CN114819420A

CN114819420A - Overhead traveling crane transportation path planning method based on conflict resolution

Info

Publication number: CN114819420A
Application number: CN202210744605.6A
Authority: CN
Inventors: 谭璜; 申国莉; 缪峰
Original assignee: Mi Fei Industrial Shanghai Co ltd
Current assignee: Mifei Technology (Shanghai) Co.,Ltd.
Priority date: 2022-06-29
Filing date: 2022-06-29
Publication date: 2022-07-29
Anticipated expiration: 2042-06-29
Also published as: CN114819420B; TW202401191A; WO2024001021A1

Abstract

The invention provides a method for planning a transportation path of an overhead traveling crane based on conflict resolution, which comprises the following steps: s101, calculating the shortest distance between any two intersections in the track map, and establishing a routing table; s102, matching the trolleys with the conveying tasks until all the trolleys or the conveying tasks are matched; s103, inquiring a routing table according to the transport task data to obtain the shortest path which each trolley needs to pass through to reach the transport task; s104, calculating the leaving time of each trolley from the current intersection point to the next intersection point on the shortest path, and sequencing the trolleys from small to large; and S105, sequentially detecting whether the trolley encounters a conflict from the current intersection to the next intersection, and S106, judging whether the conflict occurs at the intersection or in the loading/unloading process, and resolving the conflict by respectively adopting an in-situ waiting or path changing mode. The invention can resolve conflict situations in time, reduce the carrying time, improve the carrying efficiency of the AMHS and realize efficient and stable material transmission.

Description

Overhead traveling crane transportation path planning method based on conflict resolution

Technical Field

The invention relates to the technical field of wafer manufacturing and material transportation, in particular to a crown block transportation path planning method based on conflict resolution.

Background

In a chip factory, wafers are processed on various machines according to a specific process flow, and the wafers are transported by a crown block system in circulation among different machines. After the machining task is completed by the machine table, the System issues a conveying instruction, an AMHS (Automatic Material Handling System) matches an idle crown block with the issued conveying task and plans a conveying path, and after the crown block receives the instruction, the crown block goes to the machine table to load the wafer and conveys the wafer to the next appointed machine table.

After the transport command is received by the day car, the day car goes to the wafer starting machine to load the wafer, and the wafer is sent to the target machine to unload the wafer, so that a transport task is completed. Because the orbit network of the overhead traveling crane is a sparse directed cyclic graph and only one-way driving is allowed on the orbit, two conflict situations exist: 1) the front car blocks the track due to a fault or loading or unloading a wafer, causing a conflict with the rear car on the same track. 2) The two vehicles meet at the merging port of the track, namely the two vehicles drive into the same merging port from different tracks to cause collision. Therefore, if the conflict situation cannot be resolved in time, the phenomena of waiting and congestion of vehicles in partial areas can be caused, and the conveying efficiency of the AMHS is seriously influenced.

Disclosure of Invention

In view of this, the embodiment of the present application provides a method for planning a transportation path of an overhead traveling crane based on conflict resolution, and the method comprehensively considers the priority of a transportation task and the utilization rate of the overhead traveling crane, resolves a fork conflict, and realizes global optimization, so as to achieve the purposes of reducing transportation time and improving transportation efficiency of an AMHS system.

The embodiment of the application provides the following technical scheme: a method for planning a transportation path of an overhead traveling crane based on conflict resolution comprises the following steps:

s101, calculating the shortest distance between any two intersections in the track map, and establishing a routing table;

s102, optimally matching the trolleys with the issued conveying tasks until all the trolleys or the conveying tasks are matched;

s103, inquiring the routing table according to issued transport task data to obtain the shortest path which each trolley needs to pass to reach the transport task;

s104, calculating the leaving time of each trolley from the current intersection point to the next intersection point on the shortest path, and sequencing the leaving time from small to large;

s105, according to the sequence of the leaving time, sequentially detecting whether the trolley encounters conflict from the current intersection point to the next intersection point,

