AGV intelligent yarn transporting vehicle transportation path planning method and system

Abstract

The invention relates to the technical field of path planning, in particular to an AGV intelligent yarn carrier transport path planning method and system, and the method comprises the steps: determining a common path segment based on the initial transport path of each AGV intelligent yarn carrier, and determining the transport path of each AGV intelligent yarn carrier according to the relation between the time for any two AGV intelligent yarn carriers to reach the common path segment; the method comprises the following steps: determining whether any two AGV intelligent yarn carriers have a path conflict or not, if the path conflict occurs, determining the waiting cost generated by any two AGV intelligent yarn carriers waiting to give way and the bypassing cost generated by bypassing, and selecting the minimum cost in the waiting cost and the bypassing cost and the scheduling scheme corresponding to the minimum cost. In this way, even if the number of the AGV intelligent yarn transporting vehicles is large, the AGV intelligent yarn transporting vehicle dispatching scheme with the minimum cost can be determined under the condition that path conflicts occur, and therefore the situation that the AGV intelligent yarn transporting vehicles are mutually blocked is avoided, and the transporting efficiency of the AGV intelligent yarn transporting vehicles is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of path planning, and particularly to a method and system for planning the transportation path of an AGV intelligent yarn transport vehicle. Background Art

[0002] In a spinning factory, after the production line of yarn products is completed, the finished products need to be transported to the next process (such as a sorting and packing workshop, etc.), and the demand for yarn transportation operations is relatively large. Nowadays, the rapid development of AGV (Automated Guided Vehicle) automated guided vehicles has greatly reduced the labor cost and accelerated the work efficiency by using them as transportation vehicles. When using an AGV intelligent yarn transport vehicle for yarn product transportation, only by making a reasonable transportation path plan for it can it perform transportation operations quickly and efficiently.

[0003] Currently, when planning the transportation path of an AGV intelligent yarn transport vehicle, some common shortest path planning algorithms (such as the A* algorithm, Dijkstra algorithm, etc.) are used to make the transport vehicle transport along the shortest path, which greatly reduces the time consumed by the transport vehicle for transportation and increases its transportation efficiency. However, in a spinning factory with a large number of product productions, the demand for transportation volume is extremely large, and often a large number of transport vehicles need to run in parallel at the same time to meet the transportation volume demand. When the number of transport vehicles increases, there may be a large number of common paths in the transportation paths of each transport vehicle obtained by the shortest path algorithm. During the transportation process, when multiple transport vehicles are in the same common path at the same time, it is easy to cause path conflicts and affect the transportation efficiency of a large number of transport vehicles. Therefore, the prior art often uses the shortest path algorithm to plan the transportation path of the transport vehicle, but does not consider the situation that when the number of transport vehicles is large, multiple transport vehicles may share the same section of the transportation path, resulting in mutual blockage between the transport vehicles on the same path within the same time period and hindering the transportation efficiency of the transport vehicle. Summary of the Invention

[0004] In order to solve the technical problem that the existing transportation path planning method of an AGV intelligent yarn transport vehicle will affect the transportation efficiency of the AGV intelligent yarn transport vehicle, the purpose of the present invention is to provide a method and system for planning the transportation path of an AGV intelligent yarn transport vehicle, and the specific technical solutions adopted are as follows: In the first aspect of the present invention, a method for planning the transportation path of an AGV intelligent yarn transport vehicle is provided, including: Determining a common path segment based on the initial transportation paths of each AGV intelligent yarn transport vehicle; Determining whether any two AGV intelligent yarn transport vehicles will have a path conflict according to the relationship between the time taken for any two AGV intelligent yarn transport vehicles to reach the common path segment; If a path conflict occurs, determining the waiting cost generated by any two AGV intelligent yarn transport vehicles waiting for yielding and the detour cost generated by detouring; Select the minimum cost among the waiting cost and the detour cost, and determine the scheduling plan corresponding to the minimum cost.

[0005] In an exemplary embodiment, the path conflicts include same-direction path conflicts and opposite-direction path conflicts.

[0006] In an exemplary embodiment, determining whether any two AGV intelligent yarn transport vehicles will have a path conflict includes: If any two AGV intelligent yarn transport vehicles are traveling in the same direction, then if the driving time period of one of the two AGV intelligent yarn transport vehicles in the shared path segment includes the driving time period of the other AGV intelligent yarn transport vehicle in the shared path segment, there will be a same-direction path conflict between the two AGV intelligent yarn transport vehicles; If any two AGV intelligent yarn transport vehicles are traveling in opposite directions, then if the entry time point of one of the two AGV intelligent yarn transport vehicles into the shared path segment is within the driving time period of the other AGV intelligent yarn transport vehicle in the shared path segment, there will be an opposite-direction path conflict between the two AGV intelligent yarn transport vehicles.

[0007] In an exemplary embodiment, if a same-direction path conflict occurs, the process of obtaining the waiting cost includes: The waiting cost of the AGV intelligent yarn transport vehicle that enters the shared path segment later is equal to: the time duration between the exit time point of the AGV intelligent yarn transport vehicle that enters the shared path segment later when it exits the shared path segment and the exit time point of the other AGV intelligent yarn transport vehicle when it exits the shared path segment.

[0008] In an exemplary embodiment, if an opposite-direction path conflict occurs, the process of obtaining the waiting cost includes: The waiting cost of the AGV intelligent yarn transport vehicle to be yielded is equal to: the sum of the time required for the AGV intelligent yarn transport vehicle to be yielded to yield from the original route, the time required for the other AGV intelligent yarn transport vehicle among the two AGV intelligent yarn transport vehicles to pass through the yielding section, and the time required for the AGV intelligent yarn transport vehicle to be yielded to return to the original route; the AGV intelligent yarn transport vehicle to be yielded is any one of the two AGV intelligent yarn transport vehicles.

