CN113370722B - Three-axis unmanned vehicle coping strategy method and system based on external emergency - Google Patents

Three-axis unmanned vehicle coping strategy method and system based on external emergency Download PDF

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CN113370722B
CN113370722B CN202110864090.9A CN202110864090A CN113370722B CN 113370722 B CN113370722 B CN 113370722B CN 202110864090 A CN202110864090 A CN 202110864090A CN 113370722 B CN113370722 B CN 113370722B
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CN113370722A (en
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徐小军
王立亚
张国卿
刘博龙
潘迪博
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National University of Defense Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
    • B60C23/00—Devices for measuring, signalling, controlling, or distributing tyre pressure or temperature, specially adapted for mounting on vehicles; Arrangement of tyre inflating devices on vehicles, e.g. of pumps or of tanks; Tyre cooling arrangements
    • B60C23/001—Devices for manually or automatically controlling or distributing tyre pressure whilst the vehicle is moving
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60G—VEHICLE SUSPENSION ARRANGEMENTS
    • B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
    • B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60G—VEHICLE SUSPENSION ARRANGEMENTS
    • B60G17/00—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load
    • B60G17/015—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements
    • B60G17/0195—Resilient suspensions having means for adjusting the spring or vibration-damper characteristics, for regulating the distance between a supporting surface and a sprung part of vehicle or for locking suspension during use to meet varying vehicular or surface conditions, e.g. due to speed or load the regulating means comprising electric or electronic elements characterised by the regulation being combined with other vehicle control systems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W10/00—Conjoint control of vehicle sub-units of different type or different function
    • B60W10/20—Conjoint control of vehicle sub-units of different type or different function including control of steering systems
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
    • B62D—MOTOR VEHICLES; TRAILERS
    • B62D55/00—Endless track vehicles
    • B62D55/04—Endless track vehicles with tracks and alternative ground wheels, e.g. changeable from endless track vehicle into wheeled vehicle and vice versa
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60G—VEHICLE SUSPENSION ARRANGEMENTS
    • B60G2800/00—Indexing codes relating to the type of movement or to the condition of the vehicle and to the end result to be achieved by the control action
    • B60G2800/90—System Controller type
    • B60G2800/91—Suspension Control
    • B60G2800/914—Height Control System
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/08—Electric propulsion units
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2710/00—Output or target parameters relating to a particular sub-units
    • B60W2710/20—Steering systems

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Transportation (AREA)
  • Chemical & Material Sciences (AREA)
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  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention discloses a three-axis unmanned vehicle coping strategy method based on external emergency, which comprises the steps of obtaining real-time environment information; extracting target classification information of external burst conditions in real-time environment information; determining a burst condition target type based on the target classification information; controlling the three-axis unmanned vehicle to adjust the vehicle body state and the driving state based on the determination result and the real-time environment information; adjusting the state of the vehicle body comprises lifting the tire pressure of the wheels, switching the wheel track structure of the wheels and adjusting the height of the chassis of the vehicle; adjusting the driving state includes determining and switching a steering mode, adjusting a vehicle maneuver mode. The invention also discloses a triaxial unmanned vehicle coping strategy system based on the external emergency. The method can determine the emergency situation based on the external real-time environment information, and adjust the vehicle body state and the driving state according to the danger type, so as to adjust different emergency situations, has strong pertinence, improves the vehicle survival capability and the adaptability, and has high response speed and high response success rate.

Description

Three-axis unmanned vehicle coping strategy method and system based on external emergency
Technical Field
The invention relates to the technical field of unmanned combat platform danger coping, in particular to a triaxial unmanned vehicle coping strategy method based on external emergency.
Background
The unmanned vehicle is used as an important component in future unmanned systems, can be used in various fields such as agriculture, industry, geology and the like, and is used for performing field tasks such as crop irrigation, terrain exploration, geological mapping, patrol and the like.
The unmanned vehicle has strong task execution capability and better environment adaptability due to good maneuverability, stability, off-road property, safety and the like. In the process of executing tasks, people, field creatures, landforms and the like can influence the task execution condition of the unmanned vehicle.
The three-axis unmanned vehicle is an unmanned vehicle with three axles, comprises six wheels including a front axle, a middle axle and a rear axle, can adjust the height of a vehicle chassis and adjust the wheel base, and is provided with wheel-track switching wheels on the middle shafts of part of the three-axis unmanned vehicle, so that the three-axis unmanned vehicle has higher off-road property and stability.
When the existing three-axis unmanned vehicle faces an emergency, the existing three-axis unmanned vehicle mostly utilizes quick maneuvering to avoid, avoid or keep away from the emergency or an area, but as the influence of many factors such as terrain, speed, gravity center, attack speed, direction, type and the like is considered in the quick maneuvering of the vehicle, such coping strategies are difficult to realize, and the three-axis unmanned vehicle can only be used in a flat area basically and cannot adapt to the use requirements of various outdoor environments.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a three-axis unmanned vehicle coping strategy method based on external emergency, which can adjust the vehicle body state and the driving state, so that the emergency is coped with by combining factors such as terrain, vehicle structure, emergency target type and the like, and the method has the characteristics of high response speed, strong pertinence, wide application range and the like.
