CN110231040B - Path planning method and device - Google Patents
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Abstract
The invention discloses a path planning method and a path planning device, and relates to the technical field of computers. One embodiment of the method comprises: determining whether a congestion area exists; if yes, increasing the path cost of the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area; and planning the path based on the path cost of the added directed arc. According to the implementation mode, the route cost of the boundary node of the congestion area is changed, so that affected vehicles can re-plan the route, follow-up vehicles going to the congestion area are dispatched to the idle packet collection waiting points of the non-congestion area to wait, when the congestion area is not congested, the vehicles at the packet collection waiting points are rescheduled to go to the original destination, congestion caused by concentrated outburst of the package amount of a part of bag falling openings of the sorting area can be prevented, when the congestion area exists, new vehicles can be prevented from entering the congestion area, the congestion degree of the congestion area is quickened to be relieved, manual intervention is greatly reduced, and the system efficiency is improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for path planning.
Background
The sorting robot system is an unmanned sorting system with a plurality of robot vehicles running in parallel and is used for sorting small packages. The ground in robot letter sorting region can paste the two-dimensional code, links to each other through driving auxiliary line between the adjacent two-dimensional code for the direction of letter sorting robot. The robot vehicle can travel on a grid road network, and nodes on the grid correspond to two-dimensional codes on the ground one by one. In the robot sorting area, sorting robots can run in parallel respectively, run in a mode of scanning ground two-dimensional codes, and are used for sorting packages according to destinations.
The operation of the vehicle depends on a scheduling system to issue tasks, each task comprises a starting point, an end point and a path connecting the starting point and the end point, the starting point is the current position of the vehicle, the end point is a node which the vehicle needs to reach in the task, and the service logics such as sorting, temporary storage, waiting, queuing, charging and the like are completed. When a vehicle executes a moving task, the next section of the vehicle is locked by software locking points according to the planned path of the vehicle, the vehicle can only use the locked nodes and the paths among the locked nodes, and meanwhile, the vehicle locking points also need to meet a series of conditions: when the vehicle is locked, the vehicle can be dynamically locked/unlocked, the node locked by the vehicle cannot be used by other vehicles, and the vehicle locking point has an upper limit in number but cannot lock a turning node in a planned path of the vehicle. Through the vehicle locking point, the condition that a plurality of vehicles use the same node at the same time to cause collision, side collision or rear-end collision can be prevented.
Because the number of vehicles in the sorting robot system is generally larger than that of the vehicles carried by other carrying robot vehicle systems under the condition of the same area, the density of the vehicles in the sorting robot system is higher, and congestion is more likely to occur. How to reduce vehicle congestion through a path planning method is a main research problem of a sorting robot scheduling system.
For a sorted vehicle task scheduling system, vehicle functions are divided into sorting, return queuing after sorting, and charging. When the map is laid out, the crossing of the driving paths of the vehicles with three types of tasks is avoided as much as possible, and the map is divided into three functional areas, namely a sorting area, a queuing area and a charging area. The queuing area enables only one path of a single queuing position to reach by setting the path direction, so that vehicle collision can be avoided, and the path can be planned again. And the charging area is provided with two bidirectional trunk roads for charging and returning vehicles in the queuing area. The sorting zone is the largest in area and there are typically tens of alternative paths to the same destination.
In the prior art, thermodynamic diagrams can be introduced when a vehicle plans a path to change the path cost so as to relieve congestion.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
in the prior art, too many vehicles are prevented from using the same path by changing the path cost, closed loop formation is reduced, and the problem of congestion is solved to a certain extent. However, if there is a concentrated burst of packages at a certain drop-off pocket in the sorting area within a short period of time, the area still collects an excessive number of vehicles, resulting in congestion, since the destination cannot be changed.
Disclosure of Invention
In view of this, an embodiment of the present invention provides a path planning method, where a path cost of a boundary node of a congestion area is changed, so that an affected vehicle replans a path, and schedules a vehicle that subsequently travels to the congestion area to a packet aggregation waiting point of a non-congestion area to wait, and when the congestion area is no longer congested, the vehicle at the packet aggregation waiting point is rescheduled to travel to an original destination, so that congestion caused by concentrated outbreak of a part of packet dropping amount at a bag drop opening in a sorting area can be prevented, and when the congestion area exists, a new vehicle can be prevented from joining the congestion area, thereby accelerating to alleviate the congestion degree of the congestion area, thereby greatly reducing manual intervention and improving system efficiency.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a path planning method including: determining whether a congestion area exists; if yes, increasing the path cost of the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area; and planning the path based on the path cost of the added directed arc.
Optionally, the determining whether there is a congestion area comprises: dividing the sorting area into a plurality of sorting subareas according to a preset rule; for each sorting partition, judging whether the number of vehicles in the sorting partition is larger than the critical congestion vehicle number; and if so, taking the sorting subarea as a congestion area.
