CN106527448B - Improvement A* robot optimum path planning method suitable for warehouse environment - Google Patents
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Abstract
Suitable for the improvement A* robot optimum path planning method of warehouse environment, design first effectively can flexible expansion storehouse model, including shelf distribution and road operation rule design；According to road operation rule in storehouse model, path planning problem is reduced to the path planning problem between each node；Then, using the optimal path between two nodes of improved A* algorithm search；Wherein, the calculating of heuristic function includes turning to cost, manhatton distance, the estimation around row distance；Finally, forming complete path list in node listing before the path between the initial position and start node of robot and between target position and destination node is added to.Node in path list is corresponding with the position in practical warehouse, the optimal running route of robot is obtained, and be extended to the operating status list of robot.
Description
Technical field
The present invention relates to the optimum path planning problems in warehouse environment, for DYNAMIC DISTRIBUTION shelf and road rule
Storehouse model then, the invention proposes the path planning algorithms for improving A*, solve the optimal road in storehouse model between two o'clock
Diameter planning problem guarantees that storage mobile robot reaches target with optimal route.
Background technique
With technology of Internet of things, robot technology, multi-robot control system is applied to certainly by the development of computer technology
In the sorting link of dynamicization warehouse system, have become the development trend of logistics sorting.Traditional commodity sort mode is by dividing
It picks personnel and traverses corresponding shelf completion order packing work.In warehousing system, the layout of commodity shelf is using dynamic
The mode of distribution, and corresponding shelf are transported to sorting office by robot, to complete the packing work of goods orders.Storehouse
The design of library model and the path planning problem under this warehouse environment are the piths of warehousing system design.Cause
This, designing reasonable storehouse model and suitable path planning algorithm has important work for the efficiency for improving commodity sorting
With.
In traditional sort mode, sorting personnel can freely walk about under the premise of not colliding in warehouse to complete
At sorting task.Traditional sort mode low efficiency, great work intensity, labor cost is high, currently by complete by robot
Replace at the sort mode that shelf are carried.Shelf are in the state of DYNAMIC DISTRIBUTION under automated sorting mode, and have in warehouse
Multiple robots run the handling work for completing shelf simultaneously, so that assisting sorting personnel to complete commodity is packaged work.In order to protect
The normal operation of automated warehouse storage system is demonstrate,proved, need to make rational planning for operation rule and operating status of the robot in warehouse.
Automatic Warehouse in this way has the Kiva system, the Swisslog of Switzerland, domestic Geek+ of Amazon at present
Team.
Path planning problem can be solved by global path planning algorithm in storage environment.Global path planning algorithm
Mainly there are path planning algorithm, evolution algorithm, particle swarm optimization algorithm, ant colony optimization algorithm, mould based on linear time temporal logic
Quasi- annealing method etc..In the case where given robot starting point and target point, these algorithms can be cooked up most in running environment
Shortest path.
A* algorithm is a kind of didactic path planning algorithm, and the environmental information offer based on robot operation is suitably opened
Hairdo function searches out the optimal path between two o'clock.With the intelligence such as evolution algorithm, particle swarm optimization algorithm, ant colony optimization algorithm
Energy optimization algorithm is compared, and A* algorithm has real-time high, and algorithm complexity is low, the characteristic that easy programming is realized, and appropriate
Under the conditions of can guarantee the optimality of searching route.But the optimality in A* algorithm search path depends on suitable heuristic letter
Number.Path planning of the A* in geometry network uses manhatton distance as heuristic function at present, but advises with road
In geometry network then, at the same be also contemplated that robot steering cost when, it is desirable to provide more accurate heuristic information makes
Searching route optimizes.
Summary of the invention
The present invention will overcome the disadvantages mentioned above of the prior art, provide a kind of improvement A* robot suitable for warehouse environment most
Shortest path planing method.
The characteristic that the present invention is realized using the real-time and easy programming of A* algorithm, according to the operation rule of storehouse model and
Under the premise of considering that robot turns to cost, suitable heuristic information is provided, searching route is optimized, overcome tradition
The shortcomings that A* algorithm is unable to get optimal path.Design first effectively can flexible expansion storehouse model, including shelf distribution
And the design of road operation rule, storehouse model are as shown in Figure 1.According to road operation rule in storehouse model, path is advised
Draw path planning problem of the problem reduction between each node.Then, using between two nodes of improved A* algorithm search
Optimal path.Wherein, the calculating of heuristic function includes turning to cost, manhatton distance, the estimation around row distance.It is improved
The list that the path of A* algorithm search is made of several nodes.Finally, by the initial position of robot and start node it
Between and the path between target position and destination node be added to before node listing in, form complete path list.
