CN110442128A - AGV paths planning method based on feature point extraction ant group algorithm - Google Patents
AGV paths planning method based on feature point extraction ant group algorithm Download PDFInfo
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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
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
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Abstract
The present invention provides a kind of AGV paths planning methods based on feature point extraction ant group algorithm, this method includes environmental modeling and path planning, environmental modeling includes the foundation of grid map and the extraction of characteristic point, according to the AGV Environmental Map Information being known in advance, after three-dimensional barrier is projected to two-dimensional surface grid map, barrier perspective view is divided into the identical grid of size, barrier shade is subjected to expansion again, obtain initial figure, the vertex of wherein black barrier grid is extracted, and adjacency matrix is reconfigured by the judgement of grid feasibility, path planning is carried out between characteristic point using ant group algorithm, finally obtain the clear path from origin-to-destination.The problem of the method overcome traditional ant group algorithm point by point search inefficiency has effectively saved the time calculated, improves search efficiency, keeps the path cooked up more smooth；With stylish grid feasibility judgment method, it is more advantageous to the safe and reliable operation of AGV.
Description
Technical field
This disclosure relates to which the AGV Path Planning Technique field in computerized algorithm, especially a kind of to be based on feature point extraction
The AGV paths planning method of ant group algorithm.
Background technique
Existing AGV paths planning method is to first pass through environmental modeling, establishes one and the consistent grid of AGV running environment
Environmental model, then beginning and end is determined on the environmental model, one is searched out from origin-to-destination using ant group algorithm
Clear path.But although this method can successfully acquire the clear path from origin-to-destination, its
Search process, which belongs to single-frame search, has certain blindness, and a large amount of non-optimal solution can be searched in search process and makes convergence speed
Degree is slow, has seriously affected the efficiency of algorithm calculating, meanwhile, its feasibility meeting is judged according only to whether grid is barrier grid
So that the path cooked up frequently is passed through the vertex of barrier, influences the safe operation of AGV.
Summary of the invention
In order to solve the problems in the prior art, the present disclosure proposes a kind of AGV based on feature point extraction ant group algorithm
Paths planning method.This method is after Grid Method constructs the running environment model of AGV, by the vertex of black barrier grid
Grid comes out as feature point extraction, carries out route searching between these vertex grids using ant group algorithm, can be effectively
Guiding search process, the calculation amount of algorithm when reducing planning, also, due to after feature point extraction, between original grid
Connection relationship be broken, judge the connection relationship between grid using the method that new grid feasibility judges, obtain
Path more safety is smooth, is more conducive to the operation of AGV.
In a first aspect, the embodiment of the present disclosure provides a kind of path planning side AGV based on feature point extraction ant group algorithm
Method, comprising the following steps: determine the position of barrier in AGV operation map, and the three-dimensional position of the barrier is projected
On two-dimensional surface；The barrier perspective view being projected on two-dimensional surface is split；To the barrier projection after segmentation
Barrier shade in figure carries out expansionization processing, and the vertex grid for being set as black barrier grid is clicked through as feature
Row extracts；Feasibility judgement is carried out to the grid extracted and constructs adjacency matrix；To multiple initial parameter values of ant group algorithm
It is configured and route searching will be carried out when all ants of former generation are placed in starting point；According to the adjoining of transition probability and construction
Non-zero grid in matrix selects next grid until reaching home.
The described pair of barrier perspective view being projected on two-dimensional surface, which is split, in one of the embodiments, includes:
The barrier perspective view is divided into the identical grid of size, the quantity of grid is a*a.
Expansion is carried out to the barrier shade in the barrier perspective view after segmentation in one of the embodiments,
Processing includes: then to be set to black there are the shade of barrier in the grid after barrier perspective view segmentation
Barrier grid is otherwise provided as white clear grid.