Optionally, the determining whether there is a congestion area comprises: determining whether a closed loop exists; if yes, determining nodes positioned on a closed loop to form a closed loop node set; determining a minimum value x of a node abscissa in a closed-loop node set min And a maximum value x max Minimum value y of the ordinate min And a maximum value y max (ii) a Will be located in x e [ x ∈ [ ] min -α,x max +α]，y∈[y min -α,y max +α]The area in the range is regarded as a congestion area, where α is an integer greater than zero.
Optionally, the determining whether closed loop is present comprises: when a first vehicle stops at the last node of a lock point due to unsuccessful lock point, searching a next node on a path planned by the first vehicle, and determining whether a second vehicle waits at the next node on the path planned by the first vehicle; if so, searching a next node on the path planned by the second vehicle, and determining whether a third vehicle waits at the next node on the path planned by the second vehicle; and repeating the steps, and if the found next node is the last node of the first vehicle stopped at the lock point due to unsuccessful lock point, determining that a closed loop exists.
Optionally, the incremental path cost of the directed arc with the starting point located outside the congestion area and the ending point located inside the congestion area is: β (x-p φ), where β represents a unit vehicle congestion cost, β > 1, x represents the number of vehicles in the congestion area, and p φ represents the critical congestion number of vehicles.
Optionally, the incremental path cost of the directed arc with the starting point located outside the congestion area and the ending point located inside the congestion area is: max [ c ] min ，β(x-pφ)]Wherein, c min To minimize congestion cost, c min Is a constant greater than 0, beta represents the unit vehicle congestion cost, beta > 1, x represents the number of vehicles in the congestion area, and p phi represents the critical congested vehicle number.
Optionally, the planning a path based on the added directed arc includes: traversing all vehicles which are not in the congestion area at present, and determining vehicles which comprise nodes in the congestion area and vehicles of which the destinations are in the congestion area in the path to be completed; replanning the path of the vehicle containing the nodes in the congestion area in the path to be completed based on a shortest path algorithm; dispatching vehicles with destinations located in congested areas to idle packet collection waiting points in non-congested areas; and for the vehicles on the closed loop, removing other nodes on the closed loop except the current position of the vehicle to generate a new map, and planning a path based on the new map.
Optionally, after dispatching the vehicle with the destination located in the congestion area to the idle packet collection waiting point in the non-congestion area, the method further comprises: and when the congestion area is determined to be no longer congested, reducing the path cost increased by the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area to zero, and scheduling the vehicle located at the packet collection waiting point to go to the original destination.
To achieve the above object, according to another aspect of the embodiments of the present invention, there is provided a path planning apparatus, including: a congestion determination module for determining whether a congestion area exists; a cost increase module to increase a path cost for a directed arc having a starting point located outside the congestion area and an ending point located within the congestion area; and the path planning module is used for planning a path based on the increased path cost of the directed arc.
Optionally, the congestion determination module is further configured to: dividing the sorting area into a plurality of sorting subareas according to a preset rule; for each sorting partition, judging whether the number of vehicles in the sorting partition is larger than the critical congestion vehicle number; and if so, taking the sorting subarea as a congestion area.
Optionally, the congestion determination module is further configured to: determining whether a closed loop exists; if yes, determining nodes positioned on a closed loop to form a closed loop node set; determining a minimum value x of a node abscissa in a closed-loop node set min And a maximum value x max Minimum value y of ordinate min And a maximum value y max (ii) a Will be located in x e [ x ∈ [ ] min -α,x max +α]，y∈[y min -α,y mαx +α]The area in the range is regarded as a congestion area, where α is an integer greater than zero.
Optionally, the congestion determination module is further configured to: when a first vehicle stops at the last node of a lock point due to unsuccessful lock point, searching a next node on a path planned by the first vehicle, and determining whether a second vehicle waits at the next node on the path planned by the first vehicle; if so, searching a next node on the path planned by the second vehicle, and determining whether a third vehicle waits at the next node on the path planned by the second vehicle; and repeating the steps, and if the found next node is the last node of the first vehicle stopped at the lock point due to unsuccessful lock point, determining that a closed loop exists.
Optionally, the cost of the path added by the directed arc with the starting point located outside the congestion area and the ending point located inside the congestion area is: β (x-p φ), where β represents a unit vehicle congestion cost, β > 1, x represents the number of vehicles in the congestion area, and p φ represents the critical congestion number of vehicles.
Optionally, the incremental path cost of the directed arc with the starting point located outside the congestion area and the ending point located inside the congestion area is: max [ c ] min ，β(x-pφ)]Wherein c is min To minimize congestion cost, c min Is a constant greater than 0, beta represents the unit vehicle congestion cost, beta > 1, x represents the number of vehicles in the congestion area, and p phi represents the critical congested vehicle number.
