CN116923951A - Motion scheduling control system suitable for intelligent storage - Google Patents
Motion scheduling control system suitable for intelligent storage Download PDFInfo
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- CN116923951A CN116923951A CN202310831075.3A CN202310831075A CN116923951A CN 116923951 A CN116923951 A CN 116923951A CN 202310831075 A CN202310831075 A CN 202310831075A CN 116923951 A CN116923951 A CN 116923951A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
- B65G1/02—Storage devices
- B65G1/04—Storage devices mechanical
- B65G1/137—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed
- B65G1/1373—Storage devices mechanical with arrangements or automatic control means for selecting which articles are to be removed for fulfilling orders in warehouses
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G1/00—Storing articles, individually or in orderly arrangement, in warehouses or magazines
- B65G1/02—Storage devices
- B65G1/04—Storage devices mechanical
- B65G1/0492—Storage devices mechanical with cars adapted to travel in storage aisles
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Abstract
The invention discloses a motion scheduling control system suitable for intelligent storage, in particular to the technical field of motion scheduling algorithms and path planning algorithms, which comprises an intelligent storage area dividing module, a motion scheduling control module and a motion scheduling control module, wherein the intelligent storage area dividing module is used for dividing areas according to a planar gridding dividing mode to obtain intelligent storage area data to be calculated; the warehouse information acquisition module is used for extracting position data of grid points of the warehouse planarization grid map for the divided intelligent warehouse areas; the intelligent warehouse database module is used for storing grid planarization position information and transport vehicle path planning data; the intelligent warehouse first-come first-serve module is used for planning a running line for the transport vehicle and obtaining movement scheduling data of the transport vehicle through a first-come first-serve scheduling algorithm; the intelligent storage Dijkstra algorithm module is used for planning the running track of the transport vehicle which reaches the end point rapidly and meets the orientation requirement, and guiding the transport vehicle to travel according to the planned route.
Description
Technical Field
The invention relates to the technical field of motion scheduling algorithms and path planning algorithms, in particular to a motion scheduling control system suitable for intelligent warehousing.
Background
In recent years, domestic intelligent storage technology is mature gradually, intelligent storage is one link of logistics process, and the application of intelligent storage ensures the speed and accuracy of data input of each link of goods warehouse management, ensures that enterprises timely and accurately master real data of the inventory, and reasonably maintains and controls the enterprise inventory.
The existing intelligent warehouse motion scheduling control system is based on the fact that an intelligent transport vehicle is connected to a cloud server platform through a wireless network to operate in a planned warehouse path, a plurality of sensors and sensing devices are arranged on the intelligent transport vehicle, and the intelligent transport vehicle schedules by manually inputting operation time and operation places, so that dependence on manpower can be reduced, a warehouse can maintain a long-time efficient operation state, and work efficiency is improved.
However, building an intelligent warehousing system requires the cooperation of a plurality of transport vehicles, the warehouse environment is complex, the operation flow is complex, and how to distribute tasks, schedule motion and plan paths for each transport vehicle is realized, so that the transport vehicles can be efficiently and quickly moved and sorted on the premise of no collision, and the work efficiency of warehouse management is improved, so that the intelligent warehousing system is a key problem to be solved urgently in industrial application.
