CN108170146A - A kind of paths planning method based on known environment - Google Patents
A kind of paths planning method based on known environment Download PDFInfo
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- CN108170146A CN108170146A CN201711495089.3A CN201711495089A CN108170146A CN 108170146 A CN108170146 A CN 108170146A CN 201711495089 A CN201711495089 A CN 201711495089A CN 108170146 A CN108170146 A CN 108170146A
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- node
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
Abstract
Present invention is disclosed a kind of paths planning method based on known environment, this method by adjusting the weights of local edge, update adjacency matrix A in real time, it is used to implement active path planning, the utilization rate for by the section of " locked ", improving section can be reduced, improves the working efficiency of whole system on the whole；The possibility of conflict is pursued and attacked to reduce by two AGV, the weights (travel direction) on side where temporarily increasing AGV reduce the possibility (just in case pursuing and attacking conflict, also there is urgent counter-measure) for pursuing and attacking conflict.
Description
Technical field
The present invention relates to Path Planning Technique field more particularly to a kind of dynamic path planning method of more AGV, and can expand
Exhibition is applied to the Path Planning Technique field of mobile robot.
Background technology
AGV (Automated Guided Vehicle) is i.e. " automated guided vehicle ".It is industrial 4.0 intelligent plant weights
The means of transport wanted, the operational efficiency of AGV largely affect the production efficiency of entire unmanned factory.Therefore, more AGV
Efficiently, orderly, safe work compound has a very important significance, and the path planning of more AGV and dynamic adjustment are its needs
One of crucial problem of solution.
Since AGV often travels (i.e. a section once only allows an AGV to pass through) according to trapped orbit, so when more
When a AGV is run simultaneously, path is needed to be adjusted into Mobile state, current adjustable strategies are broadly divided into original place waiting and detour two
Kind.Original place waiting strategy is relatively simple, but it will substantially reduce the entire working efficiency for dispatching system, especially when one or more
A idle AGV (or failure) gear is in operating path, it is most likely that leads to the collapse of whole system；It is tactful about detouring,
More popular at present is the dispatching method based on time window, but it considerably increases the calculation amount of entire scheduling system, and right
Planning and adjusting can not be made in time in accident.So it is relatively small to find a kind of calculation amount, and entire scheduling can be improved
The dynamic path planning method of system working efficiency is extremely urgent.
Being also disclosed document discloses some methods about AGV path plannings, such as patent at present《Based under known environment
Method for planning path for mobile robot》(application number：201610569810.8) propose it is a kind of to all sections that will be passed by
" locking ", the active path planning by the section " unlock " after warp.Though this method can allow the robot for being followed by traffic order
Selection is detoured, is avoided collision, but " waste " crosses multipath, and the path for greatly reducing the robot that is followed by traffic order is selected
Space is selected (especially when robot is more, it is most likely that be " locked " because crossing multipath, and cause later to obtain traffic order
Robot " at the end of one's rope ", can only original place wait for；And the robot " being driven into a corner " being currently running, lead to whole system
Collapse；), reduce the working efficiency and stability of whole system；In addition there are one implied terms --- institutes for the patented method
Robot is constant speed (i.e. there is no pursues and attacks conflict), however in actual scene, the speed of service of each AGV is often not
With, it is understood that there may be pursue and attack collision problem.
Invention content
The technical problems to be solved by the invention are to realize a kind of section for reducing quilt " locked ", avoid section " waste ",
It can eliminate or reduce the paths planning method for the possibility for pursuing and attacking conflict.
To achieve these goals, the technical solution adopted by the present invention is：A kind of path planning side based on known environment
Method, it is known that the path of environment is the map of input, and feasible path is equipped between node and node on map, which is characterized in that
Paths planning method includes the following steps：
Step 1 carries out the path on map between node and node two-way assignment or update assignment；
Step 2, generation adjacency matrix A；
Step 3 calculates shortest distance matrix and shortest path matrix；
Step 4, according to telecontrol equipment current location, obtain the shortest path for reaching current terminus；
Step 5, telecontrol equipment are travelled by shortest path, and by current location Real-time Feedback；
Step 6 judges whether telecontrol equipment reaches new node, if then sending out path request and return to step 4 again,
If otherwise perform next step；
Step 7 judges whether that two telecontrol equipment distances are less than setting value, if otherwise return to step 5, if holding
Row is in next step；
Step 8 judges whether two telecontrol equipment directions of motion are identical, if otherwise stopping two telecontrol equipments and returning to step
Rapid 1, if then stopping the telecontrol equipment being located behind, until front truck reaches new node, restore the traveling of rear telecontrol equipment.
Weights size is assigned by distance ω per paths in the step 11It influences, rotation angle ω2And setting its
He is road conditions factor ω3It restricts, per paths one-way value ω=ω1+ω2+ω3。
The step 3 calculates shortest distance matrix D and shortest path matrix P using Floyd algorithms.