The purpose of the invention is mainly realized by the following technical scheme: a three-axis unmanned vehicle coping strategy method based on external emergency comprises the steps of obtaining real-time environment information; extracting target classification information of targets in external burst conditions in real-time environment information; determining a type of the emergency condition based on the target classification information; controlling the three-axis unmanned vehicle to adjust a vehicle body state and a driving state based on the determination result and the real-time environment information, wherein the vehicle body state adjustment comprises the steps of lifting the tire pressure of the wheels, switching the wheel-track structure and adjusting the height of the chassis of the vehicle; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
In the coping strategy method, the real-time environment information at least comprises running environment information of a three-axis unmanned vehicle, vehicle running information, vehicle structure parameter information and external environment photoelectric information.
In the coping strategy method, the external emergency is determined by an intelligent recognition evaluation method, and the intelligent recognition evaluation method comprises the following steps: acquiring real-time environment information, and extracting target classification information of a target in a suspected emergency; based on the target classification information, identifying suspected emergency conditions and evaluating the danger degree; and determining whether the suspected emergency belongs to the external emergency based on the identification and the danger degree evaluation result.
In the coping strategy method, the object classification information at least includes a position, a speed, a direction and a height of the object in the external emergency.
In the coping strategy method, the determining the type of the emergency condition includes: when the suspected emergency is determined to belong to the external emergency, determining the type of the emergency based on the target classification information and the risk degree evaluation; the burst condition type comprises at least one of a far lateral or oblique lateral burst condition, a near lateral or oblique lateral burst condition, a vertical or near vertical upper burst condition, and a vertical or near vertical lower burst condition.
In the coping strategy method, the elevating wheel tire pressure and switching wheel-track structure comprises the following steps: if the road surface is soft or muddy, the front axle and the rear axle wheels of the three-axle unmanned vehicle reduce the tire pressure, and the middle axle switches the wheels to crawler-type running; if the road surface is not soft or muddy, the tire pressure of the front axle and the rear axle of the three-axle unmanned vehicle is kept normal, and the middle axle switches the wheels into wheel type walking.
In the coping strategy method, the method for judging a soft or muddy road surface includes:
calculating the maximum horizontal shear force tau of the intermediate shaft wheel which can bear the ground when the intermediate shaft wheel travels on soft terrainmaxThe calculation formula is as follows:
Figure BDA0003186929320000021
wherein c is a constant, σ is a load borne by the ground,
Figure BDA0003186929320000022
is a shear angle;
obtaining the relation between the ground subsidence z and the load sigma borne by the ground, wherein the relation between the ground subsidence z and the load sigma borne by the ground is obtained by the following formula:
Figure BDA0003186929320000023
in the formula, b is the short side length of the contact area between the intermediate shaft wheel and the ground, namely the contact width, n is the index of soil deformation, kc is the cohesive force modulus of the soil deformation and k phi is the friction coefficient of the soil deformation;
obtaining a relation of the load sigma borne by the ground through the conversion of the formula (2):
Figure BDA0003186929320000024
based on the vertical direction force balance of the middle shaft wheel when the soft terrain advances, a vertical direction balance formula is obtained:
Figure BDA0003186929320000025
in the formula, G is a vertical acting force, delta is an integral variable, l is a contact length, and delta M is an included angle between a contact point and a vertical central line of the wheel;
r' is the radius of the part in real time contact with the ground, and has:
Figure BDA0003186929320000031
in the formula, RWRadius of parts for wheeled walking, RTThe equivalent radius is the equivalent radius when the crawler-type walking is carried out, and alpha is the deformation angle of the wheel rim;
obtaining the amount of subsidence Z of the intermediate shaft wheel on soft terrain under the same load condition through approximate processing based on the formulas (1) to (5)MAnd the rim deformation angle α:
Figure BDA0003186929320000032
calculating the horizontal traction force F of the intermediate shaft wheel when the intermediate shaft wheel travels on soft terrain to obtain:
Figure BDA0003186929320000033
combining the formulas (1), (2), (3) and (7), obtaining the relationship between the maximum traction force F provided by the intermediate shaft wheel on soft terrain and the rim deformation angle alpha under the same load condition:
Figure BDA0003186929320000034
based on the formulas (1) to (8), the settlement Z with the same traction force required when the intermediate shaft wheels are respectively tracked walking and wheeled walking is solvedt；
Solving the actual subsidence Z of the intermediate shaft wheel during actual walking based on the formulas (1) to (8)s；
And (3) comparison:
if Z iss＞ZtJudging that the road surface is soft or muddy, and adopting crawler-type walking;
if Z iss＜ZtAnd judging that the road surface is a non-soft or non-muddy road surface, and adopting a wheel type to walk.
In the coping strategy method, the adjusting the vehicle chassis height comprises: based on the type of emergency, the vehicle chassis height is raised or lowered to keep the vehicle body in high, medium or low drive.
In the coping strategy method, the determining and switching the steering mode may include: determining whether to adopt a center steering mode to quickly steer to steer a defensive surface of the side of the vehicle body to the direction of the emergency based on the type of the emergency; or, determining whether to assist the vehicle in maneuvering using the fast steering mode.