Optionally, the path planning module is further configured to: traversing all vehicles which are not in the congestion area at present, and determining the vehicles of the nodes in the congestion area and the vehicles of which the destinations are in the congestion area in the path to be completed; replanning the path of the vehicle containing the nodes in the congestion area in the path to be completed based on a shortest path algorithm; the method comprises the steps that vehicles with destinations located in congested areas are dispatched to idle packet collection waiting points in non-congested areas; and for the vehicles on the closed loop, removing other nodes on the closed loop except the current position of the vehicle to generate a new map, and planning a path based on the new map.
Optionally, the path planning module is further configured to: and when the congestion area is determined to be no longer congested, reducing the path cost increased by the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area to zero, and scheduling the vehicle located at the packet collection waiting point to go to the original destination.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided an electronic apparatus including: one or more processors; the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors realize the path planning method of the embodiment of the invention.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a computer readable medium on which a computer program is stored, the program, when executed by a processor, implementing a path planning method of an embodiment of the present invention.
One embodiment of the above invention has the following advantages or benefits: because the determination of whether a congestion area exists is adopted; if yes, increasing the path cost of the directed arcs of which the starting points are located outside the congestion area and the end points are located in the congestion area; the technical means for replanning the route based on the increased directed arc route cost can prevent congestion caused by concentrated outbreak of a part of bag falling opening wrapping amount in the sorting area, and can prevent new vehicles from entering the congestion area when the congestion area exists, so that the congestion degree of the congestion area is quickened to be relieved, thereby greatly reducing manual intervention and improving the system efficiency.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic diagram of a main flow of a path planning method according to an embodiment of the present invention;
fig. 2 is a schematic layout diagram of a sorting area in the path planning method according to the embodiment of the present invention;
fig. 3 is a schematic diagram of a congestion area determined based on a closed loop in a path planning method according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a main flow of a path planning method according to another embodiment of the present invention;
fig. 5 is a schematic diagram of a main flow of a path planning method according to yet another embodiment of the present invention;
FIG. 6 is a schematic diagram of the main modules of an apparatus for path planning according to an embodiment of the present invention;
FIG. 7 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 8 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a main flow of a path planning method according to an embodiment of the present invention. As shown in fig. 1, the method includes:
step S101: determining whether a congestion area exists;
step S102: if yes, increasing the path cost of the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area;
step S103: and planning the path based on the path cost of the added directed arc.
In this embodiment, the sorting area may be configured with bag dropping openings and bag collecting waiting points. Wherein, every bag mouth that falls corresponds a purpose website. The number of the bag openings is adapted to the number of the destination stations corresponding to the sorting center. If the wrapping amount of the destination station is large, the destination station can be corresponding to a plurality of bag falling openings so as to prevent the excessive wrapping amount of a single bag falling opening. And, the destination stations with large parcel volume can be distributed in the sorting area as far as possible. And the bag collecting waiting point is used for temporarily parking the vehicle when the bag falling opening is closed. Once a bag falling port is closed, the vehicle system broadcasts that all vehicles going to the bag falling port travel to the last point of the current locking point and return to the last point of the current locking point of the scheduling system (namely the current position of the vehicle), and the scheduling system distributes a path to the nearest bag collecting waiting point to each vehicle and occupies the bag collecting waiting point. And when the bag falling opening is re-opened, the scheduling system re-plans paths of all vehicles positioned at the bag collecting waiting point to the original bag falling opening. As a specific example, please refer to fig. 2, which shows a layout diagram of the sorting area.
For step S101, the step of determining whether there is a congested area in the sorting zone may include the sub-steps of:
substeps 101-11: dividing the sorting area into a plurality of sorting subareas according to a preset rule;
substeps 101-12: for each sorting partition, judging whether the number of vehicles in the sorting partition is larger than the critical congestion vehicle number or not;
substeps S101-13: and if so, taking the sorting subarea as a congestion area.
For substeps S101-11, the preset rule may be: the number of nodes (or the number of grids) contained in each sorting partition is equal or similar, and the sizes and the shapes of the sorting partitions are the same or similar.
For substep S101-12, the critical congested vehicle count is determined based on the number of nodes within the sorting zone. Specifically, the critical congested vehicle number may be equal to the product of the number p of nodes included in the sorting partition and a preset threshold value Φ, where the preset threshold value Φ is greater than 0.5 and smaller than 1. When the number of the nodes contained in the sorting partition is calculated, the nodes which are not available for vehicles, such as bag openings or pillars, are not included, and only the nodes which are available for vehicles in the sorting partition are counted.
