Unmanned vehicle intelligent scheduling method and device, intelligent terminal and storage medium

Abstract

The invention relates to the technical field of artificial intelligence, in particular to an unmanned vehicle intelligent scheduling method and device, an intelligent terminal and a storage medium. The method comprises the following steps: determining a reachable excavator of the unmanned vehicle according to a target operation area; determining a target operation excavator from the reachable excavators according to the position of the unmanned vehicle and the operation condition of the reachable excavators; and scheduling the unmanned vehicle according to the queuing point information corresponding to the target operation excavator. By adopting the method, the unmanned vehicle can be intelligently dispatched, the unmanned vehicle is coordinated to efficiently and safely complete operation tasks, and the overall operation efficiency of a mine is improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to an unmanned vehicle intelligent scheduling method, device, intelligent terminal and storage medium. Background Art

[0002] Green, intelligent, and digital mines are the future direction of mine construction. Unmanned systems for loading, hauling, and unloading are a key component and core technology. In mines where multiple unmanned vehicles are involved in loading, hauling, and unloading operations, the complex and ever-changing loading zones necessitate the intelligent dispatching of unmanned vehicles, coordinating their efficient and safe completion of tasks, and thereby improving overall mine efficiency. Summary of the Invention

[0003] In view of this, the embodiments of the present application provide an unmanned vehicle intelligent scheduling method, device, intelligent terminal and storage medium, which can intelligently schedule unmanned vehicles, coordinate unmanned vehicles to complete work tasks efficiently and safely, and improve the overall operating efficiency of the mine.

[0004] A first aspect of an embodiment of the present application provides an unmanned vehicle intelligent scheduling method, comprising:

[0005] Determine the excavator that the unmanned vehicle can reach based on the target operating area;

[0006] Determining a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators;

[0007] The unmanned vehicle is dispatched according to the queuing point information corresponding to the target operating excavator.

[0008] In a possible implementation of the first aspect, there is more than one reachable excavator, and the operating conditions of the reachable excavators include operating positions and operating capacities;

[0009] The step of determining a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators includes:

[0010] Determining the travel time for the unmanned vehicle to reach the operating position of the accessible excavator based on the position of the unmanned vehicle and the operating position of the accessible excavator;

[0011] Determining an estimated completion time for each reachable excavator to complete the work tasks of all vehicles in its work queue based on the work capacity of the reachable excavator and the work capacity of the vehicles in the work queue of the reachable excavator;

[0012] A target operating excavator is determined from the reachable excavators according to the travel time and the estimated completion time.

[0013] In a possible implementation of the first aspect, determining a target operating excavator from the reachable excavators based on the travel time and the estimated completion time includes:

[0014] When the driving time of the unmanned vehicle to reach the operating position of the reachable excavator is greater than or equal to the estimated completion time of the reachable excavator, the reachable excavator corresponding to the minimum driving time is determined as the target operating excavator;

[0015] When the driving time of the unmanned vehicle to reach the reachable excavator operating position is less than the estimated completion time of the reachable excavator, calculating the cost of the unmanned vehicle driving to each of the reachable excavator operating positions;

[0016] The reachable excavator corresponding to the minimum cost value is determined as the target operating excavator of the unmanned vehicle.

[0017] In a possible implementation of the first aspect, calculating the cost of the unmanned vehicle traveling to each of the reachable excavator operating positions includes:

[0018] Obtain the number of queue points and operating positions of the reachable excavator;

[0019] Based on the estimated completion time of the reachable excavator, the number of the queue points, and the number of operating positions, the cost of the unmanned vehicle traveling to each of the reachable excavator operating positions is calculated.

[0020] In a possible implementation of the first aspect, dispatching the unmanned vehicle according to the queuing point information corresponding to the target operating excavator includes:

[0021] Obtaining a position relationship diagram corresponding to the target operating excavator;

[0022] Determining the queuing point information of the target operating excavator according to the position relationship diagram corresponding to the target operating excavator;

[0023] The unmanned vehicle is dispatched based on the queuing point information.

