CN-121995872-A - Heavy load AGV transport system based on central dispatching and dispatching method thereof

CN121995872ACN 121995872 ACN121995872 ACN 121995872ACN-121995872-A

Abstract

The invention relates to a heavy object transportation system, in particular to a heavy load AGV transportation system based on central dispatching and a dispatching method thereof, and aims to solve the problems that the existing method is easy to cause increased fault risk, falls into a local optimal trap and increases cost, so that actual demands are difficult. The system comprises a central dispatching system which is in communication connection with an upper control system and a plurality of reloaded AGVs which are uniformly dispatched by the central dispatching system, wherein the central dispatching system comprises a storage module, a task processing module, a control module, a communication module and a monitoring module. Setting up a system, setting up a working area, building a global path knowledge base, throwing a heavy AGV into the working area, splitting a work task into ordered atomic action sequences, selecting heavy AGV groups capable of executing the atomic action sequences, generating control instructions, issuing the control instructions and returning the execution progress state information of the work task. The invention improves the multi-vehicle linkage effect through central unified scheduling.

Inventors

YANG HUAIYU
LIU BO
WANG DONG
ShangGuan Qingyun
ZHAO MING
LIU GANG
YAO GUISHENG
ZHU YULONG
XU HAOCHENG

Assignees

西安航天赛能自动化科技有限公司

Dates

Publication Date: 20260508
Application Date: 20251225

Claims (9)

