CN109460039A - A kind of paths planning method of AGV - Google Patents
A kind of paths planning method of AGV Download PDFInfo
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- CN109460039A CN109460039A CN201811601116.5A CN201811601116A CN109460039A CN 109460039 A CN109460039 A CN 109460039A CN 201811601116 A CN201811601116 A CN 201811601116A CN 109460039 A CN109460039 A CN 109460039A
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- 238000004364 calculation method Methods 0.000 description 7
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Classifications
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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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
-
- 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
- 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
-
- 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
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
Abstract
The present invention be suitable for automatic control technology field, provide the paths planning method of AGV a kind of, include the following steps: plan starting point node to terminal node most short driving path；The time window of next intermediate node is detected with the presence or absence of conflict, if it exists, whether the time window starting point for detecting current AGV trolley is later than the time window starting point of conflict AGV trolley, if testing result is yes, the weight of next running section is set as infinitely great, the most short driving path of quadratic programming present node to terminal node；Calculate separately time T consumed by traveling quadratic programming path1And continue to execute time T consumed by initial driving path2；If time T1>T2, then after the time window unlock of next node, walk on according to initial driving path, otherwise, according to the route of quadratic programming.When encountering the conflict of path time window, quadratic programming is carried out to path, the execution time cost that quadratic programming path and path are continued is compared, path conflict is solved the problems, such as with the smallest strategy of time cost.
Description
Technical field
The invention belongs to automatic control technology fields, provide the paths planning method of AGV a kind of.
Background technique
Automatic guide vehicle AGV (Automated Guided Vichel), refers to automatic guidance system device, can
Good route or the route automatically generated are run between starting point and ending point according to the rules, the transport with certain safeguard protection
Vehicle is to integrate sound, light, electricity, computer technology, combines the advanced theoretical and application technology of current sciemtifec and technical sphere, extensively
Apply in flexible manufacturing system and automatic factory, have conevying efficiency height, energy conservation, reliable operation, be able to achieve flexible fortune
Many advantages, such as defeated, greatly improves the degree of automation and production efficiency.
For AGV, correct and effective path is selected, conevying efficiency can be improved, reduces transportation cost.It adopts at present
Solve the problems, such as that path is shortest with the methods of dijkstra's algorithm, Floyd algorithm and A* algorithm, since AGV is turning
The turning speed of point is relatively slow, will consume certain turning time, therefore the most short method of passage path searches out the path come not necessarily
It is most short to meet travel time.In the occasion that more AGV are used, do not considered using the method that shortest path planning comes out
The problem of between opposite conflict, node conflict between AGV, to reduce the efficiency of AGV traveling.
Summary of the invention
The embodiment of the present invention provides the paths planning method of AGV a kind of, when encountering the conflict of path time window, satisfies the need
Diameter carries out quadratic programming, compares quadratic programming path time cost and path continues to execute time cost, with time cost minimum
Strategy solve the problems, such as path conflict.
To achieve the goals above, the present invention provides the paths planning method of AGV a kind of, this method includes following step
It is rapid:
The most short driving path of S1, planning starting point node to terminal node, referred to as initial driving path；
S2, the next intermediate node of detection time window with the presence or absence of conflict, if testing result be it is yes, it is small to detect current AGV
The time window starting point of vehicle whether be later than conflict AGV trolley time window starting point, if testing result be it is yes, then follow the steps S3；
S3, the weight of next running section is set as infinitely great, the most short row of quadratic programming present node to terminal node
Sail path；
S4, time T consumed by traveling quadratic programming path is calculated separately1And it continues to execute initial driving path and is consumed
Time T2；
If S5, time T1>T2, then after the time window unlock of next node, walk on according to initial driving path, it is no
Then, according to the route of quadratic programming.
Further, the time T1For in quadratic programming path straight-line travelling time C1 and turning driving time C2 it
With.
Further, the calculation formula of the straight-line travelling time C1 is as follows:
v1For the AGV trolley straight-line travelling speed of setting, djFor the Euclidean distance in j-th of section in quadratic programming path, ∑
djFor all section sum of the distance in quadratic programming path, from present node to terminal node.
Further, the calculation formula of the turning driving time C2 is specific as follows:
M is that present node is travelled to the number of turns of terminal node, and R is the minimum turning radius of AGV trolley, v2For setting
Cornering speed.
Further, after step S1, before step S2 further include:
Whether S21, detection AGV trolley current location are node；
If S22, AGV trolley current location are node, whether detection present node is terminal node, if testing result is
It is no, then calculate the time window of next node, if testing result be it is yes, stop travelling, if AGV trolley current location be not section
Point, then continue to travel along driving path.