[0024] In a possible implementation of the first aspect, the types of the queuing points include public queuing points and private queuing points, and dispatching the unmanned vehicle based on the queuing point information includes:

[0025] When the target excavator has a public queue point and a private queue point, and the public queue point is not empty, dispatch the vehicles in the public queue point to the private queue point of the target excavator, and dispatch the unmanned vehicle to the public queue point;

[0026] Alternatively, when there is only a private queuing point for the target operating excavator, the unmanned vehicle is dispatched to the private queuing point; if there is currently a queued vehicle at the private queuing point, the queued vehicle is dispatched to the operating position of the target operating excavator.

[0027] In a possible implementation of the first aspect, dispatching the unmanned vehicle based on the queuing point information includes:

[0028] If there is no queuing point for the target operating excavator, the unmanned vehicle is dispatched to travel to the operating position of the target operating excavator at a specified driving speed, wherein the specified driving speed is determined according to the operating progress of the target operating excavator.

[0029] A second aspect of the embodiments of the present application provides an unmanned vehicle intelligent dispatching device, the device comprising:

[0030] An initial determination unit, used to determine the reachable excavator of the unmanned vehicle based on the target operation area;

[0031] a target determination unit, configured to determine a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators;

[0032] The vehicle dispatching unit is used to dispatch the unmanned vehicle according to the queuing point information corresponding to the target operating excavator.

[0033] The third aspect of an embodiment of the present application provides an intelligent terminal, including a memory, a processor, and a computer program stored in the memory and runnable on the processor. When the processor executes the computer program, it implements the steps of the unmanned vehicle intelligent scheduling method provided in the first aspect of the embodiment of the present application.

[0034] The fourth aspect of the embodiments of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the steps of the unmanned vehicle intelligent scheduling method provided in the first aspect of the embodiments of the present application.

[0035] The fifth aspect of the embodiments of the present application provides a computer program product. When the computer program product is run on a terminal device, the terminal device executes the steps of the unmanned vehicle intelligent scheduling method described in the first aspect of the embodiments of the present application.

[0036] In an embodiment of the present application, the reachable excavators of the unmanned vehicle are determined according to the target operating area, and the target operating excavator is determined from the reachable excavators according to the position of the unmanned vehicle and the operating status of the reachable excavators. The queuing point information corresponding to the target operating excavator is taken into consideration, and the unmanned vehicle is intelligently dispatched to coordinate the unmanned vehicle to complete the operating task efficiently and safely when it reaches the operating area, thereby reducing the probability of the excavator waiting idle, thereby improving the overall operating efficiency of the mine. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0038] Figure 1 This is a flowchart of the implementation of the unmanned vehicle intelligent scheduling method provided in the embodiment of the present application;

[0039] Figure 2 This is a specific implementation flowchart of step S102 in the unmanned vehicle intelligent scheduling method provided in an embodiment of the present application;

[0040] Figure 2.1 This is a schematic diagram of a mine map in the unmanned vehicle intelligent scheduling method provided in an embodiment of the present application;

[0041] Figure 3 This is a specific implementation flowchart of determining a target operating excavator from reachable excavators in the unmanned vehicle intelligent scheduling method provided in an embodiment of the present application;

[0042] Figure 4 This is a specific implementation flow chart of calculating the cost value in the unmanned vehicle intelligent scheduling method provided in the embodiment of the present application;

[0043] Figure 4.1 This is a schematic diagram of a scenario in the unmanned vehicle intelligent scheduling method provided in an embodiment of the present application;

[0044] Figure 5 This is a specific implementation flowchart of step S103 in the unmanned vehicle intelligent scheduling method provided in an embodiment of the present application;

[0045] Figure 5.1 This is a schematic diagram of the position relationship in the unmanned vehicle intelligent scheduling method provided in an embodiment of the present application;

[0046] Figure 6 This is a structural block diagram of the unmanned vehicle intelligent dispatching device provided in an embodiment of the present application;

[0047] Figure 7This is a schematic diagram of a smart terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0048] In the following description, specific details such as specific device structures and techniques are provided for purposes of illustration rather than limitation to facilitate a thorough understanding of the embodiments of the present application. However, it will be apparent to those skilled in the art that the present application may be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid obscuring the description of the present application with unnecessary detail.