if not, determining that the time when the trolley leaves the next intersection is t1, and setting the scheduling time t = t1, if so, performing S106;

s106, judging whether the conflict occurs at the intersection,

if so, the trolley with high task priority is enabled to pass preferentially, the trolley with low task priority waits at the intersection,

or, the trolley with low task priority selects another branch at the last intersection point to change the path;

if not, the conflict is determined to occur in the loading/unloading process of the trolley, the blocked trolley is made to wait in situ until another trolley finishes the loading/unloading process,

or, the blocked trolley selects another branch at the last intersection point to change the path;

s107, repeatedly executing the steps S102-S106 until the scheduling period is finished or all the conveying tasks are executed;

when the path of the trolley is changed at the last intersection point, firstly, the routing table is inquired, the shortest path from the last intersection point to the target point of the trolley is obtained, and then whether the conflict occurs in the shortest path is judged;

if not, executing the shortest path;

if so, resolving the conflict in the shortest path by adopting an ejection chain algorithm;

the ejection chain algorithm is to perform ejection action on the trolley path generating the conflict, perform neighborhood action on the rest trolleys, and then re-plan the path of the ejected trolley to resolve the conflict.

Further, the process of S102 specifically includes:

s201, preprocessing issued transport task data to form a task sequence and obtain a transport task set;

s202, setting the states of all trolleys as idle, and setting the time when the trolleys reach the initial point as 0 to obtain a trolley set;

s203, carrying out bipartite graph matching on the trolley set and the conveying task set in the idle state at the time t until all trolleys or conveying tasks are matched;

further, in S201, the step of preprocessing the assigned transportation task data includes: changing the assignment time of the conveying tasks into seconds from 0 moment, and sequencing the conveying tasks according to the assignment time from small to large to form the task sequence.

Further, in S203, the process of matching bipartite graphs of the trolley set and the conveying task set in idle state at time t includes: and sorting the trolleys with idle time at the time t from high to low, sequentially selecting the conveying tasks closest to each trolley for matching, deleting the matched trolleys and the conveying tasks from respective sets, and repeatedly executing until all the trolleys or the conveying tasks are matched.

Further, in step S203, in the process of matching the bipartite graph of the trolley set and the transport task set in idle state at time t, if the number of the trolleys in idle state at time t is greater than the number of the transport tasks, a virtual task is generated and executed for the trolley that is not matched with the transport tasks, so that the trolley runs empty in Intrabay of the on-call station.

Further, in step S203, in the process of matching the bipartite graph of the cart set and the transport task set in idle at time t, if the number of carts in idle at time t is less than the number of transport tasks, all the carts are assigned to the transport tasks, and the remaining transport tasks are continuously waiting on the machine until the cart state is updated to idle.

Further, in step S106, if the conflict is determined to occur during the loading/unloading process of the cart, the loading/unloading time of the current loading/unloading cart is determined,

if the loading/unloading time is not more than the preset time, the blocked trolley waits in situ until the current loading/unloading trolley finishes the loading and unloading process,

if the loading/unloading time is longer than the preset time, the blocked trolley selects another branch at the last intersection point to change the path.

Further, in S104, the statuses of all the cars are updated to delivery, or pickup, or unload at the same time.

Further, in S106, if the conflict occurs at the intersection and the vehicle having the higher task priority is allowed to pass through preferentially, the state of the vehicle having the lower task priority waiting at the intersection is updated to wait;

if the conflict is determined to occur in the loading/unloading process of the trolley, the state of the trolley waiting in place by the blockage is updated to wait until the other trolley finishes the loading/unloading process.

Further, in S101, the shortest distance between any two intersection points in the track map is calculated by using any one algorithm selected from the group consisting of an a-algorithm, a Dijkstra algorithm, and an SPFA algorithm.

Further, in S101, an a-x algorithm is used to calculate the shortest distance between any two intersections in the acquired orbit map.

Further, in step S101, before calculating and acquiring the shortest distance between any two intersections in the track map, preprocessing the track map.