In the coping strategy method, the adjusting the vehicle maneuver mode includes: based on the emergency type, the vehicle driving state is adjusted to a fast crab travel mode, a fast S-shaped travel mode, or a fast straight travel mode.
Compared with the prior art, the method can determine the emergency situation and adjust the vehicle body state and the running state according to the target danger type based on the real-time environment information outside the three-axis unmanned vehicle, so that the vehicle can select a proper vehicle structure and running mode according to the terrain, the road surface, the emergency situation target type and the like, different vehicle structures and running modes are selected for different emergency situation targets, the pertinence is strong, the vehicle can be more suitable for running of complex terrains through the adjustment of the vehicle structures and the running modes, the emergency situation has wider space and environment when being responded, the vehicle viability and adaptability are improved, the vehicle acquires environment data in real time, the vehicle structures and the running modes are synchronously carried out after the emergency situation is determined, and the response speed is further improved.
Based on the three-axis unmanned vehicle coping strategy system, the invention also discloses a three-axis unmanned vehicle coping strategy system based on the external emergency, which comprises an acquisition module, a real-time environment information acquisition module and a real-time environment information acquisition module, wherein the acquisition module is used for acquiring the real-time environment information; the extraction module is used for extracting target classification information of targets in external burst conditions in the real-time environment information; a determining module for determining the type of the burst condition; the control module is used for controlling the three-axis unmanned vehicle to adjust a vehicle body state and a driving state, wherein the vehicle body state adjustment comprises lifting of a wheel tire pressure, switching of a wheel-track structure and adjustment of a vehicle chassis height; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
In the system, the control module includes: the wheel-track control module is used for controlling the lifting of the tire pressure of the wheel and the switching of the wheel-track structure of the wheel; the parking space control module is used for controlling the height adjustment of the vehicle chassis; the steering control module is used for determining and switching a steering mode; and the driving control module is used for controlling the adjustment of the vehicle maneuvering mode.
The triaxial unmanned vehicle coping strategy system can acquire emergency target classification information through real-time environment information under the action of each module, so that the corresponding adjustment of a vehicle body structure and a driving mode is controlled, different types of emergency conditions are coped with, and the triaxial unmanned vehicle coping strategy system has the characteristics of high response speed, strong pertinence, stability and high efficiency.
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The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart of a three-axis unmanned vehicle countermeasure method based on external emergency conditions;
FIG. 2 is a flow chart of step 102 in a three-axis unmanned vehicle countermeasure method based on an external emergency;
FIG. 3 is a flow chart of step 1021 in a three-axis unmanned vehicle countermeasure method based on an external emergency condition;
FIG. 4 is a flow chart of step 104 of the three-axis unmanned vehicle countermeasure method based on external emergency conditions;
FIG. 5 is a state diagram of the wheels in a three-axis drone vehicle center-steer mode;
FIG. 6 is a state diagram of the wheels of the three-axis drone vehicle in a fast steering mode;
FIG. 7 is a block diagram of a three-axis unmanned vehicle countermeasure system based on external emergency conditions;
FIG. 8 is a block diagram of a control module in a three-axis unmanned vehicle countermeasure system based on external emergency conditions;
FIG. 9 is a flow chart of a three-axis unmanned vehicle countermeasure methodology based on an external emergency being an emergency from a far lateral/oblique lateral;
FIG. 10 is a flow chart of a three-axis unmanned vehicle countermeasure methodology based on an external emergency being an emergency from a close range lateral/diagonal lateral;
FIG. 11 is a flow chart of a three-axis unmanned vehicle countermeasure method based on an external emergency being an emergency from vertically/near vertically above;
FIG. 12 is a flow chart of a three-axis unmanned vehicle countermeasure methodology based on an external emergency being an emergency from vertically/near vertically down;
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
It should be understood that "system", "device", "unit" and/or "module" as used herein is a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, other words may be substituted by other expressions if they accomplish the same purpose.
As used in this disclosure and in the claims, the terms "a," "an," "the," and/or "the" are not intended to be inclusive in the singular, but rather are inclusive in the plural, unless the context clearly dictates otherwise. In general, the terms "comprises" and "comprising" merely indicate that steps and elements are included which are explicitly identified, that the steps and elements do not form an exclusive list, and that a method or apparatus may include other steps or elements.
Flow charts are used in the present invention to illustrate the operations performed by a system according to embodiments of the present invention. It should be understood that the preceding or following operations are not necessarily performed in the exact order in which they are performed. Rather, the various steps may be processed in reverse order or simultaneously. Meanwhile, other operations may be added to the processes, or a certain step or several steps of operations may be removed from the processes.
