CN112486187A - Linear reciprocating type double-RGV task scheduling system and scheduling algorithm - Google Patents
Linear reciprocating type double-RGV task scheduling system and scheduling algorithm Download PDFInfo
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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
- G05D1/0225—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving docking at a fixed facility, e.g. base station or loading bay
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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
- 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 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
- G05D1/0276—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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- 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
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
- G05D1/0291—Fleet control
Abstract
The invention provides a linear reciprocating type double-RGV task scheduling system and a scheduling algorithm. The RGV dispatching system comprises a server, a client, a PLC acquisition system, a plurality of RGV trolleys, a PLC module, a sensing device for detecting the surrounding environment of the trolleys and a communication unit for communication between the RGV and the central control system, wherein each RGV trolley is provided with the PLC module; the scheduling algorithm of the invention provides calculation methods and execution steps of path planning, task management, task scheduling, task allocation and the like; the scheduling algorithm has the advantages of improving the utilization efficiency of the trolleys and reducing the conflict of the trolleys to the maximum extent; the scheduling system realized by the invention has the advantages of unified information scheduling, unified calculation and industrial informatization realization.
Description
Technical Field
The invention belongs to the technical field of logistics, and relates to a linear reciprocating type double-RGV task scheduling system and a scheduling algorithm.
Background
RGV is an abbreviation for (Rail Guided Vehicle), i.e. "Guided Vehicle". RGVs are commonly used in automated industrial systems, and have various application forms, such as one-rail-one-vehicle, one-rail-two-vehicle, one-vehicle single-station, one-vehicle double-station, one-vehicle multi-station, etc. Although the prior people research a path planning algorithm, most of the conventional RGV scheduling systems adopt a central control system or a cluster control system, and the path planning of multiple vehicles on the same rail is relatively less; in the on-orbit RGV task scheduling system, path planning is a basic component, and how tasks are managed, optimal task allocation is an important part; at present, few people are involved in the field of on-track multiple RGV task scheduling management.
Disclosure of Invention
The invention aims to provide a linear reciprocating type double-RGV task scheduling system and a scheduling algorithm, which are used for realizing optimal scheduling in an RGV scheduling process and improving RGV execution efficiency to the maximum extent.
The technical scheme of the invention is as follows:
the linear reciprocating type double-RGV task scheduling system comprises a client, a PLC control system, a bar code positioning system and a plurality of RGV trolleys; the client is a commercial industrial personal computer, the RGV is scheduled through a running scheduling algorithm and a path planning algorithm, the optimal combined task of the same-orbit executable trolley is obtained through the scheduling algorithm, and a corresponding instruction is sent to the corresponding RGV; the PLC control system is connected with the RGV and the client, receives an instruction sent by the client and enables the trolley to act; each RGV is provided with a sensing device for detecting the surrounding environment; the bar code positioning system comprises a bar code and a bar code recognizer, and is used for positioning the current coordinate of the RGV in real time; the RGV is provided with a PLC module, a sensing device for detecting the surrounding environment of the bogie and a communication unit for communication between the RGV and a central control system; each RGV trolley is provided with a sensing device, and the modules are used for collecting the information of the RGV, including the current coordinates, motion state, motion steps and IP address of the RGV trolley, to a client through a PLC.
The motion state of the RGV comprises a motion direction and a trolley dispatching state; the task operation step refers to key nodes which are required to pass by the trolley to complete a task, and comprises an initial stage of material taking, material feeding, material discharging and task completion;
the linear reciprocating type double RGV task scheduling algorithm comprises the following steps:
step 1: each RGV real-time monitoring feeds back the coordinate of the RGV, the task running step, and the equipment running state is sent to the client;
step 2: the client acquires all trolley information of the whole plant area, and the trolleys are grouped according to the trolley area to acquire all trolleys capable of executing tasks;
and step 3: generating all tasks of the area according to the trolley area;
and 4, step 4: sequentially distributing executable tasks for the executable trolleys in each trolley area according to the trolley tasks in each trolley area to form a task queue of each executable trolley; the executable rules comprise whether the trolley can be reached or not and whether the trolley needs to be carried for the second time or not after being executed;
and 5: combining task queues of executable trolleys in a trolley area, and selecting an optimal combination according to task execution levels; the task execution level refers to the weighted value of the task self priority (waiting time corresponding to a product, empty degree and the like) and the task external priority (including the type of a channel, the channel distance and the like);
step 6: and sending the obtained optimal task combination to a corresponding trolley for execution.