Node in path list is corresponding with the position in practical warehouse, the optimal running route of robot is obtained, and be extended to
The operating status list of robot.Improved A* has search efficiency height, and easy programming is realized and cartographic information building is easy
Advantage.
Improvement A* robot optimum path planning method suitable for warehouse environment of the invention, comprising:
Step 1: the distribution of design shelf and road is, it is specified that the width of road only allows a robot to pass through, i.e., and 1
A unit length.In storehouse model, what it is positioned at left side is sorting office, and right side is shelf heap, and each shelf heap is by 2 × 5
Shelf composition, the length of each shelf and it is wide be 0.9 unit length.The sum of shelf heap can be adjusted flexibly according to demand simultaneously
It and is odd number.Have between any two shelf heap and an only road, and whole shelf heap periphery have two at a distance of being 1
The road of a unit length, to guarantee the completeness and validity of path planning algorithm.If there is two road to intersect at storehouse
Some point in library, then using the point as node N, N=(x, y), wherein x is the x coordinate value of present node, and y is present node
Y-coordinate value.Define Sp=[xb yb xs ys] indicate the relative positions of shelf, wherein xb,ybRespectively indicate current shelf place
The relative position of shelf heap, xs,ysRespectively indicate relative position of the current shelf inside shelf heap.
Step 2: the operation rule of road is, it is specified that road is one-way traffic in design repository, and two of arbitrary neighborhood
The driving direction of road is opposite.Robot can only enter in shelf heap from the road of cross direction profiles.Robot is defined on road
Operating status RS=[xR yR dx dy], wherein xR,yRIndicate coordinate position of the robot in warehouse coordinate system, dx,dyPoint
Not Biao Shi robot feasible direction, i.e., the driving direction of road, d where robotx,dy∈{0,1,2,3,4}.Work as dxIt is 0
When, indicate that robot can not cross running；If dxIt is 3, then robot can be to right travel；If dxIt is 4, then robot can be to
Left lateral is sailed.Work as dyWhen being 0, indicate that robot can not longitudinal driving；If dyIt is 1, then robot can travel upwards；If dyIt is 2,
Then robot can be to downward driving.
Step 3: the initial position and target position of given robot, if robot can be reached without any node
Target position then directly gives final path list according to the initial position of robot and target position.Otherwise, simplified
Path planning problem between warehouse node.Robot is saved from first node of initial position arrival as initial
Point, robot reach the last one node passed through when target position as destination node.
Step 4: on the basis of step 3, for given start node and destination node, being searched using improved A* algorithm
Rope optimal path.When calculating heuristic function cost, improved A* algorithm needs to calculate between present node and destination node
Manhatton distance, turn to number and around row distance.Assuming that being n as the node currently estimated, manhatton distance cost is remembered
For hm(n), hm(n)=| xb-xf|+|yb-yf|, wherein xb, yb is the coordinate of start node, xf,yfFor the coordinate of destination node.
It is h that note, which turns to cost,t(n), ht(n)=q × turncost, wherein q indicates the minimum steering between present node and destination node
Number, turncost indicate the cost value turned to every time.Note is h around row distance coste(n), by judging present node and mesh
The detour number for marking node, in conjunction with the available specific h of information of storehouse modele(n) value.It is heuristic obtaining above three
After cost, the heuristic function that note improves A* algorithm is h (n), for estimating the heuristic generation of present node n and destination node
Valence, h (n)=hm(n)+ht(n)+he(n).Using A* algorithm search node listing is improved, it is denoted as Listj。
Step 5: remembering that the path list between the initial position of robot and start node is Listb, the target of robot
Path list between position and destination node is Listf.By ListbIt is added to ListjHead, by ListfIt is added to Listj
Tail portion, constitute complete path list.Node coordinate position in list is opposite with the position coordinates in actual warehouse
It answers, obtains the running route of robot.