Further, before step S1 further include:
S11, the oriented map G=(V, E) of building, wherein V represents node, and E represents the side between two nodes, between two nodes
Side contain a weight w (uv), also have a weight w (ab) between two adjacent sides, indicate the corner between adjacent edge
Value；
S12, the actual coordinates of node are converted to screen displaing coordinate, generates topology diagram.
Further, the time window of next intermediate node determines that method is specific as follows:
The time point of ' locked ' zone initial position where reaching next intermediate node is calculated, the time point is time window
Starting point；
Estimate the time point that final position is reached from the initial position of ' locked ' zone where next intermediate node, the time
Point is time window terminal.
Further, it is overlapped when at least two AGV trolleies exist in the time window of same intermediate node, that is, judges the section
The time window conflict of point.
Further, time T2For the waiting unlocked time C3 of ' locked ' zone where next intermediate node and initial traveling road
The sum of remaining running time C4 of diameter.
1. carrying out carrying out quadratic programming to path, comparing quadratic programming path time when encountering the conflict of path time window
Cost and path continue to execute time cost, solve the problems, such as path conflict with the smallest strategy of time cost；
2. can be adapted for the two way of AGV trolley.
Detailed description of the invention
Fig. 1 is AGV paths planning method flow chart provided in an embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
AGV paths planning method provided by the invention is to inquire start node to terminal node based on Floyd algorithm
Most short driving path, in the process of moving, if the time window of next node has conflict, by the weight of next running section
It is set as infinitely great, quadratic programming is carried out based on present node, when comparison quadratic programming path time cost and path continue to execute
Between cost, with time cost it is the smallest strategy solve path conflict.
Fig. 1 is AGV paths planning method flow chart provided in an embodiment of the present invention, and this method comprises the following steps:
The most short driving path of S1, planning starting point node to terminal node, referred to as initial driving path；
In embodiments of the present invention, starting point of the starting point node, that is, current task in topological map, terminal node are worked as
The terminal in topological map of preceding task is planned from starting point node to terminal node in topological map based on Floyd algorithm
Most short driving path, each node including ordered arrangement.
Before step S1 further include:
S11, the oriented map G=(V, E) of building, wherein V represents the node in road sign map, and E is represented two in road sign map
A weight w (uv) is contained on side between node, the side between node u and node v, indicates European between node u and node v
Distance, the coordinate of node u are (x1,y1), the coordinate section of node v is (x2,y2), the calculation method of weight w (uv) is as follows:
Also there is a weight w (ab) between two adjacent sides, indicate the corner value between adjacent edge a and side b, R AGV
Minimum turning radius, weight w (uv) calculation method of adjacent edge is as follows:
S12, the actual coordinates of node in the environment are converted to screen displaing coordinate, generates topology diagram；
S2, the time window for detecting next intermediate node whether there is conflict, if testing result is no, the edge AGV traveling road
Diameter continues to travel, if testing result be it is yes, whether late detect time window starting point of the current AGV trolley at the intermediate node
In time window starting point of the conflict AGV trolley at the intermediate node, if testing result be it is yes, S3 is thened follow the steps, if detecting
As a result be it is no, then AGV continues to travel along driving path；
Time window is period of the AGV trolley by ' locked ' zone where intermediate node, and intermediate node, which refers to be located at, works as prosthomere
Point is designed with corresponding ' locked ' zone on each node, in the lock of node in order to avoid conflict to the node between terminal node
Determine region and carry out traffic control, different AGV trolleies are likely to occur for the time window of same intermediate node and partly overlap, all weight
It is folded not to be overlapped completely either, it is overlapped when at least two AGV trolleies exist in the time window of same intermediate node, that is, judges the section
The time window conflict of point, needs to carry out traffic control.
In embodiments of the present invention, after step S1, before step S2 further include:
Whether S21, detection AGV trolley current location are node；
If S22, AGV trolley current location are node, whether detection present node is terminal node, if testing result is
It is no, then calculate the time window of next node, if testing result be it is yes, stop travelling, if AGV trolley current location be not section
Point, then continue to travel along driving path.
In embodiments of the present invention, the time window of next intermediate node determines that method is specific as follows:
The time point of ' locked ' zone initial position where reaching next intermediate node is calculated, the time point is time window
Starting point；
Estimate the time point that final position is reached from the initial position of ' locked ' zone where next intermediate node, the time
Point is time window terminal.
S3, the weight of next running section is set as infinitely great, the most short row of quadratic programming present node to terminal node
Sail path；
After the weight of next running section is set as infinity, quadratic programming is carried out based on Floyd algorithm, is planned
Present node to destination node shortest path.