Telecontrol equipment in the step 4 is AGV or kinematic robot.
The step 5 is by the control device of current location Real-time Feedback to system, and the control device is according to telecontrol equipment
Current location update map on the two-way assignment in path between node and node.
The method of the two-way assignment of more new route：The i-th row jth column element a (i, j)=ω ij of adjacency matrix A, when certain movement
When device is from i-node to the section of j nodes, then to a (i, j) and a (j, i) again assignment：A (i, j)=k* ω ij, a (j, i)=
+∞；If AGV is stopped on i-node to the path of j nodes, a (i, j)=a (j, i)=+ ∞.
The k is empirical value, and the frequency size used by the section, current AGV speed factors determine.
The k >=1, k value are bigger, then follow-up AGV is smaller by the possibility in the section.
The present invention can reduce the utilization rate for by the section of " locked ", improving section, improve entire system on the whole
The working efficiency of system reduces the possibility for pursuing and attacking conflict, and has the counter-measure for pursuing and attacking conflict.
Description of the drawings
The content of width attached drawing expression every in description of the invention is briefly described below：
Fig. 1 is the topological diagram of site environment construction；
Fig. 2 is paths planning method flow chart.
Specific embodiment
Such as Fig. 1 and shown, by taking AGV trolleies as an example, the paths planning method based on known environment is as follows：
1) all path topology figures that AGV can walk first are drawn, as shown in Figure 1 according to site environment；
2) topological diagram is made of (double-head arrow) node (circle) and side；
3) each node when being two-way, i.e., from node 1 to the side ω of node 212With from node 2 to the side of node 1
ω21Weights may be different (weights are assigned for infinity for the side not being connected directly)；
4) the weights ω of each edge not only distance ω between by two nodes1It influences, rotation angle ω2And other road conditions factors
ω3Influence, i.e. ω=ω1+ω2+ω3；
5) weights on all sides can be represented with adjacency matrix A in step 2), the i-th row jth column element a (i, j) of wherein A=
ωij；
6) read step 5) in matrix A, calculate shortest distance matrix D and shortest path matrix P with Floyd algorithms；
7) the i-th row jth column element d (i, j) of shortest distance matrix D represents i-th of node to the MINIMUM WEIGHT of j-th of node
Value；
8) the i-th row jth column element p (i, j) of shortest path matrix P is represented, is saved most from i-th of node to j-th
In short path, it is necessary first to the intermediate transit point of arrival；
9) AGV is travelled by traffic order, and Real-time Feedback current location；
10) the every node of AGV asks a traffic order；
11) AGV receive traffic order be from " present node " to described in step 8) " firstly the need of the transfer of arrival
Point "；
12) sensor for feedback current location in step 9) includes but not limited to StarGazer, Sick
Easily boat etc. of NAV350, Hart；
13) when certain AGV is travelled at certain moment when from i-node to the section of j nodes, then to a (i, j) and again, a (j, i) is heavy
New assignment：A (i, j)=k* ω ij, a (j, i)=+ ∞；If AGV stops (or failure) in i-node to the path of j nodes
On, then a (i, j)=a (j, i)=+ ∞；
14) k described in step 13) for empirical value, the frequency size used by the section, current AGV speed etc. because
Element determines (k >=1, k value are bigger, then follow-up AGV is smaller by the possibility in the section)；
15) in step 13) after right value update, then real-time update adjacency matrix A, real-time update calculate Distance matrix D and road
Drive matrix P；
If 16) AGV reaches new node, step 10) is performed；Otherwise the distance judged whether there is between two AGV is less than threshold
Value S (for preset value)；
17) it is less than threshold value S if there is no the distance between two AGV, then continues to travel by current path；Otherwise judge this two
Whether the direction of motion of AGV is identical；
18) if the direction of motion of two AGV on the contrary, if two AGV it is all out of service and alarm；Otherwise the latter stops (the former
Continue to travel), when the former is driven out to the section, continue to continue to travel by current path.
The present invention is exemplarily described above in conjunction with attached drawing, it is clear that present invention specific implementation is not by aforesaid way
Limitation, as long as employ the inventive concept and technical scheme of the present invention progress various unsubstantialities improvement or without changing
Other occasions are directly applied to by the design of the present invention and technical solution, within protection scope of the present invention.
Claims (8)
1. a kind of paths planning method based on known environment, it is known that the path of environment is the map of input, on map node with
Feasible path is equipped between node, which is characterized in that paths planning method includes the following steps：
Step 1 carries out the path on map between node and node two-way assignment or update assignment；
Step 2, generation adjacency matrix A；
Step 3 calculates shortest distance matrix and shortest path matrix；
Step 4, according to telecontrol equipment current location, obtain the shortest path for reaching current terminus；
Step 5, telecontrol equipment are travelled by shortest path, and by current location Real-time Feedback；
Step 6 judges whether telecontrol equipment reaches new node, if then sending out path request and return to step 4 again, if not
Then perform next step；
Step 7 judges whether that two telecontrol equipment distances are less than setting value, if otherwise return to step 5, if so then execute under
One step；
Step 8 judges whether two telecontrol equipment directions of motion are identical, if otherwise stopping two telecontrol equipments and return to step 1,
If then stopping the telecontrol equipment being located behind, until front truck reaches new node, restore the traveling of rear telecontrol equipment.