As shown in fig. 1, as a first embodiment of the present invention, the present invention discloses a three-axis unmanned vehicle countermeasure method 100 based on an external emergency, which specifically includes the following steps:
step 101, acquiring real-time environment information;
102, extracting target classification information of targets in external burst conditions in real-time environment information;
103, determining the type of the emergency condition based on the target classification information;
104, controlling the three-axis unmanned vehicle to adjust the vehicle body state and the running state based on the determination result and the real-time environment information; the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
The strategy method 100 for dealing with the three-axis unmanned vehicle based on the external emergency can determine the emergency and adjust the vehicle body state and the driving state according to the danger type based on the real-time environment information outside the three-axis unmanned vehicle, further, the vehicle can select a proper vehicle structure and a proper driving mode according to the terrain, the road surface, the target type of the emergency and the like, select different vehicle structures and driving modes aiming at different emergency, pertinently solve the emergency, and the vehicle structure and the running mode are adjusted, so that the vehicle can be more suitable for running on complex terrains, thereby having wider space and environment when dealing with emergency, improving the survival ability and adaptability of the vehicle, and the vehicle acquires the environmental data in real time, and the vehicle structure and the driving mode are synchronously performed after the emergency condition is determined, so that the response speed is improved, and the response success rate is high.
In step 101, the real-time environment information at least includes driving environment information, vehicle driving information, vehicle structure parameter information, and external environment photoelectric information.
The driving environment information may be terrain information, map information, spatial information, obstacle information, road surface information, weather information, etc.; the vehicle running information may be driving information, speed information, chassis height information, displacement information, coordinate information, direction information, vehicle slip information, wheel structure and stress information, etc. of the vehicle; the vehicle structure parameter information can be vehicle chassis height parameters, wheel tire pressure parameters, wheel state parameters, vehicle steering parameters, vehicle load parameters, vehicle inclination angle parameters and the like; the external environment photoelectric information can be external environment acousto-optic information, thermal imaging information, radiation information, electromagnetic wave information and the like.
When the real-time environment information is acquired, the three-axis unmanned vehicle can perform periodic scanning detection and real-time acquisition through the three-axis unmanned vehicle or an additionally arranged acquisition unit, module or equipment, or the acquisition command can be acquired through the guide information sent by the upper-level system of the three-axis unmanned vehicle and the received remote instruction. The acquisition unit, module or device may be a far infrared camera, a terrain scanner, a navigator, a gyroscope, a sensor, a locator, a velocimeter, a thermal imager, an electromagnetic wave detector, a radar, a visible light television viewing system, an infrared viewing system, a laser range finder, a tracking processor, a target identifier, etc.
Specifically, when the real-time environment information is acquired, a visible light television viewing system, an infrared viewing system, a laser range finder, a tracking processor, a target recognizer and the like can be used for acquiring visible light information/infrared radiation information of a target and a background, photoelectric conversion is completed, original image data of the visible light/infrared target is formed and stored in an external memory, target capture and tracking can be completed by the tracking processor and the target recognizer, target angle deviation is measured and fed back in real time, distance measurement and target positioning are realized by a positioning instrument, a thermal imager, an electromagnetic wave detector, a radar and the like under the condition of target stable tracking, and thus a data basis is provided for target determination and classification of subsequent burst conditions.
As shown in fig. 2, the step 102 may be divided into the following steps in practical application:
step 1021, judging whether an external emergency exists or not based on the real-time environment information;
step 1022, based on the determination result that the external emergency exists, target classification information of the target in the external emergency is extracted.
In this step 102, after the existence of the external emergency is determined, the target classification information of the target in the external emergency is extracted, various information does not need to be continuously extracted from the real-time environment information for determination, and the emergency detection does not need to be performed separately, so that the process is simplified, the time required by the step is shortened, and the overall response speed of the three-axis unmanned vehicle countermeasure method 100 based on the external emergency is increased.
As shown in fig. 3, specifically, in step 1021, when determining whether there is an external emergency, the external emergency is determined by an intelligent recognition and evaluation method, and the intelligent recognition and evaluation method includes the following steps:
10211. acquiring real-time environment information, and extracting target classification information of a target in a suspected emergency;
10212. based on the target classification information, identifying suspected emergency conditions and evaluating the danger degree;
10213. and determining whether the suspected emergency belongs to the external emergency based on the identification and the danger degree evaluation result.
Specifically, in step 10211, when a suspected emergency is found in the acquired real-time environment information, the target classification information of the suspected emergency is extracted.
The suspected emergency refers to a situation that the three-axis unmanned vehicle encounters when performing a task and affects the driving of the three-axis unmanned vehicle or the task, and the situation is an emergency that may cause the three-axis unmanned vehicle to collide, damage, overturn, and the like based on an external environment (target), where the external environment may be any object in the air, on the ground, and in the ground, such as a high-speed and low-speed moving object, an object having radiation, thermal imaging reaction, or biological reaction, and various obstacles and the like. The object classification information at least comprises information of speed, direction, height, distance, angle, position, size and the like of the object in the external emergency. Furthermore, the target classification information may further include information such as energy, volume, and motion trajectory of the target in the external burst condition, so as to improve the state information of the target in the external burst condition, and use the state information as an information basis or judgment content, thereby improving the accuracy of determining the subsequent external burst condition.
Specifically, in step 10212, the suspected emergency condition identification and risk level evaluation may be performed based on a control system of the three-axis unmanned vehicle, or data may be transmitted to a remote location through a network module, and the identification and evaluation may be performed remotely, and the subsequent steps may be performed through a remote command.
