Driving route allocation plan generation method, device, storage medium and program product

Abstract

Embodiments of the present invention provide a method, electronic device, storage medium, and computer program product for generating a driving route allocation plan. The method comprises: obtaining the utilization rate of each robot in a robot collection and obtaining the required number of trips for each of a plurality of driving routes. The utilization rate represents the robot's driving efficiency, taking into account at least the time required for the robot to switch routes. With the goal of minimizing the number of robots required, a driving route allocation plan is generated based on the utilization rate of each robot in the robot collection and the required number of trips for each of the plurality of driving routes. The driving route allocation plan includes at least the number of robots required, N, and a set of N routes to be driven. Thus, embodiments of the present invention can minimize the number of robots required, saving factory costs, and generating a set of routes to be driven for each robot, facilitating the efficient completion of each subsequent route.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of information processing, and in particular to a method for generating a driving route allocation plan, an electronic device, a storage medium, and a computer program product. Background Art

[0002] As the manufacturing industry upgrades, intelligent equipment is increasingly being used in factories. In many smart factory scenarios, multiple intelligent robots are required to complete route tasks. Therefore, to ensure the efficient operation of intelligent robots, it is necessary to intelligently plan the robot's route and generate a route allocation plan to maximize robot utilization, thereby minimizing the number of robots required and reducing costs.

[0003] It can be seen that there is an urgent need for a method for generating a driving route allocation plan that can improve the utilization of robots. Summary of the Invention

[0004] Embodiments of the present invention provide a driving route allocation plan generation method, electronic equipment, storage medium, and computer program product to improve robot utilization.

[0005] A first aspect of an embodiment of the present invention provides a method for generating a driving route allocation plan, the method comprising:

[0006] Obtaining a utilization rate of each robot in the robot set and obtaining the required number of trips for each of the multiple driving routes, wherein the utilization rate is used to represent the driving efficiency of the robot while at least considering the time consumed by the robot's route switching;

[0007] With the goal of minimizing the number of robots required, a route allocation plan is generated based on the utilization rate of each robot in the robot set and the required number of trips for each of the multiple routes. The route allocation plan includes at least: the number N of robots required and the N sets of routes to be traveled.

[0008] Optionally, when the utilization rates of the robots in the robot set are the same, the method further includes:

[0009] Any set of routes to be traveled in the N sets of routes to be traveled is sent to any robot in the set of robots.

[0010] Optionally, in the case where the utilization rates of the robots in the robot set are different, the driving route allocation scheme further includes: utilization rates corresponding to the respective N sets of routes to be driven;

[0011] The method further comprises:

[0012] For each set of routes to be traveled, according to the utilization rate corresponding to the set of routes to be traveled, the set of routes to be traveled is sent to the robot with the utilization rate in the set of robots.

[0013] Optionally, the method further includes:

[0014] Get the drivable routes for each robot in the robot collection;

[0015] With the goal of minimizing the number of robots required, a driving route allocation plan is generated according to the utilization rate of each robot in the robot set and the required number of trips of each of the multiple driving routes, including:

[0016] With the goal of minimizing the number of robots required, a route allocation plan is generated based on the utilization rate and drivable routes of each robot in the robot set, as well as the required number of trips for each of the multiple routes. The route allocation plan further includes: robots corresponding to each of the N routes to be traveled, wherein each route in each route set to be traveled is a drivable route for the robot corresponding to the route set to be traveled;

[0017] The method further comprises:

[0018] Each set of routes to be traveled is assigned to the robot corresponding to the set of routes to be traveled.

[0019] Optionally, the method further includes:

[0020] Obtaining an estimated driving time for each of the multiple driving routes;

[0021] determining an actual driving time of each robot for each driving route based on a utilization rate of each robot in the robot set and an estimated driving time of each of the multiple driving routes;

[0022] With the goal of minimizing the number of robots required, a driving route allocation plan is generated according to the utilization rate of each robot in the robot set and the required number of trips of each of the multiple driving routes, including:

[0023] With the goal of minimizing the number of robots required, a driving route allocation plan is generated based on the actual driving time of each robot for each driving route and the required number of driving times for each of the multiple driving routes.

[0024] Optionally, for each robot in the robot set, the utilization rate of the robot is determined based on at least one of the robot's line switching time, traffic control time, and charging efficiency.

[0025] Optionally, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0026] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0027] The utilization rate of the robot is determined based on the proportion of the robot's line switching time.

[0028] Optionally, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0029] Based on the robot's historical driving records, the ratio of the robot's total avoidance time to its total driving time is determined as the robot's traffic control time ratio;

[0030] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0031] The utilization rate of the robot is determined based on the proportion of the robot's route switching time, the robot's charging efficiency and / or the proportion of the robot's traffic control time.