The described pair of grid extracted carries out feasibility judgement and constructs adjacency matrix packet in one of the embodiments,
It includes: construction adjacency matrix D, size a2*a2。
In one of the embodiments, multiple initial parameter values to ant group algorithm be configured include: m be per generation
The quantity of population ant, n are the algebra of ant in total, and τ (0) is initial information element concentration；
Taboo list Tabu is that eucaryotic cell structure size is m*n, to record the route of each ant walking, path length square
The size of battle array PL is m*n, the path length creeped to record each ant of every generation；
Initialization information element attenuation coefficient ρ, pheromones heuristic factor α, apart from heuristic factor β, the number of iterations t；And
The initial parameter value of beginning and end is configured.
In one of the embodiments, further include: whether judgement is fully completed route searching when all ants of former generation, if entirely
Portion completes search, then records an iteration number, wherein the number of iterations t=t+1；Judge whether the number of iterations t meets iteration time
Several requirements exports shortest path if meeting；If being unsatisfactory for the requirement of the number of iterations, updates pheromones and execute and send down
The operation of generation ant；The next-generation ant operation sent is considered as and works as former generation, will be held when all ants of former generation are placed in starting point
Walking along the street path search.
In one of the embodiments, further include: whether judgement is fully completed route searching when all ants of former generation, if not
It is fully completed search, then next grid is selected according to the non-zero grid in transition probability and the adjacency matrix until reaching
Terminal.
It is described in one of the embodiments, to carry out the vertex grid for being set as black barrier grid as characteristic point
Extraction includes: by four apex angle grids of all independent black barrier grids, and all combination black barrier grids own
Apex angle and re-entrant angle grid are extracted as characteristic point.
If it includes: two vertex grid that the described pair of grid extracted, which carries out feasibility judgement, in one of the embodiments,
There are black barrier grids between lattice, then determine that two vertex grids are invisible, each other infeasible grid；If two vertex grid
Black barrier grid is not present between lattice, then judges whether the line of two vertex grids passes through the top of black barrier grid
Point, if determining that two vertex grids are invisible, each other infeasible grid by the vertex of black barrier grid, if without
The vertex of black barrier grid is crossed, then determines two vertex grids as it can be seen that feasible grid each other.
In one of the embodiments, further include: the transition probability formula are as follows:
Wherein, τijIt (t) is the pheromone concentration when the number of iterations is t between grid i and j,For repeatedly
The distance between grid i and j heuristic function when generation number is t, allowedsFor in adjacency matrix D, behalf when D (i, s) ≠ 0
Grid.
The pheromones formula in one of the embodiments, are as follows:
τij(t+1)=(1- ρ) τij(t)+Δτij(t)
Wherein, τij(k+1) for when the number of iterations is t, pheromone concentration between grid i and j, Δ τijIt (t) is current
The sum of the pheromones increment left between grid i and j for ant,For when the number of iterations is t, kth ant exists
The pheromones increment left between grid i and j.
A kind of AGV paths planning method based on feature point extraction ant group algorithm provided by the invention, this method includes ring
Border modeling and path planning, environmental modeling includes the foundation of grid map and the extraction of characteristic point, according to the AGV environment being known in advance
Barrier perspective view after three-dimensional barrier is projected to two-dimensional surface grid map, is divided into the identical grid of size by cartographic information
Lattice, then barrier shade is subjected to expansion, initial figure is obtained, the vertex of wherein black barrier grid is extracted
Come, and adjacency matrix reconfigured by the judgement of grid feasibility, carries out path planning between characteristic point using ant group algorithm,
Finally obtain the clear path from origin-to-destination.This method AGV paths planning method of the invention, overcomes biography
The problem of ant group algorithm point by point search inefficiency of uniting, has effectively saved the time calculated, improves search efficiency, makes to cook up
Path it is more smooth；Meanwhile new grid feasibility judgment method, it can effectively solve the path distance barrier cooked up
Close disadvantage is crossed, the safe and reliable operation of AGV is more advantageous to.
