CN111413980A - Automatic guided vehicle path planning method for inspection - Google Patents
Automatic guided vehicle path planning method for inspection Download PDFInfo
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- CN111413980A CN111413980A CN202010264455.XA CN202010264455A CN111413980A CN 111413980 A CN111413980 A CN 111413980A CN 202010264455 A CN202010264455 A CN 202010264455A CN 111413980 A CN111413980 A CN 111413980A
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- 238000007689 inspection Methods 0.000 title claims abstract description 39
- 238000000034 method Methods 0.000 title claims abstract description 31
- 238000009941 weaving Methods 0.000 claims abstract description 26
- 239000004753 textile Substances 0.000 claims abstract description 20
- 230000002457 bidirectional effect Effects 0.000 claims abstract description 15
- 238000012423 maintenance Methods 0.000 claims description 9
- 230000007547 defect Effects 0.000 claims description 7
- 239000011159 matrix material Substances 0.000 claims description 6
- 230000002093 peripheral effect Effects 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 238000004519 manufacturing process Methods 0.000 abstract description 10
- 230000009466 transformation Effects 0.000 abstract description 5
- 238000010845 search algorithm Methods 0.000 abstract description 4
- 238000001514 detection method Methods 0.000 description 5
- 230000004888 barrier function Effects 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- 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
- G05D1/0223—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
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- 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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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- 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
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
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- Radar, Positioning & Navigation (AREA)
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- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
The invention discloses an automatic guided vehicle path planning method for inspection, which is applied to textile weaving inspection. The invention is based on the local bidirectional closed loop and bidirectional search algorithm, effectively solves the global optimal planning of the path in the weaving routing inspection and the re-planning of the path after dynamic obstacle avoidance; the conflict problem of multiple automatic guided vehicles in path planning is solved through the arrangement and the updating of the time window and the conflict negotiation strategy; the matching suitable intelligent system can meet the requirements of automation and intelligent transformation and upgrade of production lines in the textile weaving industry.
Description
Technical Field
The invention relates to the technical field of automatic guided vehicle path planning, in particular to an automatic guided vehicle path planning method for inspection.
Background
In the production process of the textile weaving production line, the inspection work is required to be arranged, whether the textile machine works normally or not is observed, whether the fabric being produced has defects or not is observed, and the like. The traditional method arranges workers for inspection, and has the defects of high labor cost, high working strength, low inspection system efficiency, narrow product detection coverage area and the like. Under the background of intelligent manufacturing 2025 and industrial 4.0, the textile weaving production industry is in urgent need of automation and intelligent upgrading.
Specifically, in the prior art, patent application publication No. CN 110503260A discloses an AGV scheduling method based on dynamic path planning, which initializes an AGV work site, can simulate an actual map, and performs optimal scheduling on an AGV selection process and an obstacle avoidance condition of an AGV in an execution process based on an adjacency matrix and a distance matrix established by a froude algorithm. The prior art for automatic guided vehicle path planning has the following problems: the labor cost is high, and the working strength is high; the inspection system has low efficiency and a product detection coverage area is narrow; the automatic intelligent upgrading requirement of the production line cannot be met.
Disclosure of Invention
In order to solve the technical problems, the invention provides an automatic guided vehicle path planning method for routing inspection.