1. A heavy load AGV transport system based on central scheduling, characterized by: the system comprises a central dispatching system which is in communication connection with an upper control system, and a plurality of heavy load AGVs which are uniformly dispatched by the central dispatching system; The central dispatching system comprises a storage module, a task processing module, a control module, a communication module and a monitoring module; The storage module is used for storing a device action information base and a global path knowledge base, wherein the action information base comprises control parameters corresponding to all controllable atomic actions of the reloaded AGV; The task processing module is in communication connection with the upper control system and is used for receiving and analyzing the job task from the upper control system, splitting the job task into ordered atomic action sequences and returning job task execution progress state information to the upper control system; The control module is respectively connected with the storage module and the task processing module and is used for issuing control instructions to the appointed heavy-load AGV according to the equipment action information base and the global path knowledge base in the storage module and the ordered atomic action sequences obtained by splitting of the task processing module; the communication module is connected with the control module and each heavy-load AGV, and is used for sending the control instruction to the appointed heavy-load AGVs and receiving a state signal returned by each heavy-load AGV; The monitoring module is connected with the communication module and is used for monitoring equipment body state information, real-time position and motion state information and task execution progress state information of the heavy-load AGV according to the state signals.
2. The center-dispatch based heavy-duty AGV transport system of claim 1 wherein: The equipment action information base is stored in a database form of a horizontal sub-table, and the horizontal sub-table comprises a point position table, a line table, an equipment information table and a nearby point relation table; The point position table is used for storing static attributes of each navigation point in the map, including point numbers, X-direction coordinates, Y-direction coordinates, orientation angles and point states; the line table is used for storing attributes of a path segment connecting two navigation points, including path segment numbers, starting point numbers, end point numbers, path lengths, preset idle speed, preset load speed and path direction attributes; The device information table is used for storing the static attribute and the dynamic state of each heavy-load AGV, wherein the static attribute comprises a device number, a device name, a mac address, a loading capacity, size information, speed and acceleration; The proximity point relation table is used for storing navigation point pairs with direct communication relations in the working area map so as to represent the topological structure of the path network.
3. The center-dispatch based heavy-duty AGV transport system of claim 2 wherein: The control instructions comprise movement control instructions and equipment operation control instructions, the control module selects a path for a specified heavy-load AGV from the global path knowledge base aiming at the atomic actions related to movement, generates the movement control instructions by combining corresponding control parameters queried from an equipment action information base, and generates the equipment operation control instructions by querying corresponding control parameters from the equipment action information base aiming at the atomic actions not related to movement.
4. The center-dispatch based heavy-duty AGV transport system according to claim 3 wherein: the data communication protocol between the communication module and each reloaded AGV is Modbus protocol, and the polling period is less than or equal to 100ms.
5. The center-dispatch based heavy-duty AGV transport system of claim 4 wherein: the equipment body state information comprises battery electric quantity, battery health degree, voltage and current in a charging state and equipment fault codes; The real-time position and motion state information comprises an X-axis coordinate, a Y-axis coordinate, a real-time speed, a course angle and a motion control mode; the task execution progress status information comprises a task number of current execution, an atomic action instruction being executed under the task and an execution completion status of the atomic action.
6. A method of scheduling a center-based, scheduled heavy load AGV transport according to any one of claims 1-5, comprising the steps of: step1, constructing a heavy-load AGV transport system based on central dispatching, setting a working area and establishing a global path knowledge base for the area; Step 2, a plurality of heavy-load AGVs are thrown into the working area; Step 3, starting to work, wherein the upper control system sends the job task to the central dispatching system, and a task processing module of the central dispatching system splits the job task into an ordered atomic action sequence; Step 4, the control module traverses all the heavy AGVs through the communication module and selects and designates one or more heavy AGVs capable of executing the atomic action sequence; Step 5, inquiring corresponding control parameters from an equipment action information base aiming at each atomic action in the atomic action sequence, and if the atomic action involves movement, planning paths for the appointed heavy-load AGVs from the global path knowledge base established in the step 1; And step 6, issuing the control instruction to each appointed heavy-load AGV so as to drive the AGVs to sequentially execute the atomic action sequence, and returning the task execution progress state information to the upper control system by the task processing module in the execution process and after the execution is finished.
7. The method of scheduling a center-based, scheduled heavy-load AGV transport system according to claim 6, wherein: the step 1 specifically comprises the following steps: Step 1.1, setting a working area, establishing a directional weighting graph G= { V, E and W } based on a line table and a nearby point relation table in an equipment action information base, wherein V is a top point set, E is an edge set, W is a weight matrix, V= { V 1 ,v 2 …v n }, n is the number of navigation points in the working area, V 1 、v 2 …v n represents different navigation points, for any edge E in the edge set E, the edge E is represented by a triplet (V i ,v j ,w ij ), V i and V j sequentially represent a starting navigation point and a termination navigation point of the edge E, W ij represents the passing cost of a heavy load AGV for directly driving from the starting navigation point V i to the termination navigation point V j , W ij forms an element of a corresponding position in the weight matrix W, and if no direct path exists between the two navigation points, W ij = infinity is defined, and the passing cost from one navigation point to the navigation point is W ii =0; Step 1.2, initializing an n×n traffic cost matrix dist, enabling an initial traffic cost matrix dist (0) =a weight matrix W, defining dist (0) [i][j]=w ij , and taking the initial traffic cost matrix dist (0) as an iterative initial state; Step 1.3, sequentially taking each navigation point in the vertex set V as a candidate transit navigation point V k , and starting iteration on the initial traffic cost matrix dist (0) , wherein k=1, 2. In each iteration, the following is performed for each navigation point pair (v i ,v j ): a. Via calculation Cost of passage of (2) Wherein The current cost matrix after the previous iteration is used; b. Based on And (3) with The corresponding path is used for determining the complete vertex sequence from the initial navigation point v i to the final navigation point v j through the transit navigation point v k ; C. Grouping path information tuples Set of alternative paths added to correspond to navigation point pair (v i ,v j ) In (a) and (b); Step 1.4, after all iterations are completed, based on each navigation point pair (v i ,v j ), the alternative paths are gathered And selecting the first five paths with the minimum passing cost as a global path knowledge base and storing the global path knowledge base into the storage module.
8. The method of scheduling a center-based, scheduled heavy-load AGV transport system according to claim 7, wherein: In the steps 1.1-1.4, the passing cost is a distance.
9. The method of scheduling a center-based, scheduled heavy-load AGV transport system according to claim 8, wherein: In step 5, path planning is performed for each specified heavy load AGV from the global path knowledge base, specifically: a1, acquiring five pre-stored alternative paths and distances thereof for navigation point pairs formed by the starting point and the end point from the global path knowledge base according to the starting point and the end point of the current atomic action; a2, checking the real-time occupied states of the five alternative paths, and selecting the path with the smallest distance from unoccupied paths as an execution path.