Step 6: the running route of robot being extended to the operating status list of robot, is denoted as SListR, by a system
The robotary of column is constituted.According to given robot running route, the operation rule of road where each point on route are judged
Then, robot is obtained in the traffic direction of current point, so that the running route of robot to be extended to the operating status of robot.
The operating status list of robot is sent to robot, robot can be allowed to complete the task of line walking.
The invention has the advantages that the path planning problem in the warehouse of shelf DYNAMIC DISTRIBUTION is solved using A* algorithm is improved,
Reasonable effective storehouse model is devised, and proposes suitable heuristic information and searching route is optimized.Due to storehouse
The one-way traffic of library road and the steering cost for considering robot, the heuristic function that traditional A* algorithm uses can not solve
The problem of certainly searching route in this case optimizes.The invention on the basis of heuristic information of traditional A* algorithm,
According to the particularity of road information, proposes suitable heuristic information and calculate the algorithm of its cost, to solve path
The problem of optimality.Compared with dijkstra's algorithm, improving A* algorithm has search efficiency high, and it is easily excellent to establish cartographic information
Gesture.With such as ant group algorithm, the intelligent algorithms such as evolution algorithm are compared, and improving A* algorithm has easily programmable realization, and calculation amount is small,
The high advantage of real-time.For large-scale Automatic Warehouse and the warehouse environment with a fairly large number of robot, this hair
The scalability of the storehouse model of bright design and the real-time of path planning algorithm, programming easy advantage can be good at solving
Certainly corresponding problem, the sorting efficiency for improving warehouse have help.
Detailed description of the invention
Fig. 1 is storehouse model design drawing of the invention
Fig. 2 is steering number calculation flow chart of the invention
Fig. 3 is detour Distance Judgment flow chart of the invention
Fig. 4 is robot initial position and target position of the invention
Fig. 5 is the search pattern of improvement A* algorithm of the invention
Specific embodiment
It is logical to the improvement A* robot optimum path planning method suitable for warehouse environment of the invention below in conjunction with attached drawing
Simplified example is crossed to be further described.
Improvement A* optimum path planning method suitable for warehouse environment mainly has the following contents: designing effectively may be used first
The storehouse model of flexible expansion, it is as shown in Figure 1 including shelf distribution and the design of road operation rule, storehouse model.According to
Path planning problem is reduced to the path planning problem between each node by road operation rule in storehouse model.Then, it adopts
With the optimal path between two nodes of improved A* algorithm search.Wherein, the calculating of heuristic function includes turning to cost, graceful
Hatton distance, around the estimation of row distance.The list that the path of improved A* algorithm search is made of several nodes.Finally,
Before path between the initial position and start node of robot and between target position and destination node is added to
In node listing, complete path list is formed.Node in path list is corresponding with the position in practical warehouse, it obtains
The optimal running route of robot, and it is extended to the operating status list of robot.Improved A* has search efficiency high, easily compiles
Cheng Shixian and cartographic information construct easy advantage.Detailed process is as follows:
Step 1: the distribution of design shelf and road is, it is specified that the width of road only allows a robot to pass through, i.e., and 1
A unit length.In Fig. 1 storehouse model, what it is positioned at left side is Liang Ge sorting office, and right side is 5 × 5 shelf heap, each shelf
Heap is made of 2 × 5 shelf, the length of each shelf and it is wide be 0.9 unit length.The sum of shelf heap can be according to demand
It is adjusted flexibly and is odd number.Have between any two shelf heap and an only road, and whole shelf heap periphery has
Two at a distance of the road for being 1 unit length.
Step 2: the operation rule of road is, it is specified that road is one-way traffic in design repository, and two of arbitrary neighborhood
The driving direction of road is opposite.Robot can only enter in shelf heap from the road of cross direction profiles.Robot is defined on road
Operating status RS=[xR yR dx dy], wherein xR,yRIndicate coordinate position of the robot in warehouse coordinate system, dx,dyPoint
Not Biao Shi robot feasible direction, i.e., the driving direction of road, d where robotx,dy∈{0,1,2,3,4}.Work as dxIt is 0
When, indicate that robot can not cross running；If dxIt is 3, then robot can be to right travel；If dxIt is 4, then robot can be to
Left lateral is sailed.Work as dyWhen being 0, indicate that robot can not longitudinal driving；If dyIt is 1, then robot can travel upwards；If dyIt is 2,
Then robot can be to downward driving.