S4, time T consumed by traveling quadratic programming path is calculated separately1And it continues to execute initial driving path and is consumed
Time T2, initial driving path refers to the driving path that task based access control starting point is planned to task terminal, and quadratic programming path is
Refer to and the section weight in section is set as infinitely great, from current location to the planning path of task terminal.
In embodiments of the present invention, quadratic programming path institute elapsed time T1Calculation method it is specific as follows:
Time T1Equal to the straight-line travelling time C1 and the sum of turning driving time C2 in quadratic programming path, straight-line travelling
Shown in the calculating of time C1 such as formula (1):
v1For the AGV trolley straight-line travelling speed of setting, djFor the Euclidean distance in j-th of section in quadratic programming path, ∑
djFor all section sum of the distance in quadratic programming path, from present node to terminal node.；The meter of turning driving time C2
It calculates as shown in formula (2):
M is that present node is travelled to the number of turns of terminal node, and R is the minimum turning radius of AGV trolley, v2For setting
Cornering speed.
In embodiments of the present invention, time T2Calculation method it is specific as follows:
The remaining running time of waiting the unlocked time C3 and initial driving path of ' locked ' zone where next intermediate node
The sum of C4 is time T2；
Time C4 is equal to the sum of straight-line travelling time and turning driving time in remaining initial driving path, straight-line travelling
The calculation method of time and turning driving time are shown in formula (1) and formula (2) respectively, in addition, the calculating of time window is also based on
Formula (1) Lai Jinhang.
If S5, time T1>T2, then after the time window unlock of next node, walk on according to initial driving path, it is no
Then, according to the route of quadratic programming.
In embodiments of the present invention, above-mentioned AGV can be magnetic navigation AGV, first be laid with magnetic orbital, and be every in magnetic orbital
The endpoint in section sticks RFID card, and the corresponding card number of every RFID card is all different, if the AGV of two-dimension code navigation, then road
The endpoint of diameter sticks two dimensional code；If laser AGV, then need to put up reflector in the environment, and establish using laser sensor
The road sign map of entire activity space, in addition, the infall of driving path is located on node, it cannot be between two nodes.
AGV paths planning method provided by the invention has following advantageous effects:
1. carrying out carrying out quadratic programming to path, comparing quadratic programming path time when encountering the conflict of path time window
Cost and path continue to execute time cost, solve the problems, such as path conflict with the smallest strategy of time cost；
2. can be adapted for the two way of AGV trolley.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Made any modifications, equivalent replacements, and improvements etc., should all be included in the protection scope of the present invention within mind and principle.
Claims (9)
1. a kind of paths planning method of AGV, which is characterized in that described method includes following steps:
The most short driving path of S1, planning starting point node to terminal node, referred to as initial driving path；
S2, the next intermediate node of detection time window with the presence or absence of conflict, if testing result be it is yes, detect current AGV trolley
Time window starting point whether be later than conflict AGV trolley time window starting point, if testing result be it is yes, then follow the steps S3；
S3, the weight of next running section is set as infinitely great, the most short traveling road of quadratic programming present node to terminal node
Diameter；
S4, time T consumed by traveling quadratic programming path is calculated separately1And when continuing to execute consumed by initial driving path
Between T2；
If S5, time T1>T2, then after the time window unlock of next node, walk on according to initial driving path, otherwise, press
According to the route of quadratic programming.
2. the paths planning method of AGV as described in claim 1, which is characterized in that the time T1For in quadratic programming path
The sum of straight-line travelling time C1 and turning driving time C2.
3. the paths planning method of AGV as claimed in claim 2, which is characterized in that the calculating of the straight-line travelling time C1 is public
Formula is as follows:
v1For the AGV trolley straight-line travelling speed of setting, djFor the Euclidean distance in j-th of section in quadratic programming path, ∑ djFor
All section sum of the distance in quadratic programming path, from present node to terminal node.
4. the paths planning method of AGV as claimed in claim 2, which is characterized in that the calculating of the turning driving time C2 is public
Formula is specific as follows:
M is that present node is travelled to the number of turns of terminal node, and R is the minimum turning radius of AGV trolley, v2For turning for setting
Curved travel speed.
5. the paths planning method of AGV as described in claim 1, which is characterized in that after step S1, also wrapped before step S2
It includes:
Whether S21, detection AGV trolley current location are node；
If S22, AGV trolley current location be node, detection present node whether be terminal node, if testing result be it is no,
Calculate next node time window, if testing result be it is yes, stop travelling, if AGV trolley current location is not node, edge
Driving path continues to travel.
6. the paths planning method of AGV as described in claim 1, which is characterized in that before step S1 further include:
S11, the oriented map G=(V, E) of building, wherein V represents node, and E represents the side between two nodes, the side between two nodes
Containing a weight w (uv), also there is a weight w (ab) between two adjacent sides, indicates the corner value between adjacent edge；
S12, the actual coordinates of node are converted to screen displaing coordinate, generates topology diagram.