Disclosure of Invention
In order to overcome the defects in the prior art, the embodiment of the invention provides a motion scheduling control system suitable for intelligent warehouse, which is used for realizing motion scheduling of a transportation trolley by modeling a warehouse instance map as a grid map and adopting a first come first serve scheduling algorithm and carrying out path planning by combining an improved Dijkstra algorithm. The invention can avoid the collision problem of the transport trolley in the intelligent warehouse, plan the shortest transport route, realize the cooperative operation of a plurality of trolleys, and improve the operation efficiency of the warehouse so as to solve the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions: a motion scheduling control system suitable for intelligent storage comprises an intelligent storage area dividing module, an intelligent storage information acquisition module, an intelligent storage database module, an intelligent storage first-come first-serve module and an intelligent storage Dijkstra algorithm module;
the intelligent storage area dividing module: the intelligent warehouse area data acquisition module is used for carrying out area division according to a plane gridding division mode to obtain intelligent warehouse area data to be calculated and transmitting the data to the warehouse information acquisition module;
the warehouse information acquisition module is used for: the intelligent warehouse database module is used for extracting position data of grid points of the warehouse planarization grid map for the divided intelligent warehouse areas and transmitting the data to the intelligent warehouse database module;
the intelligent warehouse database module: the system comprises a first-come first-serve module, a second-serve module, a first-serve module, a second-serve module and a first-serve module, wherein the first-serve module is used for storing grid planarization position information and transport vehicle path planning data and transmitting the data to the first-serve module;
intelligent warehouse first come first serve module: the method is used for planning a running line for the transport vehicle, obtaining movement scheduling data of the transport vehicle through a first come first serve scheduling algorithm, and transmitting the data to an intelligent warehousing Dijkstra algorithm module, and comprises the following steps:
intelligent warehouse Dijkstra algorithm module: the method is used for planning the running track of the transport vehicle which reaches the end point rapidly and meets the orientation requirement, and guiding the transport vehicle to travel according to the planned route.
The method comprises the steps of SO1, using an intelligent warehouse area dividing module to divide warehouse instance map data into target areas, and dividing the target areas according to a planar gridding dividing mode, wherein the intelligent warehouse areas to be calculated are numbered 1, 2 and 3 … N in sequence;
SO2, storing grid point position data of the warehouse planarization grid map after the acquisition area division based on the intelligent warehouse database module, and storing grid planarization position information and transport vehicle path planning data;
step SO3, planning a running line for the transport vehicle based on an intelligent warehouse first-come first-serve scheduling method module, and realizing movement scheduling of the transport vehicle through a first-come first-serve scheduling algorithm to complete the function of transportation;
step SO4, planning a running track which can quickly reach a terminal point and meet the orientation requirement, and returning to a final path when the transport vehicle in the intelligent storage does not need to turn; when the transport vehicle in the intelligent warehouse needs to turn, finding the intermediate node to run the Dijkstra algorithm again, and returning to the final return path.
Preferably, the intelligent storage area dividing module is configured to collect map data of storage examples as a target area through unmanned aerial vehicle, collect map data to be mapped multiple times and comprehensively, draw the map, divide the data into 1, 2, 3 … M groups, compare N groups of data, convert the data into storage grid map, divide the storage grid map area into plane grids, and record each intelligent storage area to be calculated as 1, 2, 3 … N in sequence.
Preferably, the intelligent storage information acquisition module is configured to divide the divided intelligent storage area into 26 x 26 arrays, each point in the storage grid map represents a grid, and extract grid point position data of the storage planarization grid map, which are sequentially 1, 2 and 3 … Y.
Preferably, the intelligent warehouse database module is used for collecting position data of warehouse planarization grid map grid points after regional division, health information of the intelligent transport vehicle obtained according to the sensor network system, positioning information output by the SLAM navigation system, and transport vehicle task information issued by the dispatching system, and storing the position information of grid planarization and transport vehicle path planning data.
Preferably, the intelligent warehouse first-come first-served scheduling method module is used for planning a running line for the transport vehicle, realizing the motion scheduling of the transport vehicle through a first-come first-served scheduling algorithm, and completing the transport function, and comprises the following steps:
a1, by inputting the time when the transport vehicle needs to reach the designated grid area and the time when the transport vehicle needs to operate in the intelligent storage, sequencing all the input transport vehicle operation data according to time scales based on a motion scheduling control system of the intelligent storage, and sequentially operating;
a2, transporting in intelligent warehouseThe whole operation process of the vehicle is divided into an intelligent operation submitting moment set as B, an intelligent operation running moment set as D, an intelligent operation starting moment set as E and an intelligent operation finishing moment set as K, when the N-th transport vehicle starts the line operation according to a formula delta C=K-E, the transport vehicle operation finishing time delta C is obtained, the transport vehicle operation turnover time is obtained according to a formula delta T= (E-B) + (K-E), and the transport vehicle operation turnover time is obtained according to the formulaAnd obtaining the weighted turnover time of the operation of the transport vehicle, and completing the planning of the operation route of the transport vehicle.