[0032] Optionally, the constraints used in generating the driving route allocation plan include at least one of the following:

[0033] The drivable route of each robot is the route within the physical space where the robot is located as a constraint;

[0034] The constraint condition is that the travel time required for each set of routes to be traveled does not exceed the target time.

[0035] Optionally, generating the driving route assignment solution is achieved by solving the following integer linear programming equation:

[0036] The objective function is: min∑ j ind j

[0037] The constraints are:

[0038]

[0039] Among them, x ij The value of is 0 or 1, indicating whether the i-th route is assigned to the j-th robot for execution; L represents a set of multiple driving routes; T represents the robot set; ind j The value of is 0 or 1, indicating whether the jth robot is used; M represents a large number; d ikRepresents the travel frequency requirement of the i-th travel route.

[0040] A second aspect of an embodiment of the present invention provides a driving route allocation plan generating device, the device comprising:

[0041] A first acquisition module is configured to acquire a utilization rate of each robot in the robot set and to acquire the required number of trips for each of the plurality of driving routes, wherein the utilization rate is used to represent the driving efficiency of the robot taking into account at least the time taken to switch routes of the robot;

[0042] The generation module is configured to generate a route allocation plan based on the utilization rate of each robot in the robot set and the required number of trips of each of the multiple routes, with the goal of minimizing the number of robots required. The route allocation plan includes at least: the number N of robots required and the N sets of routes to be traveled.

[0043] Optionally, when the utilization rates of the robots in the robot set are the same, the device further comprises:

[0044] The first sending module is used to send any one of the N sets of routes to be driven to any robot in the set of robots.

[0045] Optionally, in the case where the utilization rates of the robots in the robot set are different, the driving route allocation scheme further includes: utilization rates corresponding to the respective N sets of routes to be driven;

[0046] The device further comprises:

[0047] The second sending module is used to send each set of routes to be traveled to a robot with the utilization rate in the robot set according to the utilization rate corresponding to the set of routes to be traveled.

[0048] Optionally, the device further comprises:

[0049] The second acquisition module is used to obtain a drivable route for each robot in the robot set;

[0050] The generation module is specifically used to:

[0051] With the goal of minimizing the number of robots required, a route allocation plan is generated based on the utilization rate and drivable routes of each robot in the robot set, as well as the required number of trips for each of the multiple routes. The route allocation plan further includes: robots corresponding to each of the N routes to be traveled, wherein each route in each route set to be traveled is a drivable route for the robot corresponding to the route set to be traveled;

[0052] The device further comprises:

[0053] The allocation module is used to allocate each set of routes to be traveled to the robot corresponding to the set of routes to be traveled.

[0054] Optionally, the device further comprises:

[0055] A third acquisition module is used to obtain the estimated driving time of each of the multiple driving routes;

[0056] a determination module, configured to determine an actual driving time of each robot for each driving route based on a utilization rate of each robot in the robot set and an estimated driving time of each of the plurality of driving routes;

[0057] The generation module is specifically used to:

[0058] With the goal of minimizing the number of robots required, a driving route allocation plan is generated based on the actual driving time of each robot for each driving route and the required number of driving times for each of the multiple driving routes.

[0059] Optionally, for each robot in the robot set, the utilization rate of the robot is determined based on at least one of the robot's line switching time, traffic control time, and charging efficiency.

[0060] Optionally, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0061] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0062] The utilization rate of the robot is determined based on the proportion of the robot's line switching time.

[0063] Optionally, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0064] Based on the robot's historical driving records, the ratio of the robot's total avoidance time to its total driving time is determined as the robot's traffic control time ratio;

[0065] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0066] The utilization rate of the robot is determined based on the proportion of the robot's route switching time, the robot's charging efficiency and / or the proportion of the robot's traffic control time.

[0067] Optionally, the constraints used in generating the driving route allocation plan include at least one of the following:

[0068] The drivable route of each robot is the route within the physical space where the robot is located as a constraint;

[0069] The constraint condition is that the travel time required for each set of routes to be traveled does not exceed the target time.

[0070] Optionally, generating the driving route assignment solution is achieved by solving the following integer linear programming equation:

[0071] The objective function is: min∑ j ind j

[0072] The constraints are:

[0073]

[0074] Among them, x ij The value of is 0 or 1, indicating whether the i-th route is assigned to the j-th robot for execution; L represents a set of multiple driving routes; T represents the robot set; ind j The value of is 0 or 1, indicating whether the jth robot is used; M represents a large number; d ik Represents the travel frequency requirement of the i-th travel route.

[0075] A third aspect of an embodiment of the present invention provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the method for generating a driving route allocation plan as described in the first aspect of the present invention.

[0076] A fourth aspect of an embodiment of the present invention provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the method for generating a driving route allocation plan as described in the first aspect of the present invention is implemented.

