Control decision method and system for field exploration equipment

Abstract

The present invention relates to the field of guidance decision-making of unmanned equipment, and discloses a control decision method and system for field exploration equipment. By acquiring multiple types of sensor data of the environment, various types of objects on the surface of the environment can be determined while establishing environmental terrain data, and the corresponding geological or vegetation types can be obtained. Then, different geological types, vegetation types and the soft, hard and wet types of the surface in the transition area can be fitted according to big data to determine whether the equipment can pass safely without being trapped in the environment, and then a control decision on the equipment's advancement can be made. Compared with the basic decision-making scheme based on the terrain environment in the prior art, the method is more suitable for complex environments and can autonomously complete equipment control decisions in complex field environments.

Description

Technical Field

[0001] The present invention relates to the field of guidance decision-making for unmanned equipment, and in particular to a control decision-making method and system for field exploration equipment. Background Art

[0002] Unmanned exploration equipment is an unmanned detector that detects targets through remote control or autonomous control. The main difference lies in whether it is within the signal coverage area and whether the communication personnel can be exposed by the signal. For equipment that completes exploration autonomously, its basic control decision logic is obstacle avoidance, that is, obstacle judgment is performed through radar or visual solutions, and bypass instructions are executed to achieve the purpose of avoiding obstacles. The control decision logic in the existing technology is mostly used for unmanned automatic driving of vehicles, automatic obstacle avoidance of drones, and autonomous actions of unmanned robots in the field.

[0003] However, the obstacle avoidance logic solutions in the existing technology are only suitable for simple, foreseeable and common environments. However, for more complex unexplored and uninhabited environments, such as virgin forests or wetland environments, due to the complexity of the environment, when multiple geological environments on the surface transition or overlap with vegetation, the surface may be too soft or have too high water content. If the control decision-making solutions based on the existing technology cannot effectively judge and avoid the problems, the equipment may be put at risk. Summary of the invention

[0004] The purpose of the present invention is to provide a control decision method and system for field exploration equipment to solve the problems raised in the above background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions:

[0006] A control decision method for field exploration equipment, comprising:

[0007] Performing environmental perception scanning on the sector-shaped area to be passed by means of a sensing device to obtain multiple sets of environmental sensing data, and pre-processing and superimposing the multiple sets of sensing data to obtain a three-dimensional environmental map, wherein the three-dimensional environmental map is used to characterize the distribution of surface environmental coverage types in the visible area;

[0008] Taking the current position of the decision object as the determination origin, evaluating the vertical gradient change of the three-dimensional environment map, obtaining a gradient distribution map within the visible area, and determining the gradient distribution map based on the passability of the device to obtain an area where the device can pass;

[0009] Based on the three-dimensional environment map acquisition device, the surface environment coverage type of the area can be used to perform ecological model big data fitting on the surface environment coverage type, obtain the subsurface geological type and fill the three-dimensional environment map, and the subsurface geological type is correspondingly provided with soft and hard humidity parameters;

[0010] According to the safety requirements for the passage of the equipment, the subsurface geological types of the area through which the equipment can pass are further screened to obtain a safe passage area, and a control decision plan is generated based on the safe passage area to guide the equipment to move forward.

[0011] As a further solution of the present invention: the multiple groups of environmental sensor data include terrain sensor data and visual sensor data, and the step of pre-processing and superimposing the multiple groups of sensor data to obtain a three-dimensional environmental map specifically includes:

[0012] Build a three-dimensional space structure based on the terrain sensing data scanned by radar, and generate a three-dimensional space white model of the sensing scanning area;

[0013] Feature judgment is performed on several randomly distributed object elements in the visual sensing data to match and obtain the surface environment category of the object elements, and the corresponding model objects in the three-dimensional space white model are marked based on the surface environment category to obtain a three-dimensional environment map. The surface environment category includes vegetation category and water and soil category.

[0014] As a further solution of the present invention: the gradient distribution map includes a horizontal gradient distribution map and a vertical gradient distribution map, and the step of evaluating the vertical gradient change of the three-dimensional environment map to obtain the gradient distribution map in the visible area specifically includes:

[0015] Generate a horizontal reference plane based on the current position as the determination origin, split the horizontal reference plane according to a preset minimum evaluation area, and obtain a gradient evaluation grid, wherein the gradient evaluation grid is composed of a plurality of adjacent minimum evaluation area regions;

[0016] Performing horizontal gradient evaluation, calculating height data of each corresponding grid in the gradient evaluation grid relative to a horizontal reference plane, so as to generate a horizontal gradient distribution map;

[0017] A vertical gradient evaluation is performed to determine obstacles in the space above the ground surface where the gradient rating grid is located. If an obstacle exists, its vertical distance from the ground surface is calculated, and a vertical gradient distribution map is generated based on the vertical distance.