In the step 5, selecting an optimal combination rule:
1) the tasks of the execution trolleys are sequenced according to the task execution level and are combined and classified according to the task types;
2) searching each combination classification according to the sequence from high to low until finding the task combination with the highest execution level in a certain combination classification;
3) and if the task combinations are the task combinations with the same execution level, judging the task combination with the minimum execution path conflict degree in the combinations.
And a conflict degree calculation step:
1) acquiring the positions of a starting point and a target point of the two combined tasks;
2) obtaining the running interval of the task according to the left and right positions of the trolley to be executed of the task, the starting point position and the target point position of the task;
3) and calculating the area of the overlapped area.
The invention has the advantages that: the algorithm is an application algorithm integrating various basic algorithms, and comprises optimal path planning, a weight method, regional autonomy, regional balance, sequencing combination and the like; the algorithm is formed based on various basic RGV strategies, including a strategy based on multi-RGV cooperative operation, an RGV task scheduling strategy based on priority and the like; the algorithm is combined with industrial practice to create a new RGV strategy, which comprises a task strategy generated based on real-time dynamic data, so that the scientificity and the rationality of a task are improved; based on a task combination strategy of the same-rail executable trolley, the same-rail multi-trolley cooperatively executes tasks, so that conflicts are reduced to the maximum extent, and the response efficiency is improved; the method is used in an industrial automation system, the information of each RGV trolley is uniformly controlled, all trolleys in the area are reasonably managed, tasks are scientifically distributed, and the automation efficiency is improved; because each RGV is provided with a bar code locator of a PLC module and a navigation device, the position of each trolley, the state and the task information of each trolley can be fed back in real time, and the real-time performance of the system is improved.
Drawings
Fig. 1 is a diagram illustrating the structure of an RGV task scheduling system.
Fig. 2 is a flow chart of a scheduling algorithm.
In the figure: 10-client, 21-bar code positioning system, 20-PLC control system, 30-RGV trolley, 31-RGV trolley inner PLC module, 32-RGV sensor detection device and 33-RGV inner communication unit.
Detailed Description
The following embodiments are described in detail with reference to the drawings to describe the RGV avoidance control system and the method thereof.
As shown in fig. 1, the RGV task scheduling system includes a server 10, a client 21, and a PLC acquisition system 20. The server 10 is a central control system and is responsible for docking the PLC system and the client system; the client 21 is a central control system, and is used for running a scheduling algorithm and a path planning algorithm to schedule the RGVs and sending instructions to the corresponding RGVs; the PLC acquisition system 20 is used for connecting a client and the RGV, receiving a client 10 instruction and sending RGV30 information; each RGV30 is equipped with a PLC module 31, a sensing device 32 for sensing the environment around the car, and a communication unit 33 for the RGV to communicate with the central control system.
When the system is in operation, the PLC acquisition system 20 monitors position information of the car RGV in real time, and transmits the position information to the client 21 through the server 10, and the task management system running on the client acquires information such as the position information of the RGV30, the task information on each RGV30, the operation mode of each RGV30, and the operation steps, which are transmitted from the server 10, and then transmits the information to the RGV task scheduling algorithm to operate, so as to obtain an optimal task combination, and transmit corresponding tasks to the corresponding RGV 30.
As shown in fig. 2, the process of executing the scheduling algorithm computation flow chart of the straight-line reciprocating dual-RGV task scheduling system is as follows:
s2-1, acquiring information of all unlocked trolleys; the trolley information comprises the current coordinates of the trolley, the running state of the trolley, the running steps of the trolley and the like;
s2-2, acquiring trolleys of all executable tasks, areas where the trolleys are located, and a trolley area set and a trolley set in a round-robin manner to obtain an executable trolley set corresponding to each trolley area; the task-executable trolley is in a remote scheduling mode and is in an idle state;
step S2-3, generating all trolley tasks to be executed in the area according to the trolley area;
generating a task premise:
1) s2-3-1, generating a task only if the product detection is conflict-free;
2) s2-3-2, excluding the area where the product cannot be distributed;
3) s2-3-3, excluding areas where no vehicle can reach;
4) s2-3-4, the product is empty corresponding to the destination;
step S2-4, finding the executable trolley for each task according to the trolley capable of executing the task in each area; s2-4-1 executable means that the vehicle can reach the starting point and the target point of the task;
step S2-5, distributing all executable tasks for each trolley in each area, and sequencing according to task priority levels during distribution to obtain a task queue of each trolley; s2-5-1 task priority refers to the weighted value of the task self priority (waiting time corresponding to products, empty and full degree and the like) and the task external priority (including channel type, channel distance and the like);
s2-6, combining all trolley task sets in each trolley area pairwise;
step S2-7, generating a corresponding task queue subset according to the combined task queue set and the task type; the task types are: ex-warehouse tasks, exclusive tasks, quick tasks and common tasks;
step S2-8, sequentially round-robin each task queue subset until finding the task combination with the highest execution priority in a certain task queue subset;
step S2-9, judging whether the found task combination has a plurality of combinations, if yes, executing S2-11, and if not, executing S2-10;
step S2-10, returning the task combination and sequentially sending the task combination to the corresponding tasks of the corresponding trolley;
step S2-11, calculating the conflict degree in the plurality of combinations to obtain the combination with the minimum conflict degree, and executing step S2-10.