For substeps S101-13, when the number of vehicles in a certain sorting zone is greater than the critical congested vehicle number, the sorting zone is considered as a congested zone.
In an alternative embodiment, the step of determining whether there is a congested area in the sorting zone may comprise the sub-steps of:
substeps 101-21: determining whether a closed loop exists;
substeps 101-22: if yes, determining nodes positioned on a closed loop to form a closed loop node set;
substeps 101-23: determining a minimum value x of a node abscissa in a closed-loop node set min And a maximum value x max Minimum value y of the ordinate min And a maximum value y max ；
Substeps ofStep S101-24: will be located in x e [ x ∈ [ ] min -α,x max +α]，y∈[y min The area in the range of α, ymax + α, where α is an integer greater than zero, is taken as a congestion area.
For substeps S101-21, when the first vehicle stops at the last node of the lock point due to unsuccessful lock point, finding a next node on the first vehicle 'S planned path and determining whether there is a second vehicle waiting at the next node on the first vehicle' S planned path; if so, searching a next node on the path planned by the second vehicle, and determining whether a third vehicle waits at the next node on the path planned by the second vehicle; and repeating the steps, and if the found next node is the last node of the first vehicle stopped at the lock point due to unsuccessful lock point, determining that a closed loop exists.
Specifically, for a certain vehicle A in the sorting area, once the vehicle A stops at the last point of the lock point due to unsuccessful lock point, searching the next node on the planned path of the vehicle, determining whether a vehicle waits at the node, and if not, stopping searching; if the node has the vehicle B, the vehicle B searches the next node on the path planned by the vehicle to see whether the vehicle waits; by analogy, if the node where the vehicle a is found is searched, a closed loop is formed.
As a specific example, as shown in fig. 3 below, the arrow represents the vehicle and its direction, black is a bag drop opening, the gray area indicates that the vehicle forms a closed loop, and the gray line frame represents a dynamically generated congestion area when α = 2.
In the embodiment of the invention, the path set traveled by the robot trolley can be abstracted into a graph. Adjacent nodes in the graph are connected by directional arcs, which may be referred to as directed edges.
A graph is a graph of a number of given vertices and edges connecting the two vertices, which is commonly used to describe some specific relationship between things, with vertices representing things and edges connecting the two vertices representing the relationship between the corresponding two things. The figure is the basic research object of Graph theory, which is a branch of mathematics. Edges are often referred to as arcs in the figures. If a direction is specified for each edge of the graph, the resulting graph is called a directed graph. In a directed graph, directed edges are often referred to as directed arcs.
With step S102, when it is determined that there is a congestion area, the path cost of a directed arc having a start point located outside the congestion area and an end point located inside the congestion area is increased. In this embodiment, the congestion zone boundary node is also a node located within the congestion zone. When the congestion area is determined by the number of vehicles in the sorting zone being greater than the critical number of congested vehicles, the increased path cost is: β (x-p φ); when the congestion area is determined based on a closed loop, the added path cost is max [ c ] min ，β(x-pφ)]Wherein, the unit vehicle congestion cost is expressed, beta > 1, x represents the number of vehicles in the congestion area, p phi represents the critical congestion vehicle number, c min Is the minimum congestion cost.
Therefore, when the scheduling system distributes tasks to the vehicles, the paths in the tasks can avoid passing through the congestion area as much as possible, and therefore the number of vehicles entering the congestion area can be reduced.
For step S103, the planning a path based on the added path cost of the directed arc includes:
traversing all vehicles which are not in the congestion area at present, and determining vehicles which comprise nodes in the congestion area and vehicles of which the destinations are in the congestion area in the path to be completed;
replanning the path of the vehicle containing the nodes in the congestion area in the path to be completed based on a shortest path algorithm;
the method comprises the steps that vehicles with destinations located in congested areas are dispatched to idle packet collection waiting points in non-congested areas;
and for the vehicle on the closed loop, removing other nodes on the closed loop except the current position of the vehicle to generate a new map, and planning a path based on the new map.
Specifically, after the congestion area is determined according to the number of the vehicles in the sorting partition, all the vehicles which are not in the congestion area currently are traversed according to the position information fed back by the heartbeat of the vehicles. If the incomplete path of the vehicle contains nodes in the congestion area, replanning the path of the vehicle according to the shortest path method; and if the bag falling port corresponding to the package on the vehicle is located in the congestion area, namely the destination is located in the congestion area, modifying the destination of the vehicle into an idle package collecting waiting point in the non-congestion area.