Preferably, the intelligent warehouse Dijkstra algorithm module is configured to plan a running track of the transport vehicle that reaches a destination rapidly and meets an orientation requirement by adopting Dijkstra algorithm, and instruct the transport vehicle to travel according to the planned route, and includes the following steps:
b1, obtaining two-dimensional coordinates of grid points on a grid map meshed with a plane, running Dijkstra algorithm to conduct path planning to obtain an initial path, and according to the formula: path (Path) final ＝F(A start ,B start ,A terminal ,B terminal ) Judging whether steering is needed, A, B respectively representing the head-tail direction of the transport vehicle, F being a Path planning algorithm, path final Based on the requirement of orientation of the transport vehicle during working, the front of the transport vehicle is required to face towards cargoes to carry, and the like, the front part and the rear part of the transport vehicle are respectively positioned on adjacent grids to indicate the position and the direction of the transport vehicle;
b2, calculating the limited movement angle of the transport vehicle according to a Chebyshev distance formula:x and y are respectively the abscissa of the starting point and the ordinate of the end point, the movement cost can be accurately described, when the transport vehicle in the intelligent storage does not need to turn, and the positions of the vehicle head and the vehicle tail at the end point are correct, the initial path is returned as the final path, and if the positions are incorrect, the result of the initial path is filledThe Dijkstra algorithm is operated again by using the new map at the position of the tail of the vehicle, and a final path is obtained to return; when the transport vehicle in the intelligent warehouse needs to turn, a T structure nearest to the vehicle tail is found out in the initial path to serve as an intermediate node, the Dijkstra algorithm is operated twice, and the paths returned twice are added to obtain a final return path.
The invention has the technical effects and advantages that:
the intelligent warehouse area dividing module is used for dividing areas of the warehouse map in a plane gridding dividing mode to obtain the gridding grid map, simplifying the warehouse environment, enabling the path planning of the transport vehicle to be efficient, realizing the motion scheduling of the transport vehicle based on a first-come first-serve scheduling algorithm through an intelligent warehouse first-serve scheduling method module, completing the transportation function, reducing the dependence on manpower, enabling the warehouse to keep a long-time efficient running state, improving the working efficiency, planning the running track of the transport vehicle which reaches the end point and meets the direction requirement rapidly through an intelligent warehouse Dijkstra algorithm module based on the Dijkstra algorithm, guiding the transport vehicle to run according to the planned route, realizing the co-cooperation of the transport vehicles, and moving and sorting the transport vehicle efficiently and rapidly on the basis of safety protection, improving the working efficiency of warehouse management, and realizing the intelligent warehouse.
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Fig. 1 is a block diagram of a system architecture of the present invention.
Fig. 2 is a flow chart of the method of the present invention.