[0018] As a further solution of the present invention: the equipment passability includes gradient passability and width passability, the width passability is used to characterize the width requirement perpendicular to the travel direction when the equipment passes, and each grid corresponds to eight groups of travel span directions to correspond to adjacent grids respectively, and the step of determining the gradient distribution map based on the equipment passability and obtaining the area through which the equipment can pass specifically includes:

[0019] For the passability judgment of the traveling direction, the traveling direction is set, and the gradient change with the adjacent grid in the traveling direction is calculated. If the gradient change exceeds the climbing threshold of the device, it is marked as an impassable area;

[0020] The horizontal passability judgment is to judge the peak value of the vertical fluctuation in the direction of travel. If the horizontal gradient height of the grid exceeds the straight line distance between the two ends of the equipment's travel area by a set threshold, the corresponding area is marked as an impassable area.

[0021] Vertical passability judgment: vertical gradient judgment is performed based on the travel direction and the area after horizontal passability screening. When the vertical gradient corresponding to the grid is not greater than the equipment height, the corresponding grid is marked as an impassable area.

[0022] As a further solution of the present invention, it also includes a subsurface geological feedback step, specifically including:

[0023] When the equipment is moving, an image of the wheel sinking of the equipment is obtained through an image sensing device, and the sinking depth is calculated based on the wheel sinking image. If the sinking depth exceeds a rated safety value, a risk signal is generated and the equipment is controlled to retract;

[0024] The corresponding soft, hard and humidity parameters of the geological type of the lower layer of the surface are corrected according to the subsidence depth, and the ecological model big data used for fitting the surface environment coverage type in the current area is updated based on the correction record. The soft, hard and humidity parameters are correspondingly provided with estimated subsidence depth parameters.

[0025] The embodiment of the present invention aims to provide a control decision system for field exploration equipment, comprising:

[0026] A distributed sensing module is used to perform environmental sensing scanning of the sector area to be passed through by means of sensing equipment to obtain multiple sets of environmental sensing data, and to pre-process and superimpose the multiple sets of sensing data to obtain a three-dimensional environmental map, wherein the three-dimensional environmental map is used to characterize the distribution of surface environmental coverage types in the visible area;

[0027] A gradient evaluation module is used to evaluate the vertical gradient change of the three-dimensional environment map with the current position of the decision object as the determination origin, obtain the gradient distribution map in the visible area, and determine the gradient distribution map based on the passability of the device to obtain the area where the device can pass;

[0028] An environmental fitting module is used to obtain the surface environment coverage type of the area through which the device can pass based on the three-dimensional environmental map, perform ecological model big data fitting on the surface environment coverage type, obtain the subsurface geological type and fill the three-dimensional environmental map, and the subsurface geological type is correspondingly provided with soft and hard humidity parameters;

[0029] The judgment module is used to further screen the subsurface geological types of the equipment-passable area according to the safety requirements of the equipment, obtain the safe passing area, generate a control decision plan based on the safe passing area and guide the equipment to move.

[0030] As a further solution of the present invention: the multiple groups of environmental sensing data include terrain sensing data and visual sensing data, and the distributed sensing module includes:

[0031] A three-dimensional construction unit is used to construct a three-dimensional space structure based on terrain sensing data scanned by radar, and generate a three-dimensional space white model of the sensing scanning area;

[0032] An element assessment unit is used to perform feature judgment on several randomly distributed object elements in the visual sensing data to match and obtain the surface environment category of the object elements, mark the corresponding model objects in the three-dimensional space white model based on the surface environment category, and obtain a three-dimensional environment map. The surface environment category includes vegetation category and water and soil category.