Compared with the prior art, the beneficial effects that can be achieved by the at least one technical scheme adopted by the embodiment of the specification at least comprise: the AMHS algorithm of the embodiment of the invention realizes a scheduling method of two stages of real-time task assignment and trolley path planning, can select a certain strategy to carry out matching assignment according to the tasks issued in real time aiming at all trolleys, and can clear conflict situations in time, including loading and unloading goods, intersection conflict, trolley faults and the like, thereby reducing the carrying time, improving the carrying efficiency of the AMHS and realizing efficient and stable material transmission.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.

FIG. 1 is a schematic flow diagram of an embodiment of the present invention;

FIG. 2 is an example of a spatiotemporal state diagram and spatiotemporal paths in a catapult-link algorithm according to an embodiment of the present invention;

fig. 3 is an example of an initial path of an ejection chain operation in an ejection chain algorithm of an embodiment of the present invention;

fig. 4 is an example of an initial collision of the operation of the ejection chain in the ejection chain algorithm of the embodiment of the present invention;

fig. 5 is a path pop example of a pop chain operation in a pop chain algorithm of an embodiment of the present invention;

fig. 6 is an example of heuristic actions of ejection chain operations in an ejection chain algorithm of an embodiment of the present invention.

Detailed Description

The embodiments of the present application will be described in detail below with reference to the accompanying drawings.

It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present invention will be described in detail with reference to the accompanying drawings, wherein the embodiments are described in detail, and it is to be understood that the embodiments are only a part of the embodiments of the present invention, and not all of the embodiments are described. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The embodiment of the invention provides a crown block transportation path planning method based on conflict resolution. And then, calculating the shortest distance between any two intersection points of the trolley by adopting an algorithm, namely planning the path of each pair of the trolley and the task. And finally, continuously advancing by taking time as a guideline, wherein the earliest time when all the trolleys travel to the next node is the scheduling time, detecting whether a conflict is encountered, and solving the conflict according to different strategies when the conflict is encountered, such as waiting for one of the trolleys or changing paths of one of the trolleys at the previous intersection until the scheduling period is over or all tasks are completed. The conflict which occurs firstly is processed each time, and the conflict comprises goods loading and unloading, intersection conflict, trolley fault and the like.

The AMHS algorithm in the embodiment of the invention realizes a scheduling method of two stages of real-time task assignment and trolley path planning. The conflict situation can be detected in real time, conflict situations can be resolved in time, loading and unloading, intersection conflicts, trolley faults and the like are included, the carrying time is reduced, the carrying efficiency of the AMHS is improved, and efficient and stable material transmission is achieved.

As shown in fig. 1, the first embodiment of the present invention specifically includes the following steps:

s101, calculating the shortest distance between any two intersections in the track map, and establishing a routing table.

In the embodiment of the invention, the shortest distance between any two intersection points in the track map is calculated by adopting any algorithm of an A-x algorithm, a Dijkstra algorithm and an SPFA algorithm.

The algorithm a (a-Star) is a direct search method which is most effective for solving the shortest path in the static road network, and is also an effective algorithm for solving a plurality of search problems. The closer the distance estimate is to the actual value in the algorithm, the faster the final search speed.

Dijkstra algorithm is a shortest path algorithm from one vertex to the rest of the vertices, and solves the shortest path problem in the weighted graph. The Dijkstra algorithm is mainly characterized in that a greedy algorithm strategy is adopted from a starting point, and adjacent nodes of vertexes which are nearest to the starting point and have not been visited are traversed each time until the nodes are expanded to an end point.

The SPFA (short Path Faster Algorithm) algorithm is an algorithm for solving the shortest Path of a single source, is queue optimization of Bellman-ford, and is a very efficient shortest Path algorithm.

In a specific implementation, the shortest distance between any two intersection points in the acquired orbit map can be calculated preferably by using an a-x algorithm. And rapidly planning the overhead travelling crane transportation path by using an A-x algorithm. Wherein the valuation function

Heuristic function of

The minimum cost path estimation value from the current node n to the target node is represented, the average time of the crown block passing through a certain path is counted, the edge cost is updated periodically, the heuristic function can reflect the traffic condition in a past period, and the algorithm is guided to avoid the congested road section to search for the path with the minimum cost.