[0077] A fifth aspect of an embodiment of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the method for generating a driving route allocation plan described in the first aspect of the present invention.

[0078] In an embodiment of the present invention, based on the utilization rate of the robots and the required number of trips for each of the multiple driving routes, the number of robots and the multiple driving routes are planned from a global perspective, and a driving route allocation plan is generated. This can minimize the number of robots required and maximize the utilization of the transportation capacity provided by each robot, thereby achieving the purpose of saving factory costs. In addition, in an embodiment of the present invention, a set of routes to be driven corresponding to each robot can also be generated to facilitate the efficient completion of each subsequent driving route. BRIEF DESCRIPTION OF THE DRAWINGS

[0079] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0080] Figure 1 This is a flow chart of a method for generating a driving route allocation plan according to an embodiment of the present invention;

[0081] Figure 2 is a flow chart of another method for generating a driving route allocation plan according to an embodiment of the present invention;

[0082] Figure 3 is a flow chart of another method for generating a driving route allocation plan according to an embodiment of the present invention;

[0083] Figure 4 is a flow chart of another method for generating a driving route allocation plan according to an embodiment of the present invention;

[0084] Figure 5 is a flow chart of another method for generating a driving route allocation plan according to an embodiment of the present invention;

[0085] Figure 6 This is a structural block diagram of a driving route allocation plan generating device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0086] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0087] With the development of intelligent technologies such as the Internet of Things (IoT), artificial intelligence (AI), and big data, the demand for transforming and upgrading the traditional logistics industry through these technologies is growing stronger. Intelligent logistics (Intelligent Logistics System) has become a research hotspot in the logistics field. Intelligent logistics utilizes AI, big data, and IoT devices and technologies such as information sensors, radio frequency identification (RFID), and the Global Positioning System (GPS). These technologies are widely applied to fundamental activities such as material transportation, warehousing, distribution, packaging, loading and unloading, and information services. This enables intelligent analysis and decision-making, automated operations, and efficient optimization of material management processes. IoT technologies include sensing devices, RFID, laser infrared scanning, and infrared sensor recognition. The IoT effectively connects materials in logistics to the network, enabling real-time monitoring of materials. It also senses environmental data such as humidity and temperature in warehouses to ensure a safe and secure storage environment. Big data technologies can sense and collect all logistics data, upload it to the data layer of an information platform, and filter, mine, and analyze the data. Ultimately, this data provides accurate data support for business processes such as transportation, warehousing, storage and retrieval, picking, packaging, sorting, outbound delivery, inventory, and distribution. The application of artificial intelligence in logistics can be broadly categorized into two main areas: 1) AI-enabled intelligent devices such as unmanned trucks, AGVs, AMRs, forklifts, shuttle trucks, stackers, unmanned delivery vehicles, drones, service robots, robotic arms, and smart terminals are replacing some manual labor; 2) software systems such as transportation equipment management systems, warehouse management systems, equipment scheduling systems, and order distribution systems are driven by technologies or algorithms like computer vision, machine learning, and operations optimization to improve human efficiency. With the research and advancement of smart logistics, this technology has been applied in numerous fields, including retail and e-commerce, electronics, tobacco, pharmaceuticals, industrial manufacturing, footwear and apparel, textiles, and food.

[0088] In many smart factory scenarios, multiple intelligent robots are required to complete route tasks, necessitating planning of the number of robots and their routes. A common approach employed in related technologies is to calculate the number of robots required for each route by dividing the required number of tasks by the capacity provided by a single robot and rounding up the result. However, this approach can lead to a waste of robot capacity.

[0089] Based on this, the present invention proposes a method for generating a driving route allocation scheme, referring to Figure 1 , shows a flowchart of a method for generating a driving route allocation plan according to an embodiment of the present invention, the method includes the following steps S101 and S102.

[0090] S101, obtaining the utilization rate of each robot in the robot set, and obtaining the travel frequency requirements of each of a plurality of travel routes.

[0091] In the embodiment of the present invention, the utilization rate is used to represent the driving efficiency of the robot under the condition that at least the time consumption of the robot's route switching is taken into consideration.

[0092] In real-world factory logistics environments, there are typically multiple physical spaces, each equipped with a certain number of robots to execute various driving tasks. Multiple driving routes can exist within the same physical space, and each route can be executed simultaneously by multiple robots at the same time.

[0093] In the embodiment of the present invention, each robot may choose to execute another driving route after completing one driving route.

[0094] In the embodiment of the present invention, a driving route allocation plan may be generated for multiple driving routes in one physical space, or a driving route allocation plan may be generated by performing unified planning for multiple driving routes in multiple physical spaces.