[0049] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0050] References to "one embodiment" or "some embodiments" in this specification mean that a particular feature, structure, or characteristic described in conjunction with that embodiment is included in one or more embodiments of the present application. Thus, phrases such as "in one embodiment," "in some embodiments," "in other embodiments," and "in other embodiments" appearing in various places in this specification do not necessarily refer to the same embodiment, but rather mean "one or more but not all embodiments," unless otherwise specifically emphasized. The terms "including," "comprising," "having," and variations thereof all mean "including but not limited to," unless otherwise specifically emphasized.

[0051] It should be understood that the various method embodiments of this application provide a method for intelligent dispatching of unmanned vehicles applicable to various types of intelligent terminals that require unmanned vehicle dispatching, specifically vehicle-mounted terminals, central control devices, servers, etc. This application does not impose any restrictions on the type of intelligent terminal.

[0052] The following is an illustrative description of the intelligent dispatching method for unmanned vehicles provided in this application with reference to specific embodiments.

[0053] Figure 1 The implementation process of the unmanned vehicle intelligent scheduling method provided in an embodiment of the present application is shown. The method process may include the following steps S101 to S103.

[0054] Step S101: Determine the reachable excavator of the unmanned vehicle according to the target operation area.

[0055] A reachable excavator is an excavator operating in the target operating area that is reachable by an unmanned vehicle. The aforementioned unmanned vehicle is an unmanned vehicle to be dispatched.

[0056] In this embodiment, the reachable excavators of the unmanned vehicle are determined based on the target operation area of ​​the unmanned vehicle. There are one or more excavators in the same target operation area, and the reachable excavators corresponding to the unmanned vehicle may be more than one.

[0057] In one possible implementation, the target operating area is determined based on the mine's daily production task, and the excavator and operating area are determined based on the production plan and blasting plan in the daily production task. The mine's daily production task can be determined based on the mine's production plan.

[0058] In one possible implementation, when an unmanned vehicle dispatch request is detected, the target operating area corresponding to the unmanned vehicle is determined based on the unmanned vehicle dispatch request and combined with the mine's daily production tasks, and then the reachable excavator of the unmanned vehicle is determined from the target operating area.

[0059] In some implementations, excavators in the target operation area may be screened based on the task type in the unmanned vehicle dispatch request, and excavators whose operation types match the task type may be determined as reachable excavators for the unmanned vehicle.

[0060] In this embodiment, a preliminary screening is performed on the excavators in the target operation area to determine the excavators that can be reached by the unmanned vehicle. This can avoid scheduling failures caused by the unmanned vehicle being unable to drive to the excavator, and indirectly ensure the effectiveness of the unmanned vehicle scheduling.

[0061] Step S102: determining a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators.

[0062] In this embodiment, to ensure rapid loading upon arrival at the target operation area and minimize the probability of idle excavators, the unmanned vehicle's current location and the operating status of accessible excavators are combined to determine the target excavator for the unmanned vehicle. The target excavator is the excavator accessible to the unmanned vehicle for the target operation. There is only one target excavator. The operating status of the accessible excavator includes its operating status, operation progress, and the number of vehicles in the operation queue.

[0063] As a possible implementation of the present application, when there is more than one reachable excavator, Figure 2 A specific implementation process of determining a target operating excavator from the reachable excavators according to the position of the unmanned vehicle and the operating status of the reachable excavators in the method provided in an embodiment of the present application is shown, and is detailed as follows:

[0064] A1: Determine the travel time for the unmanned vehicle to reach the accessible excavator's operating position based on the position of the unmanned vehicle and the operating position of the accessible excavator. The operating position information is the vehicle loading / unloading operating position, and the same accessible excavator may have multiple operating positions.

[0065] In one possible implementation, a route for the unmanned vehicle to the accessible excavator is planned based on the unmanned vehicle's current location and the operating location of the accessible excavator, combined with mine map information. The mine map information includes road network information and operating area boundary information. The road network information includes a reference path for the unmanned vehicle's autonomous driving within the mine; the operating area boundary information includes the boundary information of the area within the mine where the unmanned vehicle can drive.

[0066] like Figure 2.1 As shown, the mine map includes a road network and area boundaries. Based on the location of the unmanned vehicle and the operating locations of accessible excavators in the target operating area, combined with the road network information and area boundary information, a driving path for the unmanned vehicle to reach the accessible excavators is planned. Based on the unmanned vehicle's speed and driving path, the driving time for the unmanned vehicle to reach the accessible excavator's operating location is calculated. The driving speed can be a preset speed for the unmanned vehicle.

