Multi-layer finite state machine and state machine switching method for unmanned vehicles in open-pit mines

Abstract

The present invention discloses a multi-layer finite state machine and a state machine switching method for unmanned vehicles in open-pit mines. The finite state machine includes a task planning layer, a behavior decision layer, and a motion control layer; the task planning layer is used to pre-formulate task files and trajectory files of the unmanned vehicle according to the production operation process and operation specifications of the mining area; the behavior decision layer is used to automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode according to the task file and trajectory file; the motion control layer is used to execute or stop the state switching action of the unmanned vehicle under the behavior decision layer according to the control instruction. The multi-layer finite state machine jump state of the present invention is easy to maintain and the operation logic is clear. It is easy to add and delete states and state layers. It has good maintainability, scalability and reusability. It is suitable for unmanned vehicle driving on non-structured roads in mining areas, improves the degree of automation of mining operations and transportation efficiency, and eliminates personnel safety risks.

Description

Technical Field

[0001] The present invention relates to the field of unmanned driving technology, and in particular to a multi-layer finite state machine and a state machine switching method for an unmanned vehicle in an open-pit mine. Background Art

[0002] At present, in an actual production process in an open-pit mine, mining vehicles need to travel in different operating areas and perform different operating tasks, such as light-load driving, heavy-load driving, loading, unloading, etc. The requirements for unmanned vehicles in the mine area have been expanded from automatic driving to automatic operation, realizing the automation of mine production and further realizing the intelligence of the mine area.

[0003] In addition to driving in the mine area, unmanned vehicles in the mine area also need to perform different tasks. Therefore, unmanned vehicles in the mine area not only need to perform the function of autonomous driving, but also automatically perform tasks such as loading and unloading. Simple autonomous driving technology cannot meet the needs, and a set of work strategies including autonomous driving technology, remote control driving, and switching between operating states is required. In this process, autonomous driving is the foundation, and different tasks are performed on this basis.

[0004] Due to the dual influence of the complexity of the roads in the mining area and the wide variety of operating tasks in the mining area, the states of the unmanned vehicles in the mining area include various driving states and operating states. The state machine used by conventional unmanned vehicles only involves the driving state and does not exist in the operating state, and it is impossible to realize the automation of operating tasks such as loading and unloading of mining vehicles. In addition, the existing state machine for unmanned vehicles places all states on the same layer, which easily leads to complicated and unclear jump relationships between states. If all states are in a layer and a state is added or deleted, the jump of all states connected to it will be affected, and there are problems such as difficult maintenance and inconvenient state expansion. Therefore, due to the specific application scenarios and operating tasks in the mining area, the existing state machine for unmanned vehicles is difficult to use on unmanned vehicles in mining areas. Summary of the invention

[0005] In response to the problems existing in the prior art, one of the objects of the present invention is to provide a multi-layer finite state machine for unmanned vehicles in mining areas that can be applied to unstructured roads in mining areas, realize the automated operation functions of unmanned vehicles in mining areas, improve the operating efficiency of unmanned vehicles in mining areas, and reduce the difficulty of maintenance and expansion.

[0006] Another object of the present invention is to provide a state machine switching method for a multi-layer finite state machine of an unmanned vehicle in a mining area.

[0007] The third object of the present invention is to provide an unmanned vehicle for use in mining areas.

[0008] To achieve the above-mentioned object, a first aspect of the present invention provides a multi-layer finite state machine for an unmanned vehicle in a mining area, comprising a task planning layer, a behavior decision layer and a motion control layer;

[0009] The task planning layer is used to pre-formulate the task files and trajectory files of the unmanned vehicle according to the production operation process and operation specifications of the mining area;

[0010] The behavior decision layer is used to automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode according to the task file and the trajectory file;

[0011] The motion control layer is used to execute or stop the state switching action of the unmanned vehicle under the behavior decision layer according to the control instruction and control the unmanned vehicle to execute the corresponding action behavior according to the action behavior decision of the behavior decision layer.

