Intelligent integrated management system for shuttle vehicle

Abstract

The invention discloses an intelligent integrated management system for shuttle vehicles, and belongs to the technical field of shuttle vehicles, and the system comprises S1, a vehicle scheduling module which receives vehicle state information and schedules vehicles according to task priorities; s2, a task distribution module, wherein the task distribution module receives warehouse order tasks and distributes the tasks to corresponding shuttle vehicles; s3, a path planning module, wherein the step S3 comprises obtaining shelf position information and planning an optimal driving path; and S4, an equipment monitoring module. The system can plan the optimal path in real time and reduce the empty driving time and waiting time of the shuttle vehicles, so that the transportation efficiency is greatly improved, the system can improve the order processing speed, remarkably shorten the cargo turnover period, support simultaneous operation of multiple shuttle vehicles, realize parallel processing of tasks, further improve the overall efficiency of warehousing operation, and reduce the labor intensity of workers in peak hours. The system can flexibly deploy vehicles and ensure that orders are processed in time.

Description

Technical Field

[0001] The present invention belongs to the technical field of shuttle vehicles, and in particular relates to an intelligent integrated management system for shuttle vehicles. Background Art

[0002] In the field of warehousing and logistics, business volume has exploded, and warehouse management has evolved towards refinement. Warehousing efficiency and space utilization have become key factors in a company's competitiveness. Traditional warehousing systems rely on manual operations, resulting in low efficiency, low space utilization, high labor costs, and high error rates. While the emergence of multi-layer shuttle systems has improved warehousing efficiency to a certain extent, traditional shuttle management systems suffer from single functions, low integration, and insufficient intelligence. They are prone to confusion when multiple tasks are performed concurrently, have low scheduling efficiency, lack intelligent optimization in route planning, and are often delayed by obstacles. Equipment monitoring is weak, fault warnings are delayed, and processing feedback is slow, affecting equipment reliability and warehouse operational efficiency. Therefore, an intelligent integrated shuttle management system is proposed to address these issues. Summary of the Invention

[0003] The purpose of the present invention is to provide an intelligent integrated management system for shuttle vehicles to solve the problems raised in the above background technology.

[0004] To achieve the above objectives, the present invention provides the following technical solutions:

[0005] S1, vehicle dispatching module, said S1, vehicle dispatching module includes receiving vehicle status information and dispatching vehicles according to task priority;

[0006] S2, task assignment module, said S2, task assignment module includes receiving warehouse order tasks and assigning tasks to corresponding shuttle vehicles;

[0007] S3, path planning module, said S3, path planning module includes obtaining shelf location information and planning the optimal driving path;

[0008] S4, equipment monitoring module, said S4, equipment monitoring module includes real-time monitoring of the shuttle vehicle's operating status and fault warning and processing feedback.

[0009] As a further preferred embodiment of the present technical solution: the receiving of vehicle status information obtains information such as the battery level, operating status, and current location of the shuttle vehicle in real time; and the scheduling of vehicles according to task priority determines the task priority based on factors such as the urgency of the task and the importance of the cargo when a task is required, and then selects the most suitable one or several shuttle vehicles from the idle vehicles for task allocation, thereby ensuring that high-priority tasks can be processed in a timely manner.

[0010] As a further preferred embodiment of the present technical solution: the S1, vehicle dispatching module also includes dynamically adjusting the dispatching strategy, and dynamically adjusting the dispatching strategy according to the changes in the real-time vehicle status and task queue to cope with emergencies or changes in task load, thereby ensuring the optimal overall operating efficiency of the system.

[0011] As a further preferred embodiment of the present technical solution: the warehouse order receiving task receives an order task containing detailed contents such as cargo information, starting location, and target location from the warehouse management system; the task is assigned to the corresponding shuttle vehicle according to the instructions of the vehicle scheduling module, and the task is accurately assigned to the designated shuttle vehicle, and at the same time, a task execution instruction is sent to the shuttle vehicle, including detailed information of the cargo and the transportation route, etc.