Fig. 3 is a flowchart of the algorithm of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The embodiment provides a motion scheduling control system suitable for intelligent storage, as shown in fig. 1, which comprises an intelligent storage area dividing module, an intelligent storage information acquisition module, an intelligent storage database module, an intelligent storage first-come first-serve module and an intelligent storage Dijkstra algorithm module;
the intelligent storage area dividing module: the intelligent warehouse area data acquisition module is used for carrying out area division according to a plane gridding division mode to obtain intelligent warehouse area data to be calculated and transmitting the data to the warehouse information acquisition module;
the warehouse information acquisition module is used for: the intelligent warehouse database module is used for extracting position data of grid points of the warehouse planarization grid map for the divided intelligent warehouse areas and transmitting the data to the intelligent warehouse database module;
the intelligent warehouse database module: the system comprises a first-come first-serve module, a second-serve module, a first-serve module, a second-serve module and a first-serve module, wherein the first-serve module is used for storing grid planarization position information and transport vehicle path planning data and transmitting the data to the first-serve module;
intelligent warehouse first come first serve module: the system comprises a first-come first-serve scheduling algorithm, an intelligent warehousing Dijkstra algorithm module, a first-serve scheduling algorithm, a second-serve scheduling algorithm and a third-serve scheduling algorithm, wherein the first-serve scheduling algorithm is used for planning a running line of a transport vehicle, obtaining motion scheduling data of the transport vehicle, and transmitting the motion scheduling data to the intelligent warehousing Dijkstra algorithm module;
intelligent warehouse Dijkstra algorithm module: the system is used for planning the running track of the transport vehicle which reaches the end point rapidly and meets the direction requirement, guiding the transport vehicle to run according to the planned route, wherein the data storage module and the microcomputer module are in telecommunication connection with all other modules.
The implementation is different from the prior art in that the intelligent storage area dividing module, the intelligent storage first-come first-serve module and the intelligent storage Dijkstra algorithm module are used for increasing the target area dividing function, the intelligent storage first-come first-serve module is additionally provided with a motion scheduling function of obtaining the transport vehicle through an algorithm, the intelligent storage Dijkstra algorithm module is additionally provided with a planning function of rapidly reaching a destination of the transport vehicle and meeting the running track of the direction requirement, and the intelligent storage first-come first-serve module and the intelligent storage Dijkstra algorithm module form a data analysis modeling function.
The embodiment provides a motion scheduling control system suitable for intelligent storage, which specifically comprises the following steps:
101. the intelligent storage area dividing module is used for comprehensively collecting map data of storage examples as target areas, carrying out repeated comprehensive collection on map data to be mapped through an unmanned aerial vehicle, drawing a map, dividing the map data into 1, 2 and 3 … M groups, comparing N groups of data, converting the N groups of data into storage grid maps, dividing the storage grid map areas into plane grids, and sequentially marking each intelligent storage area to be calculated as 1, 2 and 3 … N.
In this embodiment, it needs to be specifically described that the unmanned aerial vehicle performs multiple comprehensive collection on map data to be mapped, and assembles a topographic image collection terminal on the unmanned aerial vehicle, performs multiple scanning on the topography in the intelligent warehouse, divides the scanned image into N groups, performs analysis and comparison on the N groups of data to obtain a topographic region with differentiation in the image, performs virtual planar grid map paving based on the differentiated topographic region, obtains grid points to be adjusted in the actual paved topography, converts the grid points into a warehouse grid map after summarized analysis, and performs planar grid region division.
102. The intelligent storage information acquisition module is used for dividing the divided intelligent storage area into 26-26 arrays, each point in the storage grid map represents a grid, and grid point position data of the storage planarization grid map are extracted and are sequentially 1, 2 and 3 … Y.
In this embodiment, the specific explanation is that the position data of grid points of the warehouse planarization grid map is marked by using different colors to indicate whether the regional transport vehicle can pass through, wherein the gray grid indicates that the regional is occupied or has an obstacle, the blue grid indicates that the regional is in a feasible region, and is a part of a path, and the transport vehicle can only move in the unoccupied grid.
103. The intelligent warehouse database module is used for collecting regional partitioned warehouse planarization grid map grid point position data, health information of the intelligent transport vehicle obtained according to the sensor network system, positioning information output by the SLAM navigation system and transport vehicle task information issued by the dispatching system, and storing the grid planarization position information and transport vehicle path planning data.