Each intersection is saved in the routing table to be passed next by other intersections. Specifically, each row of the routing table is represented by a triple < src, dest, next >, where src is the current intersection, dest is the destination intersection, and next is the next point to be traversed by dest after traversing src.

the process of S102 specifically includes:

in specific implementation, the pretreatment is as follows: changing the issuing time of the conveying tasks into seconds from 0 moment, and sequencing the conveying tasks according to the issuing time from small to large to form the task sequence;

s202, setting scheduling time t =0, setting the states of all trolleys as idle, and setting the time when the trolleys reach the initial point as 0 to obtain a trolley set;

in the algorithm A, the assignment strategy of the trolley and the task is that at a certain scheduling time t, bipartite graph matching is carried out on a trolley set in an idle state and a delivered transport task set: firstly, sorting the trolleys with idle time at the time t from high to low, secondly, calculating the distance between each trolley and the issued conveying task, sequentially selecting the conveying task with the closest distance for each trolley for matching, deleting the matched trolleys and conveying tasks from respective sets, and repeatedly executing until all the trolleys or the conveying tasks are matched.

In the specific implementation, the bipartite graph matching process is carried out on the trolley set and the conveying task set which are in idle state at the time t, and the bipartite graph matching process has two conditions:

a. if the number of the trolleys in idle state at the time t is larger than that of the conveying tasks, redundant trolleys are idle, and because the idle trolleys cannot wait on the track to avoid blocking/collision, a virtual task is generated and executed for the trolleys which are not matched with the conveying tasks, so that the trolleys carry in the Intrabay (secondary channel) of the on-call station of the trolleys, and the probability of increasing blocking caused by running on the Intrabay (main channel) is avoided. And the starting point and the end point of the virtual task are respectively selected as two end points of the Interbay, and the state of the trolley is changed into orderec (no-load running).

b. And if the number of the trolleys with idle states at the time t is less than the number of the conveying tasks, all the trolleys are allocated to the conveying tasks, the remaining conveying tasks which are not allocated continue to wait on the machine table, and the trolleys are reallocated until the trolley states are updated to idle states.

s104, calculating the leaving time of each trolley from the current intersection point to the next intersection point on the shortest path, sequencing the leaving time from small to large, and updating the states of all the trolleys to delivery, pick up or unload;

if the cart is loaded at that point, departure time = arrival time + loading time; if the cart is unloaded at this point, departure time = arrival time + unloading time. Otherwise, the cart passes only that point, then departure time = arrival time.

S105, sorting the departure time from small to large, sequentially detecting whether the cars meet conflicts from the current intersection to the next intersection or not,

if not, determining that the time when the trolley leaves the next intersection is t1, setting a scheduling time t = t1, if the trolley reaches the intersection as a discharging point, resetting the state of the trolley to idle after discharging is completed, returning to S203, and allocating a new task to the trolley.

If yes, go to S106;

in the embodiment of the invention, because the trolleys in the track run in a single direction in the semiconductor wafer manufacturing factory, when the distance between the two trolleys is smaller than a set threshold value, the conflict is determined to be generated, and the blockage occurs.

S106, judging whether the conflict occurs at the intersection,

if so, the trolley with high task priority is enabled to pass through preferentially, the trolley with low task priority waits at the intersection, meanwhile, the state of the trolley with low task priority waiting at the intersection is updated to wait,

or, the trolley with low task priority selects another branch at the last intersection, namely, the path is changed;

if not, determining that the conflict occurs in the process of loading/unloading the trolley, enabling the blocked trolley to wait in situ, updating the state of the trolley waiting in situ to wait until the other trolley finishes the loading/unloading process, wherein the leaving time of the trolley = arrival time + waiting time,

or, the blocked trolley selects another branch at the last intersection point to change the path.