Claims (3)
1. The linear reciprocating type double-RGV task scheduling system is characterized in that: the system comprises a client, a PLC control system, a bar code positioning system and a plurality of RGV trolleys; the client is a commercial industrial personal computer, the RGV is scheduled through a running scheduling algorithm and a path planning algorithm, the optimal combined task of the same-orbit executable trolley is obtained through the scheduling algorithm, and a corresponding instruction is sent to the corresponding RGV; the PLC control system is connected with the RGV and the client, receives an instruction sent by the client and enables the trolley to act; each RGV is provided with a sensing device for detecting the surrounding environment; the bar code positioning system comprises a bar code and a bar code recognizer, and is used for positioning the current coordinate of the RGV in real time; the RGV is provided with PLC modules, a sensing device for detecting the surrounding environment of the RGV and a communication unit for communicating the RGV with a central control system, wherein the modules are used for collecting the information of the RGV, including the current coordinate, motion state, motion step and IP address of the RGV to a client through the PLC; each RGV trolley is provided with a sensing device, and the information of the RGV trolley, including the current coordinate, motion state, motion step and IP address of the RGV trolley, is sent to the client through the PLC.
2. The scheduling algorithm of the linearly reciprocating dual RGV task scheduling system of claim 1, comprising the steps of:
step 1: each RGV real-time monitoring feeds back the coordinate of the RGV, the task running step, and the equipment running state is sent to the client;
step 2: the client acquires all trolley information of the whole plant area, and the trolleys are grouped according to the trolley area to acquire all trolleys capable of executing tasks;
and step 3: generating all tasks of the area according to the trolley area;
and 4, step 4: sequentially distributing executable tasks for the executable trolleys in each trolley area according to the trolley tasks in each trolley area to form a task queue of each executable trolley; the executable rules comprise whether the trolley can be reached or not and whether the trolley needs to be carried for the second time or not after being executed;
and 5: combining task queues of executable trolleys in a trolley area, and selecting an optimal combination according to task execution levels; the task execution level refers to the weighted value of the priority of the task and the external priority of the task;
step 6: and sending the obtained optimal task combination to a corresponding trolley for execution.