In this embodiment, it needs to be specifically described that the sensor network system is various sensor devices installed on a transport vehicle, and provides sensing information for operation control and safety collision avoidance of the transport vehicle, including an angle sensor, an infrared obstacle safety sensor, a horizontal motion gyroscope, a GPS positioning navigator, a color resolution sensor, a speed encoder, a laser ranging sensor, and a cargo weight sensor.
104. The intelligent warehouse first-come first-serve scheduling method module is used for planning a running line for a transport vehicle, realizing movement scheduling of the transport vehicle through a first-come first-serve scheduling algorithm and completing the transport function, and comprises the following steps:
a1, by inputting the time when the transport vehicle needs to reach the designated grid area and the time when the transport vehicle needs to operate in the intelligent storage, sequencing all the input transport vehicle operation data according to time scales based on a motion scheduling control system of the intelligent storage, and sequentially operating;
a2, dividing the whole operation process of the transport vehicle in the intelligent warehouse into an intelligent operation submitting time B, an intelligent operation running time D, an intelligent operation starting time E and an intelligent operation finishing time K, and when the units are all, starting the line operation of the Nth transport vehicleWhen the operation time delta C of the transport vehicle is obtained according to the formula delta C=K-E, the operation turnover time of the transport vehicle is obtained according to the formula delta T= (E-B) + (K-E), and the operation turnover time of the transport vehicle is obtained according to the formulaAnd obtaining the weighted turnover time of the operation of the transport vehicle, and completing the planning of the operation route of the transport vehicle.
In this embodiment, the specific description needs to be that the turn-around time and the weighted turn-around time are the sum of the waiting time and the service time of a job in the service system, which is called the turn-around time of the job in the system, and the turn-around time can only reflect the time of the job in the system, and cannot be said that the turn-around time is as good as the service that is slightly received, the weighted turn-around time is the ratio of the turn-around time of the job to the time that the system provides service for it, the weighted turn-around time reflects the job length problem, the larger the weighted turn-around time is, the shorter the job is, and the smaller the weighted turn-around time is, the longer the job is.
105. The intelligent storage Dijkstra algorithm module is used for planning a running track which is used for enabling a transport vehicle to quickly reach a terminal and meet the direction requirement by adopting Dijkstra algorithm, and guiding the transport vehicle to run according to the planned route, and comprises the following steps:
b1, obtaining two-dimensional coordinates of grid points on a grid map meshed with a plane, running Dijkstra algorithm to conduct path planning to obtain an initial path, and according to the formula: path (Path) final ＝F(A start ,B start ,A terminal ,B terminal ) Judging whether steering is needed, A, B respectively representing the head-tail direction of the transport vehicle, F being a Path planning algorithm, path final Based on the requirement of orientation of the transport vehicle during working, the front of the transport vehicle is required to face towards cargoes to carry, and the like, the front part and the rear part of the transport vehicle are respectively positioned on adjacent grids to indicate the position and the direction of the transport vehicle;
b2, calculating the limited movement angle of the transport vehicle according to a Chebyshev distance formula:x and y are the horizontal and vertical coordinates of a starting point and a terminal point respectively, so that the movement cost can be accurately described, when the transport vehicle in the intelligent storage is not required to turn, and the positions of the vehicle head and the vehicle tail at the terminal point are correct, the initial path is returned to be used as a final path, if the positions are incorrect, the positions of the vehicle tail are filled in the result of the initial path, and the Dijkstra algorithm is operated again by using a new map, so that the final path is returned; when the transport vehicle in the intelligent warehouse needs to turn, a T structure nearest to the vehicle tail is found out in the initial path to serve as an intermediate node, the Dijkstra algorithm is operated twice, and the paths returned twice are added to obtain a final return path.