Detailed description of the invention
In order to illustrate more clearly of the technical solution of the embodiment of the present disclosure, below to needed in embodiment description
Attached drawing is briefly described:
Fig. 1 is AGV paths planning method of one of the one embodiment of the invention based on feature point extraction ant group algorithm
Step flow chart；
Fig. 2 is AGV paths planning method of one of the another embodiment of the present invention based on feature point extraction ant group algorithm
Step flow chart；
Fig. 3 is AGV paths planning method of one of the one embodiment of the invention based on feature point extraction ant group algorithm
In actual environment barrier perspective view；
Fig. 4 is AGV paths planning method of one of the one embodiment of the invention based on feature point extraction ant group algorithm
In actual environment grid map；
Fig. 5 is AGV paths planning method of one of the one embodiment of the invention based on feature point extraction ant group algorithm
The middle vertex grid distribution map by number；
Fig. 6 is AGV paths planning method of one of the one embodiment of the invention based on feature point extraction ant group algorithm
Middle grid feasibility discriminatory analysis figure；And
Fig. 7 is AGV paths planning method of one of the one embodiment of the invention based on feature point extraction ant group algorithm
In Path Planning Simulation result figure under the environment.
Specific embodiment
The application is further discussed in detail with reference to the accompanying drawings and examples.
In following introductions, term " first ", " second " only for descriptive purposes, and should not be understood as instruction or dark
Show relative importance.Following introductions provide multiple embodiments of the disclosure, can replace or merge between different embodiments
Combination, therefore the application is it is also contemplated that all possible combinations comprising documented identical and/or different embodiments.Thus, such as
Fruit one embodiment include feature A, B, C, another embodiment include feature B, D, then the application also should be regarded as include containing
A, the every other possible combined embodiment of one or more of B, C, D, although the embodiment may be in the following contents
In have specific literature record.
In order to make the objectives, technical solutions, and advantages of the present invention clearer, by the following examples, it and combines attached
Figure carries out into one a kind of specific embodiment of the AGV paths planning method based on feature point extraction ant group algorithm of the present invention
Step is described in detail.It should be noted that this disclosure relates to speed and temperature are surveyed in turbomachinery rotating channel near wall boundary layer
Measure technical field, it should be understood that described herein specific examples are only used to explain the present invention, is not used to limit this hair
It is bright.
As shown in Figure 1, for AGV paths planning method of one of the one embodiment based on feature point extraction ant group algorithm
Flow diagram, specifically includes the following steps:
Step 101, it determines the position of barrier in AGV operation map, and the three-dimensional position of the barrier is projected
On two-dimensional surface.
Step 102, the barrier perspective view being projected on two-dimensional surface is split.
Specifically, being split to the barrier perspective view being projected on two-dimensional surface includes: by barrier perspective view point
It is segmented into the identical grid of size, the quantity of grid is a*a.
Step 103, expansionization processing is carried out to the barrier shade in the barrier perspective view after segmentation, and will be set as
The vertex grid of black barrier grid is extracted as characteristic point.
Specifically, extracting using the vertex grid for being set as black barrier grid as characteristic point includes: will own
Four apex angle grids of independent black barrier grid, all apex angles and re-entrant angle grid of all combination black barrier grids are made
It is characterized and a little extracts.
Specifically, carrying out expansionization processing to the barrier shade in the barrier perspective view after segmentation includes: to barrier
There are the shades of barrier in grid after hindering object perspective view to be divided, then are set to black barrier grid, are otherwise arranged
For white clear grid.
Step 104, feasibility judgement is carried out to the grid extracted and constructs adjacency matrix.
Specifically, carry out feasibility judgement to the grid extracted and construct adjacency matrix to include: construction adjacency matrix D,
Its size is a2*a2。
Further, if carrying out feasibility judgement to the grid extracted includes: that there are black between two vertex grids
Barrier grid then determines that two vertex grids are invisible, each other infeasible grid；If there is no black between two vertex grids
Color barrier grid, then judge whether the line of two vertex grids passes through the vertex of black barrier grid, if by black
The vertex of barrier grid then determines that two vertex grids are invisible, each other infeasible grid, if without black barrier grid
The vertex of lattice then determines two vertex grids as it can be seen that feasible grid each other.
Step 105, multiple initial parameter values of ant group algorithm are configured and all ants of former generation will be worked as and be placed in starting point
Carry out route searching.