[0012] Furthermore, the behavior decision layer includes a driving mode layer, a task process layer and an action behavior layer;

[0013] The driving mode layer is used to control the unmanned vehicle to switch between manual driving mode, remote control driving mode and unmanned driving mode according to control instructions;

[0014] The task process layer is used to control the unmanned vehicle to jump between the moving state, the pause state and the terminated state according to the control instruction when the unmanned vehicle is in the unmanned driving mode;

[0015] The action behavior layer is used to automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode according to the task file and the trajectory file when the unmanned vehicle is in a motion state in the unmanned driving mode.

[0016] Furthermore, the action behavior layer includes a condition judgment layer, a driving state layer and an operation state layer;

[0017] The condition judgment layer is used to compare and judge based on the condition data sensed by the unmanned vehicle and the jump trigger data recorded in the task entry in the task file, and control the unmanned vehicle to jump between the driving state under the driving state layer and the working state under the working state layer according to the comparison result.

[0018] Furthermore, the task file records a plurality of task entries in accordance with the execution order of the production operation process of the unmanned vehicle in the mining area, wherein each task entry contains action type information and the jump trigger data.

[0019] Furthermore, the jump trigger data includes time trigger data, event trigger data and location trigger data.

[0020] Furthermore, the action task is divided into a transport action task, a stop action task and an unloading action task according to the action type information, wherein the transport action task also includes the name information of the track file, and the track file records the driving track data of the transport action task.

[0021] A second aspect of the present invention provides a state machine switching method, using the multi-layer finite state machine described in the first aspect, and the state machine switching method comprises the following steps:

[0022] Pre-formulate the task file and trajectory file of the unmanned vehicle in the task planning layer according to the production operation process and operation specifications of the mining area;

[0023] Automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode at the behavior decision layer according to the task file and the trajectory file;

[0024] Execute or stop the state switching action of the unmanned vehicle under the behavior decision layer according to the control instruction.

[0025] Furthermore, it also includes:

[0026] Control the unmanned vehicle to switch between manual driving mode, remote control driving mode and unmanned driving mode according to control instructions;

[0027] When the unmanned vehicle is in the unmanned driving mode, the unmanned vehicle is controlled to jump between the moving state, the pause state and the end state according to the control instructions;

[0028] When the unmanned vehicle is in a moving state in the unmanned driving mode, the action behavior decision of the unmanned vehicle in the unmanned driving mode is automatically controlled according to the task file and the trajectory file.

[0029] Furthermore, it also includes:

[0030] A comparison is made between the condition data sensed by the unmanned vehicle and the jump trigger data recorded in the task entry in the task file, and the unmanned vehicle is controlled to jump between the driving state under the driving state layer and the operating state under the operating state layer according to the comparison result.

[0031] A third aspect of the present invention provides an unmanned vehicle for use in an open-pit mine, comprising the multi-layer finite state machine described in the first aspect.

[0032] The multi-layer finite state machine of the present invention is divided into three layers of task planning, behavior decision-making and motion control in combination with the requirements of mining operations. The jump state is easy to maintain and the operation logic is clear. It is easy to add and delete states and state layers. It has good maintainability, scalability and reusability. It is suitable for unmanned vehicle driving on non-structured roads in mining areas, improves the degree of automation of mining operations and transportation efficiency, and eliminates personnel safety risks.

[0033] It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. 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 creative work.

[0035] Figure 1 This is a schematic diagram of the structure of a multi-layer finite state machine for an unmanned vehicle in an open-pit mine according to an embodiment of the present invention;

[0036] Figure 2 The figure is a flow chart of a multi-layer finite state machine switching method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present invention will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0038] In addition, the described features, structures or characteristics may be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present invention. However, those skilled in the art will appreciate that the technical solution of the present invention can be practiced without one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid blurring various aspects of the present invention.