[0009] In an exemplary embodiment, both the time required for the AGV intelligent yarn transport vehicle to be yielded to yield from the original route and the time required for the AGV intelligent yarn transport vehicle to be yielded to return to the original route are equal to the ratio of the vehicle length of the AGV intelligent yarn transport vehicle to be yielded to the vehicle speed of the AGV intelligent yarn transport vehicle to be yielded; the time required for the other AGV intelligent yarn transport vehicle to pass through the yielding section is equal to the ratio of 2 times the vehicle length of the other AGV intelligent yarn transport vehicle to the vehicle speed of the other AGV intelligent yarn transport vehicle.

[0010] In an exemplary embodiment, the process of obtaining the detour cost includes: Obtain at least one re-planned shortest path with the path conflict point as the starting point and the final target position as the ending point for the AGV intelligent yarn transport vehicle to be detoured; the AGV intelligent yarn transport vehicle to be detoured is the AGV intelligent yarn transport vehicle that needs to detour among any two AGV intelligent yarn transport vehicles; Based on the difference between the remaining transport path in the initial transport path and the re-planned shortest path, and in combination with the speed of the AGV intelligent yarn transport vehicle to be detoured, obtain the additional time required for detouring corresponding to the re-planned shortest path; Based on the additional time required for detouring corresponding to each re-planned shortest path, obtain the final detour cost.

[0011] In an exemplary embodiment, the process of obtaining the final detour cost includes: Obtain the conflict incidence rate of each shared path segment in the re-planned shortest path, and thus obtain the first conflict incidence rate comprehensive feature of the re-planned shortest path; the conflict incidence rate is used to characterize the possibility of path conflict occurring on the shared path segment; Obtain the conflict incidence rate of each shared path segment in the remaining transport path of the initial transport path, and thus obtain the second conflict incidence rate comprehensive feature of the remaining transport path; Calculate the product of the additional time required for detouring and the detour difficulty coefficient corresponding to each re-planned shortest path to obtain the path detour cost corresponding to each re-planned shortest path; the detour difficulty coefficient is equal to the ratio of the first conflict incidence rate comprehensive feature to the second conflict incidence rate comprehensive feature; Based on the path detour cost corresponding to each re-planned shortest path, obtain the final detour cost.

[0012] In an exemplary embodiment, the process of obtaining the conflict incidence rate includes: The conflict incidence rate is obtained from the number of overlapping transport paths on the shared path segment, the length of the shared path segment, and the number of obstacles within the preset range of the shared path segment; the conflict incidence rate is proportional to the AGV intelligent yarn transport vehicle density and the number of obstacles within the preset range of the shared path segment, and the AGV intelligent yarn transport vehicle density is the ratio of the number of overlapping transport paths on the shared path segment to the length of the shared path segment.

[0013] In the second aspect of the present invention, there is provided an AGV intelligent yarn transport vehicle transport path planning system, including: a memory and a processor; the memory is connected to the processor; the memory is used to store program instructions; the processor is used to implement the above-mentioned AGV intelligent yarn transport vehicle transport path planning method when the program instructions are executed.

[0014] The present invention has the following beneficial effects: When the number of simultaneously operating AGV intelligent yarn transport vehicles is large, a shared path segment is determined based on the initial transport paths of each AGV intelligent yarn transport vehicle. Then, according to the relationship between the times taken by any two AGV intelligent yarn transport vehicles to reach the shared path segment, it is determined whether there will be a path conflict between these two AGV intelligent yarn transport vehicles. In the case of a path conflict, the waiting cost generated by the AGV intelligent yarn transport vehicle waiting to yield and the detour cost generated by detouring are determined for these two AGV intelligent yarn transport vehicles. Finally, the minimum cost between the waiting cost and the detour cost is selected to obtain the scheduling scheme corresponding to the minimum cost. In this way, even when the number of AGV intelligent yarn transport vehicles is large, in the case of a path conflict, the minimum cost and its AGV intelligent yarn transport vehicle scheduling scheme can be obtained, thereby avoiding the situation of mutual blockage between AGV intelligent yarn transport vehicles and improving the transport efficiency of AGV intelligent yarn transport vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a flowchart of a method for planning the transport path of an AGV intelligent yarn transport vehicle provided by an embodiment of the present invention; Figure 2 is a flowchart for obtaining the detour cost provided by an embodiment of the present invention; Figure 3 is a flowchart for obtaining the final detour cost provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0016] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following describes in detail the specific embodiments, structures, features, and effects of the present invention in conjunction with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0017] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. All data information collected in this application is obtained with full consent and authorization, and the collection, use, and processing of relevant information need to comply with relevant laws, regulations, and standards of relevant countries and regions.

[0018] As Figure 1 shown, this embodiment provides a method for planning the transport path of an AGV intelligent yarn transport vehicle, including: Step S1: Determine a shared path segment based on the initial transport paths of each AGV intelligent yarn transport vehicle; Step S2: Determine whether there will be a path conflict between any two AGV intelligent yarn transport vehicles according to the relationship between the time taken by any two AGV intelligent yarn transport vehicles to reach the shared path segment. Step S3: If a path conflict occurs, determine the waiting cost generated by any two AGV intelligent yarn transport vehicles waiting to yield and the detour cost generated by detouring. Step S4: Select the minimum cost among the waiting cost and the detour cost, and determine the scheduling scheme corresponding to the minimum cost.

[0019] The following will specifically describe each step in conjunction with the accompanying drawings.

[0020] Step S1: Determine the shared path segment based on the initial transportation paths of each AGV intelligent yarn transport vehicle.

[0021] Obtain the transportation environment in the yarn factory and the transportation requirements. Taking the transportation from the finished products to the sorting room as an example, there are several product production lines and sorting rooms in the transportation requirements of this embodiment, and several AGV intelligent yarn transport vehicles are allocated for transportation operations. The reason why it is called an AGV intelligent yarn transport vehicle is that the AGV intelligent yarn transport vehicle has the functions of remote communication with the background and being remotely monitored by the background.