[0033] As a further solution of the present invention: the gradient distribution map includes a horizontal gradient distribution map and a vertical gradient distribution map, and the gradient evaluation module specifically includes:

[0034] An evaluation splitting unit, used to generate a horizontal reference plane based on the current position as the determination origin, split the horizontal reference plane according to a preset minimum evaluation area, and obtain a gradient evaluation grid, wherein the gradient evaluation grid is composed of a plurality of adjacent minimum evaluation area regions;

[0035] A horizontal evaluation unit, used for performing horizontal gradient evaluation, calculating height data of each corresponding grid in the gradient evaluation grid relative to a horizontal reference plane, so as to generate a horizontal gradient distribution map;

[0036] The vertical evaluation unit is used to perform vertical gradient evaluation, to determine obstacles in the space above the ground surface where the gradient rating grid is located, and if an obstacle exists, to calculate its vertical distance from the ground surface, and to generate a vertical gradient distribution map based on the vertical distance.

[0037] As a further solution of the present invention: the equipment passability includes gradient passability and width passability, the width passability is used to characterize the width requirement perpendicular to the travel direction when the equipment travels through, and each grid corresponds to eight groups of travel span directions to correspond to adjacent grids respectively, and the gradient evaluation module also includes:

[0038] A traveling and passing judgment unit is used to judge the passability of the traveling direction, set the traveling direction, calculate the gradient change with the adjacent grid in the traveling direction, and if the gradient change exceeds the climbing threshold of the device, mark it as an impassable area;

[0039] The lateral passing judgment unit is used to judge the lateral passability and to judge the fluctuation peak value in the vertical direction of the travel direction. If the horizontal gradient height of the grid in the collinear area at both ends of the area where the equipment travels exceeds the straight line distance at both ends by a set threshold, the corresponding mark is marked as an impassable area;

[0040] The vertical pass judgment unit is used for vertical passability judgment. It makes a vertical gradient judgment based on the travel direction and the area after the lateral passability screening. When the vertical gradient corresponding to the grid is not greater than the equipment height, the corresponding grid is marked as an impassable area.

[0041] As a further solution of the present invention: it also includes a geological feedback module, specifically including:

[0042] A sinking evaluation unit is used to obtain a sinking image of a wheel of the device through an image sensing device when the device is traveling, calculate a sinking depth based on the sinking image of the wheel, and generate a risk signal and control the device to retreat if the sinking depth exceeds a rated safety value;

[0043] The geological feedback unit is used to correct the corresponding soft, hard and humidity parameters of the geological type of the lower layer of the surface according to the subsidence depth, and update the ecological model big data used for fitting the surface environment coverage type in the current area based on the correction record. The soft, hard and humidity parameters are correspondingly provided with estimated subsidence depth parameters.

[0044] Compared with the prior art, the beneficial effect of the present invention is that by acquiring multiple types of sensor data of the environment, various types of objects on the surface of the environment can be judged while establishing environmental terrain data, and the corresponding geological or vegetation types can be obtained. Then, different geological types, vegetation types and surface hardness and humidity types of transition areas can be fitted according to big data to determine whether the equipment can pass safely without being trapped in the environment, and then control decisions on the equipment's advancement can be made. Compared with the basic decision-making scheme based on terrain environment in the prior art, it is more suitable for complex environments and can autonomously complete equipment control decisions in complex field environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The flowchart is a control decision method for field exploration equipment.

[0046] Figure 2 The present invention is a flowchart of the step of obtaining a gradient distribution map in a control decision method for field exploration equipment.

[0047] Figure 3 This is a block diagram of the control decision system for field exploration equipment. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0049] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0050] like Figure 1 The control decision method for field exploration equipment provided by an embodiment of the present invention comprises the following steps:

[0051] S10, performing environmental perception scanning on the sector-shaped area to be passed by means of a sensor device to obtain multiple sets of environmental sensor data, and pre-processing and superimposing the multiple sets of sensor data to obtain a three-dimensional environmental map, wherein the three-dimensional environmental map is used to characterize the distribution of surface environmental coverage types in the visible area;

[0052] S20, taking the current position of the decision object as the determination origin, evaluating the vertical gradient change of the three-dimensional environment map, obtaining a gradient distribution map within the visible area, and determining the gradient distribution map based on the passability of the device to obtain an area where the device can pass;

[0053] S30, based on the three-dimensional environment map acquisition device, the surface environment coverage type of the area can be obtained by fitting the ecological model big data to the surface environment coverage type, the subsurface geological type is obtained and the three-dimensional environment map is filled, and the subsurface geological type is correspondingly provided with soft and hard humidity parameters;

[0054] S40, further screening the subsurface geological types of the area through which the equipment can pass according to the safety requirements of the equipment passing, obtaining a safe passing area, generating a control decision plan based on the safe passing area and guiding the equipment to move.