[0095] In an embodiment of the present invention, each driving route has a corresponding driving frequency requirement, indicating the number of times it needs to be driven. In an embodiment of the present invention, the driving frequency requirement for each driving route for the day can be determined before the factory begins operation, and a driving route allocation plan can be generated based on this and the utilization rate of each robot. In an embodiment of the present invention, the driving frequency requirement for each driving route within a preset cycle period (e.g., one hour) can also be determined. Based on this and the utilization rate of each robot, multiple sets of routes to be driven are generated to obtain a cyclical driving route allocation plan.

[0096] In an embodiment of the present invention, for each robot in the robot set, the utilization rate of the robot is determined based on at least one of the route switching time, traffic control time, and charging efficiency of the robot.

[0097] In this embodiment of the present invention, route switching time refers to the time it takes for the robot to switch from route A to route B. Traffic control time refers to the time it takes for the robot to avoid and wait when performing route tasks in a physical space.

[0098] In practical applications, the robot may need to be recharged after running out of battery while performing route tasks. In embodiments of the present invention, the robot's charging efficiency can be determined based on the robot's charging time and driving time. For example, if a robot takes 10 minutes to fully charge, and that amount of battery can support the robot's driving for 40 minutes, the robot's charging efficiency is 80%.

[0099] In an optional embodiment of the present invention, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0100] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0101] The utilization rate of the robot is determined based on the proportion of the robot's line switching time.

[0102] In this embodiment of the present invention, since the robot's fixed route restrictions are removed, the robot's route allocation plan can include multiple routes. Therefore, when the robot switches from route A to route B, route switching takes time, affecting the robot's actual utilization. Therefore, in this embodiment of the present invention, the robot's route switching time is taken into account when determining the robot's utilization.

[0103] In an optional embodiment of the present invention, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0104] Based on the robot's historical driving records, the ratio of the robot's total avoidance time to its total driving time is determined as the robot's traffic control time ratio;

[0105] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0106] The utilization rate of the robot is determined based on the proportion of the robot's route switching time, the robot's charging efficiency and / or the proportion of the robot's traffic control time.

[0107] In an embodiment of the present invention, the route switching time ratio and traffic control time ratio can be estimated in advance based on the robot's historical driving records, and the route switching time ratio and traffic control time ratio can be used as fixed parameters for subsequent calculations.

[0108] S102 , with the goal of minimizing the number of robots required, generate a driving route allocation plan based on the utilization rate of each robot in the robot set and the required number of driving times of each of the multiple driving routes.

[0109] In the embodiment of the present invention, each driving route allocation plan at least includes: the number N of robots to be used, and a set of N routes to be driven.

[0110] In embodiments of the present invention, when generating a driving route allocation plan, the plan can be generated based on the utilization rate of each robot and the required number of trips for each of the multiple driving routes. Thus, in embodiments of the present invention, under the premise that robots can switch routes, with the goal of minimizing the number of robots, the number of robots N required to execute all driving routes can be determined, thereby obtaining a set of N to-be-traveled routes.

[0111] In an optional embodiment of the present invention, when the utilization rates of the robots in the robot set are the same, after obtaining the route allocation plan, any one of the N routes to be traveled can be sent to any robot in the robot set.

[0112] In an optional embodiment of the present invention, when the utilization rates of the robots in the robot set are different, the driving route allocation scheme further includes: the utilization rates corresponding to the N sets of routes to be driven;

[0113] The method further comprises:

[0114] For each set of routes to be traveled, according to the utilization rate corresponding to the set of routes to be traveled, the set of routes to be traveled is sent to the robot with the utilization rate in the set of robots.

[0115] In an embodiment of the present invention, when the utilization rates of the robots are different, each set of routes to be traveled in the generated route allocation plan corresponds to the utilization rate of the robot, so that the set of routes to be traveled can be distributed to the robot with the utilization rate in the robot set according to the utilization rate corresponding to the set of routes to be traveled.

[0116] The generation of the driving route allocation plan is achieved by solving the following integer linear programming equation:

[0117] The objective function is: min∑ j ind j

[0118] The constraints are:

[0119]

[0120] Among them, x ij The value of is 0 or 1, indicating whether the i-th route is assigned to the j-th robot for execution; L represents a set of multiple driving routes; T represents the robot set; ind j The value of is 0 or 1, indicating whether the jth robot is used; M represents a large number; d ik Represents the travel frequency requirement of the i-th travel route.

[0121] In an embodiment of the present invention, based on the utilization rate of the robots and the required number of trips for each of the multiple driving routes, the number of robots and the multiple driving routes are planned from a global perspective, and a driving route allocation plan is generated. This can minimize the number of robots required and maximize the utilization of the transportation capacity provided by each robot, thereby achieving the purpose of saving factory costs. In addition, in an embodiment of the present invention, a set of routes to be driven corresponding to each robot can also be generated to facilitate the efficient completion of each subsequent driving route.