[0022] A positioning sensor is set on each AGV intelligent yarn transport vehicle to obtain the real-time position signal of the AGV intelligent yarn transport vehicle, and a speed sensor and the like are also set on each AGV intelligent yarn transport vehicle to obtain the vehicle speed of the AGV intelligent yarn transport vehicle. It should be understood that the vehicle speeds of each AGV intelligent yarn transport vehicle are not necessarily the same, and the vehicle lengths of each AGV intelligent yarn transport vehicle are not necessarily the same.

[0023] The background monitoring system previously obtains information such as the coordinates of the entire driving area of the AGV intelligent yarn transport vehicle, and previously obtains the positions of each product production line and sorting room in the entire driving area, as well as information such as the occupied space. Moreover, environmental impact factors during transportation (certain obstacles that will block the progress of the transport vehicle, etc.) are previously entered into the background monitoring system. The background monitoring system assigns the end point of the transportation operation, that is, the final target position, to each AGV intelligent yarn transport vehicle, and obtains the shortest path between the starting position and the final target position of each AGV intelligent yarn transport vehicle according to existing algorithms such as the shortest path algorithm as the initial transportation path.

[0024] Initially, each AGV intelligent yarn transport vehicle travels according to the corresponding initial transportation path, and the background monitoring system can know the real-time position of each AGV intelligent yarn transport vehicle in the corresponding initial transportation path.

[0025] Due to the large demand for product transportation flow in spinning factories, multiple AGV smart yarn transport vehicles are often required to carry out transportation operations in parallel. When multiple operations are scheduled in parallel, route conflicts between AGV smart yarn transport vehicles are inevitable, such as: multiple AGV smart yarn transport vehicles passing through a point at the same time causing a blockage; two AGV smart yarn transport vehicles traveling in opposite directions occupy each other's roads, etc. In order to ensure transportation efficiency, each AGV smart yarn transport vehicle monitors in real time whether there is a path conflict or occupation on its own transportation route, and takes timely response measures.

[0026] It should be understood that there may be a situation where the transport paths overlap between multiple initial transport paths, that is, a certain path segment is a path segment where at least two initial transport paths overlap, that is, the path segment is an overlapping path segment of at least two initial transport paths. Based on this, the existing shared path segments are determined according to the initial transport paths of each AGV intelligent yarn transport vehicle. For any shared path segment, it may be formed by the overlap of two initial transport paths, or it may be formed by the overlap of more initial transport paths.

[0027] Then, the length of each common path segment and the number of initial transport paths overlapping on each common path segment are obtained. Moreover, the present embodiment also obtains the number of obstacles within the preset range of each common path segment. For any common path segment, the preset range can be a circle with the midpoint of the common path segment as the center point and the preset length as the radius. The obtained circular area is the preset range of the common path segment, wherein the preset length is set according to actual needs, for example: the preset length is equal to twice the length of the common path segment. Among them, obstacles refer to immovable fixed objects that exist in the entire driving area, such as storage racks, etc. The more obstacles there are, the more difficult it is for the AGV intelligent yarn transport vehicle to bypass, and the more likely it is to cause a conflict.

[0028] Step S2: Determine whether any two AGV intelligent yarn transport vehicles will have a path conflict based on the relationship between the time taken for any two AGV intelligent yarn transport vehicles to reach the common path segment.

[0029] Taking any two of the multiple AGV intelligent yarn transport vehicles as an example, by determining the common path segment corresponding to the initial transport paths of the two AGV intelligent yarn transport vehicles, it is possible to determine whether the two AGV intelligent yarn transport vehicles will have a path conflict based on the relationship between the time taken by the two AGV intelligent yarn transport vehicles to reach the common path segment. In this embodiment, path conflict includes two situations, namely: same-direction path conflict and opposite-direction path conflict. It should be understood that in this embodiment, the common path segment reached by the two AGV intelligent yarn transport vehicles is the closest common path segment on the driving route, that is, the first common path segment reached.

[0030] The closer the arrival times of these two AGV intelligent yarn carriers at the shared path section are, the more likely they are to meet within the shared path section and cause a conflict.

[0031] In an exemplary embodiment, determining that these two AGV intelligent yarn carriers have a path conflict includes two cases, namely: these two AGV intelligent yarn carriers will have a same-direction path conflict and an opposite-direction path conflict. The following explains these two cases separately.

[0032] Set the two endpoints of the shared path section as and . If these two AGV intelligent yarn carriers are traveling in the same direction, then both of these two AGV intelligent yarn carriers enter the shared path section from the same endpoint and exit the shared path section from the same endpoint. For example: both of these two AGV intelligent yarn carriers enter the shared path section from and exit the shared path section from .

[0033] For any one of these two AGV intelligent yarn carriers, calculate the ratio of the distance from the current position of this AGV intelligent yarn carrier to to the vehicle speed of this AGV intelligent yarn carrier to obtain the time required for this AGV intelligent yarn carrier to enter the shared path section, thereby obtaining the time point when this AGV intelligent yarn carrier enters the shared path section, which is the entry time point; calculate the ratio of the distance from the current position of this AGV intelligent yarn carrier to to the vehicle speed of this AGV intelligent yarn carrier to obtain the time required for this AGV intelligent yarn carrier to exit the shared path section, thereby obtaining the time point when this AGV intelligent yarn carrier exits the shared path section, which is the exit time point. And the entry time point, the exit time point, and the time length between the entry time point and the exit time point constitute the driving time period of this AGV intelligent yarn carrier in the shared path section. Thus, the driving time periods of each of these two AGV intelligent yarn carriers are obtained.