To achieve the purpose, the embodiment of the invention adopts the following technical scheme:
the automatic guided vehicle path planning method for inspection is applied to textile weaving inspection and is characterized by comprising the following steps of:
step S1: according to the weaving routing inspection environment, a map is constructed by adopting a topological modeling method through path nodes and an automatic guided vehicle, wherein the path nodes are the weaving machines;
step S2: when the path planning is started, the automatic guided vehicle sends a command to select whether to be dispatched to an initial position or not through the control system, if the automatic guided vehicle is dispatched to the initial position, the working state information of the path node, the position and the working state information of the automatic guided vehicle are initialized, and the time window variable information is cleared; if the position is not scheduled, updating the working state information of the path node, the position and the working state information of the automatic guided vehicle, and clearing time window variable information, wherein the time window variable records the serial number and the arrival time of the automatic guided vehicle associated with the path node;
step S3: local bidirectional closed-loop constraint is designed, the automatic guided vehicle runs on the adjacent track in a closed-loop mode under the condition of no conflict, and the running of the adjacent track is preferentially considered under the condition of conflict;
step S4: after the initial path planning is finished, generating the number of the automatic guided vehicle and the time of the automatic guided vehicle reaching a path node, and verifying whether the path planning has conflict or not;
step S5: under the condition that the path planning has conflict, dynamically allocating priorities to the multiple automatic guided vehicles according to the conflict types of the automatic guided vehicles based on a conflict negotiation strategy; when an obstacle appears in the path, the road weight is dynamically changed, and path planning is carried out again to realize real-time obstacle avoidance of the multiple automatic guided vehicles;
step S6: under the condition that no conflict exists in path planning, judging whether a path node has a maintenance obstacle conflict, and if the maintenance obstacle conflict exists, continuously and dynamically allocating priorities to the multiple automatic guided vehicles on the basis of a conflict negotiation strategy;
step S7: and repeating the steps S3-S6, searching a path plan which aims at the optimal overall efficiency of the automatic guided vehicle and generating a global path plan under the constraint condition of local bidirectional closed loop based on the adjustment of the path priority and the search of the obstacle avoidance information, and generating and executing an inspection task when each path node is inspected by the automatic guided vehicle and no conflict exists in the path.
In the technical scheme of the invention, in step S1, path nodes in the weaving routing inspection environment are numbered according to a matrix, tracks are arranged between each row or each column of the path nodes and the peripheral side edges of the path nodes, the automatic guided vehicle runs on all the tracks in two directions, can turn and convert to the tracks between each row or each column of the path nodes through the tracks on the peripheral side edges of the path nodes, and sets the automatic guided vehicle to run at a constant speed and adjusts the speed according to requirements, and only one vehicle is allowed to pass through the same path node.
In the technical scheme of the invention, the conflict negotiation strategy in the step S5 comprises two modes of a waiting strategy and a path re-planning strategy, wherein the waiting strategy refers to waiting with low priority, and the path is traveled according to the original path with high priority; the path replanning strategy refers to replanning paths with low priority and waiting with high priority.
In the technical scheme of the invention, in the step S5, the conflict types of the automatic guided vehicle path planning include the following types:
the collision of opposite encounters, namely two vehicles traveling in opposite directions meet at the same node;
vertical encounter conflict, namely two vehicles in the vertical direction meet in a turning direction;
and the occupation conflict, namely the forward direction prevents other automatic guided vehicles from advancing due to the idle or fault parking of the automatic guided vehicles.
In the technical scheme of the invention, the overhaul barrier conflict specifically comprises: when the automatic guided vehicle detects that the path nodes do not work normally or the products have defects in the routing inspection process, the automatic guided vehicle informs a maintenance engineer of processing and occupies the running position of the track.
Compared with the prior art, the method has the following beneficial technical effects:
(1) the automatic guided vehicle replaces manual inspection, labor cost is reduced, and the automatic guided vehicle is used for intelligent inspection.
(2) And the optimal path planning improves the efficiency of the inspection system and widens the product detection area.
(3) The matching suitable intelligent system can meet the requirements of automation and intelligent transformation and upgrade of production lines in the textile weaving industry.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic view of an environmental site topology of the present invention;
FIG. 2 is a schematic view of the present invention illustrating a service barrier conflict;
fig. 3 is a flowchart of the automated guided vehicle path planning method of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
The invention provides an automatic guided vehicle for automatic routing inspection of textile weaving, which replaces manual routing inspection, and particularly provides a path planning method under a specific field.