7. the paths planning method of AGV described in claim 1, which is characterized in that the time window of next intermediate node determines method
It is specific as follows:
The time point of ' locked ' zone initial position where reaching next intermediate node is calculated, the time point is that time window rises
Point；
The time point that final position is reached from the initial position of ' locked ' zone where next intermediate node is estimated, the time point is
For time window terminal.
8. the paths planning method of AGV described in claim 1, which is characterized in that when at least two AGV trolleies are in same middle node
The time window of point, which exists, to be overlapped, that is, judges the time window conflict of the node.
9. the paths planning method of AGV as described in claim 1, which is characterized in that time T2For locking where next intermediate node
The sum of the remaining running time C4 of waiting the unlocked time C3 and initial driving path in region.
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Cited By (15)
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| CN110162058A (en) * | 2019-06-03 | 2019-08-23 | 西交利物浦大学 | AGV method and device for planning |
| CN110488826A (en) * | 2019-08-20 | 2019-11-22 | 集美大学 | A kind of AGV collision prevention method, terminal device and storage medium suitable for path conflict |
| CN110751334A (en) * | 2019-10-21 | 2020-02-04 | 兰剑智能科技股份有限公司 | AGV (automatic guided vehicle) scheduling method and device based on intersection region prediction |
| CN110768904A (en) * | 2019-10-31 | 2020-02-07 | 广东电网有限责任公司 | Service communication detection method, device, terminal and storage medium for power communication network |
| CN111127890A (en) * | 2019-12-26 | 2020-05-08 | 广东嘉腾机器人自动化有限公司 | AGV traffic control scheduling method and storage device |
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| CN112099502A (en) * | 2020-09-15 | 2020-12-18 | 广东弓叶科技有限公司 | Intelligent garbage truck autonomous navigation path direction conflict regulation and control method and device |
| CN112525196A (en) * | 2020-11-23 | 2021-03-19 | 山东亚历山大智能科技有限公司 | AGV route planning and scheduling method and system based on multidimensional data |
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| CN114217615A (en) * | 2021-12-13 | 2022-03-22 | 哈尔滨工业大学芜湖机器人产业技术研究院 | Path planning method based on adjacency list |
| CN114383615A (en) * | 2021-12-02 | 2022-04-22 | 广东嘉腾机器人自动化有限公司 | Path planning method, system, equipment and medium of AGV (automatic guided vehicle) system |
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| CN110751334A (en) * | 2019-10-21 | 2020-02-04 | 兰剑智能科技股份有限公司 | AGV (automatic guided vehicle) scheduling method and device based on intersection region prediction |
| CN110768904A (en) * | 2019-10-31 | 2020-02-07 | 广东电网有限责任公司 | Service communication detection method, device, terminal and storage medium for power communication network |
| CN113111296A (en) * | 2019-12-24 | 2021-07-13 | 浙江吉利汽车研究院有限公司 | Vehicle path planning method and device, electronic equipment and storage medium |
| CN111127890A (en) * | 2019-12-26 | 2020-05-08 | 广东嘉腾机器人自动化有限公司 | AGV traffic control scheduling method and storage device |
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| CN111136658B (en) * | 2019-12-30 | 2021-10-19 | 广东博智林机器人有限公司 | Robot control method, device, electronic device and storage medium |
| CN111738649A (en) * | 2020-04-16 | 2020-10-02 | 北京京东乾石科技有限公司 | Track coordination method, device and system |
| CN112099502A (en) * | 2020-09-15 | 2020-12-18 | 广东弓叶科技有限公司 | Intelligent garbage truck autonomous navigation path direction conflict regulation and control method and device |
| CN112099502B (en) * | 2020-09-15 | 2024-04-16 | 广东弓叶科技有限公司 | Intelligent garbage truck autonomous navigation path direction conflict regulation and control method and device |
| CN112525196A (en) * | 2020-11-23 | 2021-03-19 | 山东亚历山大智能科技有限公司 | AGV route planning and scheduling method and system based on multidimensional data |
| CN112525196B (en) * | 2020-11-23 | 2023-04-28 | 山东亚历山大智能科技有限公司 | AGV route planning and scheduling method and system based on multidimensional data |
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| CN114217615A (en) * | 2021-12-13 | 2022-03-22 | 哈尔滨工业大学芜湖机器人产业技术研究院 | Path planning method based on adjacency list |
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| CN116679724B (en) * | 2023-07-05 | 2024-02-02 | 湘南学院 | Multi-load AGV collision-free and deadlock-free path planning method |
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