[0034] If the driving time period of one of the two AGV intelligent yarn transport vehicles in the shared path section includes the driving time period of the other AGV intelligent yarn transport vehicle in the shared path section, that is, the driving time period of one of the AGV intelligent yarn transport vehicles in the shared path section is within the time range of the driving time period of the other AGV intelligent yarn transport vehicle in the shared path section, then a same-direction path conflict will occur between the two AGV intelligent yarn transport vehicles. Specifically: Assume the two AGV intelligent yarn transport vehicles are the first AGV intelligent yarn transport vehicle and the second AGV intelligent yarn transport vehicle, the first entry time point and the first exit time point are the time points when the first AGV intelligent yarn transport vehicle enters and exits the shared path section respectively, and the second entry time point and the second exit time point are the time points when the second AGV intelligent yarn transport vehicle enters and exits the shared path section respectively. Then, if the first entry time point is earlier than the second entry time point and the first exit time point is later than the second exit time point, that is: compared with the second AGV intelligent yarn transport vehicle, the first AGV intelligent yarn transport vehicle enters the shared path section earlier but exits later. Then, the second AGV intelligent yarn transport vehicle will be blocked by the first AGV intelligent yarn transport vehicle, and there must be a contact situation between the first AGV intelligent yarn transport vehicle and the second AGV intelligent yarn transport vehicle in the shared path section, so a same-direction path conflict will occur between the two AGV intelligent yarn transport vehicles.

[0035] Example: If the first entry time point when the first AGV intelligent yarn transport vehicle enters the shared path section is 10:05 and the first exit time point when the first AGV intelligent yarn transport vehicle exits the shared path section is 10:10, the second entry time point when the second AGV intelligent yarn transport vehicle enters the shared path section is 10:06, and the second exit time point when the second AGV intelligent yarn transport vehicle exits the shared path section is 10:09, then the first entry time point is earlier than the second entry time point, the first exit time point is later than the second exit time point, the first AGV intelligent yarn transport vehicle enters the shared path section earlier but exits later, the second AGV intelligent yarn transport vehicle will be blocked by the first AGV intelligent yarn transport vehicle, and there must be a contact situation between the first AGV intelligent yarn transport vehicle and the second AGV intelligent yarn transport vehicle in the shared path section, so a same-direction path conflict will occur between the two AGV intelligent yarn transport vehicles.

[0036] It should be understood that the setting of the first AGV intelligent yarn transport vehicle and the second AGV intelligent yarn transport vehicle in this embodiment is not specifically referred to, but generally defines the two AGV intelligent yarn transport vehicles as the first AGV intelligent yarn transport vehicle and the second AGV intelligent yarn transport vehicle respectively. Therefore, when comparing above, it is necessary to compare whether the driving time period of one of the AGV intelligent yarn transport vehicles in the shared path section is within the time range of the driving time period of the other AGV intelligent yarn transport vehicle in the shared path section.

[0037] If these two AGV intelligent yarn carriers are moving towards each other, then these two AGV intelligent yarn carriers enter the shared path segment from different endpoints and exit the shared path segment from different endpoints. For example, one of the AGV intelligent yarn carriers is from entering the shared path segment and from exiting the shared path segment; the other AGV intelligent yarn carrier is from entering the shared path segment and from exiting the shared path segment.

[0038] If these two AGV intelligent yarn carriers are moving towards each other, then if the time point when one of the two AGV intelligent yarn carriers enters the shared path segment is within the driving time period of the other AGV intelligent yarn carrier in the shared path segment, then these two AGV intelligent yarn carriers will have an oncoming path conflict. Specifically: if the entry time point when the first AGV intelligent yarn carrier enters the shared path segment is later than the entry time point when the second AGV intelligent yarn carrier enters the shared path segment and earlier than the exit time point when the second AGV intelligent yarn carrier exits the shared path segment, that is, when the first AGV intelligent yarn carrier enters the shared path segment, the second AGV intelligent yarn carrier is driving in the shared path segment, then the first AGV intelligent yarn carrier and the second AGV intelligent yarn carrier will surely meet in the shared path segment, then these two AGV intelligent yarn carriers will have an oncoming path conflict.

[0039] For example: if the first entry time point when the first AGV intelligent yarn carrier enters the shared path segment is 10:05, the second entry time point when the second AGV intelligent yarn carrier enters the shared path segment is 10:04, and the second exit time point when the second AGV intelligent yarn carrier exits the shared path segment is 10:09, these two AGV intelligent yarn carriers will have an oncoming path conflict.

[0040] It should be understood that when making the above comparisons, it is necessary to compare whether the time point when one of the AGV intelligent yarn carriers enters the shared path segment is within the driving time period of the other AGV intelligent yarn carrier in the shared path segment, so as to determine whether these two AGV intelligent yarn carriers will have an oncoming path conflict.

[0041] Step S3: If a path conflict occurs, determine the waiting cost generated by any two AGV intelligent yarn carriers waiting to yield, and the detour cost generated by detouring.

[0042] If the above step S2 determines that there may be a path conflict phenomenon, then it is necessary to perform a scheme scheduling in advance to cope with various possible path conflict phenomena.

[0043] Since the ultimate goal of path scheduling is to achieve fast and efficient transportation efficiency, after a path conflict occurs, the AGV intelligent yarn carrier can perform scheduling operations such as waiting to yield or detouring to reduce the impact of the path conflict on transportation efficiency. By quantifying the transportation efficiency of each scheduling plan, the scheduling plan for resolving the path conflict is determined through comparison. Correspondingly, in the case where a path conflict is determined to occur, it is necessary to separately determine the waiting cost generated by the waiting to yield of these two AGV intelligent yarn carriers and the detouring cost generated by detouring.

[0044] Therefore, regarding the waiting cost generated by waiting to yield, it is necessary to determine the waiting cost separately based on the occurrence of a same-direction path conflict and an oncoming path conflict.