Firstly, a map is constructed by adopting a topological modeling method according to a weaving routing inspection environment. The method is characterized in that a bidirectional breadth search algorithm based on time factors is adopted, a local bidirectional closed loop mode is designed, and global optimal planning of paths of multiple automatic guided vehicles and re-planning of paths after dynamic obstacle avoidance are achieved.
Secondly, the time of the automatic guided vehicles passing through the path nodes (namely the textile machines) is calculated, and the collision and conflict problems of the multiple automatic guided vehicles in the path planning are solved through the arrangement and the updating of the time windows. Based on a conflict negotiation strategy, the system efficiency is improved by dynamically allocating the priority to the multiple automatic guided vehicles; when an obstacle appears in the path, the road weight is dynamically changed, path planning is carried out again to realize real-time obstacle avoidance of the multiple automatic guided vehicles, and the dynamic adaptability and the robustness of the system under complex conditions are enhanced.
Finally, site conditions can be considered for intelligent upgrading, information interaction can be further carried out through the site conditions and the sensing of the Internet of things of a factory workshop to form an intelligent automatic guided vehicle group, and the intelligent automatic guided vehicle group is matched with a proper machine vision textile defect detection system, so that the automation and intelligent transformation upgrading requirements of the production line of the textile weaving industry can be met, and the intelligent automatic guided vehicle group has higher practical value.
Specifically, as shown in fig. 1 to 3, the invention provides an automatic guided vehicle path planning method for inspection, which is applied to textile weaving inspection and comprises the following steps:
step S1: according to the weaving routing inspection environment, a map is constructed by adopting a topological modeling method through path nodes and an automatic guided vehicle, wherein the path nodes are the weaving machines;
as shown in fig. 1, path nodes in the textile weaving inspection environment are numbered according to a matrix, tracks are arranged between each row or each column of the path nodes and on the peripheral side edges of the path nodes, the automatic guided vehicle runs on all the tracks in a bidirectional mode, turns and is converted to the tracks between each row or each column of the path nodes through the tracks on the peripheral side edges of the path nodes, the automatic guided vehicle is set to run at a constant speed, the speed is adjusted according to requirements, and only one vehicle is allowed to pass through the same path node.
Specifically, as identified in FIG. 1, the path nodes, i.e., the textile machines, are numbered in a matrix A11-Amn, where m and n are both integers greater than 1.
Step S2: when the path planning is started, the automatic guided vehicle sends a command to select whether to be dispatched to an initial position or not through the control system, if the automatic guided vehicle is dispatched to the initial position, the working state information of the path node, the position and the working state information of the automatic guided vehicle are initialized, and the time window variable information is cleared; if the position is not scheduled, updating the working state information of the path node, the position and the working state information of the automatic guided vehicle, and clearing time window variable information, wherein the time window variable records the serial number and the arrival time of the automatic guided vehicle associated with the path node;
step S3: local bidirectional closed-loop constraint is designed, the automatic guided vehicle runs on the adjacent track in a closed-loop mode under the condition of no conflict, and the running of the adjacent track is preferentially considered under the condition of conflict;
step S4: after the initial path planning is finished, generating the number of the automatic guided vehicle and the time of the automatic guided vehicle reaching a path node, and verifying whether the path planning has conflict or not;
step S5: under the condition that the path planning has conflict, dynamically allocating priorities to the multiple automatic guided vehicles according to the conflict types of the automatic guided vehicles based on a conflict negotiation strategy; when an obstacle appears in the path, the road weight is dynamically changed, and path planning is carried out again to realize real-time obstacle avoidance of the multiple automatic guided vehicles;
the conflict negotiation strategy comprises a waiting strategy and a path re-planning strategy, wherein the waiting strategy refers to waiting with low priority, and the priority is high to walk according to the original path; the path replanning strategy refers to replanning paths with low priority and waiting with high priority.