[0012] As a further preferred embodiment of the present technical solution: the S2, task allocation module also includes task splitting and merging. For complex tasks or batch tasks, it can intelligently split tasks and assign them to multiple shuttle vehicles for collaborative completion. At the same time, it supports merging multiple small tasks into one task batch to improve the operating efficiency of the shuttle vehicles.

[0013] As a further preferred embodiment of the present technical solution: the acquisition of shelf location information allows real-time grasp of the location coordinates of each shelf in the warehouse and the aisle layout; and the planning of the optimal driving path, after receiving the task from the task assignment module, utilizes an intelligent algorithm to plan an optimal driving path based on the current position of the shuttle vehicle, the target shelf position, and the warehouse aisle layout, so as to reduce the travel time of the shuttle vehicle, improve transportation efficiency, and avoid possible obstacles or congested areas.

[0014] As a further preferred embodiment of the present technical solution: the S3, path planning module also includes dynamic path adjustment, which can adjust the path planning in real time when encountering unexpected situations to ensure that the shuttle vehicle can reach the destination smoothly.

[0015] As a further preferred embodiment of the present technical solution: the real-time monitoring of the shuttle vehicle's operating status performs real-time monitoring of the shuttle vehicle's operating parameters and equipment status, and collects the shuttle vehicle's operating data. The fault warning and processing feedback performs real-time analysis of the monitored data through data analysis and fault diagnosis algorithms. When an abnormal situation is found, a fault warning signal is issued in a timely manner, and the fault information is fed back to the system maintenance personnel. At the same time, according to the severity and type of the fault, corresponding processing measures are automatically taken, such as emergency stop, switching to standby mode, etc., to ensure the safe operation of the shuttle vehicle.

[0016] As a further preferred embodiment of the present technical solution: the S4, equipment monitoring module also includes remote monitoring and diagnosis, which supports remote monitoring of the operating status of the shuttle vehicle. Maintenance personnel can remotely connect to the system through the network to perform fault diagnosis and debugging on the shuttle vehicle, thereby reducing the time and cost of on-site maintenance.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] 1. The present invention can plan the optimal route in real time, reducing the idle time and waiting time of shuttle vehicles, thereby significantly improving transportation efficiency. The system can speed up order processing and significantly shorten the cargo turnover cycle. It supports multiple shuttle vehicles operating simultaneously, realizing parallel processing of tasks, and further improving the overall efficiency of warehousing operations. During peak periods, the system can flexibly deploy vehicles to ensure that orders are processed in a timely manner.

[0019] 2. The present invention monitors the operating status and equipment status of the shuttle in real time, discovers and handles faults in a timely manner, and ensures stable operation of the system. The fault warning mechanism can issue an alarm before the equipment becomes abnormal, avoiding equipment damage and operation interruption. It supports remote monitoring of the operating status of the shuttle. Maintenance personnel can remotely connect to the system through the network to diagnose and debug the shuttle, reducing on-site maintenance time and improving operation and maintenance response speed.

[0020] 3. The present invention supports the splitting and merging of complex tasks, and intelligently allocates tasks based on task characteristics and shuttle status to improve work efficiency. For scattered small orders, the system can cluster and merge them according to similar routes and cargo types, reducing the frequency of shuttle trips. It supports flexible increase in the number of shuttles or shelf modules based on business growth to meet warehousing needs of different scales. At the same time, the system is compatible with multiple mainstream warehouse management system formats to ensure smooth access to task sources. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a structural diagram of an intelligent integrated management system for shuttle vehicles according to the present invention;

[0022] Figure 2 This is a flow chart of an intelligent integrated management system for shuttle vehicles according to the present invention;

[0023] Figure 3 This is a flow chart of a vehicle dispatching module of a shuttle vehicle intelligent integrated management system of the present invention;

[0024] Figure 4 This is a flow chart of a task allocation module of a shuttle vehicle intelligent integrated management system of the present invention;

[0025] Figure 5 This is a flow chart of a path planning module of a shuttle vehicle intelligent integrated management system of the present invention;

[0026] Figure 6 This is a flow chart of an equipment monitoring module of a shuttle vehicle intelligent integrated management system of the present invention. DETAILED DESCRIPTION

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. All other embodiments derived by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts are also within the scope of protection of the present invention.