[0055] In this embodiment, a control decision method for field exploration equipment is provided. By acquiring multiple types of sensor data of the environment, various types of objects on the surface of the environment can be determined while establishing environmental terrain data, and the corresponding geological or vegetation types can be obtained. Then, different geological types, vegetation types, and the soft, hard, and wet types of the surface in the transition area can be fitted according to big data to determine whether the equipment can pass safely without being trapped in the environment, and then a control decision on the equipment's advancement is made. Compared with the basic decision-making scheme based on the terrain environment in the prior art, this method is more suitable for complex environments and can autonomously complete equipment control decisions in complex field environments. In the prior art The basic control decision logic of unmanned field exploration equipment is obstacle avoidance, that is, obstacle judgment is performed through radar or visual solutions, and detour instructions are executed to achieve the purpose of avoiding obstacles. The control decision logic in the existing technology is mostly used for unmanned automatic driving of vehicles, automatic obstacle avoidance of drones, and autonomous field actions of unmanned robots, but their common feature is the simplicity of the environment, that is, they are only applicable to more foreseeable common environments; and for more complex unexplored unmanned areas, such as virgin forests or wetland environments, due to the complexity of the environment, when multiple geological environments on the surface are in transition or stacked with vegetation, the surface may be too soft or have too much water. High, if the control decision-making plan based on the existing technology cannot effectively avoid it, it may cause the equipment to get stuck, and rescue in unmanned areas is also difficult; the solution adopted here is: after obtaining the three-dimensional environmental map based on lidar and image sensors, on the basis of the existing obstacle avoidance technology, the ecological model big data is fitted for the intersection and overlap of the geological type and vegetation type represented by the three-dimensional environmental map. The ecological model big data here refers to the environmental transition model fitted according to the large amount of data collected under different climatic conditions in the corresponding dimensions, and the influence of a certain geological environment on the softness and humidity of the geological environment when it transitions to other geological environments or vegetation. For example, loose soil has a certain type of plant growing on it. During its long-term survival, this plant will drop a lot of fallen leaves, resulting in a thicker layer of humus on the surface. This humus layer is very soft and rich in nutrients, which may further attract more microorganisms and decomposers, causing the soil below the humus layer to become further loose. The control decision-making scheme in the existing technology cannot judge this scenario and may directly control the equipment to pass through. However, in fact, the area is too soft and the depth cannot be determined. Rash entry may cause the equipment to fall into a state of being unable to save itself. Therefore, it is necessary to avoid it and ensure the safety of the equipment, which is not achievable with the existing technical scheme.

[0056] As another preferred embodiment of the present invention, the multiple groups of environmental sensor data include terrain sensor data and visual sensor data, and the step of pre-processing and superimposing the multiple groups of sensor data to obtain a three-dimensional environmental map specifically includes:

[0057] Build a three-dimensional space structure based on the terrain sensing data scanned by radar, and generate a three-dimensional space white model of the sensing scanning area;

[0058] Feature judgment is performed on several randomly distributed object elements in the visual sensing data to match and obtain the surface environment category of the object elements, and the corresponding model objects in the three-dimensional space white model are marked based on the surface environment category to obtain a three-dimensional environment map. The surface environment category includes vegetation category and water and soil category.

[0059] In this embodiment, the steps of superimposing a three-dimensional environmental map are explained in a distributed manner, which mainly includes two stages. The first is the modeling of the three-dimensional space. This step also exists in traditional obstacle avoidance control, and its main purpose is to realize the recognition and marking of graphics in the space. The second is the type recognition of graphics in the space, which is mainly based on big data graphic feature retrieval and recognition, and retrieval and matching are performed according to the graphic features of the corresponding area in the three-dimensional space to obtain the corresponding vegetation type and geology and obstacle type.

[0060] like Figure 2 As shown, as another preferred embodiment of the present invention, the gradient distribution map includes a horizontal gradient distribution map and a vertical gradient distribution map, and the step of evaluating the vertical gradient change of the three-dimensional environment map to obtain the gradient distribution map in the visible area specifically includes:

[0061] S21, generating a horizontal reference plane based on the current position as the determination origin, splitting the horizontal reference plane according to a preset minimum evaluation area, and obtaining a gradient evaluation grid, wherein the gradient evaluation grid is composed of a plurality of adjacent minimum evaluation area regions;

[0062] S22, performing horizontal gradient evaluation, calculating height data of each corresponding grid in the gradient evaluation grid relative to a horizontal reference plane, so as to generate a horizontal gradient distribution map;

[0063] S23, perform vertical gradient evaluation, determine obstacles in the space above the ground surface where the gradient rating grid is located, and if an obstacle exists, calculate its vertical distance from the ground surface, and generate a vertical gradient distribution map based on the vertical distance.

