dispatched by the order with parking order number i, maxvelocity represents the maximum travel speed that the AGV transport can achieve, and va (V) represents the maximum score that the speed score is assigned to in the greedy algorithm.
Preferably, when executing step 4, the method specifically comprises the following steps:
step 4-1: acquiring a travelling image;
step 4-2: performing image preprocessing on the travelling image to obtain a preprocessed image;
step 4-3: carrying out gray scale treatment on the preprocessed image to obtain a gray scale image;
Step 4-4: carrying out gray scale identification on pixels in the gray scale map, and identifying a projection cursor of the projection lamp on the ground according to gray scale values of the pixels;
Step 4-5: identifying a contour mark and a caption mark according to the geometric shape of the projection cursor;
Step 4-6: setting a rectangular frame surrounding the outline mark at the outline mark to obtain a mark image;
step 4-7: and obtaining a parking list number according to the identification of the caption mark, and establishing a mapping list among the parking list number, the mark image and the identification serial number.
According to the intelligent navigation method for the parking lot, the technical problems that the actual monitoring feedback of the AGV transport vehicle is realized through a third party camera monitoring system, a traditional single-lane is changed into a double-lane, and meanwhile, the AGV transport vehicle is subjected to translational avoidance scheduling according to the monitoring feedback are solved.
Drawings
FIG. 1 is a main flow chart of the present invention;
FIG. 2 is a flow chart of step 10 of the present invention;
FIG. 3 is a diagram of a mathematical model of the present invention when calculating the adjustment angle of a projection lamp;
fig. 4 is a schematic diagram of a model of the invention for avoiding when an actual vehicle encounters.
Detailed Description
The intelligent navigation method for the parking lot as shown in fig. 1-4 specifically comprises the following steps:
step 1: the method comprises the steps that an AGV navigation system and an AGV monitoring system are established, the AGV navigation system is used for providing scheduling information and navigation route data for AGV transport vehicles in a parking lot, the scheduling information comprises parking list numbers and vehicle access information, the AGV transport vehicles send speed data of the AGV transport vehicles to the AGV navigation system in the process of traveling, the AGV monitoring system comprises a plurality of monitoring cameras, a monitoring data acquisition server, a picture processing server and a model construction server, the monitoring cameras are deployed on a traffic channel of the AGV transport vehicles, and the monitoring data acquisition server is used for acquiring real-time traffic channel monitoring images shot by all the monitoring cameras through data lines;
each monitoring camera is preset with a unique identification serial number;
The vehicle access information is used for marking and representing a vehicle storage event or a vehicle taking event;
The AGV car navigation system comprises a navigation communication server and a scheduling server, wherein the AGV transport vehicle is communicated with the navigation communication server through a wireless network, the navigation communication server is communicated with the scheduling server through a network cable, the scheduling server is used for acquiring a parking application sent by a user from a mobile phone through a mobile network, generating a parking single number according to the parking application, simultaneously marking a parking event corresponding to the parking single number as a parking or taking car, generating car access information, and the navigation communication server is used for drawing a navigation route of the AGV transport vehicle according to the car access information and the parking single number, sending the navigation route to the AGV transport vehicle, and meanwhile, sending speed data by the mobile phone AGV transport vehicle.
In this embodiment, the AGV car navigation system is a standard configuration system in the existing three-dimensional parking lot, and is in the prior art, and the present invention adds a third party monitoring system, that is, an AGV car monitoring system, on the basis of the AGV car navigation system, in the actual application process, a plurality of monitoring cameras can be deployed on the main traffic channel of the AGV transport vehicle, so that the effect of real-time monitoring is achieved.
Step 2: in the traveling process of the AGV, a contour mark for representing the contour of the AGV and a caption mark for representing a parking list number are projected on the ground through a projection lamp;
The projection lamp is prior art and will not be described in detail.
The projection lamp is arranged at the front car light of the AGV transport vehicle, the AGV transport vehicle is in the prior art, the front car light of the AGV transport vehicle comprises a left car light and a right car light, the left car light and the right car light respectively comprise a plurality of front car lights, two projection lamps are respectively arranged on the left car light and the right car light, one projection is used for representing the actual occupation profile of the AGV transport vehicle, the other projection is used for representing the parking unit number corresponding to the AGV transport vehicle, the monitoring camera is used for shooting a projection cursor to identify the running state of the AGV transport vehicle, and monitoring feedback is provided for an AGV navigation system more intuitively and accurately.