[0028] Example:

[0029] See also Figures 1-6 As shown, the present invention provides a technical solution: comprising:

[0030] S1, vehicle dispatching module, S1, vehicle dispatching module includes receiving vehicle status information and dispatching vehicles according to task priority;

[0031] S2, task allocation module, S2, task allocation module includes receiving warehouse order tasks and allocating tasks to corresponding shuttle vehicles;

[0032] S3, path planning module, S3, path planning module includes obtaining shelf location information and planning the optimal driving path;

[0033] S4, equipment monitoring module, S4, equipment monitoring module includes real-time monitoring of shuttle vehicle operation status and fault warning and processing feedback;

[0034] In this embodiment, specifically: receiving vehicle status information to obtain real-time information such as the shuttle's battery level, operating status, and current location. The operating status includes whether the shuttle is idle or faulty. With the help of sensors and communication technology, the shuttle's operating data can be promptly transmitted back to the module, and vehicles are dispatched according to task priority. When a task is required, the task priority is determined based on factors such as the urgency of the task and the importance of the cargo. Then, the most suitable one or several shuttles are selected from the idle vehicles for task allocation, ensuring that high-priority tasks can be processed in a timely manner, minimizing task response time, and improving system agility.

[0035] In this embodiment, specifically: S1, the vehicle scheduling module also includes dynamically adjusting the scheduling strategy. According to the changes in the real-time vehicle status and task queue, the scheduling strategy is dynamically adjusted to cope with emergencies or changes in task load, ensuring the optimal overall operating efficiency of the system. When the warehouse suddenly receives a temporary expedited order or some vehicles fail, resulting in an imbalance in transportation capacity, the scheduling plan is quickly reshaped, and the number of vehicles is reasonably deployed during peak business hours to achieve dynamic optimization of the overall operating efficiency of the system and ensure that task scheduling smoothly adapts to changes in the rhythm of warehouse operations;

[0036] In this embodiment, specifically: Receive warehouse order tasks receive order tasks containing detailed information such as cargo information, starting location, and destination location from the warehouse management system. This is compatible with multiple mainstream warehouse management system formats, ensuring smooth access to task sources and adapting to different warehousing business architectures. Tasks are assigned to corresponding shuttle vehicles based on instructions from the vehicle scheduling module, accurately allocating tasks to designated shuttle vehicles and simultaneously sending task execution instructions to the shuttle vehicles, including detailed cargo information and transportation routes.

[0037] In this embodiment, specifically: S2, the task allocation module also includes task splitting and merging. For complex tasks or batch tasks, it can intelligently split tasks and assign them to multiple shuttle vehicles for collaborative completion. It also supports merging multiple small tasks into a task batch to improve the shuttle vehicle's operating efficiency. For scattered small orders, it clusters and merges them according to similar routes and cargo types, reducing the shuttle vehicle's round-trip frequency, optimizing task execution efficiency, and fully tapping the vehicle's transportation capacity potential.

[0038] In this embodiment, specifically: shelf location information is acquired to grasp the location coordinates of each shelf in the warehouse and the aisle layout in real time, and the optimal driving path is planned. After receiving the task from the task assignment module, an optimal driving path is planned using an intelligent algorithm, such as an ant colony algorithm or a genetic algorithm, based on the shuttle's current position, the target shelf location, and the warehouse aisle layout. This calculates the driving trajectory with the shortest travel time and the lowest collision risk, thereby reducing the shuttle's travel time, improving transportation efficiency, and avoiding possible obstacles or congested areas.