Specifically, multiple initial parameter values of ant group algorithm are configured with the quantity for including: m for per generation population ant, n
For the algebra of ant in total, τ (0) is initial information element concentration；
Taboo list Tabu is that eucaryotic cell structure size is m*n, to record the route of each ant walking, path length square
The size of battle array PL is m*n, the path length creeped to record each ant of every generation；
Initialization information element attenuation coefficient ρ, pheromones heuristic factor α, apart from heuristic factor β, the number of iterations t；And it is right
The initial parameter value of beginning and end is configured.
Step 106, select next grid straight according to the non-zero grid in the adjacency matrix of transition probability and construction
To reaching home.
Specifically, transition probability formula are as follows:
Wherein, τijIt (t) is the pheromone concentration when the number of iterations is t between grid i and j,For repeatedly
The distance between grid i and j heuristic function when generation number is t, allowedsFor in adjacency matrix D, behalf when D (i, s) ≠ 0
Grid.
In addition, in one embodiment, the disclosure propose based on feature point extraction ant group algorithm AGV paths planning method
Further include: whether judgement is fully completed route searching when all ants of former generation, if being fully completed search, records an iteration time
Number, wherein the number of iterations t=t+1；Judge whether the number of iterations t meets the requirement of the number of iterations, exports shortest path if meeting
Diameter；If being unsatisfactory for the requirement of the number of iterations, updates pheromones and execute and next-generation ant is sent to operate；The next generation that will be sent
Ant operation, which is considered as, works as former generation, will be placed in starting point executive path search when all ants of former generation.
Wherein, it should be noted that pheromones formula is
τij(t+1)=(1- ρ) τij(t)+Δτij(t)
Wherein, τij(k+1) for when the number of iterations is t, pheromone concentration between grid i and j, Δ τijIt (t) is current
The sum of the pheromones increment left between grid i and j for ant,For when the number of iterations is t, kth ant exists
The pheromones increment left between grid i and j.
Further, in one embodiment, the disclosure propose based on feature point extraction ant group algorithm AGV path planning
Method further include: whether judgement is fully completed route searching when all ants of former generation, if search is not fully completed, according to transfer
Non-zero grid in probability and the adjacency matrix selects next grid until reaching home.
In summary it is found that in existing paths planning method, algorithm is often extended from whole grids layer by layer, single-frame
Planning is to obtain from the clear path of origin-to-destination, this can make the calculation amount of algorithm excessive, the non-optimal solution of search
Excessively, cause efficiency of algorithm low, the excessive problem of the number of iterations, the present invention carries out the processing of feature point extraction to grid map, will
The search range of algorithm narrows down to the vertex grid of all black barrier grids from all grids, can reduce the calculating of algorithm
Amount accelerates convergence rate.
Further, feasibility judges between existing grid, is by whether judging eight grids around current grid
Judge for barrier grid, it is if black barrier grid, then infeasible between two grids, if the non-barrier of white
Grid, then be between two grids it is feasible, this, which will cause the path cooked up, can not avoid the apex angle of black barrier grid,
To influence the safety of AGV operation, the new grid feasibility judgement that the present invention uses will pass through black barrier grid top
The path of point is set as infeasible path, keeps the path cooked up more safety smooth, is conducive to the operation of AGV.
The AGV paths planning method based on feature point extraction ant group algorithm that the disclosure proposes overcomes traditional ant group algorithm
The problem of point by point search inefficiency, has effectively saved the time calculated, improves search efficiency, makes the path cooked up more
Smoothly；Meanwhile new grid feasibility judgment method, can effectively solve the path distance barrier cooked up it is excessively close lack
Point is more advantageous to the safe and reliable operation of AGV.
For the AGV path planning based on feature point extraction ant group algorithm for being more clearly understood that with being proposed using the disclosure
Method carries out following example.It should be noted that the range that the disclosure is protected is not limited to following example.
Specifically, Fig. 2 is that one of another embodiment of the present invention is based on feature point extraction ant colony as shown in Fig. 2-Fig. 7
The step flow chart of the AGV paths planning method of algorithm.Specific step is as follows
S1: it determines the position of barrier in AGV operation map, and three-dimensional barrier is projected on two-dimensional surface, obstacle
Object perspective view is as shown in Figure 3.