In this step of the embodiment of the present invention, because there is an intersection between Interbay and Intrabay, congestion mainly occurs when two cars pass through the intersection, when a car is loaded/unloaded, and when a car fails. When the blockage occurs, the following strategies are adopted for releasing: (1) waiting in place; (2) one of the vehicles changes the path.

Therefore, whether the conflict occurs at the intersection or not is judged firstly, and for the situation that two vehicles are blocked at the intersection, the time for passing the intersection is short, the vehicle loaded with the task with high priority can be selected to pass preferentially, the vehicle loaded with the task with low priority waits on site, or another branch is selected at the previous intersection, namely the path is replaced. If the conflict is judged not to occur at the intersection, the conflict is judged to occur in the process of loading/unloading the trolley, and the change path can be preferentially selected according to the waiting time length when the loading/unloading of the trolley is carried out or the fault occurs in the front, namely: for a car that is about to reach the conflict road segment through the previous intersection of the conflict road segment, another branch is selected at the previous intersection of the conflict road segment, and the car that has been blocked is made to wait in place.

In this embodiment, the setting rule of the task priority may be set according to specific situations. For example, the delay time of the existing path of the overhead traveling crane is sorted from high to low, the priority of the wafer task is sorted from high to low, and the waiting time of the overhead traveling crane due to collision is sorted from high to low.

In practice, when the trolley selects another branch at the last intersection, namely the path is changed, the optimal path can be selected again at the last intersection.

In one embodiment, when the cart changes path, the optimal path is reselected at the last intersection. The specific operation is as follows: firstly, inquiring the routing table, acquiring the shortest path from the last intersection point to a target point of the trolley, and then judging whether conflict occurs in the shortest path;

if not, executing the shortest path;

if yes, resolving the conflict in the shortest path by adopting an ejection chain algorithm;

Specifically, the method comprises the following steps: in order to further carry out congestion control and flow dispersion on the crown blocks on the track, space nodes on the track are expanded along a time axis to obtain a space-time state diagram, and then a meta-heuristic algorithm of an ejection chain is used for carrying out flow dispersion on the space-time state diagram.

The space-time state diagram is based on space nodes in the classical vehicle routing problem, is expanded into a series of space-time nodes according to a time axis, models the collision detection of the crown block in a directed graph mode, and is structured as shown in fig. 2. All tracks are first discretized into a series of nodes, ensuring that each time tick crown block can move from the current node to its neighboring nodes. For each node

And a series of space-time nodes are developed according to the time beat number contained in the whole planning period

Edges in the original topology map

Is also unfolded along with the

While increasing the number of slave units

To

The edges of (a) represent in-place waiting, while the paths in space become spatio-temporal paths accordingly. Through the expression, the collision constraint of the transport vehicle is converted into the degree constraint of the nodes, and the in-degree and out-degree of each time-space node passed by the instant air path do not exceed 1 respectively.

The ejection chain is an efficient meta-heuristic algorithm and is very suitable for solving the resource allocation problem with strong capacity constraint. As shown in fig. 3-6, the basic idea is to select an object to release the occupied resources, form a partial solution with more relaxed resource restriction, and then perform the neighborhood action on the partial solution to obtain the reference structure. Starting from the optimal reference structure, the neighborhood action can be continuously executed to obtain a new reference structure; and a heuristic action can be executed to obtain a complete solution again, and the ejection chain search of the current round is finished.

In order to describe the specific operation of the catapult chain algorithm, the following description is made by taking the example shown in fig. 3-6 as an example:

in fig. 3: example information is calculated. 4 nodes are shown, 4 crown blocks, each performing 4 traffic path calculations.

FIG. 4: at the initial solution, there is a conflict. Namely, A → B and B → C collide at point C at time T1.

FIG. 5: and (4) an ejection operation schematic diagram. And executing a pop-up action to remove the path D → C, executing a neighborhood action pair B → C to reroute, and eliminating a conflict to obtain a reference structure.