It should be noted that the target identification technology is already common in the prior art, and the embodiment is not redundantly described, as a feasible way: the suspected emergency recognition can be implemented by performing pre-training (also called initial training) by adopting a large visual data set such as ImageNet and KITTI, accurately constructing characterization modes of different types of targets through deep neural network and small sample training described by hierarchical parameters, realizing significant region extraction, potential target prediction, target classification and position regression in a single-frame image by utilizing a lightweight deep network, performing post-training and performance evaluation by adopting measured data, classifying and recognizing multiple types of targets, and completing the suspected emergency recognition.
Specifically, in step 10213, after the identification and the corresponding risk level evaluation are completed, if the suspected emergency is dangerous to the three-axis unmanned vehicle and the safety of the three-axis unmanned vehicle, the three-axis unmanned vehicle may be determined as an external emergency.
With continuing reference to fig. 1, in step 103, the determining the type of the emergency condition includes:
when the suspected emergency is determined to belong to the external emergency, determining the type of the emergency based on the target classification information and the risk degree evaluation; the burst condition type comprises at least one of a far lateral or oblique lateral burst condition, a near lateral or oblique lateral burst condition, a vertical or near vertical upper burst condition, and a vertical or near vertical lower burst condition.
The determination of the burst condition type can be determined based on the height information, angle information and position information of the target in the target classification information, and can be used for risk degree assessment based on thermal imaging information, speed information, photoelectric information and the like of the target, such as threat of some external landforms (trenches, hills and the like), can be assessed as a low-risk burst condition, and some high-speed moving objects and objects with high radiation energy can be assessed as a high-risk burst condition.
Specifically, the target in the long-distance transverse or oblique transverse emergency, the short-distance transverse or oblique transverse emergency, the vertical or near-vertical upper emergency may be an external tree, a mountain, a missile, an enemy, an animal, a trap, a tank, an armored car, a rockfall, etc., and the target in the vertical or near-vertical lower emergency may be a trench, a mine, a raised obstacle (a stone, a hill, a humus), etc.
And step 104, mainly controlling the three-axis unmanned vehicle to adjust the vehicle body state and the driving state correspondingly based on the target type of the emergency and the real-time environment information, and further solving the problem of the external emergency in a targeted, safe and stable manner.
As shown in fig. 4, step 104 mainly includes a vehicle body state adjusting step 1041 and a running state adjusting step 1042 of the vehicle.
Specifically, the vehicle body state adjusting step 1041 mainly includes lifting the tire pressure of the wheel, switching the wheel-track structure of the wheel, and adjusting the height of the chassis of the vehicle.
Further, lift wheel tire pressure, switch wheel track structure mainly include: if the road surface is soft or muddy, the front axle and the rear axle wheels of the three-axle unmanned vehicle reduce the tire pressure, and the middle axle switches the wheels to crawler-type running; if the road surface is not soft or muddy, the tire pressure of the front axle and the rear axle of the three-axle unmanned vehicle is kept normal, and the middle axle switches the wheels into wheel type walking. Through this step regulation, when the road surface is soft or muddy road surface, can increase adhesive force through reducing front and rear axle wheel tire pressure to switch into the crawler-type walking with the jackshaft wheel, increase the wheel middle part and support area, reduce rolling resistance, avoid the automobile body to sink, and then can be fast, steadily advance and can not appear skidding, sink.
It should be noted that, in order to realize the switching between the crawler type and the wheel type structure, the wheel of the intermediate shaft of the three-shaft unmanned vehicle may be selected from the existing wheel-track switching type wheel structure to realize the switching between the wheel type and the crawler type structure.
It should be noted that: the triaxial unmanned vehicle has the advantages that the contact area between the intermediate shaft wheels and the ground is small in the wheel type mode, the resistance is small when the triaxial unmanned vehicle travels on flat and solid terrain, the speed is high, the efficiency is high, and the support passing characteristic of the triaxial unmanned vehicle under soft and slippery terrain is poor, so that the triaxial unmanned vehicle is prone to sinking and slipping. After the wheel type mode is converted into the crawler type mode, the contact mode between the wheels of the intermediate shaft and the ground is changed from point contact to surface contact, the ground contact area can be effectively increased, the ground contact specific pressure is reduced, and therefore the bearing passing performance of the unmanned vehicle on soft and slippery terrain is improved. And because the intermediate shaft wheel generates shearing force through pressure and traveling power applied to the ground, the ground applies corresponding supporting force and traction force to the intermediate shaft wheel. Because the three-axis unmanned vehicle has different driving modes, the intermediate shaft wheels have different shapes and different contact conditions with the ground. Under the soft topography, still can produce the subsidence when receiving the pressure of wheel on ground, when the settlement volume is big to a certain extent, the unmanned car of triaxial just can not pass through smoothly.
Therefore, the three-axis unmanned vehicle is switched between a wheel type advancing mode and a crawler type advancing mode by designing the middle shaft wheels into a wheel-track switching structure so as to meet the driving requirements of different road surfaces, ensure that the three-axis unmanned vehicle can normally drive on soft or muddy road surfaces, and reasonably judge whether the driving road surface of the vehicle is soft or muddy road surfaces.