When projection lamp projection profile mark, because the AGV transport vechicle generally all bears a vehicle tray, the size of vehicle tray is greater than AGV transport vechicle self size in fact, so when carrying out projection profile mark, the projection angle of projection lamp is obtained after the edge that needs to be calculated vehicle tray in fact, when carrying out programming calculation in fact, regard AGV transport vechicle and vehicle tray as an organic wholely, the edge profile of vehicle tray promptly is the edge profile of AGV transport vechicle, this embodiment adopts the following method to calculate the adjustment angle who obtains the projection lamp:
Setting theta z as the rotation angle of the projection lamp on the vertical plane, setting theta y as the rotation angle of the projection lamp on the horizontal plane, and calculating theta z and theta y according to a trigonometric function formula:
tanθz＝d÷h；
tanθy＝w÷d；
Wherein d is the horizontal distance between the cursor projected by the projection lamp and the front car lamp (left car lamp or right car lamp) where the projection lamp is positioned, h is the height of the front car lamp (left car lamp or right car lamp) where the projection lamp is positioned from the ground, and w is the minimum distance between the front car lamp where the projection lamp is positioned and the contour edge of the AGV transport vehicle; the projection lamp performs an angle adjustment according to the rotation angle θ z and the rotation angle θ y, thereby projecting the outline marker on the ground.
Specifically, as shown in fig. 3, XYZ is a world coordinate system, point a is a position of a projection lamp, that is, a position of a front car light, d is a preset value, w represents a distance between an edge contour of an AGV transport vehicle and the front car light (that is, point a), h represents a height of the front car light (that is, point a), and an offset angle of the projection lamp on a horizontal plane and a vertical plane can be obtained through calculation of a trigonometric function, so that a position of a projection cursor is controlled.
The outline mark is a preset geometric pattern light spot, and the subtitle mark is a digital light spot representing a parking single number.
In this embodiment, in practical application, the geometric pattern light spot of the outline mark may be preset into a light spot pattern that is easy to be identified, such as a cross, a rectangle, or a circle.
Step 3: when the AGV transport vehicle moves in the shooting range of any monitoring camera, the monitoring camera sends the shot traveling image of the AGV transport vehicle to a monitoring data acquisition server, and the monitoring data acquisition server sends the traveling image and the identification serial number of the monitoring camera shooting the traveling image to a picture processing server;
step 4: the picture processing server analyzes the travelling image through an image recognition technology and recognizes a contour mark and a caption mark;
The picture processing server marks the outline mark in the travelling image to obtain a mark image, and meanwhile, a parking list number is obtained according to the identification of the caption mark, and a mapping list among the parking list number, the mark image and the identification serial number is established;
when executing the step 4, the method specifically comprises the following steps:
step 4-1: acquiring a travelling image;
step 4-2: performing image preprocessing on the travelling image to obtain a preprocessed image;
step 4-3: carrying out gray scale treatment on the preprocessed image to obtain a gray scale image;
Step 4-4: carrying out gray scale identification on pixels in the gray scale map, and identifying a projection cursor of the projection lamp on the ground according to gray scale values of the pixels;
Step 4-5: identifying a contour mark and a caption mark according to the geometric shape of the projection cursor;
Step 4-6: setting a rectangular frame surrounding the outline mark at the outline mark to obtain a mark image;
step 4-7: and obtaining a parking list number according to the identification of the caption mark, and establishing a mapping list among the parking list number, the mark image and the identification serial number.
The image recognition technique for recognizing the pattern by the gray value is the prior art, so that the analysis process thereof will not be described in detail.
Step 5: the model construction server constructs a mathematical model of the traffic channel in a world coordinate system, wherein the mathematical model is established by dividing the traffic channel into a left lane and a right lane according to the width of the traffic channel, and a safety interval is set between the left lane and the right lane;
the model construction server presets a translation threshold in a mathematical model of the traffic channel;
As shown in fig. 4, the left lane is set to be denoted by D (L 1,L2), the left lane is set to be denoted by D (R 1,R2), then the safety interval is set to be D (L 1,R2), wherein L 1 denotes the left edge of the left lane, L 2 denotes the right edge of the left lane, R 1 denotes the right edge of the right lane, R 2 denotes the left edge of the right lane, in this embodiment, the translation amount threshold is divided into a left translation threshold and a right translation threshold in actual application, the model building server divides the translation amount threshold of the left lane in the mathematical model of the traffic channel, setting a threshold value of L 1 to shift left as L 1o, a threshold value of L 1p,L2 to shift left as L 2o, a threshold value of L 2p,R1 to shift left as R 1o, a threshold value of R 1p,R2 to shift left as R 2o, and a threshold value of R 2p to shift right as R 1p,R2, when vehicles meet, the two vehicles are expressed as AGV_R and AGV_L and run on a lane D (R 1,L2) at the same time, acquiring a contour mark LA and a contour mark LB of the AGV_L by cameras L_N1 and L_N2 on a left lane D (L 1,L2), wherein the contour mark LA represents the left contour edge of the agv_l car, the contour mark LB represents the right contour edge of the agv_l car, and the contour mark RA and the contour mark RB of the agv_r car are obtained by the cameras r_n1 and r_n2 set on the right lane D (R 1,R2) for representing the right contour edge and the left contour edge of the agv_r car, respectively.