S2: being split barrier perspective view, is divided into the identical grid of size, and the quantity of grid is a*a.
S3: by barrier shade expansionization, as long as there are the shades of barrier in the grid, it is set to black barrier
Hinder object grid, is otherwise white clear grid, grid map is as shown in Figure 4.
S4: the vertex grid of black barrier grid is come out as feature point extraction, the vertex grid by number point
Butut is as shown in Figure 5.
S5: feasibility judgement is carried out to the vertex grid extracted, reconfigures adjacency matrix D, size a2*a2。
S6: set the initial parameter value of ant group algorithm: for m as the quantity of per generation population ant, n is the algebra of ant in total, τ
It (0) is initial information element concentration, taboo list Tabu is that eucaryotic cell structure size is m*n, to record the road of each ant walking
Line, the size of path length matrix PL are m*n, the path length creeped to record each ant of every generation；It is initial simultaneously
Change pheromones attenuation coefficient ρ, pheromones heuristic factor α, apart from heuristic factor β, the number of iterations t and beginning and end.
S7: it will be placed in starting point when all ants of former generation, and will start to carry out route searching.
S8: selecting next grid according to the non-zero grid in transition probability and adjacency matrix, complete until reaching home
Cheng Yici route searching.
S9: whether judgement is fully completed route searching when all ants of former generation, if being fully completed search, into S10, otherwise
Return to S8.
S10: record an iteration number, t=t+1.
S11: judging whether the number of iterations t meets the requirement of the number of iterations, exports shortest path if meeting, otherwise, into
Enter S12, finally obtained optimal route is as shown in Figure 7.
S12: updating pheromones, and send next-generation ant, returns to S7.
Further, in the step S4, the characteristic point of extraction includes: four tops of all independent black barrier grids
Angle, all apex angles and re-entrant angle of all combination black barrier grids.
Further, in the step S5, the method for grid feasibility judgement is, as shown in fig. 6, if two vertex grids it
Between there are black barrier grid, then determine that two vertex grids are invisible, each other infeasible grid；If two vertex grids it
Between be not present black barrier grid, then judge whether the line of two vertex grids passes through the vertex of black barrier grid,
If determining that two vertex grids are invisible, each other infeasible grid, if without black by the vertex of black barrier grid
The vertex of color barrier grid then determines two vertex grids as it can be seen that feasible grid each other.
Further, in the step S8, ant selects the transition probability formula of next grid are as follows:
Wherein, τijIt (t) is the pheromone concentration when the number of iterations is t between grid i and j,For repeatedly
The distance between grid i and j heuristic function when generation number is t, allowedsFor in adjacency matrix D, behalf when D (i, s) ≠ 0
Grid.
Further, in the step S12, the more new formula of pheromones are as follows:
τij(t+1)=(1- ρ) τij(t)+Δτij(t) (2)
Wherein, τij(k+1) for when the number of iterations is t, pheromone concentration between grid i and j, Δ τijIt (t) is current
The sum of the pheromones increment left between grid i and j for ant,For when the number of iterations is t, kth ant exists
The pheromones increment left between grid i and j.
In conclusion a kind of AGV paths planning method based on feature point extraction ant group algorithm that the disclosure proposes overcomes
Traditional ant group algorithm path planning there are the drawbacks of, pass through and extract characteristic point and new grid feasibility judgment method, improve
The efficiency of algorithm, the path cooked up more safety is smooth, has obtained more preferably result.At the same time, this method can subtract
The calculation amount of algorithm when few path planning, while keeping the path cooked up more safety smooth, be conducive to AGV and safely and reliably transport
Row.