When the congestion area is determined according to the closed loop, traversing all vehicles which are not in the congestion area currently according to the position information fed back by the heartbeat of the vehicles. If the uncompleted path of the vehicle contains nodes in the congestion area, replanning the path of the vehicle according to a shortest path method; if the bag falling port corresponding to the package on the vehicle is located in the congested area, namely the destination is located in the congested area, modifying the destination of the vehicle into an idle package collecting waiting point in the non-congested area; and for the vehicles on the closed loop, removing other nodes on the closed loop except the current vehicle position to generate a new map, and replanning the path based on the new map and the shortest path method.
The shortest path method is as follows: from a certain node, one of the paths that pass along the map and then reach another node and whose sum of the weights on each edge is the minimum is called the shortest path. Such as Dijkstra Algorithm (Dijkstra Algorithm) and SPFA Algorithm (Shortest Path fast Algorithm, queue optimization Algorithm).
In an optional embodiment, after dispatching the vehicle with the destination located in the congestion area to an idle packet collection waiting point in the non-congestion area, the method further comprises the following steps: and when the congestion area is determined to be no longer congested, reducing the path cost increased by the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area to zero, and scheduling the vehicle located at the packet collection waiting point to go to the original destination. Specifically, when a congestion area is determined according to the number of vehicles in the sorting subarea, the number of vehicles in the congestion area is counted regularly, when the number of vehicles in the congestion area does not exceed a critical congested vehicle, the congestion area is determined not to be congested any more, the path cost increased by a directed arc with a starting point located outside the congestion area and an end point located in the congestion area is reduced to initial path cost, and the vehicles located at a packet collection waiting point are scheduled to go to the original destination; when the congestion area is determined based on the closed loop, when the vehicles on the closed loop plan the path successfully again, the congestion area is determined to be no longer congested, the path cost increased by the directed arc with the starting point located outside the congestion area and the end point located in the congestion area is reduced to the initial path cost, and the vehicles located at the collection packet waiting point are scheduled to go to the original destination.
According to the path planning method provided by the embodiment of the invention, whether a congestion area exists is determined; if yes, increasing the path cost of the directed arcs of which the starting points are located outside the congestion area and the end points are located in the congestion area; the technical means for replanning the route based on the increased directed arc route cost can prevent congestion caused by concentrated outbreak of a part of bag falling opening wrapping amount in the sorting area, and can prevent new vehicles from entering the congestion area when the congestion area exists, so that the congestion degree of the congestion area is quickened to be relieved, thereby greatly reducing manual intervention and improving the system efficiency.
Fig. 4 is a schematic diagram of a main flow of a path planning method according to an embodiment of the present invention. As shown in fig. 4, the method includes:
step S401: regularly judging whether the number of the vehicles in the sorting subarea is larger than the critical congestion vehicle number or not;
step S402: if so, increasing the path cost of the directed arc with the starting point positioned outside the congestion area and the end point positioned inside the congestion area;
step S403: replanning a route for a vehicle which is outside the congestion area and contains nodes in the congestion area in a route to be completed; the vehicles outside the congestion area and with the destination being the bag falling openings in the congestion area go to idle bag collecting waiting points in the non-congestion area;
step S404: when vehicles outside the congestion area and at the bag falling opening of the congestion area reach an idle bag collecting waiting point in the non-congestion area, regularly counting the number of the vehicles in the congestion area;
step S405: and when the number of vehicles in the congestion area is less than the critical congestion vehicle number, correcting the cost of the directional arc with the starting point located outside the congestion area and the end point located inside the congestion area, and scheduling the vehicles at the current packet collection waiting point to go to the original destination.
Fig. 5 is a schematic diagram of a main flow of a path planning method according to an embodiment of the present invention. As shown in fig. 5, the method includes:
step S501: detecting whether a closed loop exists or not at fixed time;
step S502: if the closed loop exists, determining a congestion area according to the detected closed loop;
step S503: increasing the path cost of a directed arc having a starting point located outside the congestion area and an ending point located within the congestion area;
step S504: replanning a path for a vehicle outside the congestion area and containing nodes in the congestion area in a path to be completed; the vehicles outside the congestion area and with the destination being the bag falling openings in the congestion area go to idle bag collecting waiting points in the non-congestion area; when a path is planned again for a vehicle on the closed loop, other nodes on the closed loop except the current vehicle position are removed to generate a new map, and the path is planned based on the new map;
step S505: and when the vehicle on the closed loop replans the path successfully, unlocking the congestion area, correcting the cost of the directional arc of which the starting point is positioned outside the congestion area and the end point is positioned in the congestion area, and scheduling the vehicle with the packet collection waiting point to go to the original destination.
Fig. 6 is a schematic diagram of main modules of a path planning apparatus according to an embodiment of the present invention. As shown in fig. 6, the apparatus 600 includes: a congestion determination module 601, configured to determine whether a congestion area exists; a cost increasing module 602 for increasing the path cost of a directed arc having a starting point located outside the congestion area and an ending point located within the congestion area; a path planning module 603 configured to plan a path based on the path cost of the added directed arc.