2. the paths planning method based on known environment according to claim 1, it is characterised in that：Every in the step 1
Weights size is assigned by distance ω in path1It influences, rotation angle ω2And other road conditions factors ω of setting3It restricts, every road
Diameter one-way value ω=ω1+ω2+ω3。
3. the paths planning method based on known environment according to claim 1, it is characterised in that：The step 3 utilizes
Floyd algorithms calculate shortest distance matrix D and shortest path matrix P.
4. according to the paths planning method based on known environment described in claim 1,2 or 3, it is characterised in that：In the step 4
Telecontrol equipment be AGV or kinematic robot.
5. the paths planning method based on known environment according to claim 4, it is characterised in that：The step 5 will be current
Position Real-time Feedback is to the control device of system, and the control device is according to node on the current location of telecontrol equipment update map
The two-way assignment in path between node.
6. the paths planning method based on known environment according to claim 5, it is characterised in that：The two-way assignment of more new route
Method：The i-th row jth column element a (i, j)=ω ij of adjacency matrix A, when certain telecontrol equipment is from i-node to the section of j nodes
When, then to a (i, j) and a (j, i) again assignment：A (i, j)=k* ω ij, a (j, i)=+ ∞；If AGV stops at i-node to j
On the path of node, then a (i, j)=a (j, i)=+ ∞.
7. the paths planning method based on known environment according to claim 6, it is characterised in that：The k is empirical value, by
Frequency size that the section is used, current AGV speed factors determine.
8. the paths planning method based on known environment according to claim 1, it is characterised in that：The k >=1, k value are got over
Greatly, then follow-up AGV is smaller by the possibility in the section.
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| CN109029478A (en) * | 2018-06-20 | 2018-12-18 | 华南理工大学 | A kind of intelligent vehicle paths planning method based on improvement Floyd algorithm |
| CN109724612A (en) * | 2019-01-14 | 2019-05-07 | 浙江大华技术股份有限公司 | A kind of AGV paths planning method and equipment based on topological map |
| CN111207765A (en) * | 2020-01-07 | 2020-05-29 | 珠海丽亭智能科技有限公司 | Robot parking lot path mutual exclusion solution method |
| CN111435249A (en) * | 2019-01-10 | 2020-07-21 | 招商局国际信息技术有限公司 | Control method, device and equipment of unmanned equipment and storage medium |
| CN112233427A (en) * | 2020-10-15 | 2021-01-15 | 芜湖哈特机器人产业技术研究院有限公司 | Laser forklift traffic control system |
| CN112665603A (en) * | 2020-12-16 | 2021-04-16 | 的卢技术有限公司 | Multi-vehicle path planning method based on improvement with time window A |
| CN112783167A (en) * | 2020-12-30 | 2021-05-11 | 南京熊猫电子股份有限公司 | Multi-region-based real-time path planning method and system |
| TWI796017B (en) * | 2021-11-16 | 2023-03-11 | 新加坡商鴻運科股份有限公司 | Automated guided vehicle scheduling method, electronic device and computer-readable storage medium |
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| CN111435249A (en) * | 2019-01-10 | 2020-07-21 | 招商局国际信息技术有限公司 | Control method, device and equipment of unmanned equipment and storage medium |
| CN111435249B (en) * | 2019-01-10 | 2023-12-15 | 招商局国际科技有限公司 | Control method, device, equipment and storage medium of unmanned equipment |
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| CN111207765A (en) * | 2020-01-07 | 2020-05-29 | 珠海丽亭智能科技有限公司 | Robot parking lot path mutual exclusion solution method |
| CN112233427A (en) * | 2020-10-15 | 2021-01-15 | 芜湖哈特机器人产业技术研究院有限公司 | Laser forklift traffic control system |
| CN112665603A (en) * | 2020-12-16 | 2021-04-16 | 的卢技术有限公司 | Multi-vehicle path planning method based on improvement with time window A |
| CN112665603B (en) * | 2020-12-16 | 2022-03-25 | 的卢技术有限公司 | Multi-vehicle path planning method based on improvement with time window A |
| CN112783167A (en) * | 2020-12-30 | 2021-05-11 | 南京熊猫电子股份有限公司 | Multi-region-based real-time path planning method and system |
| TWI796017B (en) * | 2021-11-16 | 2023-03-11 | 新加坡商鴻運科股份有限公司 | Automated guided vehicle scheduling method, electronic device and computer-readable storage medium |
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