[0067] In this embodiment, the driving speed of the unmanned vehicle may be different depending on the driving path.

[0068] In some embodiments, the road network information also includes speed limit information. The driving time for the unmanned vehicle to reach the reachable excavator operating position is calculated by combining the driving speed, the driving path, and the speed limit information on the path.

[0069] A2: Based on the operating capabilities of the reachable excavator and the operating capabilities of the vehicles in the reachable excavator's operation queue, determine the estimated completion time for each reachable excavator to complete the operation tasks of all vehicles in its operation queue. The operating capabilities of the reachable excavator include digging and loading capabilities, which can be specifically expressed as digging and loading speed. The operating capabilities of the vehicle include loading capabilities, which can be specifically expressed as loading speed. The operating capabilities of the reachable excavator and the vehicle are preset. The operation queue of the reachable excavator refers to the unmanned vehicles that are bound to the reachable excavator for operation.

[0070] In this embodiment, the theoretical completion time of a vehicle is calculated based on the operating capacity of the accessible excavator and the operating capacity of the vehicle. The theoretical completion time is combined with the number of vehicles in the operation queue of the accessible excavator to determine the estimated completion time for each accessible excavator to complete the operation tasks of all vehicles in its operation queue.

[0071] A3: Determine a target operating excavator from the reachable excavators based on the travel time and the estimated completion time.

[0072] As a possible implementation of this application, Figure 3 A specific implementation process of determining a target operating excavator from the reachable excavators according to the travel time and the estimated completion time in the method provided in an embodiment of the present application is shown, and is detailed as follows:

[0073] B1: When the driving time of the unmanned vehicle to reach the operating position of the reachable excavator is greater than or equal to the estimated completion time of the reachable excavator, the reachable excavator corresponding to the minimum driving time is determined as the target operating excavator.

[0074] In this embodiment, the travel time of the unmanned vehicle to each accessible excavator in the target operation area is calculated, and the estimated completion time of each accessible excavator in the target operation area is calculated. The travel time of the unmanned vehicle to each accessible excavator is compared with the estimated completion time of each accessible excavator. If the travel time of the unmanned vehicle to the operating location of each accessible excavator is greater than or equal to the estimated completion time of the accessible excavator, the accessible excavator corresponding to the minimum travel time is selected as the target operation excavator.

[0075] For example, when there are three reachable excavators A, B, and C in the target work area, the driving time A, driving time B, and driving time C of the unmanned vehicle to work position A, work position B, and work position C are determined, and the estimated completion time A, estimated completion time B, and estimated completion time C of A, B, and C are determined, respectively. When driving time A is greater than or equal to the estimated completion time A, driving time B is greater than or equal to the estimated completion time B, and driving time C is greater than or equal to the estimated completion time C, the reachable excavator corresponding to the smallest driving time among driving time A, driving time B, and driving time C is determined as the target working excavator. For example, if driving time A is the smallest, reachable excavator A is determined as the target working excavator.

[0076] B2: When the driving time of the unmanned vehicle to reach the reachable excavator operating position is less than the estimated completion time of the reachable excavator, the cost of the unmanned vehicle driving to each reachable excavator operating position is calculated.

[0077] B3: Determine the reachable excavator corresponding to the minimum cost value as the target operating excavator for the unmanned vehicle.

[0078] When the driving time of the unmanned vehicle to reach the reachable excavator operating position is less than the estimated completion time of the reachable excavator, the cost of the unmanned vehicle traveling to each of the reachable excavator operating positions is calculated, and the reachable excavator corresponding to the minimum cost is determined as the target operating excavator for the unmanned vehicle.

[0079] If the travel time required for the unmanned vehicle to reach the accessible excavator's operating location is less than the estimated completion time of the accessible excavator, this means that when the unmanned vehicle arrives at the operating location, there are vehicles waiting in line for loading operations in the accessible excavator's operating area. In this case, the unmanned vehicle to be dispatched must wait in line. In this embodiment, the cost value is calculated to determine the most suitable queue for the unmanned vehicle to wait in, thereby minimizing idle waiting time and improving operational efficiency.