[0039] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0040] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0041] Figure 1 The structure diagram of a multi-layer finite state machine for an unmanned vehicle in an open-pit mine according to an embodiment of the present invention is schematically shown.

[0042] like Figure 1 As shown, the multi-layer finite state machine for unmanned vehicles in mining areas of the present invention includes a task planning layer 10, a behavior decision layer 11 and a motion control layer 12;

[0043] The task planning layer 10 is used to pre-formulate the task files and trajectory files of the unmanned vehicle according to the production operation process and operation specifications of the mining area. The function of the task planning layer 10 is to make a rough plan for the operation tasks and operation processes before a single unmanned vehicle is dispatched. The task planning layer 10 can be uniformly controlled by the cloud control platform, and the unmanned vehicles in the mining area are uniformly dispatched according to the production operation process and production operation specifications of the open-pit mining area. The task files and trajectory files are prepared before each unmanned vehicle is dispatched. The specific composition of the task files and trajectory files is shown in Tables 1 and 2. The platform sends the planned task files and trajectory files to the corresponding unmanned vehicles.

[0044] The behavior decision layer 11 is used to automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode according to the task file and the trajectory file. During the operation of the unmanned vehicle, the behavior decision layer 11 makes behavior decisions for the unmanned vehicle according to the pre-set operation process, the change of the behavior state triggered by time, events, locations, manual factors, etc., and completes the automated operation through the jump of the behavior state.

[0045] The motion control layer 12 is used to execute or stop the state switching action of the unmanned vehicle under the behavior decision layer 11 according to the control instruction and control the unmanned vehicle to execute the corresponding action behavior according to the action behavior decision of the behavior decision layer. The motion control layer 12 controls the unmanned vehicle accordingly based on the state switching action of the unmanned vehicle under the behavior decision layer 11. For example, the unmanned vehicle is automatically controlled to "self-check", "start", "park", "standby", "reverse", "terminate", etc. In view of the production operation process and production operation specifications of the mining area, automatic control such as "light load driving", "heavy load driving", and "unloading" can also be performed.

[0046] In one embodiment of the present invention, the behavior decision layer 11 includes a driving mode layer 111 , a task process layer 112 and an action behavior layer 113 .

[0047] The driving mode layer 111 is used to control the unmanned vehicle to switch between manual driving mode, remote control driving mode and unmanned driving mode according to the control command. The driving mode layer 111 can switch between three driving modes: manual driving mode, unmanned driving mode and remote control driving mode. At present, the production operation in the mining area is manually driven. In order to adapt to the existing production work arrangement in the mining area, the manual driving mode is adapted in the driving mode layer. In specific application scenarios and safety operation needs, it can be switched to manual driving mode and the vehicle can be driven manually. In order to ensure the safety of the automated operation of unmanned vehicles in the mining area, on the basis of the realization of automatic driving by the unmanned vehicle, in order to cope with emergencies, the redundant configuration can be remotely controlled by the remote safety officer to ensure that the unmanned vehicle can still operate safely in the face of undefined situations of the finite state machine of unmanned driving, such as sudden vehicle damage, changes in operating scenarios and other situations. In the driving mode layer 111, the default driving mode is unmanned driving, and the driving mode control authority priority is manual driving> remote control driving mode> unmanned driving mode. The driving mode can be switched through the intervention of the cloud control platform or manual intervention. The manual intervention behaviors include: 1. The accelerator pedal is pressed down by 5%; 2. The brake pedal is pressed down by 5%; 3. Operating the gear lever to shift gears; 4. The steering wheel wire control instructions and feedback are inconsistent, etc. The above manual intervention behaviors are only examples for illustration, and the present invention is not limited to this.