Based on this, the present embodiment provides the following determination method for determining whether the road surface where the three-axis unmanned vehicle is located is a soft or muddy road surface based on the contact model of the deformation wheel established by the beck theory with the ground in different modes:
calculating the maximum horizontal shear force tau of the intermediate shaft wheel which can bear the ground when the intermediate shaft wheel travels on soft terrainmaxThe calculation formula is as follows:
Figure BDA0003186929320000091
wherein c is a constant, σ is a load borne by the ground,
Figure BDA0003186929320000092
is a shear angle;
obtaining the relation between the ground subsidence z and the load sigma borne by the ground, wherein the relation between the ground subsidence z and the load sigma borne by the ground is obtained by the following formula:
Figure BDA0003186929320000093
in the formula, b is the short side length of the contact area between the intermediate shaft wheel and the ground, namely the contact width, n is the index of soil deformation, kc is the cohesive force modulus of the soil deformation and k phi is the friction coefficient of the soil deformation;
obtaining a relation of the load sigma borne by the ground through the conversion of the formula (2):
Figure BDA0003186929320000094
based on the vertical direction force balance of the middle shaft wheel when the soft terrain advances, a vertical direction balance formula is obtained:
Figure BDA0003186929320000095
in the formula, G is a vertical acting force, delta is an integral variable, l is a contact length, and delta M is an included angle between a contact point and a vertical central line of the wheel;
r' is the radius of the part in real time contact with the ground, and has:
Figure BDA0003186929320000096
in the formula, RWRadius of parts for wheeled walking, RTThe equivalent radius is the equivalent radius when the crawler-type walking is carried out, and alpha is the deformation angle of the wheel rim;
obtaining an in-phase by approximation processing based on the formulas (1) to (5)Under the same load condition, the sinking amount Z of the intermediate shaft wheel on soft terrainMAnd the rim deformation angle α:
Figure BDA0003186929320000101
calculating the horizontal traction force F of the intermediate shaft wheel when the intermediate shaft wheel travels on soft terrain to obtain:
Figure BDA0003186929320000102
combining the formulas (1), (2), (3) and (7), obtaining the relationship between the maximum traction force F provided by the intermediate shaft wheel on soft terrain and the rim deformation angle alpha under the same load condition:
Figure BDA0003186929320000103
based on the formulas (1) to (8), the settlement Z with the same traction force required when the intermediate shaft wheels are respectively tracked walking and wheeled walking is solvedt；
Solving the actual subsidence Z of the intermediate shaft wheel during actual walking based on the formulas (1) to (8)s；
And (3) comparison:
if Z iss＞ZtJudging that the road surface is soft or muddy, and adopting crawler-type walking;
if Z iss＜ZtAnd judging that the road surface is a non-soft or non-muddy road surface, and adopting wheel type walking.
The running road condition of the three-axis unmanned vehicle can be judged by the soft or muddy road judging method, so that the vehicle structure is adjusted based on the road condition, and the maneuverability and feasibility of the three-axis unmanned vehicle are ensured.
Further, adjusting the vehicle chassis height mainly comprises: based on the type of emergency, the vehicle chassis height is raised or lowered to keep the vehicle body in high, medium or low ride. In the embodiment, the height of the chassis can be adjusted according to the requirements of the stability and the maneuverability of the vehicle, and when the three-axis unmanned vehicle is in continuous steering, oblique running or in a sudden situation facing to the transverse direction/oblique transverse direction, the chassis can be reduced to be driven to a low position, the gravity center of the vehicle body is reduced, and the stability of the vehicle is improved; when the linear rapid maneuvering is in a sudden situation facing the vertical/near-vertical upper part, the chassis can be adjusted to run to a normal middle position, and the maneuverability of the chassis is improved; when the vehicle is in a straight line rapid maneuvering and faces a sudden situation under the vertical/near vertical direction, the chassis can be improved to be driven to a high position, so that the chassis of the vehicle is far away from danger, and the damage to the vehicle is reduced.
It should be noted that, the height of the vehicle chassis can be adjusted by installing a lifting device such as a hydraulic cylinder between the axle and the wheel, the telescopic end of the hydraulic cylinder is connected with the wheel, and the wheel is connected with a hub motor or a motor, so that the wheel is driven to lift by the telescopic of the hydraulic cylinder, the chassis can be lifted, and the driving of the wheel is not influenced in the lifting process.
The driving state adjusting step 1042 mainly includes determining and switching a steering mode, and adjusting a vehicle maneuvering mode, wherein determining and switching the steering mode includes: determining whether to adopt a center steering mode to quickly steer to steer a defensive surface of the side of the vehicle body to the emergency direction based on the emergency target type; or, determining whether to assist the vehicle in maneuvering using the fast steering mode. Adjusting the vehicle maneuver mode includes: based on the emergency target type, the vehicle driving state is adjusted to a fast crab travel mode, a fast S-shaped travel mode, or a fast straight travel mode.
Specifically, as shown in fig. 5, the center steering mode is that the vehicle rotates clockwise or counterclockwise along the center.