Step 6: the model building server acquires speed data of the AGV from the AGV navigation system through the Internet;
In this embodiment, the shooting area of the monitoring camera is a preset fixed area, and an image with a fixed size and a fixed focal length position can be obtained according to the shooting angle and the height of the monitoring camera, the size and the focal length position in the marker image are fixed values, and the local coordinate system where the marker image is located is overlapped into the world coordinate system, which is not described in detail. In this embodiment, only one coordinate system registration correction is required for each image shot by the monitoring camera, and the first registration correction result can be used in the post-processing.
Judging whether the AGV is positioned in a left lane or a right lane according to the position of the contour mark:
If the vehicle is in the left lane or the right lane, namely whether the actual driving position of the AVG vehicle is in D (R 1,R2) or D (L 1,L2), the AGV transport vehicle normally runs, the step 11 is executed, and if not, the step 7 is executed;
Step 7: determining whether the position of the profile mark has exceeded a translation threshold, i.e., whether the actual driving position of the AVG vehicle is within D (R 1o,R2o)、D(R1p,R2p)、D(L1o,L2o) or D (L 1p,L2p): step 8 is executed; if not, executing the step 9;
step 8: judging the lane where the AGV is located:
If the left lane is the left lane, judging whether the position of the contour mark exceeds the maximum translation amount of left lane translation according to the translation amount threshold, namely, whether LA exceeds L 2o: if yes, the AGV carries out right translation; if not, executing the step 9;
if the position of the contour mark is right lane, judging whether the position of the contour mark exceeds the maximum translation amount of right lane translation to the right according to the translation amount threshold, namely whether RA exceeds R 1p: if yes, the AGV carries out left translation; if not, executing the step 9;
Step 9: judging whether a vehicle arrives or not: if not, the AGV transport vehicle normally passes, and the step 11 is executed; if yes, executing step 10;
In this embodiment, when there is no opposite vehicle, it indicates that only one AGV transport is in the aisle at this time, and in order to improve transport efficiency, the process is normal running at this time, and avoidance is no longer performed.
Step 10: the model construction server takes vehicle access information, parking unit number and vehicle speed as value conditions, calculates the priority values of two AGV transport vehicles in a left lane and a right lane through a greedy algorithm, and the AGV transport vehicles with low priority values translate and avoid the AGV transport vehicles with high priority values;
In the execution of step 10, the greedy algorithm is specifically calculated using the following formula:
Score(car(i))＝w1×value(access(i))+w2×value(number(i))+w3×value(V(i))；
Wherein Score represents a greedy Score, i represents a parking order number, car (i) represents a number of an AGV transport dispatched by an order of the parking order number i, value (access(i)) represents a Score of an access event of the order of the parking order number i, value (number(i)) represents a single number Score of the order of the parking order number i, value (V(i)) represents a speed Score of the AGV transport dispatched by the order of the parking order number i, and w 1、w2 and w 3 are weight values.
In this embodiment, when avoidance is required, the present invention uses the vehicle access information, the parking list number and the vehicle speed as the value conditions, assigns the maximum score of the obtained components to the three conditions, and determines which vehicle is avoided according to the final greedy algorithm result, thereby improving the efficiency of vehicle departure or parking.
The score of the access event is a fixed preset value, the access event comprises a parking event and a picking event, and the score of the parking event is smaller than that of the picking event.
In calculating the single number score, the calculation is performed by the following formula:
Wherein i represents a parking bill number, maxNUM represents the maximum number value in all the issued parking bill numbers, va (number) represents the maximum score assigned by the bill number score in a greedy algorithm; in the embodiment, the score of the single number is calculated according to the principle that the vehicle with the front parking single number should take the lead or store the vehicle as preferentially as possible.