[0048] The task process layer 112 is used to control the unmanned vehicle to jump between the motion state, the pause state and the termination state according to the control command when the unmanned vehicle is in the unmanned driving mode. That is, in the unmanned driving mode, the flow from the driving mode layer 111 to the task process layer 112 controls the overall operation process and controls the unmanned vehicle to switch the motion state. The basic states of the task process layer 112 are the motion state (autonomous driving, working state), the pause state and the termination state (power off in the parking lot of the mining area). The motion state switching can be switched through the intervention of the operation control platform or the intervention of manual remote control. The terminal control can also continue to expand the HMI interactive control. The remote control driving can be realized by the remote cockpit, or it can be interactively controlled by the on-site personnel using the handle. The present invention is not limited to this. Movement, suspension and termination are uniformly scheduled by the mining area cloud control scheduling platform. This is a task process related to the production scheduling and scheduling of mining operations, and it is also a special embodiment of the mining area.

[0049] The action behavior layer 113 is used to automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode according to the task file and the trajectory file when the unmanned vehicle is in the motion state in the unmanned driving mode. When the unmanned vehicle is in the unmanned driving mode and in the motion state, it flows to the action behavior layer 113 to control the action, and the state jumps according to the conditions and sequence recorded in the task file and the trajectory file. The action behavior layer 113 is divided into a condition judgment layer, a driving state layer, and an operating state layer according to the state and the jump condition. The condition judgment layer is used to compare and judge according to the condition data sensed by the unmanned vehicle and the jump trigger data recorded in the task item in the task file, and control the unmanned vehicle to jump between the driving state in the driving state layer and the operating state in the operating state layer according to the comparison result. The driving state layer includes "start", "park", "standby", "reverse", "light load driving", "heavy load driving", etc., and jumps to each other according to the task item conditions and sequence recorded in the task file. The action behavior layer 113 can be expanded and maintained. For example, "start" can be further subdivided into "start on flat road" and "start on slope road". Other driving states such as driving states involving road rights can be added to the driving state. As long as the layering and the jump conditions within the layer are clearly defined, the expansion and maintenance are very flexible. Only the corresponding task items and jump conditions of the task file need to be modified.

[0050] In one embodiment of the present invention, the task file records multiple task entries in the order of execution of the production operation process of the unmanned vehicle in the mining area, wherein each task entry contains action type information and the jump trigger data. In practical applications, the transportation task and the operation task can be saved in a txt file, and each behavior in the file needs to execute an action action, including "self-check", "start", "parking", "standby", "reversing", "light load driving", "heavy load driving", "unloading", "termination", etc. Each action type uses a digital mark, and each line is id, type, end point coordinates, and trajectory file name, as shown in the following table, where types 0 and 1 are transportation task actions, 2 is a stop action, and 3 is an unloading action, etc. The above is only an example, and the number of task entries in the task file can be added accordingly according to the mining area operation process and sequence. The task entries in the task file are shown in Table 1 below, which is only an example, and the present invention is not limited to this.

[0051] Table 1

[0052]

[0053] As shown in Table 1 above, the action tasks are divided into transport action tasks, stop action tasks and unloading action tasks according to the action type information, wherein the transport action task also includes the name information of the trajectory file, and the trajectory file records the driving trajectory data of the transport action task.

[0054] The condition judgment layer compares and judges the condition data sensed by the unmanned vehicle and the jump trigger data recorded in the task item in the task file, and controls the unmanned vehicle to jump between the driving state in the driving state layer and the operating state in the operating state layer according to the comparison result. For example, the jump between operating states can be triggered according to the location conditions, and the unmanned vehicle executes the task items in the task file in the order of id 0-7, and jumps to the next line of task items after the unmanned vehicle moves to the key point coordinates, until the unmanned vehicle is controlled to execute all the task items recorded in the task file and terminates.