[0122] In an embodiment of the present invention, the constraints used to generate the driving route allocation plan include at least one of the following:

[0123] The drivable route of each robot is the route within the physical space where the robot is located as a constraint;

[0124] The constraint condition is that the travel time required for each set of routes to be traveled does not exceed the target time.

[0125] In actual application, when generating a driving route allocation plan, it may be necessary to uniformly plan the routes of multiple physical spaces. At the same time, due to the long distance between physical spaces, the robot's execution of tasks across physical spaces will lead to a decrease in its utilization rate. Therefore, physical space constraints need to be imposed when generating a driving route allocation plan. Specifically, in an optional embodiment of the present invention, a flowchart of another driving route allocation plan generation method is provided, as shown in FIG. Figure 2 As shown, the method includes the following steps:

[0126] S201, obtaining the utilization rate of each robot in the robot set, and obtaining the travel frequency requirements of each of the multiple travel routes.

[0127] This step is similar to the above-mentioned step S101 and will not be described in detail in this embodiment of the present invention.

[0128] S202: Obtain the respective identifications of the multiple robots and the physical spaces in which they are located, and obtain the physical spaces in which the multiple driving routes are located.

[0129] In the embodiment of the present invention, the physical space where the robot is located can be understood as an independent space, such as a workshop, a factory building, etc.

[0130] In an embodiment of the present invention, considering that in actual applications, it is difficult and inefficient to complete a driving route across physical spaces, each robot is configured to move only in its own physical space and execute the driving route within the physical space.

[0131] S203, with the goal of minimizing the number of robots required and the constraint that each robot can only execute routes within the physical space where the robot is located, generate a driving route allocation plan based on the utilization rate of each robot in the robot set and the required number of trips for each of the multiple driving routes.

[0132] In this embodiment of the present invention, when determining the set of routes to be driven by multiple robots, each robot is constrained to execute only routes within its physical space. This physical space constraint restricts the routes that the robots can execute. Furthermore, the physical spaces to which the routes belong are differentiated, ultimately resulting in a list of routes for different physical spaces and the corresponding robots.

[0133] Specifically, in an embodiment of the present invention, an integer linear programming equation can also be used to determine the number of robots required to complete the number of times all driving routes need to be driven, and the set of routes to be driven corresponding to each of the multiple robots, wherein the physical space constraint can be expressed as:

[0134]

[0135] Among them, s j Identify the physical space to which the jth robot belongs.

[0136] In an embodiment of the present invention, when generating a driving route allocation plan, multiple driving routes in different physical spaces can be planned at the same time, and physical space constraints can be performed. This can avoid the situation where the driving route list corresponding to the robot crosses physical spaces when planning individual driving routes in multiple physical spaces.

[0137] In actual application, when generating a driving route allocation plan, due to the different models of robots, the tasks that can be executed may also be different. Accordingly, the routes that can be executed by each robot are also different. Therefore, in this case, it is necessary to perform route constraints when generating a driving route allocation plan. Specifically, in an optional embodiment of the present invention, a flowchart of another driving route allocation plan generation method is provided, as shown in FIG. Figure 3 As shown, the method includes the following steps:

[0138] S301, obtaining the utilization rate of each robot in the robot set, and obtaining the travel frequency requirements of each of the multiple travel routes.

[0139] This step is similar to the above-mentioned step S101 and will not be described in detail in this embodiment of the present invention.

[0140] S302: Obtain a drivable route for each robot in the robot set.

[0141] In the embodiment of the present invention, the robot usually travels along the travel route in order to perform related tasks, such as a transporting task or a sorting task.

[0142] In the embodiment of the present invention, considering that robots exist in different models, the tasks that can be executed may also be different. Accordingly, the driving routes that can be completed by each robot are also different. For example, a robot of model A can perform a handling task, and the tasks corresponding to routes a and b are handling tasks. Then the executable route set of the robot of model A is a, b.

[0143] S303, with the goal of minimizing the number of robots required and the constraint that each robot can only perform corresponding executable tasks, generate a driving route allocation plan based on the utilization rate of each robot in the robot set and the number of driving times required for each of the multiple driving routes.

[0144] In this embodiment of the present invention, when determining the set of routes to be driven corresponding to multiple robots, each robot is constrained to execute only routes in its corresponding set of executable routes. This constrains the routes that the robot can execute, thereby limiting the routes it can execute. Ultimately, a set of routes to be driven corresponding to each robot is obtained.