FIG. 6: schematic diagram of heuristic action. And executing a heuristic action to recalculate the shortest path with the least number of conflicts for the removed path D → C to obtain a heuristic solution. And (c) then, executing a new pop-up action, or considering that the neighborhood action is continuously executed from the step (b). For example, popping B → C back to get a heuristic solution may eliminate all conflicts.

In the example of the process of executing the ejection chain shown in fig. 3 to 6, starting from the initial slack solution of incompletely eliminating the collision of the crown blocks, by popping up the path from the node D to the node C, the remaining paths can be optimized, so that the shortest path with the least collision is recalculated for each path as a neighborhood action, and the number of collided paths (that is, two crown blocks pass through the same node at the same time) is reduced, thereby obtaining the reference structure. Next, the neighborhood action may be continued, but since the optimal reference structure of the current round has no conflict, no further neighborhood action needs to be performed, so the heuristic action is performed directly, and the popped path is put back. Similarly, continuing to proceed with the next round of ejection chain can eliminate all conflicts, resulting in a feasible solution.

And S107, repeatedly executing the steps S102-S106 until the scheduling period is finished or all the conveying tasks are executed.

In the embodiment of the invention, the motion state of the trolley which can exist until the end of the scheduling period or the completion of all the carrying tasks comprises the following steps: (1) idle, no assigned task; (2) orderrec, the trolley receives the command, goes to the destination to pick up goods and runs in no-load; (3) pickup, trolley picking; (4) delivery, carrying cargo operation of the trolley; (5) unloading the unload trolley; (6) wait, trolley waiting; failure, (7) car failure.

In the second embodiment of the present invention, in S106, if the conflict is determined to occur during the loading/unloading process of the cart, the loading/unloading time of the current loading/unloading cart is determined,

if the loading/unloading time is greater than a preset time, the blocked trolley selects another branch at the last intersection, namely the change path.

In this embodiment, if it is determined that the conflict occurs during the loading/unloading process of the cart, the loading/unloading time of the current loading/unloading cart is determined to determine whether the jammed cart is loaded/unloaded or whether the cart is malfunctioning. In specific implementation, the loading/unloading time is compared with a threshold value for judgment, if the loading/unloading time is larger than the threshold value, the trolley is judged to have a fault, and the blocked trolley is enabled to select another branch at the last intersection point for replacing the path. If the loading/unloading time is less than or equal to the threshold value, the trolley is judged to be loaded/unloaded, the blocked trolley waits in situ until the current loading/unloading trolley finishes the loading/unloading process.

In the third embodiment of the present invention, in S101, before calculating and acquiring the shortest distance between any two intersections in the track map, the track map is preprocessed.

The original track map includes cross points, barcode, tool sites, stocker sites, and the like. The preprocessing is to remove other points in the original track map, only reserve intersection points and construct a new simple graph. And then solving the shortest distance between any two intersection points by adopting a shortest path algorithm. The purpose of the preprocessing is therefore to scale down the orbit map to reduce the algorithm run time.

In the AMHS algorithm of the embodiment of the invention, in order to simplify the model, all trolleys run at the same speed at a constant speed, and wait in situ on a certain node when a block is encountered without considering the conditions of actual braking, acceleration and deceleration during turning and the like. Meanwhile, in order to simulate the actual operation scenario, the input data of the AMHS algorithm is all the actually performed transport tasks in a certain fab for a period of time (e.g. one day). The map is a real factory map, when the algorithm starts to run, the map is preprocessed, the shortest distance between any two intersections is found by adopting an A-x algorithm, and for each intersection, the passing point of the next step of other intersections is recorded. After processing, in the execution process of the algorithm, the shortest distance between any two points can be found by finding the shortest path of the intersection point which is closest to the two points, namely, by looking up the table.