[0045] If a same-direction path conflict occurs, the AGV intelligent yarn carrier that enters the shared path segment earlier will block the AGV intelligent yarn carrier that enters the shared path segment later, thus affecting the transportation efficiency of the AGV intelligent yarn carrier that enters the shared path segment later. Therefore, if a same-direction path conflict occurs, only the scheduling plan of the AGV intelligent yarn carrier that enters the shared path segment later (i.e., the AGV intelligent yarn carrier that exits the shared path segment earlier) is considered.

[0046] Since the AGV intelligent yarn carrier that enters the shared path segment later will exit the shared path segment earlier, then, the minimum waiting cost is for the two AGV intelligent yarn carriers to exit the shared path segment simultaneously. Then, the waiting cost of the AGV intelligent yarn carrier that enters the shared path segment later is equal to: the duration between the exit time point when the AGV intelligent yarn carrier that enters the shared path segment later exits the shared path segment and the exit time point when the other AGV intelligent yarn carrier (i.e., the AGV intelligent yarn carrier that exits the shared path segment later) exits the shared path segment.

[0047] For example: If the first entry time point of the first AGV intelligent yarn carrier into the shared path segment is 10:05, the first exit time point of the first AGV intelligent yarn carrier from the shared path segment is 10:10, the second entry time point of the second AGV intelligent yarn carrier into the shared path segment is 10:06, and the second exit time point of the second AGV intelligent yarn carrier from the shared path segment is 10:09, then the waiting cost of the second AGV intelligent yarn carrier is equal to: the duration between 10:10 and 10:09, that is, 1 minute.

[0048] If there is a conflict in the opposite path, any one of the two AGV intelligent yarn carriers can be the AGV intelligent yarn carrier to give way, and give way to the other AGV intelligent yarn carrier. The AGV intelligent yarn carrier to give way needs to temporarily avoid first, and then continue to drive along the original route after giving way to the other AGV intelligent yarn carrier. Then, the giving-way process is as follows: The AGV intelligent yarn carrier to give way gives way a body position of one vehicle length, and then allows the other AGV intelligent yarn carrier to continue driving. After the other AGV intelligent yarn carrier drives a body position of two vehicle lengths, the AGV intelligent yarn carrier to give way returns to the original position. Then, the time consumed in the giving-way process is the waiting cost of the AGV intelligent yarn carrier to give way. The waiting cost of the AGV intelligent yarn carrier to give way includes: the time required for the AGV intelligent yarn carrier to give way from the original route, the time required for the other AGV intelligent yarn carrier to pass through the giving-way section, and the time required for the AGV intelligent yarn carrier to give way to return to the original route. The waiting cost of the AGV intelligent yarn carrier to give way is equal to the sum of the time required for the AGV intelligent yarn carrier to give way from the original route, the time required for the other AGV intelligent yarn carrier to pass through the giving-way section among any two AGV intelligent yarn carriers, and the time required for the AGV intelligent yarn carrier to give way to return to the original route.

[0049] Among them, the time required for the AGV intelligent yarn carrier to give way from the original route is equal to the ratio of the vehicle length of the AGV intelligent yarn carrier to give way to the vehicle speed of the AGV intelligent yarn carrier to give way. The time required for the other AGV intelligent yarn carrier to pass through the giving-way section is equal to the ratio of twice the vehicle length of the other AGV intelligent yarn carrier to the vehicle speed of the other AGV intelligent yarn carrier. The time required for the AGV intelligent yarn carrier to give way to return to the original route is equal to the ratio of the vehicle length of the AGV intelligent yarn carrier to give way to the vehicle speed of the AGV intelligent yarn carrier to give way.

[0050] Regardless of whether there is a conflict in the same-direction or opposite-path, a detour plan can be selected to directly detour to the final target position, and a certain detour cost will be generated after the detour.

[0051] In an exemplary embodiment, as Figure 2 shown, the following gives a specific acquisition process of the detour cost: Step S3-1: Obtain at least one re-planned shortest path with the path conflict point as the starting point and the final target position as the ending point for the AGV intelligent yarn carrier to be detoured.

[0052] For ease of explanation, it is assumed that the AGV intelligent yarn transport vehicle to be bypassed is the AGV intelligent yarn transport vehicle that needs to bypass among these two AGV intelligent yarn transport vehicles. Among them, for the same-direction path conflict, the AGV intelligent yarn transport vehicle to be bypassed is the AGV intelligent yarn transport vehicle that enters the shared path segment later; for the opposite-direction path conflict, the AGV intelligent yarn transport vehicle to be bypassed can be any one of the two AGV intelligent yarn transport vehicles, and it is necessary to analyze with one of the AGV intelligent yarn transport vehicles as the AGV intelligent yarn transport vehicle to be bypassed respectively.

[0053] First, it is necessary to confirm the path conflict point, which is the starting point where the AGV intelligent yarn transport vehicle to be bypassed starts to bypass. In an exemplary embodiment, the path conflict point is the entry point where the AGV intelligent yarn transport vehicle to be bypassed enters the shared path segment, that is, among the two endpoints of the shared path segment, the endpoint where the AGV intelligent yarn transport vehicle to be bypassed enters.

[0054] Obtain at least one re-planned shortest path with the path conflict point as the starting point and the final target position as the ending point for the AGV intelligent yarn transport vehicle to be bypassed. In an exemplary embodiment, the depth-first search algorithm is used to perform path search with the path conflict point as the starting point and the final target position as the ending point to obtain at least one path, which is defined as the re-planned shortest path. Further, when performing path search, the position of the other AGV intelligent yarn transport vehicle when the AGV intelligent yarn transport vehicle to be bypassed travels to the path conflict point can also be used as an obstacle area.

[0055] Step S3-2: Based on the difference between the remaining transport path in the initial transport path and the re-planned shortest path, and combined with the speed of the AGV intelligent yarn transport vehicle to be bypassed, obtain the additional time required for bypassing corresponding to the re-planned shortest path.