[0039] In this embodiment, specifically: S3, the path planning module also includes dynamic path adjustment. When encountering unexpected situations, the path planning can be adjusted in real time to ensure that the shuttle can reach the destination smoothly, such as when the channel is temporarily blocked or other equipment is fixed;

[0040] In this embodiment, specifically: real-time monitoring of the shuttle vehicle's operating status is performed on the shuttle vehicle's operating parameters and equipment status in real time, and the shuttle vehicle's operating data is collected at the same time. The operating parameters include the shuttle vehicle's speed, acceleration, and steering angle, and the equipment status includes the motor temperature and controller working status. Fault warning and processing feedback are performed through data analysis and fault diagnosis algorithms to analyze the monitored data in real time. When an abnormal situation is found, a fault warning signal is issued in a timely manner, and the fault information is fed back to the system maintenance personnel. At the same time, according to the severity and type of the fault, corresponding processing measures are automatically taken, such as emergency stop, switching to standby mode, etc., to ensure the safe operation of the shuttle vehicle;

[0041] In this embodiment, specifically: S4, the equipment monitoring module also includes remote monitoring and diagnosis, which supports remote monitoring of the operating status of the shuttle vehicle. Maintenance personnel can remotely connect to the system through the network to diagnose and debug the shuttle vehicle, reducing the time and cost of on-site maintenance. Remotely control and debug equipment parameters, quickly locate the root cause of the fault, simplify the maintenance process, greatly improve the operation and maintenance response speed, and shorten the downtime.

[0042] Working principle or structural principle: The task allocation module keeps in communication with the warehouse management system at all times, and receives order tasks containing key content such as cargo information, starting and target locations. It is compatible with a variety of mainstream warehouse management system formats, ensuring smooth access to task sources and adapting to different warehousing business architectures. After receiving the task, the priority is determined by the intelligent algorithm based on factors such as the urgency of the task and the importance of the cargo, laying a solid foundation for subsequent efficient scheduling; the vehicle scheduling module obtains the shuttle vehicle's power and operating status in real time, covering idle, faulty and other situations as well as current location data. When a task is issued, the scheduling module selects the best vehicle from the standby vehicles based on the task priority. For high-priority tasks, priority is given to ensuring that they obtain vehicle resources as soon as possible. The task allocation module follows the scheduling instructions and accurately assigns the task to the designated shuttle vehicle, and simultaneously pushes cargo details and planned routes to ensure that the shuttle vehicle can start the task execution with one click; the path planning module continuously obtains shelf location information, accurately grasps the shelf coordinates and channel layout in the warehouse, and after receiving the task, uses the ant colony algorithm to simulate the natural ant path-finding behavior, and through the colony algorithm, it simulates the natural ant path-finding behavior, and simulates the path-finding behavior of the ant colony. The system uses intelligent iterative optimization to plan the shuttle's route with the shortest travel time and lowest collision risk. If a blocked passage or adjacent equipment malfunctions, the dynamic route adjustment mechanism is instantly triggered, urgently replanning the route and guiding the shuttle to a flexible detour to ensure uninterrupted mission delivery. The equipment monitoring module comprehensively monitors the shuttle's operating parameters in real time, including details such as speed, acceleration, and steering angle. It also monitors equipment health indicators such as motor temperature and controller operation. Leveraging big data analysis and machine learning algorithms, it deeply mines underlying patterns in operating data, accurately identifies precursors to faults, and issues early warning signals. At the moment of a fault, detailed information is instantly pushed to the maintenance terminal, automatically initiating corresponding emergency plans based on the fault mode, such as emergency braking and switching to redundant systems. This ensures safe equipment degradation and creates a critical time window for maintenance. The shuttle executes its mission according to the planned route, while the equipment monitoring module monitors it day and night, keeping track of even the slightest fluctuations in operating parameters. Upon mission completion, the equipment monitoring module automatically archives the operating data, and all modules reset to standby for the next mission cycle.