[0080] As a possible implementation of this application, Figure 4 A specific implementation process for calculating the cost of the unmanned vehicle traveling to each of the reachable excavator operating positions in the method provided in the embodiment of the present application is shown, and is detailed as follows:

[0081] C1: Obtain the number of queuing points and work locations for the accessible excavator. Generally, any switch point that does not affect main road transportation can be used as a queuing point for the vehicle. The number of queuing points and work locations can be customized by the user. Queuing points and work locations are planned based on the accessible excavator's work location and the reference path for the unmanned vehicle to reach the accessible excavator. The number of queuing points and work locations corresponding to accessible excavators in different locations may vary.

[0082] In a possible implementation, a queuing area for the reachable excavator is planned according to the operating position of the reachable excavator and a reference path for the unmanned vehicle to reach the reachable excavator, and the number of queuing points is determined based on the queuing area.

[0083] For example, Figure 4.1 As shown, on the loading route, the queue area A is planned according to the working position A, and the queue area B is planned according to the working position B.

[0084] C2: Based on the estimated completion time of the reachable excavator, the number of queue points, and the number of work locations, calculate the cost of the unmanned vehicle traveling to each of the reachable excavator work locations.

[0085] In one possible implementation, the cost F of the accessible excavator i is calculated according to the following formula (1): i :

[0086] F i =T Si / C(M i +L i ) (1)

[0087] Where, represents the estimated completion time of the excavator i, M i represents the number of queue points that can reach excavator i, L i represents the number of working positions that can be reached by excavator i, and C is a constant.

[0088] In this embodiment, the cost of each reachable excavator is calculated according to the above formula (1), and the reachable excavator with the smallest cost is determined as the target operating excavator of the unmanned vehicle.

[0089] In an embodiment of the present application, a cost value is calculated based on the estimated completion time, the number of queue points, and the number of working positions of the reachable excavators, and then the reachable excavators in the target working area are further screened based on the cost value to determine the reachable excavator that is most suitable for the unmanned vehicle. The unmanned vehicle can be effectively dispatched and coordinated to complete the working tasks efficiently and safely.

[0090] Step S103: dispatching the unmanned vehicle according to the queue point information corresponding to the target operating excavator.

[0091] In this embodiment, the unmanned vehicle is intelligently dispatched based on the queue point information corresponding to the target operating excavator.

[0092] As a possible implementation of this application, Figure 5 The following is a specific implementation process of dispatching the unmanned vehicle according to the queue point information corresponding to the target excavator in the method provided in the embodiment of the present application, which is detailed as follows:

[0093] D1: Obtain a position relationship diagram corresponding to the target excavator; the position relationship diagram is used to identify the position relationship between the target excavator's operating position and the queue point. The position relationship diagram identifies the queue point corresponding to the target excavator.

[0094] In one possible implementation, a position relationship diagram can be established based on the operating position of the accessible excavator, the reverse parking switch point, and the queuing area. The reverse parking switch point is a parking position that does not affect the unloading route. The position relationship diagram can reflect the queuing point information.

[0095] In this embodiment, the excavator's operating position can be set based on the actual on-site operation conditions. After the excavator's operating position is determined, the excavator's reverse parking switch point is defined based on the driving path independently planned by the unmanned vehicle's autonomous driving system and the reference path of the road network information. Reverse parking switch points that do not affect main road transportation can be used as vehicle queuing points.

[0096] For example, taking excavator loading as an example, Figure 5.1As shown, work points A, B, and C are the loading positions of excavators A, B, and C. Queuing points P1, P2, P3, P6, P7, P8, and P9 are the queuing points in the queuing area of ​​excavator C, of ​​which P1, P2, and P3 are private queuing points for excavator C, and T1 is the switching point for reversing into the warehouse for excavator C. Queuing points P4, P5, P6, P7, P8, and P9 are the queuing points in the queuing area of ​​excavator B, of which P4 and P5 are private queuing points for excavator B, and T2 is the switching point for reversing into the warehouse for excavator B. Queuing points P8 and P9 are the queuing points in the queuing area of ​​excavator A, and T3 is the switching point for reversing into the warehouse for excavator A.

[0097] D2: Determine the queuing point information of the target excavator based on the position relationship diagram corresponding to the target excavator. The queuing point information includes the location of the queuing point, the type of queuing point, the availability of the queuing point, etc. The types of queuing points include private queuing points and public queuing points.