A kind of AGV paths planning method based on feature point extraction ant group algorithm provided by the invention, this method includes ring
Border modeling and path planning, environmental modeling includes the foundation of grid map and the extraction of characteristic point, according to the AGV environment being known in advance
Barrier perspective view after three-dimensional barrier is projected to two-dimensional surface grid map, is divided into the identical grid of size by cartographic information
Lattice, then barrier shade is subjected to expansion, initial figure is obtained, the vertex of wherein black barrier grid is extracted
Come, and adjacency matrix reconfigured by the judgement of grid feasibility, carries out path planning between characteristic point using ant group algorithm,
Finally obtain the clear path from origin-to-destination.This method AGV paths planning method of the invention, overcomes biography
The problem of ant group algorithm point by point search inefficiency of uniting, has effectively saved the time calculated, improves search efficiency, makes to cook up
Path it is more smooth；Meanwhile new grid feasibility judgment method, it can effectively solve the path distance barrier cooked up
Close disadvantage is crossed, the safe and reliable operation of AGV is more advantageous to.
The embodiment of the invention also provides a kind of computer readable storage medium, stored on the computer readable storage medium
There is computer program, which is executed by processor in Fig. 1.
The embodiment of the invention also provides a kind of computer program products comprising instruction.When the computer program product exists
When being run on computer, so that the method that computer executes above-mentioned Fig. 1.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the program can be stored in a computer-readable storage medium
In, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random Access
Memory, RAM) etc..
The embodiments described above only express several embodiments of the present invention, and the description thereof is more specific and detailed, but simultaneously
Limitations on the scope of the patent of the present invention therefore cannot be interpreted as.It should be pointed out that for those of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Protect range.Therefore, the scope of protection of the patent of the invention shall be subject to the appended claims.
The basic principle of the disclosure is described in conjunction with specific embodiments above, however, it is desirable to, it is noted that in the disclosure
The advantages of referring to, advantage, effect etc. are only exemplary rather than limitation, must not believe that these advantages, advantage, effect etc. are the disclosure
Each embodiment is prerequisite.In addition, detail disclosed above is merely to exemplary effect and the work being easy to understand
With, rather than limit, it is that must be realized using above-mentioned concrete details that above-mentioned details, which is not intended to limit the disclosure,.
Device involved in the disclosure, device, equipment, system block diagram only as illustrative example and being not intended to
It is required that or hint must be attached in such a way that box illustrates, arrange, configure.As those skilled in the art will appreciate that
, it can be connected by any way, arrange, configure these devices, device, equipment, system.Such as "include", "comprise", " tool
" etc. word be open vocabulary, refer to " including but not limited to ", and can be used interchangeably with it.Vocabulary used herein above
"or" and "and" refer to vocabulary "and/or", and can be used interchangeably with it, unless it is not such that context, which is explicitly indicated,.Here made
Vocabulary " such as " refers to phrase " such as, but not limited to ", and can be used interchangeably with it.
In addition, as used herein, the "or" instruction separation used in the enumerating of the item started with "at least one"
It enumerates, such as enumerating for " at least one of A, B or C " means A or B or C or AB or AC or BC or ABC (i.e. A and B and C).
In addition, wording " exemplary " does not mean that the example of description is preferred or more preferable than other examples.
Above description is had been presented for for purposes of illustration and description.But this description is not meant that the implementation of the disclosure
Example is restricted to form disclosed herein.
Claims (10)
1. a kind of AGV paths planning method based on feature point extraction ant group algorithm, which comprises the following steps:
It determines the position of barrier in AGV operation map, and the three-dimensional position of the barrier is projected on two-dimensional surface；
The barrier perspective view being projected on two-dimensional surface is split；
Expansionization processing is carried out to the barrier shade in the barrier perspective view after segmentation, and black obstacle will be set as
The vertex grid of object grid is extracted as characteristic point；
Feasibility judgement is carried out to the grid extracted and constructs adjacency matrix；
Multiple initial parameter values of ant group algorithm are configured and route searching will be carried out when all ants of former generation are placed in starting point；
Next grid is selected according to the non-zero grid in the adjacency matrix of transition probability and construction until reaching home.
2. the AGV paths planning method according to claim 1 based on feature point extraction ant group algorithm, which is characterized in that
The described pair of barrier perspective view being projected on two-dimensional surface is split and the processing of barrier expansionization includes: by the obstacle
Object perspective view is divided into the identical grid of size, and the quantity of grid is a*a, if there are barrier shade in the grid after segmentation,
It is then set to black barrier grid, is otherwise provided as white clear grid.