[0055] For driving tasks, the transport trajectory is segmented according to the action behavior. Each transport action is a transport trajectory point, which is saved in multiple txt files. Each line in the file saves a trajectory point. Each line saves the latitude, longitude, elevation, north angle, vehicle speed, road curvature and other information in turn. The saving format is shown in Table 2 below:

[0056]

[0057] The trajectory file and task file are uniformly generated by the cloud control platform and sent to each vehicle before departure. When the actual operation is not correctly executed according to the task file due to human intervention or site reasons, the unmanned vehicle will report to the platform, and the platform will re-plan and send it according to the situation; when encountering obstacles that can be circumvented during transportation, the unmanned vehicle will plan a local obstacle avoidance path, modify the trajectory file, and report to the platform.

[0058] In one embodiment of the present invention, the jump trigger data includes time trigger data, event trigger data and location trigger data. The operating state jump conditions are classified as follows: 1. Time trigger: After the current state has been in operation for a certain period of time, it jumps to the next state; 2. Event trigger: The sensor senses obstacles, action completion and other events, triggering the current state to jump to the next state; 3. Location trigger: The unmanned vehicle uses combined navigation to locate the hardware and arrives at the specified location, triggering the current state to jump to the next state; 4. Manual trigger: The safety officer manually intervenes or performs remote control, the action behavior layer jumps to the driving mode layer, and the safety officer presses the pause button of the remote control handle / human-computer interaction interface, and the action behavior layer jumps to the task process layer. The task entry in the task file corresponds to the order of task entries and key point coordinate data, etc.

[0059] like Figure 2 As shown, the second aspect of the present invention provides a state machine switching method, using the multi-layer finite state machine described in the first aspect, the state machine switching method comprises the following steps:

[0060] Step S200: pre-formulate the task file and trajectory file of the unmanned vehicle in the task planning layer according to the production operation process and operation specification of the mining area;

[0061] Step S210: automatically controlling the action behavior decision of the unmanned vehicle in the unmanned driving mode at the behavior decision layer according to the task file and the trajectory file;

[0062] Step S220: Execute or stop the state switching action of the unmanned vehicle under the behavior decision layer according to the control instruction and control the unmanned vehicle to perform corresponding action behaviors according to the action behavior decision of the behavior decision layer.

[0063] In one embodiment of the present invention, the following steps are further included between step S200 and step S210:

[0064] Control the unmanned vehicle to switch between manual driving mode, remote control driving mode and unmanned driving mode according to control instructions;

[0065] When the unmanned vehicle is in the unmanned driving mode, the unmanned vehicle is controlled to jump between the moving state, the pause state and the end state according to the control instructions;

[0066] When the unmanned vehicle is in a moving state in the unmanned driving mode, the action behavior decision of the unmanned vehicle in the unmanned driving mode is automatically controlled according to the task file and the trajectory file.

[0067] In an embodiment of the present invention, step S210 specifically further includes the following steps:

[0068] A comparison is made between the condition data sensed by the unmanned vehicle and the jump trigger data recorded in the task entry in the task file, and the unmanned vehicle is controlled to jump between the driving state under the driving state layer and the operating state under the operating state layer according to the comparison result.

[0069] A third aspect of the present invention provides an unmanned vehicle for an open-pit mine, comprising: Figure 1 The multi-layer finite state machine is used to control the unmanned vehicle in the open-pit mine area.

[0070] In summary, the present invention proposes a practical multi-layer finite state machine for unmanned vehicles in mining areas, which replaces manual driving, improves the automation level of mining areas, eliminates personnel safety risks, and improves transportation efficiency. This method has good maintainability, scalability, and reusability. It is easy to add and delete states and state layers, control the number of single-layer states, and the jump state is easy to maintain. At the same time, the operation logic is clear, and it has good reusability for different models and types of unmanned vehicles in mining areas.

[0071] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0072] The modules involved in the embodiments of the present invention may be implemented by software or hardware, and the modules described may also be arranged in a processor. The names of these modules do not, in some cases, limit the modules themselves.