Optionally, the congestion determination module 601 is further configured to: dividing the sorting area into a plurality of sorting subareas according to a preset rule; for each sorting partition, judging whether the number of vehicles in the sorting partition is larger than the critical congestion vehicle number; and if so, taking the sorting subarea as a congestion area.
Optionally, the congestion determination module 601 is further configured to: determining whether a closed loop exists; if yes, determining nodes positioned on a closed loop to form a closed loop node set; determining a minimum value x of a node abscissa in a closed-loop node set min And a maximum value x max Minimum value y of the ordinate min And a maximum value y max (ii) a Will be located at x e [ x ∈ ] min -α,x max +α]，y∈[y min -α,y max +α]The area in the range is regarded as a congestion area, where α is an integer greater than zero.
Optionally, the congestion determination module 601 is further configured to: when a first vehicle stops at the last node of a lock point due to unsuccessful lock point, searching a next node on a path planned by the first vehicle, and determining whether a second vehicle waits at the next node on the path planned by the first vehicle; if so, searching a next node on the path planned by the second vehicle, and determining whether a third vehicle waits at the next node on the path planned by the second vehicle; and repeating the steps, and if the found next node is the last node of the first vehicle stopped at the lock point due to unsuccessful lock point, determining that a closed loop exists.
Optionally, the cost of the path added by the directed arc with the starting point located outside the congestion area and the ending point located inside the congestion area is: β (x-p φ), where β represents a unit vehicle congestion cost, β > 1, x represents the number of vehicles in the congestion area, and p φ represents the critical congestion number of vehicles.
Optionally, the incremental path cost of the directed arc with the starting point located outside the congestion area and the ending point located inside the congestion area is: max [ c ] min ，β(x-pφ)]Wherein, c min For minimum congestion cost, β represents unit vehicle congestion cost, β > 1, x represents the number of vehicles in the congestion area, and p φ represents the critical congestion vehicle number.
Optionally, the path planning module 603 is further configured to: traversing all vehicles which are not in the congestion area at present, and determining vehicles which comprise nodes in the congestion area and vehicles of which the destinations are in the congestion area in the path to be completed; replanning the path of the vehicle containing the nodes in the congestion area in the path to be completed based on a shortest path algorithm; dispatching vehicles with destinations located in congested areas to idle packet collection waiting points in non-congested areas; and for the vehicles on the closed loop, removing other nodes on the closed loop except the current vehicle position to generate a new map, and planning a path based on the new map.
Optionally, the path planning module 603 is further configured to: and when the congestion area is determined to be no longer congested, reducing the cost of the path increased by the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area to zero, and scheduling the vehicle located at the packet collection waiting point to go to the original destination.
The device can execute the method provided by the embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method. For technical details that are not described in detail in this embodiment, reference may be made to the method provided by the embodiment of the present invention.
Fig. 7 shows an exemplary system architecture 700 to which the path planning method or the path planning apparatus according to the embodiments of the present invention may be applied.
As shown in fig. 7, the system architecture 700 may include terminal devices 701, 702, 703, a network 704, and a server 705. The network 704 serves to provide a medium for communication links between the terminal devices 701, 702, 703 and the server 705. Network 704 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
A user may use the terminal devices 701, 702, 703 to interact with a server 705 over a network 704, to receive or send messages or the like. Various communication client applications, such as shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, and the like, may be installed on the terminal devices 701, 702, and 703.
The terminal devices 701, 702, 703 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 705 may be a server that provides various services, such as a background management server that supports shopping websites browsed by users using the terminal devices 701, 702, and 703. The background management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (e.g., target push information and product information) to the terminal device.
It should be noted that the path planning method provided by the embodiment of the present invention is generally executed by the server 705, and accordingly, the path planning apparatus is generally disposed in the server 705.
It should be understood that the number of terminal devices, networks, and servers in fig. 7 are merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 8, shown is a block diagram of a computer system 800 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 8 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 8, a computer system 800 includes a Central Processing Unit (CPU) 801 which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 802 or a program loaded from a storage section 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data necessary for the operation of the system 800 are also stored. The CPU 801, ROM 802, and RAM 803 are connected to each other via a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.
The following components are connected to the I/O interface 805: an input portion 806 including a keyboard, a mouse, and the like; an output section 807 including a signal such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 808 including a hard disk and the like; and a communication section 809 including a network interface card such as a LAN card, a modem, or the like. The communication section 809 performs communication processing via a network such as the internet. A drive 810 is also connected to the I/O interface 805 as necessary. A removable medium 811 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 810 as necessary, so that the computer program read out therefrom is mounted on the storage section 808 as necessary.