3. the AGV paths planning method according to claim 1 based on feature point extraction ant group algorithm, which is characterized in that
The described pair of grid extracted carries out feasibility judgement and constructs adjacency matrix to include: construction adjacency matrix D, size a2*
a2。
4. according to claim 1 be based on feature point extraction ant group algorithm AGV paths planning method, which is characterized in that institute
State that be configured to multiple initial parameter values of ant group algorithm include: quantity that m is per generation population ant, n be ant in total
Algebra, τ (0) are initial information element concentration；
Taboo list Tabu is that eucaryotic cell structure size is m*n, to record the route of each ant walking, path length matrix PL
Size be m*n, the path length creeped to record each ant of every generation；
Initialization information element attenuation coefficient ρ, pheromones heuristic factor α, apart from heuristic factor β, the number of iterations t；And
The initial parameter value of beginning and end is configured.
5. according to claim 1 be based on feature point extraction ant group algorithm AGV paths planning method, which is characterized in that also
Include: judgement when whether all ants of former generation are fully completed route searching, if being fully completed search, records an iteration time
Number, wherein the number of iterations t=t+1；
Judge whether the number of iterations t meets the requirement of the number of iterations, exports shortest path if meeting；
If being unsatisfactory for the requirement of the number of iterations, updates pheromones and execute and next-generation ant is sent to operate；
The next-generation ant operation sent is considered as and works as former generation, will be searched when all ants of former generation are placed in starting point execution route
Rope.
6. according to claim 1 be based on feature point extraction ant group algorithm AGV paths planning method, which is characterized in that also
Include: whether judgement is fully completed route searching when all ants of former generation, if not being fully completed search, according to transition probability with
And the non-zero grid in the adjacency matrix selects next grid until reaching home.
7. according to claim 1 be based on feature point extraction ant group algorithm AGV paths planning method, which is characterized in that institute
State that extract the vertex grid for being set as black barrier grid as characteristic point include: by all independent black barriers
Four apex angle grids of grid, all apex angles and re-entrant angle grid of all combination black barrier grids are mentioned as characteristic point
It takes.
8. according to claim 1 be based on feature point extraction ant group algorithm AGV paths planning method, which is characterized in that institute
If stating and carrying out feasibility judgement to the grid extracted includes: to sentence between two vertex grids there are black barrier grid
Fixed two vertex grids are invisible, each other infeasible grid；
If black barrier grid is not present between two vertex grids, it is black to judge whether the line of two vertex grids passes through
The vertex of color barrier grid, if determining that two vertex grids are invisible, each other not by the vertex of black barrier grid
Feasible grid, if determining two vertex grids as it can be seen that feasible grid each other without the vertex of black barrier grid.
9. the AGV paths planning method according to claim 1 based on feature point extraction ant group algorithm, which is characterized in that
Further include: the transition probability formula are as follows:
Wherein, τijIt (t) is the pheromone concentration when the number of iterations is t between grid i and j,For iteration time
The distance between grid i and j heuristic function when number is t, allowedsFor in adjacency matrix D, the grid of behalf when D (i, s) ≠ 0
Lattice.
10. the AGV paths planning method according to claim 6 based on feature point extraction ant group algorithm, which is characterized in that
The pheromones formula is
τij(t+1)=(1- ρ) τij(t)+Δτij(t)
Wherein, τij(k+1) for when the number of iterations is t, pheromone concentration between grid i and j, Δ τij(t) for when former generation ant
The sum of the pheromones increment that ant leaves between grid i and j,For when the number of iterations is t, kth ant is in grid
The pheromones increment left between i and j.
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Application publication date: 20191112 Assignee: SHIJIAZHUANG JIAKE ELECTROMECHANICAL TECHNOLOGY Co.,Ltd. Assignor: HEBEI University OF SCIENCE AND TECHNOLOGY Contract record no.: X2023980043391 Denomination of invention: AGV Path Planning Method Based on Ant Colony Algorithm for Feature Point Extraction Granted publication date: 20220816 License type: Common License Record date: 20231013 |