[0098] D3: Dispatching the unmanned vehicle based on the queuing point information.

[0099] In one possible implementation, when all queue points are idle, the unmanned vehicle is preferentially dispatched to the private queue point of the target operating excavator; when the private queue point is not empty and there is a public queue point for the target operating excavator, the unmanned vehicle is dispatched to the public queue point of the target operating excavator.

[0100] In one possible implementation, when the target excavator has both a public and private queue point, and the public queue point is not empty, vehicles queued at the public queue point are dispatched to the target excavator's private queue point, and the unmanned vehicle is dispatched to the public queue point. In this scenario, if the private queue point is also not empty, vehicles queued at the private queue point are dispatched to the target excavator's operating position. In other words, unmanned vehicles are dispatched in a reciprocal manner.

[0101] In a possible implementation, when there is only a private queuing point for the target operating excavator, the unmanned vehicle is dispatched to the private queuing point; if there is currently a queued vehicle at the private queuing point, the queued vehicle is dispatched to the operating position of the target operating excavator.

[0102] In one possible implementation, if there is no queue point for the target excavator, the unmanned vehicle is dispatched to travel to the operating position of the target excavator at a specified speed, wherein the specified speed is determined according to the operating progress of the target excavator. Specifically,

[0103] In this embodiment, when a dispatch vehicle arrives at the target excavator's operating location, it is instructed to travel at a specified speed. This specified speed can be determined based on the progress of the work at that location. The specified speed is positively correlated with the progress of the work. The faster the progress, the faster the specified speed. Conversely, the slower the progress, the slower the specified speed. By controlling the vehicle's speed, waiting time is minimized and dispatched unmanned vehicles are prevented from being left stranded.

[0104] In an embodiment of the present application, the position relationship diagram of the target operating excavator is combined to determine the queuing point information, and then the unmanned vehicle is reasonably and intelligently dispatched based on the queuing point information to avoid affecting the operation while ensuring that the unmanned vehicle has somewhere to go, so as to ensure that the operation task is carried out safely and efficiently as much as possible and reduce the probability of the excavator waiting idle.

[0105] As can be seen from the above, by determining the reachable excavators of the unmanned vehicle according to the target operating area, determining the target operating excavator from the reachable excavators according to the position of the unmanned vehicle and the operating conditions of the reachable excavators, and considering the queuing point information corresponding to the target operating excavator, the unmanned vehicle is intelligently dispatched, and coordinated to complete the operating tasks efficiently and safely when the unmanned vehicle reaches the operating area, reducing the probability of the excavator waiting idle, thereby improving the overall operating efficiency of the mine.

[0106] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0107] Corresponding to the unmanned vehicle intelligent dispatching method described in the above embodiment, Figure 6 A structural block diagram of the unmanned vehicle intelligent dispatching device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.

[0108] Reference Figure 6 The device is applied to an intelligent terminal and includes: an initial determination unit 61, a target determination unit 62, and a vehicle dispatching unit 63, wherein:

[0109] An initial determination unit 61 is used to determine the reachable excavator of the unmanned vehicle according to the target operation area;

[0110] a target determination unit 62 for determining a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators;

[0111] The vehicle dispatching unit 63 is configured to dispatch the unmanned vehicle according to the queue point information corresponding to the target operating excavator.

[0112] As a possible implementation of the present application, there is more than one reachable excavator, and the target determination unit 62 includes:

[0113] A travel time determination module, configured to determine the travel time for the unmanned vehicle to reach the operating position of the reachable excavator based on the position of the unmanned vehicle and the operating position of the reachable excavator;

[0114] a completion time determination module, configured to determine an estimated completion time for each reachable excavator to complete the operation tasks of all vehicles in its operation queue based on the operation capacity of the reachable excavator and the operation capacity of the vehicles in the operation queue of the reachable excavator;

[0115] The target excavator determination module is used to determine a target operating excavator from the reachable excavators according to the travel time and the estimated completion time.