In particular, according to embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 809 and/or installed from the removable medium 811. The computer program executes the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 801.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a sending module, an obtaining module, a determining module, and a first processing module. The names of these modules do not in some cases constitute a limitation on the unit itself, and for example, the sending module may also be described as a "module that sends a picture acquisition request to a connected server".
As another aspect, the present invention also provides a computer-readable medium, which may be contained in the apparatus described in the above embodiments; or may be separate and not assembled into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise:
determining whether a congestion area exists;
if so, increasing the cost of the directed arc with the starting point located outside the congestion area and the ending point located inside the congestion area;
and planning the path based on the path cost of the added directed arc.
According to the technical scheme of the embodiment of the invention, whether a congestion area exists is determined; if yes, increasing the path cost of the directed arcs of which the starting points are located outside the congestion area and the end points are located in the congestion area; the technical means for replanning the route based on the increased directed arc route cost can prevent congestion caused by concentrated outbreak of a part of bag falling opening wrapping amount in the sorting area, and can prevent new vehicles from entering the congestion area when the congestion area exists, so that the congestion degree of the congestion area is quickened to be relieved, thereby greatly reducing manual intervention and improving the system efficiency.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (18)
1. A method of path planning, comprising:
arranging bag falling ports and bag collecting waiting points, wherein each bag falling port corresponds to a terminal point; responding to the closing of a bag falling port, acquiring the current position of a vehicle to a terminal point corresponding to the bag falling port, and allocating a bag collecting waiting point closest to the vehicle to plan a path to drive to the bag collecting waiting point;
determining whether a congestion area exists in response to the opening of the bag falling opening;
if yes, increasing the path cost of the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area;
and planning the path based on the path cost of the added directed arc.
2. The method of claim 1, wherein the determining whether a congestion area exists comprises:
dividing the sorting area into a plurality of sorting subareas according to a preset rule;
for each sorting partition, judging whether the number of vehicles in the sorting partition is larger than the critical congestion vehicle number or not; and if so, taking the sorting subarea as a congestion area.
3. The method of claim 1, wherein the determining whether a congestion zone exists comprises:
determining whether a closed loop exists;
if yes, determining nodes positioned on a closed loop to form a closed loop node set;
determining a minimum value x of node abscissas in a closed-loop node set min And a maximum value x max Minimum value y of the ordinate min And a maximum value y max ；
Will be located in x e [ x ∈ [ ] min -α,x max +α]，y∈[y min -α,y max +α]The area in the range is regarded as a congestion area, where α is an integer greater than zero.
4. The method of claim 3, wherein the determining whether closed loop is present comprises:
when a first vehicle stops at the last node of a lock point due to unsuccessful lock point, searching a next node on a path planned by the first vehicle, and determining whether a second vehicle waits at the next node on the path planned by the first vehicle;
if yes, searching a next node on the path planned by the second vehicle, and determining whether a third vehicle waits at the next node on the path planned by the second vehicle;
and repeating the steps, and if the found next node is the last node of the first vehicle stopped at the lock point due to unsuccessful lock point, determining that a closed loop exists.
5. The method of claim 2, wherein the directed arcs with the starting point located outside the congestion area and the ending point located inside the congestion area add path costs of: beta (x-p phi),
wherein, beta represents the congestion cost of the unit vehicle, beta > 1, x represents the number of vehicles in the congestion area, and p phi represents the critical congestion vehicle number.
6. The method of claim 3, wherein the directed arcs with the starting point outside the congestion zone and the ending point inside the congestion zone add path costs of: max [ c ] min ，β(x-pφ)]Wherein c is min To minimize congestion costs, c min Is a constant greater than 0, beta represents the unit vehicle congestion cost, beta > 1, x represents the number of vehicles in the congestion area, and p phi represents the critical congested vehicle number.
7. The method according to claim 2 or 3, wherein planning the path based on the increased path cost of the directed arc comprises:
traversing all vehicles which are not in the congestion area at present, and determining the vehicles of the nodes in the congestion area and the vehicles of which the destinations are in the congestion area in the path to be completed;
replanning the path of the vehicle containing the nodes in the congestion area in the path to be completed based on a shortest path algorithm;
the method comprises the steps that vehicles with destinations located in congested areas are dispatched to idle packet collection waiting points in non-congested areas;
and for the vehicles on the closed loop, removing other nodes on the closed loop except the current position of the vehicle to generate a new map, and planning a path based on the new map.
8. The method of claim 7, wherein after scheduling vehicles destined for congested areas to vacant packet collection waiting points in uncongested areas, the method further comprises:
and when the congestion area is determined to be no longer congested, reducing the path cost increased by the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area to zero, and scheduling the vehicle located at the packet collection waiting point to go to the original destination.