[0073] It should be noted that, although several functional layers or units of the device for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules or units described above can be concretized in one module or unit. On the contrary, the features and functions of one module or unit described above can be further divided into being concretized by multiple modules or units.

[0074] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a touch terminal, or a network device, etc.) to execute the method according to the implementation of the present invention.

[0075] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0076] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A multi-layer finite state machine for unmanned vehicles in mining areas, characterized in that: Includes task planning layer, behavior decision layer and motion control layer; The task planning layer is used to pre-formulate the task files and trajectory files of the unmanned vehicle according to the production operation process and operation specifications of the mining area; The behavior decision layer is used to automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode according to the task file and the trajectory file; The motion control layer is used to execute or stop the state switching action of the unmanned vehicle under the behavior decision layer according to the control instruction and control the unmanned vehicle to execute the corresponding action behavior according to the action behavior decision of the behavior decision layer; The behavior decision layer includes a driving mode layer, a task process layer and an action behavior layer; The driving mode layer is used to control the unmanned vehicle to switch between manual driving mode, remote control driving mode and unmanned driving mode according to control instructions; The task process layer is used to control the unmanned vehicle to jump between the moving state, the pause state and the terminated state according to the control instruction when the unmanned vehicle is in the unmanned driving mode; The action behavior layer is used to automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode according to the task file and the trajectory file when the unmanned vehicle is in the motion state in the unmanned driving mode; The action behavior layer includes a condition judgment layer, a driving state layer and an operation state layer; The conditional judgment layer is used to compare and judge based on the condition data sensed by the unmanned vehicle and the jump trigger data recorded in the task item in the task file, and control the unmanned vehicle to jump between the driving state under the driving state layer and the operating state under the operating state layer according to the comparison result; the task file records multiple task items in the order of execution of the production operation process of the unmanned vehicle in the mining area, and each task entry contains action type information and the jump trigger data.

2. The multi-layer finite state machine for unmanned mining vehicles according to claim 1, characterized in that: The jump trigger data includes time trigger data, event trigger data and location trigger data.

3. The multi-layer finite state machine for unmanned mining vehicles according to claim 1, characterized in that: The action tasks are divided into transport action tasks, stop action tasks and unloading action tasks according to the action type information, wherein the transport action task also includes the name information of the track file, and the track file records the driving track data of the transport action task.

4. A state machine switching method, characterized in that: Using the multi-layer finite state machine as described in any one of claims 1 to 3, the state machine switching method comprises the following steps: Pre-formulate the task file and trajectory file of the unmanned vehicle in the task planning layer according to the production operation process and operation specifications of the mining area; Automatically control the action behavior decision of the unmanned vehicle in the unmanned driving mode at the behavior decision layer according to the task file and the trajectory file; According to the control instruction, the state switching action of the unmanned vehicle under the behavior decision layer is executed or stopped, and the unmanned vehicle is controlled to execute the corresponding action behavior according to the action behavior decision of the behavior decision layer.

5. The state machine switching method according to claim 4, characterized in that: Also includes: Control the unmanned vehicle to switch between manual driving mode, remote control driving mode and unmanned driving mode according to control instructions; When the unmanned vehicle is in the unmanned driving mode, the unmanned vehicle is controlled to jump between the moving state, the pause state and the end state according to the control instructions; When the unmanned vehicle is in a moving state in the unmanned driving mode, the action behavior decision of the unmanned vehicle in the unmanned driving mode is automatically controlled according to the task file and the trajectory file.

6. The state machine switching method according to claim 4, characterized in that: Also includes: A comparison is made between the condition data sensed by the unmanned vehicle and the jump trigger data recorded in the task entry in the task file, and the unmanned vehicle is controlled to jump between the driving state under the driving state layer and the operating state under the operating state layer according to the comparison result.

7. An unmanned vehicle for open-pit mining, characterized in that: It comprises a multi-layer finite state machine as described in any one of claims 1-3.

Images