[0056] Since the AGV intelligent yarn transport vehicle to be bypassed travels to the path conflict point for bypassing, then, with the path conflict point as the dividing point, the initial transport path is divided into the traveled path and the remaining transport path in the initial transport path.

[0057] For the AGV intelligent yarn transport vehicle to be bypassed, it is necessary to compare the difference between the remaining transport path in the initial transport path and the re-planned shortest path. Since the re-planned shortest path is the path planned for bypassing, the position of the other AGV intelligent yarn transport vehicle will be used as an obstacle area and needs to be bypassed, while the initial transport path is the initially planned shortest path, then the path length of the re-planned shortest path must be greater than or equal to the length of the remaining transport path in the initial transport path. Correspondingly, according to the amount by which the path length of the re-planned shortest path exceeds the length of the remaining transport path, and combined with the vehicle speed of the AGV intelligent yarn transport vehicle to be bypassed, obtain the additional time required for bypassing corresponding to each re-planned shortest path.

[0058] The calculation formula for the additional time required for detouring corresponding to the re-planned shortest path is as follows: ; Wherein, represents the additional time required for detouring the th re-planned shortest path, represents the path length of the th re-planned shortest path, represents the path length of the remaining transport path in the initial transport path of the AGV intelligent yarn transport vehicle to be detoured, represents the vehicle speed of the AGV intelligent yarn transport vehicle to be detoured, and b represents the AGV intelligent yarn transport vehicle to be detoured.

[0059] Step S3-3: Based on the additional time required for detouring corresponding to each re-planned shortest path, obtain the final detouring cost.

[0060] According to the additional time required for detouring corresponding to each re-planned shortest path, obtain the final detouring cost. The selection principle of the final detouring cost is the minimum cost. Then, the minimum value can be directly selected from the additional time required for detouring corresponding to each re-planned shortest path as the final detouring cost. Since in addition to the influence of the path length, the difficulty of re-planning the shortest path also determines the detouring cost to a certain extent, then, as a more optimal embodiment, as Figure 3 shown, the following gives a specific obtaining process of the final detouring cost: Step S3-3-1: Obtain the conflict occurrence rate of each shared path segment in the re-planned shortest path, so as to obtain the first conflict occurrence rate comprehensive feature of the re-planned shortest path.

[0061] For any re-planned shortest path, by analyzing it with the initial transport paths of other AGV intelligent yarn transport vehicles, each shared path segment in the re-planned shortest path is obtained, and thus the conflict occurrence rate of each shared path segment is obtained. Among them, the conflict occurrence rate is used to characterize the possibility of path conflict on the shared path segment.

[0062] In an exemplary embodiment, for any shared path segment. Obtain the number of overlapping transport paths on the shared path segment. Here, the overlapping transport paths on the shared path segment include the re-planned shortest path and other respective initial transport paths. It should be understood that the other respective initial transport paths do not include the initial transport path replaced by the re-planned shortest path.

[0063] Obtain the length of the shared path segment, and the number of obstacles within the preset range of the shared path segment. The specific obtaining method of the number of obstacles within the preset range of the shared path segment is as described above.

[0064] The conflict incidence rate is obtained from the number of overlapping transportation paths on the shared path segment, the length of the shared path segment, and the number of obstacles within the preset range of the shared path segment.

[0065] Obtain the density of AGV intelligent yarn carriers. The density of AGV intelligent yarn carriers is the ratio of the number of overlapping transportation paths on the shared path segment to the length of the shared path segment. The higher the density of AGV intelligent yarn carriers, the higher the possibility of path conflicts occurring on the shared path segment, and the higher the conflict incidence rate. Therefore, the conflict incidence rate is proportional to the density of AGV intelligent yarn carriers. The more the number of obstacles within the preset range of the shared path segment, the higher the possibility of path conflicts occurring during detouring, and the higher the conflict incidence rate. Therefore, the conflict incidence rate is proportional to the number of obstacles within the preset range of the shared path segment.

[0066] In an exemplary embodiment, a specific quantification method for the conflict incidence rate is given as follows: ; where represents the conflict incidence rate of the shared path segment, represents the number of overlapping transportation paths on the shared path segment, represents the length of the shared path segment, represents the density of AGV intelligent yarn carriers, represents the number of obstacles within the preset range of the shared path segment.

[0067] represents normalization of Here, the normalization method can be: sigmoid function.

[0068] For any re-planned shortest path, obtain the conflict incidence rates of each shared path segment in the re-planned shortest path. Thus, according to the conflict incidence rates of each shared path segment in the re-planned shortest path, obtain the first conflict incidence rate comprehensive feature of the re-planned shortest path. In an exemplary embodiment, the first conflict incidence rate comprehensive feature is equal to the sum of the conflict incidence rates of each shared path segment.

[0069] Step S3-3-2: Obtain the conflict incidence rates of each shared path segment in the remaining transportation paths in the initial transportation path, and thus obtain the second conflict incidence rate comprehensive feature of the remaining transportation paths.

[0070] Obtain each common path segment in the remaining transport paths of the initial transport path corresponding to the re-planned shortest path, and use the calculation method of the conflict incidence rate in step S3-3-1 to obtain the conflict incidence rate of each common path segment in the remaining transport path, so as to obtain the second conflict incidence rate comprehensive feature of the remaining transport path. In an exemplary embodiment, the second conflict incidence rate comprehensive feature is equal to the sum of the conflict incidence rates of each common path segment in the remaining transport path.

[0071] Step S3-3-3: Obtain the path detour cost corresponding to each re-planned shortest path according to the additional time required for detour, the first conflict incidence rate comprehensive feature, and the second conflict incidence rate comprehensive feature corresponding to each re-planned shortest path.