[0064] In this embodiment, the acquisition of the gradient distribution map mainly includes two parts. The first is the gradient division in the plane direction, which is mainly used to determine the obstacles that the device needs to bypass, and the height changes in the area, which are used to determine whether the device can pass through the slope changes caused by them; the second is the gradient change in the vertical direction, that is, when there is a suspended obstacle in the vertical direction, the vertical distance between its lower end and the ground that allows the device to pass. By judging the vertical gradient, the collision between the device and the suspended obstacle can be effectively avoided.

[0065] As another preferred embodiment of the present invention, the device passability includes gradient passability and width passability, the width passability is used to characterize the width requirement perpendicular to the travel direction when the device passes, and each grid corresponds to eight groups of travel span directions to correspond to adjacent grids respectively, and the step of determining the gradient distribution map based on the device passability and obtaining the device passable area specifically includes:

[0066] For the passability judgment of the traveling direction, the traveling direction is set, and the gradient change with the adjacent grid in the traveling direction is calculated. If the gradient change exceeds the climbing threshold of the device, it is marked as an impassable area;

[0067] The horizontal passability judgment is to judge the peak value of the vertical fluctuation in the direction of travel. If the horizontal gradient height of the grid exceeds the straight line distance between the two ends of the equipment's travel area by a set threshold, the corresponding area is marked as an impassable area.

[0068] Vertical passability judgment: vertical gradient judgment is performed based on the travel direction and the area after horizontal passability screening. When the vertical gradient corresponding to the grid is not greater than the equipment height, the corresponding grid is marked as an impassable area.

[0069] In this embodiment, the steps of determining the passable area of ​​the device based on the passability judgment of the device are explained. The specific implementation steps of this process are: first, a travel direction is set based on the positioning information, and the vertical height change in the travel direction is judged to determine whether it exceeds the climbable distance of the device; and whether the width of the passable area in the vertical direction of the forward direction can accommodate the vehicle to pass; when all of these conditions are met, the obstacle situation in the vertical direction is further judged, that is, screening is performed by whether the vertical gradient is greater than the height of the vehicle.

[0070] As another preferred embodiment of the present invention, it also includes a subsurface geological feedback step, specifically including:

[0071] When the equipment is moving, an image of the wheel sinking of the equipment is obtained through an image sensing device, and the sinking depth is calculated based on the wheel sinking image. If the sinking depth exceeds a rated safety value, a risk signal is generated and the equipment is controlled to retract;

[0072] The corresponding soft, hard and humidity parameters of the geological type of the lower layer of the surface are corrected according to the subsidence depth, and the ecological model big data used for fitting the surface environment coverage type in the current area is updated based on the correction record. The soft, hard and humidity parameters are correspondingly provided with estimated subsidence depth parameters.

[0073] In this embodiment, a subsurface geological feedback step is added, which mainly includes two functions. First, the depth of the equipment's immersion is obtained and recorded through real-time image monitoring. If the depth of the equipment's wheels exceeds the estimated value when reaching a certain area, feedback is given through risk signals and the equipment is controlled to retreat to a safe area. Second, the sinking depth obtained based on actual monitoring is compared with the sinking depth evaluated during the fitting process, and then the ecological model big data of the current area is supplemented with data to improve the accuracy of subsequent data fitting, that is, to improve the ecological environment big data of the current area.

[0074] like Figure 3 As shown, the present invention also provides a control decision system for field exploration equipment, which comprises:

[0075] The distributed sensing module 100 is used to perform environmental sensing scanning on the sector-shaped area to be passed through by means of sensing equipment to obtain multiple sets of environmental sensing data, and to pre-process and superimpose the multiple sets of sensing data to obtain a three-dimensional environmental map, wherein the three-dimensional environmental map is used to characterize the distribution of surface environmental coverage types in the visible area;

[0076] The gradient evaluation module 200 is used to evaluate the vertical gradient change of the three-dimensional environment map with the current position of the decision object as the determination origin, obtain the gradient distribution map in the visible area, and determine the gradient distribution map based on the passability of the device to obtain the area where the device can pass;

[0077] The environment fitting module 300 is used to obtain the surface environment coverage type of the area through the three-dimensional environment map acquisition device, perform ecological model big data fitting on the surface environment coverage type, obtain the subsurface geological type and fill the three-dimensional environment map, and the subsurface geological type is correspondingly provided with soft and hard humidity parameters;

[0078] The determination module 400 is used to further screen the subsurface geological types of the area through which the equipment can pass according to the safety requirements of the equipment passing, obtain the safe passing area, generate a control decision plan based on the safe passing area and guide the equipment to move.