Description

Heavy load AGV transport system based on central dispatching and dispatching method thereof Technical Field The invention relates to a heavy object transportation system, in particular to a heavy-load AGV transportation system based on central dispatching and a dispatching method thereof. Background In the field of automated logistics and intelligent manufacturing, automated guided vehicles (Automated Guided Vehicle, AGVs) are used as key execution equipment, and the core is that unmanned material handling is achieved through a preset path or a navigation system, so that the flexibility and the efficiency of operation are improved. Along with the deepening of industrial scenes, a variant AGV with significantly stronger bearing capacity, namely a heavy-load AGV, is increasingly becoming a rigid requirement in the industries of automobile manufacturing, aerospace, port and dock, heavy equipment and the like. In the industry, an AGV with rated load not lower than 2 tons is generally defined as a heavy-load AGV, and the upper load limit of the AGV can reach tens or even hundreds of tons, so that the problem of accurate transfer of large and overweight materials is solved. Compared with a conventional AGV, the heavy-load AGV not only presents the magnitude improvement of physical size and loading capacity, but also brings a series of technical challenges of extremely high control precision requirement (often reaching millimeter level), huge motion inertia, complex multi-vehicle collaborative operation and the like. Currently, a traditional scheduling system designed for a light-load AGV generally adopts a distributed and weakly centralized control architecture, but the architecture has obvious fundamental limitation and inadaptability when dealing with severe working conditions unique to a heavy-load AGV, and mainly shows the contradiction between the following three main cores: First is the contradiction between the catastrophic consequences of the risk of runaway and the lack of distributed control safety. The heavy load AGVs carry high value of material, and their great kinetic energy means that any slight collision, offset or loss of synchronization can cause major accidents such as equipment damage, production line paralysis, etc. Particularly, when multiple heavy-duty AGVs cooperatively transport the same oversized component (such as an aircraft fuselage, a wind blade), each vehicle is required to maintain absolute synchronization in speed, direction and phase, forming a "virtual rigid platform". Traditional distributed scheduling depends on autonomous decision-making and local sensing information of a bicycle, precise coordination and conflict pre-judgment are difficult to realize on a global level, and deterministic safety guarantee cannot be provided for high-risk operation. And secondly, the contradiction between the optimal system-level operation efficiency and the blindness of the local decision of the bicycle is realized. In a complex working area path network, a plurality of heavy-load AGVs can work simultaneously, so that congestion and even system deadlock are easily caused at key geographic bottlenecks such as intersections, narrow channels and the like. In the distributed scheduling mode, each AGV performs path planning by adopting an a-x algorithm (an efficient heuristic search algorithm) or a variant thereof based on a decision made by itself optimal (such as a shortest path), which often causes the whole system to sink into a "public tragedy (THE TRAGEDY of the common)", so that the overall transport throughput is greatly reduced. Finally, the contradiction between the high bicycle control complexity and the large-scale cost-reducing and efficiency-increasing requirements is caused. In order to realize large-load and high-precision movement, a heavy-load AGV usually adopts a complex configuration of multiple gear trains and multiple driving motors, and a kinematic model, power distribution and precision control algorithm of the heavy-load AGV are extremely complex. If such complex algorithms and programs are completely loaded into the vehicle-mounted controller, the hardware cost (high-performance computing unit and high-end sensor) and the difficulty of software development of a single AGV will be increased. In summary, aiming at the specificity of the heavy-load AGV, developing a system and a method capable of realizing refined and centralized unified scheduling has become a key point for breaking through the bottleneck of the industry and releasing the full application potential of the system. Disclosure of Invention The invention aims to solve the problems that in the existing distributed AGV scheduling method, each heavy-load AGV is easy to cause increased fault risk, and is trapped in a local optimal trap and cost surge, so that the high-precision and safe transportation requirements of a large number of heavy cargoes are difficult to meet, and provides a heavy-load AGV transportation