[0072] The first conflict incidence rate comprehensive feature represents the conflict incidence rate corresponding to the re-planned shortest path, and the second conflict incidence rate comprehensive feature represents the conflict incidence rate corresponding to the original transport path. Then, if the first conflict incidence rate comprehensive feature is greater than the second conflict incidence rate comprehensive feature, it means that the cost of path detour will increase compared with the original transport path, and the greater the first conflict incidence rate comprehensive feature is greater than the second conflict incidence rate comprehensive feature, the greater the increase in the cost of path detour; if the first conflict incidence rate comprehensive feature is less than the second conflict incidence rate comprehensive feature, it means that the cost of path detour will decrease compared with the original transport path, and the smaller the first conflict incidence rate comprehensive feature is less than the second conflict incidence rate comprehensive feature, the greater the decrease in the cost of path detour.

[0073] Therefore, for any re-planned shortest path, obtain the detour difficulty coefficient of the re-planned shortest path. The detour difficulty coefficient is equal to the ratio of the first conflict incidence rate comprehensive feature to the second conflict incidence rate comprehensive feature. Then, if the first conflict incidence rate comprehensive feature is greater than the second conflict incidence rate comprehensive feature, the detour difficulty coefficient is greater than 1; if the first conflict incidence rate comprehensive feature is less than the second conflict incidence rate comprehensive feature, the detour difficulty coefficient is less than 1; if the first conflict incidence rate comprehensive feature is equal to the second conflict incidence rate comprehensive feature, the detour difficulty coefficient is equal to 1.

[0074] Therefore, the detour difficulty coefficient represents the difficulty level of the detour path relative to the original path. The smaller this value is, the easier it is to pass through the detour and the lower the detour cost. On the contrary, the larger this value is, the more difficult it is to pass through the detour and the higher the detour cost.

[0075] Calculate the product of the additional time required for detour and the detour difficulty coefficient corresponding to the re-planned shortest path. The result obtained is the path detour cost corresponding to the re-planned shortest path. The greater the detour difficulty coefficient, the greater the increase in the additional time required for detour, and the higher the resulting path detour cost.

[0076] In the above manner, the path detour costs of each re-planned shortest path of the AGV intelligent yarn transport vehicle to be detoured are obtained.

[0077] It should be understood that if there is no common path segment in the re-planned shortest path or the remaining transport path in the corresponding initial transport path, the processes of steps S3-3-1 to S3-3-3 are not carried out, and the obtained additional time required for detour is directly used as the corresponding path detour cost.

[0078] Step S3-3-4: Based on the path detour costs corresponding to each re-planned shortest path, the final detour cost is obtained.

[0079] Based on the path detour costs of each re-planned shortest path of the AGV intelligent yarn transport vehicle to be detoured, the final detour cost of the AGV intelligent yarn transport vehicle to be detoured is obtained. Since the principle for obtaining the scheduling plan is the minimum cost, therefore, the minimum value among the path detour costs of each re-planned shortest path of the AGV intelligent yarn transport vehicle to be detoured is used as the final detour cost of the AGV intelligent yarn transport vehicle to be detoured.

[0080] Step S4: Select the minimum cost between the waiting cost and the detour cost, and determine the scheduling plan corresponding to the minimum cost.

[0081] For the same-direction path conflict, select the minimum value from the waiting cost and the final detour cost of the AGV intelligent yarn transport vehicle to be detoured, and use the scheduling plan corresponding to the obtained minimum value as the final scheduling plan of the AGV intelligent yarn transport vehicle to be detoured. For example: If the waiting cost is greater than the final detour cost, indicating that the detour cost is lower, then select the re-planned shortest path corresponding to the final detour cost as the final scheduling plan of the AGV intelligent yarn transport vehicle to be detoured, and then control the AGV intelligent yarn transport vehicle to be detoured to travel according to this final scheduling plan; if the waiting cost is less than the final detour cost, indicating that the waiting cost is lower, then the cost of waiting for another AGV intelligent yarn transport vehicle to yield to it is lower, then select the scheduling method corresponding to the waiting cost (i.e., waiting to yield) as the final scheduling plan of the AGV intelligent yarn transport vehicle to be detoured, and then control the AGV intelligent yarn transport vehicle to be detoured with this final scheduling plan.

[0082] For head-on path conflicts, first take one of the AGV intelligent yarn carriers as the AGV intelligent yarn carrier to be bypassed, obtain the waiting cost and the final bypass cost of this AGV intelligent yarn carrier to be bypassed, and then take the other AGV intelligent yarn carrier as the AGV intelligent yarn carrier to be bypassed to obtain the waiting cost and the final bypass cost. Therefore, two waiting costs and two final bypass costs are finally obtained. Since the scheduling of these two AGV intelligent yarn carriers needs to be considered simultaneously to achieve the optimal solution for both sides, the minimum cost among these four costs is selected, and the AGV intelligent yarn carrier corresponding to this minimum cost is used as the final AGV intelligent yarn carrier to be bypassed, as well as the final scheduling plan for the final AGV intelligent yarn carrier to be bypassed. Furthermore, the AGV intelligent yarn carrier to be bypassed is controlled according to this final scheduling plan.

[0083] The above analysis is based on any two AGV intelligent yarn carriers. For other AGV intelligent yarn carriers in the application scenario, the final scheduling plan for each AGV intelligent yarn carrier is determined according to this analysis process to achieve the transportation path planning of the AGV intelligent yarn carrier.

[0084] This embodiment also provides an AGV intelligent yarn carrier transportation path planning system, including: a memory and a processor; the memory is connected to the processor, and the memory is used to store program instructions; the processor is used to implement the steps in the above AGV intelligent yarn carrier transportation path planning method embodiment when the program instructions are executed.

[0085] In an exemplary embodiment, the present invention provides a computer-readable storage medium storing a computer program, which implements the steps in the above AGV intelligent yarn carrier transportation path planning method embodiment when executed by a processor.

[0086] It should be noted that: the above sequence of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0087] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other, and the key points of each embodiment are the differences from other embodiments.