[0079] As another preferred embodiment of the present invention, the multiple groups of environmental sensing data include terrain sensing data and visual sensing data, and the distributed sensing module includes:

[0080] A three-dimensional construction unit is used to construct a three-dimensional space structure based on terrain sensing data scanned by radar, and generate a three-dimensional space white model of the sensing scanning area;

[0081] An element assessment unit is used to perform feature judgment on several randomly distributed object elements in the visual sensing data to match and obtain the surface environment category of the object elements, mark the corresponding model objects in the three-dimensional space white model based on the surface environment category, and obtain a three-dimensional environment map. The surface environment category includes vegetation category and water and soil category.

[0082] As another preferred embodiment of the present invention, the gradient distribution map includes a horizontal gradient distribution map and a vertical gradient distribution map, and the gradient evaluation module specifically includes:

[0083] An evaluation splitting unit, used to generate a horizontal reference plane based on the current position as the determination origin, split the horizontal reference plane according to a preset minimum evaluation area, and obtain a gradient evaluation grid, wherein the gradient evaluation grid is composed of a plurality of adjacent minimum evaluation area regions;

[0084] A horizontal evaluation unit, used for performing horizontal gradient evaluation, calculating height data of each corresponding grid in the gradient evaluation grid relative to a horizontal reference plane, so as to generate a horizontal gradient distribution map;

[0085] The vertical evaluation unit is used to perform vertical gradient evaluation, to determine obstacles in the space above the ground surface where the gradient rating grid is located, and if an obstacle exists, to calculate its vertical distance from the ground surface, and to generate a vertical gradient distribution map based on the vertical distance.

[0086] As another preferred embodiment of the present invention, the device passability includes gradient passability and width passability, the width passability is used to characterize the width requirement perpendicular to the travel direction when the device travels through, and each grid corresponds to eight groups of travel span directions to correspond to adjacent grids respectively, and the gradient evaluation module also includes:

[0087] A traveling and passing judgment unit is used to judge the passability of the traveling direction, set the traveling direction, calculate the gradient change with the adjacent grid in the traveling direction, and if the gradient change exceeds the climbing threshold of the device, mark it as an impassable area;

[0088] The lateral passing judgment unit is used to judge the lateral passability and to judge the fluctuation peak value in the vertical direction of the travel direction. If the horizontal gradient height of the grid in the collinear area at both ends of the area where the equipment travels exceeds the straight line distance at both ends by a set threshold, the corresponding mark is marked as an impassable area;

[0089] The vertical pass judgment unit is used for vertical passability judgment. It makes a vertical gradient judgment based on the travel direction and the area after the lateral passability screening. When the vertical gradient corresponding to the grid is not greater than the equipment height, the corresponding grid is marked as an impassable area.

[0090] As another preferred embodiment of the present invention, it also includes a geological feedback module, specifically including:

[0091] A sinking evaluation unit is used to obtain a sinking image of a wheel of the device through an image sensing device when the device is traveling, calculate a sinking depth based on the sinking image of the wheel, and generate a risk signal and control the device to retreat if the sinking depth exceeds a rated safety value;

[0092] The geological feedback unit is used to correct the corresponding soft, hard and humidity parameters of the geological type of the lower layer of the surface according to the subsidence depth, and update the ecological model big data used for fitting the surface environment coverage type in the current area based on the correction record. The soft, hard and humidity parameters are correspondingly provided with estimated subsidence depth parameters.

[0093] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the program can be stored in a non-volatile computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0094] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the disclosure in the specification and examples. This application is intended to cover any variations, uses or adaptations of the present disclosure, which follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0095] It should be understood that the present disclosure is not limited to the exact structures that have 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 disclosure is limited only by the appended claims.