In this embodiment, the specific explanation is that the motion scheduling of the transport vehicle is based on the large volume of the transport vehicle, an arc is needed to be taken when the transport vehicle turns, for an arc turning area, a right angle L-shaped structure in one, two and four grid maps is used to represent a path planning used in an original grid map of a turning curve in an example map, the transport vehicle can only advance along a straight line or oblique line, a turning curve path when the transport vehicle actually moves cannot be completely fitted, the turning on the path is represented based on the curve and the right angle, three structures of 'L', 'T' and 'plus' are defined, and the right angle in the grid map is used to represent the curve in the example map.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Claims (8)
1. A motion scheduling control system suitable for intelligent warehousing, comprising:
the intelligent storage area dividing module: the method comprises the steps of dividing the warehouse instance map data into target areas according to a planar gridding dividing mode, and numbering each intelligent warehouse area to be calculated into 1, 2 and 3 … N in sequence;
the intelligent storage information acquisition module: the method is used for extracting position data of grid points of the warehouse planarization grid map from the divided intelligent warehouse areas, wherein the position data are sequentially 1, 2 and 3 … Y;
the intelligent warehouse database module: the storage planarization grid map grid point position data acquisition module is used for acquiring storage planarization grid map grid point position data after regional division and storing grid planarization position information and transport vehicle path planning data;
intelligent warehouse first come first serve dispatch method module: the system is used for planning a running line of the transport vehicle, realizing the motion scheduling of the transport vehicle through a first come first serve scheduling algorithm and completing the transport function;
intelligent warehouse Dijkstra algorithm module: the method comprises the steps of planning a running track which rapidly reaches a terminal point and meets the direction requirement by adopting a Dijkstra algorithm, guiding the running track to run according to the planned route, returning an initial path to be used as a final path when the running track in the intelligent storage is not required to be turned and the positions of a head and a tail at the terminal point are correct, filling the position of the tail in the result of the initial path if the positions are incorrect, and running the Dijkstra algorithm again by using a new map to obtain the final path to return; when the transport vehicle in the intelligent warehouse needs to turn, a T structure nearest to the vehicle tail is found out in the initial path to serve as an intermediate node, the Dijkstra algorithm is operated twice, and the paths returned twice are added to obtain a final return path.
2. A motion scheduling control system for intelligent warehousing as set forth in claim 1, wherein: the intelligent storage area dividing module is used for comprehensively collecting map data of storage examples as target areas, carrying out repeated comprehensive collection on map data to be mapped through an unmanned aerial vehicle, drawing a map, dividing the map data into 1, 2 and 3 … M groups, comparing N groups of data, converting the N groups of data into storage grid maps, dividing the storage grid map areas into plane grids, and sequentially marking each intelligent storage area to be calculated as 1, 2 and 3 … N.
3. A motion scheduling control system for intelligent warehousing as set forth in claim 1, wherein: the intelligent storage information acquisition module is used for dividing the divided intelligent storage area into 26-26 arrays, each point in the storage grid map represents a grid, and grid point position data of the storage planarization grid map are extracted and are sequentially 1, 2 and 3 … Y.
4. A motion scheduling control system for intelligent warehousing as set forth in claim 1, wherein: the intelligent warehouse database module is used for collecting regional partitioned warehouse planarization grid map grid point position data, health information of the intelligent transport vehicle obtained according to the sensor network system, positioning information output by the SLAM navigation system and transport vehicle task information issued by the dispatching system, and storing the grid planarization position information and transport vehicle path planning data.
5. A motion scheduling control system for intelligent warehousing as set forth in claim 1, wherein: the intelligent warehouse first-come first-serve scheduling method module is used for planning a running line for a transport vehicle, realizing movement scheduling of the transport vehicle through a first-come first-serve scheduling algorithm and completing the transport function, and comprises the following steps:
a1, by inputting the time when the transport vehicle needs to reach the designated grid area and the time when the transport vehicle needs to operate in the intelligent storage, sequencing all the input transport vehicle operation data according to time scales based on a motion scheduling control system of the intelligent storage, and sequentially operating;
a2, dividing the whole operation process of the transport vehicle in the intelligent storage into an intelligent operation submitting time B, an intelligent operation running time D, an intelligent operation starting time E and an intelligent operation finishing time K, when the N transport vehicle starts the line operation according to a formula delta C=K-E, obtaining the transport vehicle operation finishing time delta C, obtaining the transport vehicle operation turnover time according to a formula delta T= (E-B) + (K-E), and obtaining the transport vehicle operation turnover time according to the formulaObtainingAnd the transportation vehicle operation has the right turnover time, so that the planning of the transportation vehicle operation line is completed.