[0145] Specifically, in an embodiment of the present invention, an integer linear programming equation can also be used to determine the number of robots required to execute all driving routes and the set of routes to be driven corresponding to each of the multiple robots. The route constraint condition can be expressed as:

[0146] x ij ≤y ij ,i=1,…,|L|,j=1,…,|T|

[0147] Among them, y ij The value of is 0 or 1, indicating whether the j-th robot can execute the i-th driving route.

[0148] S304: Allocate each set of routes to be driven to a robot corresponding to the set of routes to be driven.

[0149] In the embodiment of the present invention, when generating the driving route allocation plan, the executable route set of each robot is taken into consideration, so that the determined multiple routes to be driven can be accurately adapted to each selected robot.

[0150] In actual application, when generating a driving route allocation plan, in order to reduce the amount of calculation, each route task can be divided according to a cycle period to obtain the number of travel times of each of the multiple driving routes within a unit time, and based on the demand, a driving route allocation plan within a unit time is generated, thereby obtaining a driving route allocation plan that can be cyclically circulated. In this case, it is necessary to impose a time constraint when generating the driving route allocation plan. Specifically, in an optional embodiment of the present invention, a flowchart of another driving route allocation plan generation method is provided, as shown in FIG. Figure 4 As shown, in an embodiment of the present invention, the cycle period of the driving route allocation scheme generation method is the target duration, and the method includes the following steps:

[0151] S401, obtaining the utilization rate of each robot in the robot set, and obtaining the travel frequency requirements of each of the multiple travel routes.

[0152] In this embodiment of the present invention, a driving route allocation scheme is determined using the target duration as a cycle period, such that the robot can cyclically execute the corresponding set of routes to be driven according to the cycle period. Accordingly, in this embodiment of the present invention, the number of times a driving route needs to be executed can also be calculated based on the cycle period to determine the number of times a driving route needs to be executed within the target duration.

[0153] S402, with the goal of minimizing the number of robots required and the constraint that the travel time required for each set of routes to be traveled does not exceed the target time, a travel route allocation plan is generated based on the utilization rate of each robot in the robot set and the travel times required for each of the multiple travel routes.

[0154] In an embodiment of the present invention, when determining the set of routes to be driven corresponding to multiple robots, the target duration of the cycle is used as a constraint condition and duration constraint is performed, so that the set of routes to be driven corresponding to each robot within a unit time can be determined.

[0155] Specifically, in an embodiment of the present invention, an integer linear programming equation can also be used to determine the number of robots required to complete the number of times each of the multiple driving routes is required, as well as the set of routes to be driven corresponding to each of the multiple robots. The duration constraint can be expressed as:

[0156]

[0157] in,

[0158]

[0159] cost i It represents the actual time taken for the i-th route, and cap represents the target time.

[0160] In an embodiment of the present invention, after determining a set of to-be-traveled routes corresponding to each robot within the target duration, each robot can be controlled to cyclically execute the corresponding route with the target duration as the cycle period.

[0161] In an embodiment of the present invention, a list of driving routes that each vehicle needs to execute can be accurately determined while maximizing the overall robot utilization, and the total time consumed by each robot to allocate a route does not exceed the time period, thereby preventing the impact of task timeouts caused by estimation errors.

[0162] In the embodiment of the present invention, the target duration can be preset in advance by a technician according to actual needs, for example, it can be 1 hour.

[0163] In an optional embodiment of the present invention, when executing the driving route allocation scheme generation method, at least one of the above-mentioned physical space constraints, route constraints, and time constraints can be considered simultaneously.

[0164] In an optional embodiment of the present invention, a flowchart of another method for generating a driving route allocation solution is provided, such as Figure 5 As shown, in an embodiment of the present invention, the method includes the following steps:

[0165] S501, obtaining the utilization rate of each robot in the robot set, and obtaining the travel frequency requirements of each of the multiple travel routes.

[0166] This step is similar to the above-mentioned step S101 and will not be described in detail in this embodiment of the present invention.

[0167] S502: Obtain the estimated driving duration of each of the multiple driving routes.

[0168] In the embodiment of the present invention, the estimated driving duration of each driving route can be obtained based on the route length of each driving route and the average driving speed of the robot. The estimated driving duration of each driving route is determined in advance and is fixed.

[0169] S503 : determining the actual driving time of each robot for each driving route according to the utilization rate of each robot in the robot set and the estimated driving time of each of the multiple driving routes.

[0170] In an embodiment of the present invention, when generating a driving route allocation plan, the actual time required for each robot to complete each driving route can be determined based on the utilization rate of each robot and the estimated driving time of each of the multiple driving routes.

[0171] S504 , with the goal of minimizing the number of robots required, generate a route allocation plan based on the actual driving time of each robot for each route and the required number of driving times for each of the multiple routes.

[0172] In an embodiment of the present invention, after determining the actual time required for each robot to complete each driving route, linear programming can be performed based on the actual driving time and the number of driving times required for each of the multiple driving routes to obtain a driving route allocation plan.