Step 3: the initial position and target position of given robot, corresponding shelf coordinate is respectively [0330] A=, B
=[2130], as shown in Figure 4.Its corresponding warehouse coordinate is respectively RA=(4,10), RB=(16,4).It is reduced to initial
Node NA=(0,9) and destination node NBPath planning problem between=(18,3).
Step 4: on the basis of step 3, for given start node and destination node, being searched using improved A* algorithm
Rope optimal path.When calculating heuristic function cost, improved A* algorithm needs to calculate between start node and destination node
Manhatton distance, turn to number and around row distance.Assuming that being n as the node currently estimated, manhatton distance cost is remembered
For hm(n), hm(n)=| xb-xf|+|yb-yf|, wherein xb,ybFor the coordinate of start node, xf,yfFor the coordinate of destination node.
It is h that note, which turns to cost,t(n), ht(n)=n × turncost, wherein n indicates the minimum steering between start node and destination node
Number, turncost indicate the cost value turned to every time, and the process for calculating steering number is as shown in Figure 2.Note is around row distance cost
For he(n), detour number algorithm flow as shown in figure 3, in conjunction with storehouse model the available specific h of informatione(n) value.?
After obtaining the heuristic cost of above three, the heuristic function that note improves A* algorithm is h (n), for estimating present node n and mesh
Mark the heuristic cost of node, h (n)=hm(n)+ht(n)+he(n).Using A* algorithm search node listing is improved, it is denoted as
Listj。Listj(0,9) is contained, (0,6), (0,3), (0,0), (6,0), (12,0), (18,0), (18,3).
Step 5: remembering that the path list between the initial position of robot and start node is Listb, (4,10) are contained,
(4,9) two o'clock.Path list between the target position and destination node of robot is Listf, (16,3) are contained, (16,
4).By ListbIt is added to ListjHead, by ListfIt is added to ListjTail portion, constitute complete path list ListjPacket
Contain (4,10), (4,9), (0,9), (0,6), (0,3), (0,0), (6,0), (12,0), (18,0), (18,3), (16,3)
(16,4).Node coordinate position in list is corresponding with the position coordinates in actual warehouse, obtain the operation of robot
Route, as shown in Figure 5.
Step 6: the running route of robot being extended to the operating status list of robot, is denoted as SListR, by a system
The robotary of column is constituted.According to given robot running route, the operation rule of road where each point on route are judged
Then, robot is obtained in the traffic direction of current point, so that the running route of robot to be extended to the operating status of robot.
SListR[4 10 2 0] are contained, [4 90 4], [0 90 4], [0 62 0], [0 32 0], [0 02 0], [6 0
0 3], [12 00 3], [18 00 3], [18 31 0], [16 30 4], [16 41 0].By the operation shape of robot
State list is sent to robot, and robot can be allowed to complete the task of line walking.
The present invention solves the path planning problem in the warehouse of shelf DYNAMIC DISTRIBUTION using A* algorithm is improved, and devises rationally
Effective storehouse model, and propose suitable heuristic information and searching route is optimized.Due to the list of depot road
To the steering cost of travelling and consideration robot, the heuristic function that traditional A* algorithm uses can not solve such case
Under searching route optimize the problem of.The invention is believed on the basis of the heuristic information of traditional A* algorithm according to road
The particularity of breath proposes suitable heuristic information and calculates the algorithm of its cost, to solve asking for path optimality
Topic.Compared with dijkstra's algorithm, improving A* algorithm has search efficiency high, establishes the easy advantage of cartographic information.With such as
Ant group algorithm, the intelligent algorithms such as evolution algorithm are compared, and improving A* algorithm has easily programmable realization, and calculation amount is small, and real-time is high
Advantage.For large-scale Automatic Warehouse and the warehouse environment with a fairly large number of robot, what the present invention designed
The scalability of storehouse model and the real-time of path planning algorithm, programming easy advantage can be good at solving accordingly
Problem, the sorting efficiency for improving warehouse have help.