Claims

1. A control decision method for field exploration equipment, characterized in that: Include: Performing environmental perception scanning on the sector-shaped area to be passed by means of a sensing device to obtain multiple sets of environmental sensing data, and pre-processing and superimposing the multiple sets of sensing data to obtain a three-dimensional environmental map, wherein the three-dimensional environmental map is used to characterize the distribution of surface environmental coverage types in the visible area; Taking the current position of the decision object as the determination origin, evaluating the vertical gradient change of the three-dimensional environment map, obtaining a gradient distribution map within the visible area, and determining the gradient distribution map based on the passability of the device to obtain an area where the device can pass; Based on the three-dimensional environment map acquisition device, the surface environment coverage type of the area can be used to perform ecological model big data fitting on the surface environment coverage type, obtain the subsurface geological type and fill the three-dimensional environment map, and the subsurface geological type is correspondingly provided with soft and hard humidity parameters; Further screening the subsurface geological types of the area through which the equipment can pass according to the safety requirements of the equipment passing, obtaining a safe passing area, generating a control decision plan based on the safe passing area and guiding the equipment to move; The equipment passability includes gradient passability and width passability. The width passability is used to characterize the width requirement perpendicular to the travel direction when the equipment passes through, and each grid corresponds to eight groups of travel span directions to correspond to adjacent grids respectively. The step of determining the gradient distribution map based on the equipment passability and obtaining the equipment passable area specifically includes: For the passability judgment of the traveling direction, the traveling direction is set, and the gradient change with the adjacent grid in the traveling direction is calculated. If the gradient change exceeds the climbing threshold of the device, it is marked as an impassable area; The horizontal passability judgment is to judge the peak value of the vertical fluctuation in the direction of travel. If the horizontal gradient height of the grid exceeds the straight line distance between the two ends of the equipment's travel area by a set threshold, the corresponding area is marked as an impassable area. Vertical passability judgment: vertical gradient judgment is performed based on the travel direction and the area after lateral passability screening. When the vertical gradient corresponding to the grid is not greater than the equipment height, the corresponding grid is marked as an impassable area.

2. The control decision method for field exploration equipment according to claim 1, characterized in that: The multiple sets of environmental sensor data include terrain sensor data and visual sensor data, and the step of pre-processing and superimposing the multiple sets of sensor data to obtain a three-dimensional environmental map specifically includes: Build a three-dimensional space structure based on the terrain sensing data scanned by radar, and generate a three-dimensional space white model of the sensing scanning area; Feature judgment is performed on several randomly distributed object elements in the visual sensing data to match and obtain the surface environment category of the object elements, and the corresponding model objects in the three-dimensional space white model are marked based on the surface environment category to obtain a three-dimensional environment map. The surface environment category includes vegetation category and water and soil category.

3. The control decision method for field exploration equipment according to claim 2, characterized in that: The gradient distribution map includes a horizontal gradient distribution map and a vertical gradient distribution map. The step of evaluating the vertical gradient change of the three-dimensional environment map to obtain the gradient distribution map in the visible area specifically includes: Generate a horizontal reference plane based on the current position as the determination origin, split the horizontal reference plane according to a preset minimum evaluation area, and obtain a gradient evaluation grid, wherein the gradient evaluation grid is composed of a plurality of adjacent minimum evaluation area regions; Performing horizontal gradient evaluation, calculating height data of each corresponding grid in the gradient evaluation grid relative to a horizontal reference plane, so as to generate a horizontal gradient distribution map; A vertical gradient evaluation is performed to determine obstacles in the space above the ground surface where the gradient rating grid is located. If an obstacle exists, its vertical distance from the ground surface is calculated, and a vertical gradient distribution map is generated based on the vertical distance.

4. The control decision method for field exploration equipment according to claim 1, characterized in that: It also includes subsurface geological feedback steps, including: When the equipment is moving, an image of the wheel sinking of the equipment is obtained through an image sensing device, and the sinking depth is calculated based on the wheel sinking image. If the sinking depth exceeds a rated safety value, a risk signal is generated and the equipment is controlled to retract; The corresponding soft, hard and humidity parameters of the geological type of the lower layer of the surface are corrected according to the subsidence depth, and the ecological model big data used for fitting the surface environment coverage type in the current area is updated based on the correction record. The soft, hard and humidity parameters are correspondingly provided with estimated subsidence depth parameters.