[0043] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent integrated management system for shuttle vehicles, characterized by: include: S1, vehicle dispatching module, said S1, vehicle dispatching module includes receiving vehicle status information and dispatching vehicles according to task priority; S2, task assignment module, said S2, task assignment module includes receiving warehouse order tasks and assigning tasks to corresponding shuttle vehicles; S3, path planning module, said S3, path planning module includes obtaining shelf location information and planning the optimal driving path; S4, equipment monitoring module, said S4, equipment monitoring module includes real-time monitoring of the shuttle vehicle's operating status and fault warning and processing feedback.

2. The intelligent integrated management system for shuttle vehicles according to claim 1, characterized in that: The receiving vehicle status information obtains information such as the shuttle vehicle's power level, operating status, and current location in real time. The scheduling of vehicles according to task priority determines the task priority based on factors such as the urgency of the task and the importance of the cargo when there is a task requirement, and then selects the most suitable one or several shuttle vehicles from the idle vehicles for task allocation, ensuring that high-priority tasks can be processed in a timely manner.

3. The intelligent integrated management system for shuttle vehicles according to claim 2, characterized in that: The S1, vehicle scheduling module also includes dynamically adjusting the scheduling strategy, which dynamically adjusts the scheduling strategy according to the real-time vehicle status and changes in the task queue to cope with emergencies or changes in task load, ensuring the optimal overall operating efficiency of the system.

4. The intelligent integrated management system for shuttle vehicles according to claim 3, characterized in that: The receiving warehouse order task receives an order task containing detailed information such as cargo information, starting location, and target location from the warehouse management system. The assigning task to the corresponding shuttle vehicle accurately assigns the task to the designated shuttle vehicle according to the instructions of the vehicle scheduling module, and sends a task execution instruction to the shuttle vehicle, including detailed information of the cargo and the transportation route, etc.

5. The intelligent integrated management system for shuttle vehicles according to claim 4, characterized in that: The S2, task allocation module also includes task splitting and merging. For complex tasks or batch tasks, it can intelligently split tasks and assign them to multiple shuttle vehicles for collaborative completion. At the same time, it supports merging multiple small tasks into a task batch to improve the operating efficiency of the shuttle vehicles.

6. The intelligent integrated management system for shuttle vehicles according to claim 5, characterized in that: The shelf location information is obtained to grasp the location coordinates of each shelf in the warehouse and the aisle layout in real time. After receiving the task from the task assignment module, the optimal driving path is planned using an intelligent algorithm based on the current position of the shuttle vehicle, the target shelf position and the warehouse aisle layout to reduce the shuttle vehicle's travel time, improve transportation efficiency, and avoid possible obstacles or congested areas.

7. The intelligent integrated management system for shuttle vehicles according to claim 6, characterized in that: The S3, path planning module also includes dynamic path adjustment. When encountering unexpected situations, the path planning can be adjusted in real time to ensure that the shuttle can reach the destination smoothly.

8. The intelligent integrated management system for shuttle vehicles according to claim 7, characterized in that: The real-time monitoring of the shuttle vehicle's operating status monitors the shuttle vehicle's operating parameters and equipment status in real time, and collects the shuttle vehicle's operating data. The fault warning and processing feedback uses data analysis and fault diagnosis algorithms to analyze the monitored data in real time. When an abnormal situation is found, a fault warning signal is issued in time, and the fault information is fed back to the system maintenance personnel. At the same time, according to the severity and type of the fault, corresponding processing measures are automatically taken, such as emergency stop, switching to standby mode, etc., to ensure the safe operation of the shuttle vehicle.

9. The intelligent integrated management system for shuttle vehicles according to claim 8, characterized in that: The S4, equipment monitoring module also includes remote monitoring and diagnosis, which supports remote monitoring of the operating status of the shuttle vehicle. Maintenance personnel can remotely connect to the system through the network to diagnose and debug the shuttle vehicle, reducing the time and cost of on-site maintenance.

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