[0116] As a possible implementation of the present application, the target excavator determination module includes:

[0117] A first determination submodule is configured to, when the driving time of the unmanned vehicle to reach the operating position of the reachable excavator is greater than or equal to the estimated completion time of the reachable excavator, determine the reachable excavator corresponding to the minimum driving time as the target operating excavator;

[0118] The second determination submodule is configured to calculate the cost of the unmanned vehicle traveling to each of the reachable excavator operating locations when the driving time of the unmanned vehicle to reach the reachable excavator operating location is less than the estimated completion time of the reachable excavator; and determine the reachable excavator corresponding to the minimum cost as the target operating excavator for the unmanned vehicle.

[0119] As a possible implementation manner of the present application, the second determining submodule is further configured to:

[0120] Obtain the number of queue points and operating positions of the reachable excavator;

[0121] Based on the estimated completion time of the reachable excavator, the number of the queue points, and the number of operating positions, the cost of the unmanned vehicle traveling to each of the reachable excavator operating positions is calculated.

[0122] As a possible implementation of the present application, the vehicle dispatching unit 63 includes:

[0123] A position relationship diagram acquisition module, configured to acquire a position relationship diagram corresponding to the target operating excavator;

[0124] a queuing point information determination module, configured to determine the queuing point information of the target operating excavator according to a position relationship diagram corresponding to the target operating excavator, wherein the position relationship diagram includes the queuing point information of the target operating excavator;

[0125] The unmanned vehicle scheduling module is used to schedule the unmanned vehicle based on the queuing point information.

[0126] As a possible implementation of the present application, the types of the above-mentioned queuing points include public queuing points and private queuing points, and the above-mentioned unmanned vehicle scheduling module is used to:

[0127] When the target excavator has a public queue point and a private queue point, and the public queue point is not empty, the vehicles in the public queue point are dispatched to the private queue point of the target excavator, and the unmanned vehicle is dispatched to the public queue point.

[0128] Alternatively, when there is only a private queuing point for the target operating excavator, the unmanned vehicle is dispatched to the private queuing point; if there is currently a queued vehicle at the private queuing point, the queued vehicle is dispatched to the operating position of the target operating excavator.

[0129] As a possible implementation of the present application, the unmanned vehicle dispatching module is further configured to:

[0130] If there is no queuing point for the target operating excavator, the unmanned vehicle is dispatched to travel to the operating position of the target operating excavator at a specified driving speed, wherein the specified driving speed is determined according to the operating progress of the target operating excavator.

[0131] In an embodiment of the present application, the reachable excavators of the unmanned vehicle are determined according to the target operating area, and the target operating excavator is determined from the reachable excavators according to the position of the unmanned vehicle and the operating status of the reachable excavators. The queuing point information corresponding to the target operating excavator is taken into consideration, and the unmanned vehicle is intelligently dispatched to coordinate the unmanned vehicle to complete the operating task efficiently and safely when it reaches the operating area, thereby reducing the probability of the excavator waiting idle, thereby improving the overall operating efficiency of the mine.

[0132] The embodiment of the present application further provides a computer-readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the following Figures 1 to 5 The steps of any unmanned vehicle intelligent scheduling method are represented.

[0133] The embodiment of the present application also provides an intelligent terminal, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, Figures 1 to 5 The steps of any unmanned vehicle intelligent scheduling method are represented.

[0134] The embodiment of the present application also provides a computer program product, which, when executed on a terminal device, enables the terminal device to execute the following Figures 1 to 5The steps of any unmanned vehicle intelligent scheduling method are represented.

[0135] Figure 7 Schematic diagram of a smart terminal provided by an embodiment of the present application. Figure 7 As shown, the intelligent terminal 7 of this embodiment includes: a processor 70, a memory 71, and a computer program 72 stored in the memory 71 and executable on the processor 70. When the processor 70 executes the computer program 72, the steps in the above-mentioned embodiments of the intelligent dispatching method for unmanned vehicles are implemented, such as Figure 1 Alternatively, when the processor 70 executes the computer program 72, the functions of the modules / units in the above-mentioned device embodiments are realized, for example, Figure 6 The functions of the units 61 to 63 are shown.

[0136] The computer program 72 may be divided into one or more modules / units, which are stored in the memory 71 and executed by the processor 70 to implement the present application. The one or more modules / units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 72 in the smart terminal 7.