Claims (2)
1. being suitable for the improvement A* robot optimum path planning method of warehouse environment, the specific steps are as follows:
Step 1: the distribution of design shelf and road is, it is specified that the width of road only allows a robot to pass through, i.e. 1 list
Bit length；In storehouse model, what it is positioned at left side is sorting office, and right side is shelf heap, and each shelf heap is by 2 × 5 shelf
Composition, the length of each shelf and it is wide be 0.9 unit length；The sum of shelf heap adjusts according to demand and is odd number；Appoint
Anticipating between two shelf heaps has and an only road, and whole shelf heap periphery have two at a distance of being 1 unit length
Road, to guarantee the completeness and validity of path planning algorithm；If there is two road to intersect at some in warehouse
Point, then using the point as node N, N=(x, y), wherein x is the x coordinate value of present node, and y is the y-coordinate value of present node；
Define Sp=[xb yb xs ys] indicate the relative positions of shelf, wherein xb,ybThe phase of shelf heap where respectively indicating current shelf
To position, xs,ysRespectively indicate relative position of the current shelf inside shelf heap；
Step 2: the operation rule of road is, it is specified that road is one-way traffic in design repository, and the two road of arbitrary neighborhood
Driving direction it is opposite；Robot can only enter in shelf heap from the road of cross direction profiles；Define fortune of the robot on road
Row state RS=[xR yR dx dy], wherein xR,yRIndicate coordinate position of the robot in warehouse coordinate system, dx,dyTable respectively
Show the feasible direction of robot, the i.e. driving direction of road where robot, dx,dy∈{0,1,2,3,4}；Work as dxWhen being 0, table
Show that robot can not cross running；If dxIt is 3, then robot can be to right travel；If dxIt is 4, then robot can be to left lateral
It sails；Work as dyWhen being 0, indicate that robot can not longitudinal driving；If dyIt is 1, then robot can travel upwards；If dyIt is 2, then machine
Device people can be to downward driving；
Step 3: the initial position and target position of given robot, if robot can reach target without any node
Position then directly gives final path list according to the initial position of robot and target position；Otherwise, it is reduced to storehouse
Path planning problem between the node of library；Using robot from first node of initial position arrival as start node,
Robot reaches the last one node passed through when target position as destination node；
Step 4: on the basis of step 3, for given start node and destination node, most using improved A* algorithm search
Shortest path；When calculating heuristic function cost, improved A* algorithm needs to calculate graceful between present node and destination node
Hatton's distance turns to number and around row distance；Assuming that being n as the node currently estimated, note manhatton distance cost is hm
(n), hm(n)=| xb-xf|+|yb-yf|, wherein xb,ybFor the coordinate of start node, xf,yfFor the coordinate of destination node；Note turns
It is h to costt(n), ht(n)=q × turncost, wherein q indicates the minimum steering time between present node and destination node
Number, turncost indicate the cost value turned to every time；Note is h around row distance coste(n), by judging present node and target
The detour number of node, in conjunction with the available specific h of information of storehouse modele(n) value；Obtain manhatton distance cost,
Turn to cost, after row distance cost, the heuristic function that note improves A* algorithm is h (n), for estimating present node n and mesh
Mark the heuristic cost of node, h (n)=hm(n)+ht(n)+he(n)；Using A* algorithm search node listing is improved, it is denoted as
Listj；
Step 5: remembering that the path list between the initial position of robot and start node is Listb, the target position of robot with
Path list between destination node is Listf；By ListbIt is added to ListjHead, by ListfIt is added to ListjTail
Portion constitutes complete path list；Node coordinate position in list is corresponding with the position coordinates in actual warehouse, it obtains
To the running route of robot；
Step 6: the running route of robot being extended to the operating status list of robot, is denoted as SListR, by a series of machine
Device people's state is constituted；According to given robot running route, judges the operation rule of road where each point on route, obtain
Robot current point traffic direction, so that the running route of robot to be extended to the operating status of robot；By machine
The operating status list of people is sent to robot, and robot is allowed to complete the task of line walking.
2. the improvement A* robot optimum path planning method according to claim 1 suitable for warehouse environment, feature
Be: the road quantity for guaranteeing transverse and longitudinal direction is even number, avoids the occurrence of the irremovable state of robot；Shelf in step 1
Position coordinates indicate integrally to establish coordinate system with shelf heap, define each shelf relative position in whole shelf heap, pass through
Coordinate transform obtains the coordinate in warehouse coordinate system.
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