[0173] Therefore, in the embodiment of the present invention, under the premise that the robots can switch routes, with the goal of minimizing the number of robots, the number of robots N required to execute all driving routes can be determined, and a set of N routes to be driven can be obtained.

[0174] Based on the same inventive concept, an embodiment of the present invention provides a driving route allocation scheme generating device. Figure 6 , Figure 6 2 is a schematic diagram of a driving route allocation scheme generating device provided by an embodiment of the present invention.

[0175] like Figure 6 As shown, the device includes:

[0176] A first acquisition module 601 is configured to acquire a utilization rate of each robot in the robot set and to acquire the required number of trips for each of the plurality of driving routes. The utilization rate is used to represent the driving efficiency of the robot, taking into account at least the time required for the robot to switch routes.

[0177] A generation module 602 is configured to generate a route allocation plan based on the utilization rate of each robot in the robot set and the required number of trips for each of the multiple routes, with the goal of minimizing the number of robots required. The route allocation plan includes at least: the number N of robots required and the N sets of routes to be traveled.

[0178] Optionally, when the utilization rates of the robots in the robot set are the same, the device further comprises:

[0179] The first sending module is used to send any one of the N sets of routes to be driven to any robot in the set of robots.

[0180] Optionally, in the case where the utilization rates of the robots in the robot set are different, the driving route allocation scheme further includes: utilization rates corresponding to the respective N sets of routes to be driven;

[0181] The device further comprises:

[0182] The second sending module is used to send each set of routes to be traveled to a robot with the utilization rate in the robot set according to the utilization rate corresponding to the set of routes to be traveled.

[0183] Optionally, the device further comprises:

[0184] The second acquisition module is used to obtain a drivable route for each robot in the robot set;

[0185] The generating module 602 is specifically configured to:

[0186] With the goal of minimizing the number of robots required, a route allocation plan is generated based on the utilization rate and drivable routes of each robot in the robot set, as well as the required number of trips for each of the multiple routes. The route allocation plan further includes: robots corresponding to each of the N routes to be traveled, wherein each route in each route set to be traveled is a drivable route for the robot corresponding to the route set to be traveled;

[0187] The device further comprises:

[0188] The allocation module is used to allocate each set of routes to be traveled to the robot corresponding to the set of routes to be traveled.

[0189] Optionally, the device further comprises:

[0190] A third acquisition module is used to obtain the estimated driving time of each of the multiple driving routes;

[0191] a determination module, configured to determine an actual driving time of each robot for each driving route based on a utilization rate of each robot in the robot set and an estimated driving time of each of the plurality of driving routes;

[0192] The generating module 602 is specifically configured to:

[0193] With the goal of minimizing the number of robots required, a driving route allocation plan is generated based on the actual driving time of each robot for each driving route and the required number of driving times for each of the multiple driving routes.

[0194] Optionally, for each robot in the robot set, the utilization rate of the robot is determined based on at least one of the robot's line switching time, traffic control time, and charging efficiency.

[0195] Optionally, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0196] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0197] The utilization rate of the robot is determined based on the proportion of the robot's line switching time.

[0198] Optionally, for each robot in the robot set, the utilization rate of the robot is determined according to the following steps:

[0199] Based on the robot's historical driving records, the ratio of the robot's total avoidance time to its total driving time is determined as the robot's traffic control time ratio;

[0200] Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio;

[0201] The utilization rate of the robot is determined based on the proportion of the robot's route switching time, the robot's charging efficiency and / or the proportion of the robot's traffic control time.

[0202] Optionally, the constraints used in generating the driving route allocation plan include at least one of the following:

[0203] The drivable route of each robot is the route within the physical space where the robot is located as a constraint;

[0204] The constraint is that the travel time required for each set of routes to be traveled does not exceed the target time. Optionally, the travel route allocation scheme is generated by solving the following integer linear programming equation:

[0205] The objective function is: min∑ j ind j

[0206] The constraints are:

[0207]

[0208] Among them, x ij The value of is 0 or 1, indicating whether the i-th route is assigned to the j-th robot for execution; L represents a set of multiple driving routes; T represents the robot set; ind j The value of is 0 or 1, indicating whether the jth robot is used; M represents a large number; d ik Represents the travel frequency requirement of the i-th travel route.

[0209] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0210] An embodiment of the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory, wherein when the processor executes the computer program, the computer program implements the steps in the method for generating a driving route allocation plan described in any of the above embodiments.

[0211] An embodiment of the present invention further provides a computer-readable storage medium having a computer program / instruction stored thereon. When the computer program / instruction is executed by a processor, the steps in the method for generating a driving route allocation plan described in any of the above embodiments are implemented.