The conflict types of the automatic guided vehicle path planning comprise the following types:
the collision of opposite encounters, namely two vehicles traveling in opposite directions meet at the same node;
vertical encounter conflict, namely two vehicles in the vertical direction meet in a turning direction;
and the occupation conflict, namely the forward direction prevents other automatic guided vehicles from advancing due to the idle or fault parking of the automatic guided vehicles.
Step S6: under the condition that no conflict exists in path planning, judging whether a path node has a maintenance obstacle conflict, and if the maintenance obstacle conflict exists, continuously and dynamically allocating priorities to the multiple automatic guided vehicles on the basis of a conflict negotiation strategy;
as shown in fig. 2, the overhaul obstacle conflict specifically includes: when the automatic guided vehicle detects that the path nodes do not work normally or the products have defects in the routing inspection process, the automatic guided vehicle informs a maintenance engineer of processing and occupies the running position of the track.
Step S7: and repeating the steps S3-S6, searching a path plan which aims at the optimal overall efficiency of the automatic guided vehicle and generating a global path plan under the constraint condition of local bidirectional closed loop based on the adjustment of the path priority and the search of the obstacle avoidance information, and generating and executing an inspection task when each path node is inspected by the automatic guided vehicle and no conflict exists in the path.
The method is based on the local bidirectional closed loop and the bidirectional search algorithm, namely comprises the steps of adjusting the priority of the path and avoiding the obstacle information, so that the global optimal planning of the path in the weaving routing inspection and the re-planning of the path after dynamic obstacle avoidance are effectively solved; the conflict problem of multiple automatic guided vehicles in path planning is solved through the arrangement and the updating of the time window and the conflict negotiation strategy; the matching suitable intelligent system can meet the requirements of automation and intelligent transformation and upgrade of production lines in the textile weaving industry.
The invention provides an automatic guided vehicle for automatic routing inspection of textile weaving instead of manual routing inspection, and particularly relates to a path planning method under a specific field. The invention relates to a method for constructing a textile weaving inspection environment map by adopting a topological modeling method, which is based on a bidirectional search algorithm of a time factor and designs a local bidirectional closed loop mode to realize the global optimal planning of a multi-automatic guided vehicle path and the re-planning of the path after dynamic obstacle avoidance. And the site condition can be considered for intelligent upgrading, information interaction can be further carried out through the Internet of things perception of a factory workshop to form an intelligent AGV group, and the intelligent AGV group is matched with a proper machine vision textile defect detection system, so that the automation of a production line of the textile weaving industry can be met, the intelligent transformation upgrading requirement is met, and the practical value is high.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (5)
1. The automatic guided vehicle path planning method for inspection is applied to textile weaving inspection and is characterized by comprising the following steps of:
step S1: according to the weaving routing inspection environment, a map is constructed by adopting a topological modeling method through path nodes and an automatic guided vehicle, wherein the path nodes are the weaving machines;
step S2: when the path planning is started, the automatic guided vehicle sends a command to select whether to be dispatched to an initial position or not through the control system, if the automatic guided vehicle is dispatched to the initial position, the working state information of the path node, the position and the working state information of the automatic guided vehicle are initialized, and the time window variable information is cleared; and if the position is not scheduled, updating the working state information of the path node, the position and the working state information of the automatic guided vehicle, and clearing time window variable information, wherein the time window variable records the serial number and the arrival time of the automatic guided vehicle associated with the path node.