When the embodiment of the invention is implemented specifically, the algorithm input comprises:

(1) wafer fab track map: point, edge, point attribute, maintenance location, etc.;

(2) raw task data over a period of time: task number, starting point, end point and task priority;

(3) trolley data: the method comprises the following steps of (1) carrying out automatic control on the vehicle, wherein the vehicle comprises a vehicle initial position, a vehicle running speed, historical driving mileage, vehicle priority, a vehicle cycling rule and an on call station;

the algorithm output comprises: the execution path of each task, including the allocated cart, all points traversed and the time at which these points were traversed.

The overhead traveling crane transportation path planning method based on conflict resolution can rapidly and accurately convey wafers to the destination, reduce the cycle time of the wafers between equipment of the platform, improve the throughput rate of the system and realize efficient and stable material transmission.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present application should be covered within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method for planning a transportation path of an overhead traveling crane based on conflict resolution is characterized by comprising the following steps:

s106, judging whether the conflict occurs at the intersection,

if not, executing the shortest path;

2. The overhead traveling crane transportation path planning method based on conflict resolution as claimed in claim 1, wherein the process of S102 specifically includes:

and S203, carrying out bipartite graph matching on the trolley set and the conveying task set in the idle state at the time t until all the trolleys or conveying tasks are matched.

3. The overhead traveling crane transportation path planning method based on conflict resolution according to claim 2, wherein in S201, the process of preprocessing the issued transportation task data includes: changing the assignment time of the conveying tasks into seconds from 0 moment, and sequencing the conveying tasks according to the assignment time from small to large to form the task sequence.

4. The overhead traveling crane transportation path planning method based on conflict resolution as claimed in claim 2, wherein in S203, the process of performing bipartite graph matching on the trolley set and the transport task set in idle state at time t includes: and sorting the trolleys with idle time at the time t from high to low, sequentially selecting the conveying tasks closest to each trolley for matching, deleting the matched trolleys and the conveying tasks from respective sets, and repeatedly executing until all the trolleys or the conveying tasks are matched.

5. The overhead traveling crane transportation path planning method based on conflict resolution according to claim 2 or 4, wherein in step S203, in the process of bipartite graph matching between the trolley set and the transport task set in idle state at time t, if the number of trolleys in idle state at time t is greater than the number of transport tasks, a virtual task is generated and executed for the trolley that is not matched with the transport tasks, so that the trolley runs empty in Intrabay of on call state.

6. The overhead traveling crane transportation path planning method based on conflict resolution according to claim 2 or 4, wherein in step S203, in the process of bipartite graph matching between the trolley set and the transportation task set in the state of idle at time t, if the number of trolleys in the state of idle at time t is less than the number of transportation tasks, all trolleys are allocated to the transportation tasks, and the remaining unallocated transportation tasks continue to wait on the machine until the trolley state is updated to idle and then are reallocated.

7. The method for planning a transportation path of an overhead traveling crane based on collision resolution as claimed in claim 1, wherein in step S106, if the collision is determined to occur during the loading/unloading of the overhead traveling crane, the loading/unloading time of the current loading/unloading truck is determined,

8. The overhead traveling crane transportation path planning method based on conflict resolution as claimed in claim 1, wherein in S104, all the car states are updated to delivery, or pick up, or unload at the same time.

9. The overhead traveling crane transportation path planning method based on conflict resolution as claimed in claim 1, wherein in S106, if the conflict occurs at an intersection and a vehicle with a high task priority is allowed to pass preferentially, the state of a vehicle with a low task priority waiting at the intersection is updated to wait;

10. The method for planning a transportation path of a crown block based on collision resolution according to claim 1, wherein in the step S101, the shortest distance between any two intersections in the track map is calculated by using any one algorithm selected from the group consisting of a-x algorithm, Dijkstra algorithm and SPFA algorithm.

11. The crown block transportation path planning method based on collision resolution according to claim 10, wherein in S101, an a-x algorithm is adopted to calculate and obtain the shortest distance between any two intersections in the track map.

12. The overhead traveling crane transportation path planning method based on conflict resolution as claimed in claim 1, further comprising, in S101, preprocessing the track map before calculating and obtaining the shortest distance between any two intersections in the track map.