6. A motion scheduling control system for intelligent warehousing as set forth in claim 1, wherein: the intelligent storage Dijkstra algorithm module is used for planning a running track which is used for enabling a transport vehicle to quickly reach a terminal and meet the direction requirement by adopting Dijkstra algorithm, and guiding the transport vehicle to run according to the planned route, and comprises the following steps:
b1, obtaining two-dimensional coordinates of grid points on a grid map meshed with a plane, running Dijkstra algorithm to conduct path planning to obtain an initial path, and according to the formula: path (Path) final ＝F(A start ,B start ,A terminal ,B terminal ) Judging whether steering is needed, A, B respectively representing the head-tail direction of the transport vehicle, F being a Path planning algorithm, path final Based on the requirement of orientation of the transport vehicle during working, the front of the transport vehicle is required to face towards cargoes to carry, and the like, the front part and the rear part of the transport vehicle are respectively positioned on adjacent grids to indicate the position and the direction of the transport vehicle;
b2, calculating the limited movement angle of the transport vehicle according to a Chebyshev distance formula:x and y are the horizontal and vertical coordinates of a starting point and a terminal point respectively, so that the movement cost can be accurately described, when the transport vehicle in the intelligent storage is not required to turn, and the positions of the vehicle head and the vehicle tail at the terminal point are correct, the initial path is returned to be used as a final path, if the positions are incorrect, the positions of the vehicle tail are filled in the result of the initial path, and the Dijkstra algorithm is operated again by using a new map, so that the final path is returned; when the transport vehicle in the intelligent warehouse needs to turn, a T structure nearest to the vehicle tail is found out in the initial path to serve as an intermediate node, the Dijkstra algorithm is operated twice, and the paths returned twice are added to obtain a final return path.
7. A motion scheduling control system for intelligent warehousing as set forth in claim 3 wherein: the storage planarization grid map grid point position data indicates whether the transport vehicle can pass through the area by marking grid points with different colors, wherein gray grids indicate that the area is occupied or has an obstacle, blue grids indicate that the area is in a feasible area and is part of a path, and the transport vehicle can only move in unoccupied grids.
8. The motion scheduling control system for intelligent warehousing of claim 5, wherein: the motion scheduling of the transport vehicle is based on the fact that the transport vehicle is large in size, an arc needs to be taken when the transport vehicle turns, an arc turning area is represented by a right-angle L-shaped structure in one, two and four grid maps, a path planning used in an original grid map of a turning curve in an example map is represented, the transport vehicle can only advance along a straight line or oblique lines, a turning curve path when the transport vehicle actually moves cannot be completely fitted, turning on the path is represented based on the fact that the curve is identical to the right angle, three structures of L, T and + -are defined, and the right angle in the grid map is used for representing the curve in the example map.
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| CN117852988A (en) * | 2024-03-08 | 2024-04-09 | 天津万事达物流装备有限公司 | Cooperative control method for neutron mother vehicle and elevator in intelligent warehousing system |
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| CN117852988A (en) * | 2024-03-08 | 2024-04-09 | 天津万事达物流装备有限公司 | Cooperative control method for neutron mother vehicle and elevator in intelligent warehousing system |
| CN117852988B (en) * | 2024-03-08 | 2024-05-14 | 天津万事达物流装备有限公司 | Cooperative control method for neutron mother vehicle and elevator in intelligent warehousing system |
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