5. A control decision system for field exploration equipment, characterized in that: Include: A distributed sensing module is used to perform environmental sensing scanning of the sector area to be passed through by means of sensing equipment to obtain multiple sets of environmental sensing data, and to pre-process and superimpose the multiple sets of sensing data to obtain a three-dimensional environmental map, wherein the three-dimensional environmental map is used to characterize the distribution of surface environmental coverage types in the visible area; A gradient evaluation module is used to evaluate the vertical gradient change of the three-dimensional environment map with the current position of the decision object as the determination origin, obtain the gradient distribution map in the visible area, and determine the gradient distribution map based on the passability of the device to obtain the area where the device can pass; An environmental fitting module is used to obtain the surface environment coverage type of the area through which the device can pass based on the three-dimensional environmental map, perform ecological model big data fitting on the surface environment coverage type, obtain the subsurface geological type and fill the three-dimensional environmental map, and the subsurface geological type is correspondingly provided with soft and hard humidity parameters; A determination module is used to further screen the geological type of the subsurface layer in the area where the equipment can pass according to the safety requirements of the equipment passing, obtain the safe passing area, generate a control decision plan based on the safe passing area and guide the equipment to move; The equipment passability includes gradient passability and width passability. The width passability is used to characterize the width requirement perpendicular to the travel direction when the equipment passes through. Each grid corresponds to eight groups of travel span directions to correspond to adjacent grids respectively. The gradient evaluation module also includes: A traveling and passing judgment unit is used to judge the passability of the traveling direction, set the traveling direction, calculate the gradient change amount with the adjacent grid in the traveling direction, and if the gradient change amount exceeds the climbing threshold of the device, it is marked as an impassable area; The lateral passing judgment unit is used to judge the lateral passability and to judge the fluctuation peak value in the vertical direction of the travel direction. If the horizontal gradient height of the grid in the collinear area at both ends of the area where the equipment travels exceeds the straight line distance at both ends by a set threshold, the corresponding mark is marked as an impassable area; The vertical pass judgment unit is used for vertical passability judgment. It makes a vertical gradient judgment based on the travel direction and the area after the lateral passability screening. When the vertical gradient corresponding to the grid is not greater than the equipment height, the corresponding grid is marked as an impassable area.

6. The control decision system for field exploration equipment according to claim 5, characterized in that: The plurality of sets of environmental sensing data include terrain sensing data and visual sensing data, and the distributed sensing module includes: A three-dimensional construction unit is used to construct a three-dimensional space structure based on terrain sensing data scanned by radar, and generate a three-dimensional space white model of the sensing scanning area; An element assessment unit is used to perform feature judgment on several randomly distributed object elements in the visual sensing data to match and obtain the surface environment category of the object elements, mark the corresponding model objects in the three-dimensional space white model based on the surface environment category, and obtain a three-dimensional environment map. The surface environment category includes vegetation category and water and soil category.

7. The control decision system for field exploration equipment according to claim 6, characterized in that: The gradient distribution map includes a horizontal gradient distribution map and a vertical gradient distribution map, and the gradient evaluation module specifically includes: An evaluation splitting unit, used to generate a horizontal reference plane based on the current position as the determination origin, split the horizontal reference plane according to a preset minimum evaluation area, and obtain a gradient evaluation grid, wherein the gradient evaluation grid is composed of a plurality of adjacent minimum evaluation area regions; A horizontal evaluation unit, used for performing horizontal gradient evaluation, calculating height data of each corresponding grid in the gradient evaluation grid relative to a horizontal reference plane, so as to generate a horizontal gradient distribution map; The vertical evaluation unit is used to perform vertical gradient evaluation, to determine obstacles in the space above the ground surface where the gradient rating grid is located, and if an obstacle exists, to calculate its vertical distance from the ground surface, and to generate a vertical gradient distribution map based on the vertical distance.

8. The control decision system for field exploration equipment according to claim 5, characterized in that: It also includes a geological feedback module, which includes: A sinking evaluation unit is used to obtain a sinking image of a wheel of the device through an image sensing device when the device is traveling, calculate a sinking depth based on the sinking image of the wheel, and generate a risk signal and control the device to retreat if the sinking depth exceeds a rated safety value; The geological feedback unit is used to correct the corresponding soft, hard and humidity parameters of the geological type of the lower layer of the surface according to the subsidence depth, and update the ecological model big data used for fitting the surface environment coverage type in the current area based on the correction record. The soft, hard and humidity parameters are correspondingly provided with estimated subsidence depth parameters.

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