Claims

1. A method for planning the transport path of an AGV intelligent yarn transport vehicle, characterized in that: include: Determine the common path segment based on the initial transport path of each AGV intelligent yarn transport vehicle; According to the relationship between the time taken by any two AGV intelligent yarn transport vehicles to reach the shared path segment, determine whether any two AGV intelligent yarn transport vehicles will have a path conflict; If a path conflict occurs, determine the waiting cost incurred by any two AGVs waiting to give way, as well as the detour cost incurred by the detour; The minimum cost between the waiting cost and the detour cost is selected, and a scheduling scheme corresponding to the minimum cost is determined.

2. The AGV intelligent yarn transport vehicle transportation path planning method according to claim 1 is characterized in that: The path conflict includes a same-direction path conflict and an opposite-direction path conflict.

3. The AGV intelligent yarn transport vehicle transportation path planning method as described in claim 2 is characterized in that: The step of determining whether any two AGV intelligent yarn transport vehicles will have a path conflict includes: If any two AGVs are traveling in the same direction, then if the driving time period of one of the two AGVs in the shared path segment includes the driving time period of the other AGV in the shared path segment, then any two AGVs will have a same-direction path conflict; If any two AGV intelligent yarn transport vehicles are traveling in opposite directions, then if the entry time point of one of the two AGV intelligent yarn transport vehicles into the common path segment is within the driving time period of the other AGV intelligent yarn transport vehicle in the common path segment, then any two AGV intelligent yarn transport vehicles will have a conflict of opposite paths.

4. The AGV intelligent yarn transport vehicle transportation path planning method as described in claim 2 is characterized in that: If a same-direction path conflict occurs, the process of obtaining the waiting cost includes: The waiting cost of the AGV intelligent yarn transport vehicle that enters the shared path segment late is equal to: the duration between the exit time point of the AGV intelligent yarn transport vehicle that enters the shared path segment late and the exit time point of another AGV intelligent yarn transport vehicle that exits the shared path segment.

5. The AGV intelligent yarn transport vehicle transportation path planning method as described in claim 2 is characterized in that: If a conflict of opposite paths occurs, the process of obtaining the waiting cost includes: The waiting cost of the AGV intelligent yarn transport vehicle to be given way is equal to: the sum of the time required for the AGV intelligent yarn transport vehicle to be given way from the original route, the time required for the other AGV intelligent yarn transport vehicle among any two AGV intelligent yarn transport vehicles to pass through the giving way section, and the time required for the AGV intelligent yarn transport vehicle to be given way to return to the original route; the AGV intelligent yarn transport vehicle to be given way is any one of the two AGV intelligent yarn transport vehicles.

6. The method for planning the transport path of an AGV intelligent yarn transport vehicle as claimed in claim 5 is characterized in that: The time required for the AGV intelligent yarn transport vehicle to give way from the original route and the time required for the AGV intelligent yarn transport vehicle to give way to return to the original route are both equal to the ratio of the length of the AGV intelligent yarn transport vehicle to give way to the speed of the AGV intelligent yarn transport vehicle to give way; the time required for another AGV intelligent yarn transport vehicle to pass the yielding section is equal to the ratio of twice the length of the other AGV intelligent yarn transport vehicle to the speed of the other AGV intelligent yarn transport vehicle.

7. The AGV intelligent yarn transport vehicle transportation path planning method as claimed in claim 2 is characterized in that: The process of obtaining the detour cost includes: Obtain at least one re-planned shortest path of the AGV intelligent yarn transport vehicle to be bypassed, starting from the path conflict point and ending at the final target position; the AGV intelligent yarn transport vehicle to be bypassed is the AGV intelligent yarn transport vehicle that needs to be bypassed among any two AGV intelligent yarn transport vehicles; Based on the difference between the remaining transport path in the initial transport path and the re-planned shortest path, combined with the speed of the AGV intelligent yarn transport vehicle to be detoured, the additional time required for detouring corresponding to the re-planned shortest path is obtained; The final detour cost is obtained based on the additional time required for the detour corresponding to each re-planned shortest path.

8. The method for planning the transport path of an AGV intelligent yarn transport vehicle as claimed in claim 7 is characterized in that: The process of obtaining the final detour cost includes: Obtaining the conflict occurrence rate of each common path segment in the re-planned shortest path, thereby obtaining a first conflict occurrence rate comprehensive feature of the re-planned shortest path; the conflict occurrence rate is used to characterize the possibility of path conflict on the common path segment; Obtaining the conflict occurrence rate of each common path segment in the remaining transportation paths in the initial transportation path, thereby obtaining a second conflict occurrence rate comprehensive feature of the remaining transportation paths; Calculate the product of the additional time required for detour and the detour difficulty coefficient corresponding to each re-planned shortest path to obtain the path detour cost corresponding to each re-planned shortest path; the detour difficulty coefficient is equal to the ratio of the first conflict occurrence rate comprehensive feature to the second conflict occurrence rate comprehensive feature; Based on the path detour costs corresponding to each re-planned shortest path, a final detour cost is obtained.

9. The method for planning the transport path of an AGV intelligent yarn transport vehicle as claimed in claim 8, characterized in that: The process of obtaining the conflict occurrence rate includes: The conflict occurrence rate is obtained by the number of overlapping transport paths on the common path segment, the length of the common path segment and the number of obstacles within the preset range of the common path segment; the conflict occurrence rate is proportional to the density of AGV intelligent yarn transport vehicles and the number of obstacles within the preset range of the common path segment, and the density of AGV intelligent yarn transport vehicles is the ratio of the number of overlapping transport paths on the common path segment to the length of the common path segment.

10. An AGV intelligent yarn transport vehicle transportation path planning system, characterized in that it includes: Memory and processor; The memory is connected to the processor; The memory is used to store program instructions; The processor is used to implement the AGV intelligent yarn transport vehicle transportation path planning method described in any one of claims 1-9 when the program instructions are executed.

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