In calculating the vehicle speed score, the calculation is performed by the following formula:
Wherein, the vehicle speed (i) represents the actual speed of the AGV transport vehicle dispatched by the order with the parking order number i, maxvelocity represents the maximum driving speed that the AGV transport vehicle can reach, va (V) represents the maximum score that the speed score is distributed in the greedy algorithm, and the speed score is calculated according to the principle that the vehicle with low speed should avoid the vehicle with high speed as much as possible.
The application scenario illustrated in fig. 4 is that the agv_r vehicle has left offset during running, the actual left edge thereof is within the range of the translation threshold of R 2o, and the greedy score of the agv_l vehicle is lower than that of the agv_r vehicle, i.e., the agv_l vehicle needs to avoid to the agv_r vehicle.
Step 11: and (5) ending.
According to the intelligent navigation method for the parking lot, the technical problems that the actual monitoring feedback of the AGV transport vehicle is realized through a third party camera monitoring system, a traditional single-lane is changed into a double-lane, and meanwhile, the AGV transport vehicle is subjected to translational avoidance scheduling according to the monitoring feedback are solved.
Claims (8)
1. An intelligent navigation method for a parking lot is characterized by comprising the following steps of: the method specifically comprises the following steps:
step 1: the method comprises the steps that an AGV navigation system and an AGV monitoring system are established, the AGV navigation system is used for providing scheduling information and navigation route data for AGV transport vehicles in a parking lot, the scheduling information comprises parking list numbers and vehicle access information, the AGV transport vehicles send speed data of the AGV transport vehicles to the AGV navigation system in the process of traveling, the AGV monitoring system comprises a plurality of monitoring cameras, a monitoring data acquisition server, a picture processing server and a model construction server, the monitoring cameras are deployed on a traffic channel of the AGV transport vehicles, and the monitoring data acquisition server is used for acquiring real-time traffic channel monitoring images shot by all the monitoring cameras through data lines;
each monitoring camera is preset with a unique identification serial number;
The vehicle access information is used for marking and representing a vehicle storage event or a vehicle taking event;
step 2: in the traveling process of the AGV, a contour mark for representing the contour of the AGV and a caption mark for representing a parking list number are projected on the ground through a projection lamp;
Step 3: when the AGV transport vehicle moves in the shooting range of any monitoring camera, the monitoring camera sends the shot traveling image of the AGV transport vehicle to a monitoring data acquisition server, and the monitoring data acquisition server sends the traveling image and the identification serial number of the monitoring camera shooting the traveling image to a picture processing server;
step 4: the picture processing server analyzes the travelling image through an image recognition technology and recognizes a contour mark and a caption mark;
The picture processing server marks the outline mark in the travelling image to obtain a mark image, and meanwhile, a parking list number is obtained according to the identification of the caption mark, and a mapping list among the parking list number, the mark image and the identification serial number is established;
Step 5: the model construction server constructs a mathematical model of the traffic channel in a world coordinate system, wherein the mathematical model is established by dividing the traffic channel into a left lane and a right lane according to the width of the traffic channel, and a safety interval is set between the left lane and the right lane;
the model construction server presets a translation threshold in a mathematical model of the traffic channel;
step 6: the model building server acquires speed data of the AGV from the AGV navigation system through the Internet;
the model building server calls the mark image, coordinates of the mark image are overlapped into a world coordinate system, and whether the AGV is located in a left lane or a right lane is judged according to the position of the outline mark:
if the AGV is in the left lane or the right lane, the AGV transport vehicle normally passes, the step 11 is executed, and if not, the step 7 is executed;
step 7: judging whether the position of the profile mark exceeds a translation threshold value: step 8 is executed; if not, executing the step 9;
step 8: judging the lane where the AGV is located:
if the position of the contour mark is the left lane, judging whether the position of the contour mark exceeds the maximum translation amount of left translation of the left lane according to the translation amount threshold value: if yes, the AGV carries out right translation; if not, executing the step 9;
if the position of the contour mark is the right lane, judging whether the position of the contour mark exceeds the maximum translation amount of right lane translation according to the translation amount threshold value: if yes, the AGV carries out left translation; if not, executing the step 9;
Step 9: judging whether a vehicle arrives or not: if not, the AGV transport vehicle normally passes, and the step 11 is executed; if yes, executing step 10;
step 10: the model construction server takes vehicle access information, parking unit number and vehicle speed as value conditions, calculates the priority values of two AGV transport vehicles in a left lane and a right lane through a greedy algorithm, and the AGV transport vehicles with low priority values translate and avoid the AGV transport vehicles with high priority values;
Step 11: and (5) ending.