[0212] An embodiment of the present invention further provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the method for generating a driving route allocation plan described in any of the above embodiments.

[0213] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0214] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, apparatus, or computer program products. Thus, embodiments of the present invention may take the form of a fully hardware embodiment, a fully software embodiment, or an embodiment combining software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0215] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the process in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0216] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0217] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0218] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they become aware of the basic creative concepts. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0219] Finally, it should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or terminal device that includes a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or terminal device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or terminal device that includes the element.

[0220] The above describes in detail a method for generating a driving route allocation plan, an electronic device, a storage medium, and a computer program product provided by the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only intended to help understand the method and core concept of the present invention. At the same time, for those skilled in the art, according to the concept of the present invention, there may be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for generating a driving route allocation plan, characterized in that: The method comprises: Obtaining a utilization rate of each robot in the robot set and obtaining the required number of trips for each of the multiple driving routes, wherein the utilization rate is used to represent the driving efficiency of the robot while at least considering the time consumed by the robot's route switching; With the goal of minimizing the number of robots required, generating a route allocation plan based on the utilization rate of each robot in the robot set and the required number of trips of each of the plurality of routes, the route allocation plan including at least: the number N of robots required, and the N sets of routes to be traveled; For each robot in the robot set, the utilization rate of the robot is determined according to the following steps: Based on the robot's historical driving records, the ratio of the robot's total avoidance time to its total driving time is determined as the robot's traffic control time ratio; Based on the robot's historical driving records, the ratio of the total time spent on the robot's driving route to the total driving time is determined as the robot's route switching time ratio; The utilization rate of the robot is determined based on the proportion of the robot's route switching time, the robot's charging efficiency and / or the proportion of the robot's traffic control time.

2. The method for generating a driving route allocation plan according to claim 1, wherein: When the utilization rates of the robots in the robot set are the same, the method further includes: Any set of routes to be traveled in the N sets of routes to be traveled is sent to any robot in the set of robots.

3. The method for generating a driving route allocation plan according to claim 1, wherein: In the case where the utilization rates of the robots in the robot set are different, the driving route allocation scheme further includes: the utilization rates corresponding to the N sets of routes to be driven; The method further comprises: For each set of routes to be traveled, according to the utilization rate corresponding to the set of routes to be traveled, the set of routes to be traveled is sent to the robot with the utilization rate in the set of robots.

4. The method for generating a driving route allocation plan according to claim 1, wherein: The method further comprises: Get the drivable routes for each robot in the robot collection; With the goal of minimizing the number of robots required, a driving route allocation plan is generated according to the utilization rate of each robot in the robot set and the required number of trips of each of the multiple driving routes, including: With the goal of minimizing the number of robots required, a route allocation plan is generated based on the utilization rate and drivable routes of each robot in the robot set, as well as the required number of trips for each of the multiple routes. The route allocation plan further includes: robots corresponding to each of the N routes to be traveled, wherein each route in each route set to be traveled is a drivable route for the robot corresponding to the route set to be traveled; The method further comprises: Each set of routes to be traveled is assigned to the robot corresponding to the set of routes to be traveled.

5. The method for generating a driving route allocation plan according to any one of claims 1 to 4, characterized in that: The method further comprises: Obtaining an estimated driving time for each of the multiple driving routes; determining an actual driving time of each robot for each driving route based on a utilization rate of each robot in the robot set and an estimated driving time of each of the multiple driving routes; With the goal of minimizing the number of robots required, a driving route allocation plan is generated according to the utilization rate of each robot in the robot set and the required number of trips of each of the multiple driving routes, including: With the goal of minimizing the number of robots required, a driving route allocation plan is generated based on the actual driving time of each robot for each driving route and the required number of driving times for each of the multiple driving routes.

6. The method for generating a driving route allocation plan according to any one of claims 1 to 4, characterized in that: The constraints used to generate the driving route assignment plan include at least one of the following: The drivable route of each robot is the route within the physical space where the robot is located as a constraint; The constraint condition is that the travel time required for each set of routes to be traveled does not exceed the target time.

7. The method for generating a driving route allocation plan according to any one of claims 1 to 4, characterized in that: The route assignment is generated by solving the following integer linear programming equation: The objective function is: min∑ j ind j The constraints are: Among them, x ij The value of is 0 or 1, indicating whether the i-th driving route is sent to the j-th robot; L represents the set of multiple driving routes; T represents the set of robots; ind j The value of is 0 or 1, indicating whether the jth robot is used; M represents a large number; d ik Represents the travel frequency requirement of the i-th travel route.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the driving route allocation solution generating method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instruction is executed by a processor, the method for generating a driving route allocation plan according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instruction is executed by a processor, the method for generating a driving route allocation plan according to any one of claims 1 to 7 is implemented.

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