9. A path planning apparatus, comprising:
the congestion determining module is used for laying bag falling ports and bag collecting waiting points, and each bag falling port corresponds to a terminal point; responding to the closing of a bag falling port, acquiring the current position of a vehicle to a terminal point corresponding to the bag falling port, and allocating a bag collecting waiting point closest to the vehicle to plan a path to drive to the bag collecting waiting point; determining whether a congestion area exists in response to the opening of the bag falling port;
a cost increase module to increase a path cost for a directed arc having a starting point located outside the congestion area and an ending point located within the congestion area;
and the path planning module is used for planning a path based on the increased path cost of the directed arc.
10. The apparatus of claim 9, wherein the congestion determination module is further configured to:
dividing the sorting area into a plurality of sorting subareas according to a preset rule;
for each sorting partition, judging whether the number of vehicles in the sorting partition is larger than the critical congestion vehicle number; and if so, taking the sorting subarea as a congestion area.
11. The apparatus of claim 9, wherein the congestion determination module is further configured to:
determining whether a closed loop exists;
if yes, determining nodes positioned on a closed loop to form a closed loop node set;
determining a minimum value x of a node abscissa in a closed-loop node set min And a maximum value x max Minimum value y of the ordinate min And a maximum value y max ；
Will be located in x e [ x ∈ [ ] min -α,x max +α]，y∈[y min -α,y max +α]The area in the range is regarded as a congestion area, where α is an integer greater than zero.
12. The apparatus of claim 11, wherein the congestion determination module is further configured to:
when a first vehicle stops at the last node of a lock point due to unsuccessful lock point, searching the next node on the path planned by the first vehicle, and determining whether a second vehicle waits at the next node on the path planned by the first vehicle;
if so, searching a next node on the path planned by the second vehicle, and determining whether a third vehicle waits at the next node on the path planned by the second vehicle;
and repeating the steps, and if the found next node is the last node of the first vehicle stopped at the lock point due to unsuccessful lock point, determining that a closed loop exists.
13. The apparatus of claim 10, wherein the directed arcs with the starting point outside the congestion area and the ending point inside the congestion area add path costs of: beta (x-p phi),
wherein, beta represents the congestion cost of the unit vehicle, beta > 1, x represents the number of vehicles in the congestion area, and p phi represents the critical congestion vehicle number.
14. The apparatus of claim 11, wherein the starting point is located outside of the congestion zone and the ending point is located within the congestion zoneThe incremental path cost of the directed arc of (a) is: max [ c ] min ，β(x-pφ)]Wherein c is min To minimize congestion cost, c min Is a constant greater than 0, beta represents the unit vehicle congestion cost, beta > 1, x represents the number of vehicles in the congestion area, and p phi represents the critical congested vehicle number.
15. The apparatus of claim 10 or 11, wherein the path planning module is further configured to:
traversing all vehicles which are not in the congestion area at present, and determining the vehicles of the nodes in the congestion area and the vehicles of which the destinations are in the congestion area in the path to be completed;
replanning the path of the vehicle containing the nodes in the congestion area in the path to be completed based on a shortest path algorithm;
the method comprises the steps that vehicles with destinations located in congested areas are dispatched to idle packet collection waiting points in non-congested areas;
and for the vehicles on the closed loop, removing other nodes on the closed loop except the current position of the vehicle to generate a new map, and planning a path based on the new map.
16. The apparatus of claim 15, wherein the path planning module is further configured to: and when the congestion area is determined to be no longer congested, reducing the path cost increased by the directed arc with the starting point located outside the congestion area and the end point located inside the congestion area to zero, and scheduling the vehicle located at the packet collection waiting point to go to the original destination.
17. An electronic device, comprising:
one or more processors;
a storage device to store one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method recited in any of claims 1-8.
18. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-8.
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| CN111768629B (en) * | 2019-11-04 | 2022-04-12 | 北京京东乾石科技有限公司 | Vehicle scheduling method, device and system |
| CN113075921B (en) * | 2019-12-17 | 2024-02-09 | 北京京东尚科信息技术有限公司 | Local path planning method and device for unmanned equipment |
| CN111824646B (en) * | 2020-06-16 | 2022-06-21 | 浙江天尚元科技有限公司 | Intelligent medical waste transport vehicle and transport method |
| CN112213113B (en) * | 2020-09-02 | 2022-07-15 | 中国第一汽车股份有限公司 | Method for selecting and planning actual road test scene of intelligent driving mobile device |
| CN113551685B (en) * | 2021-07-30 | 2022-08-26 | 重庆大学 | Multi-preference route planning method for double-time-varying road network |
| CN116795087A (en) * | 2022-03-15 | 2023-09-22 | 灵动科技（北京）有限公司 | Scheduling method, scheduling system, electronic equipment and storage medium of autonomous mobile robot |
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