As shown in fig. 6, the fast steering mode is: the front wheels rotate by a required angle along the steering direction, the direction of the middle wheels is unchanged, and the rear wheels rotate by the same angle along the steering direction in the reverse direction, so that four-wheel steering is realized by the front wheels and the rear wheels, the steering radius is smaller, the steering sensitivity is higher, and the steering speed is high.
In some embodiments, when facing a long range lateral/oblique lateral hazard, a center steering mode may be used for fast steering to steer the body side defensive surfaces in the direction of the emergency and a fast steering mode may be used for fast maneuvers in a fast S-shaped travel mode. In some embodiments, when facing short range lateral/diagonal hazards, center steering mode may be used to turn the body side defensive surfaces into the direction of the emergency and quick crab mode may be used for quick maneuvers. In some embodiments, when facing an emergency situation above or below the vertical/near hammer, the fast steering mode may be employed to maneuver quickly in a fast straight mode.
As a second embodiment of the present invention, as shown in fig. 7, there is provided a three-axis unmanned vehicle countermeasure system 200 based on an external emergency situation, which includes,
an obtaining module 201, configured to obtain real-time environment information;
the extraction module 202 is configured to extract target classification information of a target in an external emergency in the real-time environment information;
a determining module 203, configured to determine a type of the emergency condition;
the control module 204 is used for controlling the three-axis unmanned vehicle to adjust the vehicle body state and the running state;
the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
The triaxial unmanned vehicle coping strategy system 200 based on the external emergency obtains real-time environment information based on the obtaining module 201, the extracting module 202 and the determining module 203, accurately determines the emergency target type and provides basic reference data for the control of the subsequent control module 204 based on the real-time environment information, and then adjusts the vehicle body state and the driving state in a targeted manner by utilizing the control module 204 according to the emergency target type and the environment information, so that the emergency coping is completed in a targeted and efficient manner, the stability, the safety and the quick maneuverability of a vehicle are guaranteed, and the success rate of the emergency of the vehicle is high.
As shown in fig. 8, when actually used, the control module 204 may be built based on an autonomous driving controller of the three-axis unmanned vehicle itself, so as to supplement the autonomous driving controller, and for facilitating the classification control of the control module 204, it may be composed of the following modules:
the wheel-track control module 2041 is used for controlling the lifting of the tire pressure of the wheels and the switching of wheel-track structures of the wheels;
the parking space control module 2042 is used for controlling the height adjustment of the vehicle chassis;
a steering control module 2043 for determining and switching a steering mode;
and a drive control module 2044 for controlling vehicle maneuver mode adjustment.
When the vehicle body state needs to be adjusted, the tire pressure, the wheel state switching and the chassis height switching can be respectively controlled by the wheel track control module 2041 and the parking space control module 2042, when the driving state needs to be adjusted, the steering mode can be determined and controlled by the steering control module 2043, the vehicle maneuvering mode is controlled by the driving control module 2044 to be adjusted, and then classification control is performed, so that the control precision and the response speed are improved.
It should be noted that, when necessary, information may also be transmitted and received by the remote signal transmitting and receiving device of the autonomous driving controller, so as to implement remote control.
To better implement the above embodiments, the present invention will be described in further detail with reference to different specific embodiments for a three-axis unmanned vehicle coping strategy method 100 based on an external emergency and a three-axis unmanned vehicle coping strategy system 200 based on an external emergency.
Detailed description of the preferred embodiment 1
As shown in fig. 9, the three-axis unmanned vehicle coping strategy method based on external emergency comprises:
and acquiring the real-time environment information based on the acquisition module. The equipment for acquiring the real-time environment information can be a far infrared camera, a terrain scanner, a navigator, a gyroscope, a sensor, a position finder, a velocimeter, a thermal imager, an electromagnetic wave detection instrument, a radar, a visible light television viewing system, an infrared viewing system, a laser range finder, a tracking processor, a target recognizer and the like.
The extraction module extracts target classification information of external burst conditions in the real-time environment information. The target classification information at least comprises information of speed, direction, height, distance, angle, position, size and the like of the external emergency.
The determining module determines the type of the emergency as a long-distance transverse/oblique transverse emergency based on the target classification information;
the control module is used for controlling the three-axis unmanned vehicle to adjust the vehicle body state and the running state;
the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
During adjustment, the wheel-track control module controls the lifting of the tire pressure of the wheel and the switching of the wheel-track structure of the wheel; when the road surface is soft or muddy, the wheel-track control module controls the front and rear axle wheels to reduce the tire pressure, and the middle axle wheels are switched to a crawler type walking mode to walk; when the road surface is not soft or muddy, the wheel-track control module controls the front and rear axle wheels to keep normal tire pressure, and the middle axle wheels are switched to a wheel type walking mode to walk.
Meanwhile, the parking space control module controls the height of the vehicle chassis to be reduced to the lowest position, and the vehicle runs according to the low-position running state.