[0137] The processor 70 may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0138] The memory 71 can be an internal storage unit of the smart terminal 7, such as a hard disk or memory of the smart terminal 7. The memory 71 can also be an external storage device of the smart terminal 7, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the smart terminal 7. Furthermore, the memory 71 can also include both an internal storage unit of the smart terminal 7 and an external storage device. The memory 71 is used to store the computer program and other programs and data required by the smart terminal. The memory 71 can also be used to temporarily store data that has been output or is about to be output.

[0139] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned device can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0140] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0141] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0142] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0143] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules or units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0144] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0145] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0146] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program, when executed by the processor, can implement the steps of the above-mentioned various method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0147] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. An intelligent dispatching method for unmanned vehicles, characterized in that: The method comprises: Determine the excavator that the unmanned vehicle can reach based on the target operating area; Determining a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators; The unmanned vehicle is dispatched according to the queuing point information corresponding to the target operating excavator.

2. The method according to claim 1, wherein There is more than one reachable excavator, and the operating conditions of the reachable excavator include operating position and operating capacity; The step of determining a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators includes: Determining the travel time for the unmanned vehicle to reach the operating position of the accessible excavator based on the position of the unmanned vehicle and the operating position of the accessible excavator; Determining an estimated completion time for each reachable excavator to complete the work tasks of all vehicles in its work queue based on the work capacity of the reachable excavator and the work capacity of the vehicles in the work queue of the reachable excavator; A target operating excavator is determined from the reachable excavators according to the travel time and the estimated completion time.

3. The method according to claim 2, wherein The determining of a target operating excavator from the reachable excavators based on the travel time and the estimated completion time includes: When the driving time of the unmanned vehicle to reach the operating position of the reachable excavator is greater than or equal to the estimated completion time of the reachable excavator, the reachable excavator corresponding to the minimum driving time is determined as the target operating excavator; When the driving time of the unmanned vehicle to reach the reachable excavator operating position is less than the estimated completion time of the reachable excavator, calculating the cost of the unmanned vehicle driving to each of the reachable excavator operating positions; The reachable excavator corresponding to the minimum cost value is determined as the target operating excavator of the unmanned vehicle.

4. The method according to claim 3, wherein The calculating of the cost of the unmanned vehicle traveling to each of the reachable excavator operating positions includes: Obtain the number of queue points and operating positions of the reachable excavator; Based on the estimated completion time of the reachable excavator, the number of the queue points, and the number of operating positions, the cost of the unmanned vehicle traveling to each of the reachable excavator operating positions is calculated.

5. The method according to any one of claims 1 to 4, characterized in that The step of dispatching the unmanned vehicle according to the queue point information corresponding to the target excavator includes: Obtaining a position relationship diagram corresponding to the target operating excavator; Determining the queuing point information of the target operating excavator according to the position relationship diagram corresponding to the target operating excavator; The unmanned vehicle is dispatched based on the queuing point information.

6. The method according to claim 5, wherein The types of the queuing points include public queuing points and private queuing points. The dispatching of the unmanned vehicle based on the queuing point information includes: When the target excavator has a public queue point and a private queue point, and the public queue point is not empty, dispatch the vehicles in the public queue point to the private queue point of the target excavator, and dispatch the unmanned vehicle to the public queue point; Alternatively, when there is only a private queuing point for the target operating excavator, the unmanned vehicle is dispatched to the private queuing point; if there is currently a queued vehicle at the private queuing point, the queued vehicle is dispatched to the operating position of the target operating excavator.

7. The method according to claim 5, wherein The dispatching of the unmanned vehicle based on the queuing point information includes: If there is no queuing point for the target operating excavator, the unmanned vehicle is dispatched to travel to the operating position of the target operating excavator at a specified driving speed, wherein the specified driving speed is determined according to the operating progress of the target operating excavator.

8. An intelligent dispatching device for unmanned vehicles, characterized in that: The device comprises: An initial determination unit, used to determine the reachable excavator of the unmanned vehicle based on the target operation area; a target determination unit, configured to determine a target operating excavator from the reachable excavators based on the position of the unmanned vehicle and the operating conditions of the reachable excavators; The vehicle dispatching unit is used to dispatch the unmanned vehicle according to the queuing point information corresponding to the target operating excavator.

9. An intelligent terminal comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the unmanned vehicle intelligent scheduling method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the unmanned vehicle intelligent scheduling method according to any one of claims 1 to 7 are implemented.

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