Step S3: local bidirectional closed-loop constraint is designed, the automatic guided vehicle runs on the adjacent track in a closed-loop mode under the condition of no conflict, and the running of the adjacent track is preferentially considered under the condition of conflict;
step S4: after the initial path planning is finished, generating the number of the automatic guided vehicle and the time of the automatic guided vehicle reaching a path node, and verifying whether the path planning has conflict or not;
step S5: under the condition that the path planning has conflict, dynamically allocating priorities to the multiple automatic guided vehicles according to the conflict types of the automatic guided vehicles based on a conflict negotiation strategy; when an obstacle appears in the path, the road weight is dynamically changed, and path planning is carried out again to realize real-time obstacle avoidance of the multiple automatic guided vehicles;
step S6: under the condition that no conflict exists in path planning, judging whether a path node has a maintenance obstacle conflict, and if the maintenance obstacle conflict exists, continuously and dynamically allocating priorities to the multiple automatic guided vehicles on the basis of a conflict negotiation strategy;
step S7: and repeating the steps S3-S6, searching a path plan which aims at the optimal overall efficiency of the automatic guided vehicle and generating a global path plan under the constraint condition of local bidirectional closed loop based on the adjustment of the path priority and the search of the obstacle avoidance information, and generating and executing an inspection task when each path node is inspected by the automatic guided vehicle and no conflict exists in the path.
2. The automated guided vehicle path planning method according to claim 1, wherein in step S1, path nodes in the weaving routing inspection environment are numbered in a matrix, tracks are arranged between each row or each column of the path nodes and on the peripheral sides of the path nodes, the automated guided vehicle travels bidirectionally on all the tracks, turns around the tracks on the peripheral sides of the path nodes and switches to the tracks between each row or each column of the path nodes, and sets the automated guided vehicle to travel at a constant speed and adjusts the speed according to the requirements, and the same path node allows only one vehicle to pass through.
3. The automated guided vehicle path planning method according to claim 2, wherein the conflict negotiation strategy in step S5 includes two modes, namely a waiting strategy and a path re-planning strategy, wherein the waiting strategy refers to waiting with low priority, and the path is traveled along the original path with high priority; the path replanning strategy refers to replanning paths with low priority and waiting with high priority.
4. The automated guided vehicle path planning method according to claim 1, wherein in step S5, the conflict types of the automated guided vehicle path planning include the following types:
the collision of opposite encounters, namely two vehicles traveling in opposite directions meet at the same node;
vertical encounter conflict, namely two vehicles in the vertical direction meet in a turning direction;
and the occupation conflict, namely the forward direction prevents other automatic guided vehicles from advancing due to the idle or fault parking of the automatic guided vehicles.
5. The automated guided vehicle path planning method according to claim 3, wherein the service obstacle conflict specifically comprises: when the automatic guided vehicle detects that the path nodes do not work normally or the products have defects in the routing inspection process, the automatic guided vehicle informs a maintenance engineer of processing and occupies the running position of the track.
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| CN113159433A (en) * | 2021-04-28 | 2021-07-23 | 中国科学院沈阳应用生态研究所 | Dynamic navigation path searching method for integrated indoor mixed three-dimensional road network |
| CN113500605A (en) * | 2021-09-13 | 2021-10-15 | 中科开创（广州）智能科技发展有限公司 | Inspection task visualization method and device, computer equipment and storage medium |
| CN113625716A (en) * | 2021-08-12 | 2021-11-09 | 西安电子科技大学 | Multi-agent dynamic path planning method |
| CN113821024A (en) * | 2021-08-12 | 2021-12-21 | 苏州坤厚自动化科技有限公司 | Priority determination processing method suitable for AGV car scheduling |
| CN114384908A (en) * | 2021-12-16 | 2022-04-22 | 杭州申昊科技股份有限公司 | Intelligent navigation path planning system and method for track robot |
| CN115049347A (en) * | 2022-08-17 | 2022-09-13 | 成都秦川物联网科技股份有限公司 | Industrial Internet of things for AGV control and control method |
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| CN115049347A (en) * | 2022-08-17 | 2022-09-13 | 成都秦川物联网科技股份有限公司 | Industrial Internet of things for AGV control and control method |
| CN115049347B (en) * | 2022-08-17 | 2022-12-06 | 成都秦川物联网科技股份有限公司 | Industrial Internet of things system for AGV control and control method thereof |
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Application publication date: 20200714 |