2. The intelligent navigation method for a parking lot according to claim 1, wherein: the AGV car navigation system comprises a navigation communication server and a scheduling server, wherein the AGV transport vehicle is communicated with the navigation communication server through a wireless network, the navigation communication server is communicated with the scheduling server through a network cable, the scheduling server is used for acquiring a parking application sent by a user from a mobile phone through a mobile network, generating a parking single number according to the parking application, simultaneously marking a parking event corresponding to the parking single number as a parking or taking car, generating car access information, and the navigation communication server is used for drawing a navigation route of the AGV transport vehicle according to the car access information and the parking single number, sending the navigation route to the AGV transport vehicle and simultaneously collecting speed data sent by the AGV transport vehicle.
3. The intelligent navigation method for a parking lot according to claim 1, wherein: the projection lamp is arranged at the front car lamp of the AGV transport vehicle, and when the projection lamp projects the outline mark, the adjustment angle of the projection lamp is calculated by adopting the following method:
Setting theta z as the rotation angle of the projection lamp on the vertical plane, setting theta y as the rotation angle of the projection lamp on the horizontal plane, and calculating theta z and theta y according to a trigonometric function formula:
tanθz＝d÷h；
tanθy＝w÷d；
Wherein d is the horizontal distance between the cursor projected by the projection lamp and the front lamp where the projection lamp is positioned, h is the height of the front lamp where the projection lamp is positioned from the ground, and w is the minimum distance between the front lamp where the projection lamp is positioned and the contour edge of the AGV;
The projection lamp performs an angle adjustment according to the rotation angle θ z and the rotation angle θ y, thereby projecting the outline marker on the ground.
4. A method of intelligent navigation in a parking area as claimed in claim 3, wherein: the outline mark is a preset geometric pattern light spot, and the subtitle mark is a digital light spot representing a parking single number.
5. A method of intelligent navigation in a parking area as claimed in claim 3, wherein: in the execution of step 10, the greedy algorithm is specifically calculated using the following formula:
Score(car(i))＝w1×value(access(i))+w2×value(number(i))+w3×value(V(i))；
Wherein Score represents a greedy Score, i represents a parking order number, car (i) represents a number of an AGV transport dispatched by an order of the parking order number i, value (access(i)) represents a Score of an access event of the order of the parking order number i, value (number(i)) represents a single number Score of the order of the parking order number i, value (V(i)) represents a speed Score of the AGV transport dispatched by the order of the parking order number i, and w 1、w2 and w 3 are weight values.
6. The intelligent navigation method for the parking lot according to claim 5, wherein: the score of the access event is a fixed preset value, the access event comprises a parking event and a picking event, and the score of the parking event is smaller than that of the picking event.
7. The intelligent navigation method for the parking lot according to claim 5, wherein: in calculating the single number score, the calculation is performed by the following formula:
Wherein i represents a parking bill number, maxNUM represents the maximum number value in all the issued parking bill numbers, va (number) represents the maximum score assigned by the bill number score in a greedy algorithm;
In calculating the vehicle speed score, the calculation is performed by the following formula:
Wherein, the velocity (i) represents the actual speed of the AGV transport dispatched by the order with the parking order number i, maxvelocity represents the maximum driving speed which the AGV transport can reach, Representing the maximum score assigned to the vehicle speed score in the greedy algorithm.
8. The intelligent navigation method for a parking lot according to claim 1, wherein: when executing the step 4, the method specifically comprises the following steps:
step 4-1: acquiring a travelling image;
step 4-2: performing image preprocessing on the travelling image to obtain a preprocessed image;
step 4-3: carrying out gray scale treatment on the preprocessed image to obtain a gray scale image;
Step 4-4: carrying out gray scale identification on pixels in the gray scale map, and identifying a projection cursor of the projection lamp on the ground according to gray scale values of the pixels;
Step 4-5: identifying a contour mark and a caption mark according to the geometric shape of the projection cursor;
Step 4-6: setting a rectangular frame surrounding the outline mark at the outline mark to obtain a mark image;
step 4-7: and obtaining a parking list number according to the identification of the caption mark, and establishing a mapping list among the parking list number, the mark image and the identification serial number.
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