3. The scheduling algorithm of the linearly reciprocating dual RGV task scheduling system of claim 2, wherein the optimization combining rule in step 5:
1) the tasks of the execution trolleys are sequenced according to the task execution level and are combined and classified according to the task types;
2) searching each combination classification according to the sequence from high to low until finding the task combination with the highest execution level in a certain combination classification;
3) if the task combinations are the task combinations with the same execution level, judging the task combination with the minimum execution path conflict degree in the combinations;
and a conflict degree calculation step:
acquiring the positions of a starting point and a target point of the two combined tasks;
obtaining the running interval of the task according to the left and right positions of the trolley to be executed of the task, the starting point position and the target point position of the task;
3) and calculating the area of the overlapped area.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114936783A (en) * | 2022-06-02 | 2022-08-23 | 暨南大学 | RGV (vehicle target volume) trolley scheduling method and system based on MMDDPG (multimedia messaging service data distribution group) algorithm |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1505836A (en) * | 2001-12-27 | 2004-06-16 | 东京毅力科创株式会社 | Work convey system, unmanned convey vehicle system, unmanned convey vehicle, and work convey method |
| CN102722169A (en) * | 2012-07-13 | 2012-10-10 | 昆山工研院工业机器人研究所有限公司 | Intelligent rail guide vehicle (RGV) control device based on two vehicles on one rail |
| CN107479403A (en) * | 2017-09-14 | 2017-12-15 | 长春北方化工灌装设备股份有限公司 | Annular RGV semi-matter simulating systems based on virtual reality and run dispatching algorithm without sky |
| CN108455214A (en) * | 2017-04-27 | 2018-08-28 | 中国国际海运集装箱(集团)股份有限公司 | Control method, apparatus, system, transporting equipment and the electronic equipment of vehicle |
| CN108454640A (en) * | 2017-06-23 | 2018-08-28 | 中国国际海运集装箱(集团)股份有限公司 | Control method for vehicle and system |
| CN109634187A (en) * | 2018-12-26 | 2019-04-16 | 芜湖哈特机器人产业技术研究院有限公司 | A kind of AGV remote monitoring system |
| CN109669456A (en) * | 2018-12-26 | 2019-04-23 | 芜湖哈特机器人产业技术研究院有限公司 | A kind of AGV Dispatching Control System |
| CN110264120A (en) * | 2019-05-06 | 2019-09-20 | 盐城品迅智能科技服务有限公司 | A kind of intelligent storage route planning system and method based on more AGV |
| CN110727275A (en) * | 2019-03-20 | 2020-01-24 | 沈阳新松机器人自动化股份有限公司 | RGV dynamic collision avoidance control system and method based on PLC |
| CN110817220A (en) * | 2019-11-11 | 2020-02-21 | 四川长虹智能制造技术有限公司 | RGV avoiding method, RGV and RGV avoiding system |
| CN111596658A (en) * | 2020-05-11 | 2020-08-28 | 东莞理工学院 | Multi-AGV collision-free operation path planning method and scheduling system |
-
2020
- 2020-12-18 CN CN202011511893.8A patent/CN112486187A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1505836A (en) * | 2001-12-27 | 2004-06-16 | 东京毅力科创株式会社 | Work convey system, unmanned convey vehicle system, unmanned convey vehicle, and work convey method |
| CN102722169A (en) * | 2012-07-13 | 2012-10-10 | 昆山工研院工业机器人研究所有限公司 | Intelligent rail guide vehicle (RGV) control device based on two vehicles on one rail |
| CN108455214A (en) * | 2017-04-27 | 2018-08-28 | 中国国际海运集装箱(集团)股份有限公司 | Control method, apparatus, system, transporting equipment and the electronic equipment of vehicle |
| CN108454640A (en) * | 2017-06-23 | 2018-08-28 | 中国国际海运集装箱(集团)股份有限公司 | Control method for vehicle and system |
| CN107479403A (en) * | 2017-09-14 | 2017-12-15 | 长春北方化工灌装设备股份有限公司 | Annular RGV semi-matter simulating systems based on virtual reality and run dispatching algorithm without sky |
| CN109634187A (en) * | 2018-12-26 | 2019-04-16 | 芜湖哈特机器人产业技术研究院有限公司 | A kind of AGV remote monitoring system |
| CN109669456A (en) * | 2018-12-26 | 2019-04-23 | 芜湖哈特机器人产业技术研究院有限公司 | A kind of AGV Dispatching Control System |
| CN110727275A (en) * | 2019-03-20 | 2020-01-24 | 沈阳新松机器人自动化股份有限公司 | RGV dynamic collision avoidance control system and method based on PLC |
| CN110264120A (en) * | 2019-05-06 | 2019-09-20 | 盐城品迅智能科技服务有限公司 | A kind of intelligent storage route planning system and method based on more AGV |
| CN110817220A (en) * | 2019-11-11 | 2020-02-21 | 四川长虹智能制造技术有限公司 | RGV avoiding method, RGV and RGV avoiding system |
| CN111596658A (en) * | 2020-05-11 | 2020-08-28 | 东莞理工学院 | Multi-AGV collision-free operation path planning method and scheduling system |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114936783A (en) * | 2022-06-02 | 2022-08-23 | 暨南大学 | RGV (vehicle target volume) trolley scheduling method and system based on MMDDPG (multimedia messaging service data distribution group) algorithm |
| CN114936783B (en) * | 2022-06-02 | 2023-01-17 | 暨南大学 | RGV (vehicle target volume) trolley scheduling method and system based on MMDDPG (multimedia messaging service data distribution group) algorithm |
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