After the vehicle is turned, the steering control module determines that the vehicle body is turned in a central steering mode, so that the defense surface of the three-axis unmanned vehicle faces to a dangerous direction, the vehicle is quickly maneuvered in an S-shaped trajectory, and the vehicle is switched into a quick steering mode;
and finally, the driving control module controls the vehicle maneuvering mode to be a rapid S-shaped traveling mode, and rapid maneuvering is carried out according to the S-shaped trajectory, so that the adjustment of the whole three-axis unmanned vehicle responding vehicle under the external emergency is completed.
Specific example 2
As shown in fig. 10, the three-axis unmanned vehicle coping strategy method based on external emergency comprises:
and acquiring the real-time environment information based on the acquisition module. The real-time environment information acquisition equipment can be a far infrared camera, a terrain scanner, a navigator, a gyroscope, a sensor, a position finder, a speed meter, a thermal imager, an electromagnetic wave detector, a radar, a visible light television viewing and aiming system, an infrared viewing and aiming system, a laser range finder, a tracking processor, a target recognizer and the like.
The extraction module extracts target classification information of external burst conditions in the real-time environment information. The target classification information at least comprises information of speed, direction, height, distance, angle, position, size and the like of the external emergency.
The determining module determines the type of the emergency situation as a short-distance transverse/oblique transverse emergency situation based on the target classification information;
the control module is used for controlling the three-axis unmanned vehicle to adjust the vehicle body state and the running state;
the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
During adjustment, the wheel-track control module controls the lifting of the tire pressure of the wheel and the switching of the wheel-track structure of the wheel; when the road surface is soft or muddy, the wheel-track control module controls the front and rear axle wheels to reduce the tire pressure, and the middle axle wheels are switched to a crawler type walking mode to walk; when the road surface is not soft or muddy, the wheel-track control module controls the front and rear axle wheels to keep normal tire pressure, and the middle axle wheels are switched to a wheel type walking mode to walk.
Meanwhile, the parking space control module controls the height of the vehicle chassis to be reduced to the lowest position, and the vehicle runs according to the low-position running state.
After the completion, the steering control module determines that the vehicle body steering is carried out in a central steering mode, so that the vehicle body defense surface of the three-axis unmanned vehicle faces to a dangerous direction, and the vehicle is switched into a rapid crab running mode;
and finally, the driving control module controls the vehicle maneuvering mode to be a quick crab walking mode, and completes the adjustment of the whole three-axis unmanned vehicle responding vehicle under the external emergency by quickly maneuvering on the crab walking trajectory.
Specific example 3
As shown in fig. 11, the three-axis unmanned vehicle coping strategy method based on external emergency includes:
and acquiring the real-time environment information based on the acquisition module. The real-time environment information acquisition equipment can be a far infrared camera, a terrain scanner, a navigator, a gyroscope, a sensor, a position finder, a speed meter, a thermal imager, an electromagnetic wave detector, a radar, a visible light television viewing and aiming system, an infrared viewing and aiming system, a laser range finder, a tracking processor, a target recognizer and the like.
The extraction module extracts target classification information of external burst conditions in the real-time environment information. The target classification information at least comprises information of speed, direction, height, distance, angle, position, size and the like of the external emergency.
The determining module determines the type of the emergency as a vertical/near-vertical upper emergency based on the target classification information;
the control module is used for controlling the three-axis unmanned vehicle to adjust the vehicle body state and the running state;
the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
During adjustment, the wheel-track control module controls the lifting of the tire pressure of the wheel and the switching of the wheel-track structure of the wheel; when the road surface is soft or muddy, the wheel-track control module controls the front and rear axle wheels to reduce the tire pressure, and the middle axle wheels are switched to a crawler type walking mode to walk; when the road surface is not soft or muddy, the wheel-track control module controls the front and rear axle wheels to keep normal tire pressure, and the middle axle wheels are switched to a wheel type walking mode to walk.
Meanwhile, the parking space control module controls the height of the vehicle chassis to be reduced to a middle position, and the vehicle runs according to a middle running state.
After the steering is finished, the steering control module determines that the steering is quickly steered in a quick steering mode;
and finally, the driving control module controls the vehicle maneuvering mode to be a rapid straight-going mode, and rapid maneuvering is carried out by the straight-going trajectory line, so that adjustment of the whole external emergency three-axis unmanned vehicle to the vehicle is completed.
Specific example 4
As shown in fig. 12, the three-axis unmanned vehicle coping strategy method based on external emergency includes:
and acquiring the real-time environment information based on the acquisition module. The real-time environment information acquisition equipment can be a far infrared camera, a terrain scanner, a navigator, a gyroscope, a sensor, a position finder, a speed meter, a thermal imager, an electromagnetic wave detector, a radar, a visible light television viewing and aiming system, an infrared viewing and aiming system, a laser range finder, a tracking processor, a target recognizer and the like.
The extraction module extracts target classification information of external burst conditions in the real-time environment information. The target classification information at least comprises information of speed, direction, height, distance, angle, position, size and the like of the external emergency.
The determining module determines the burst condition type to be a vertical/near-vertical lower burst condition based on the target classification information;
the control module is used for controlling the three-axis unmanned vehicle to adjust the vehicle body state and the running state;
the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
During adjustment, the wheel-track control module controls the lifting of the tire pressure of the wheel and the switching of the wheel-track structure of the wheel; when the road surface is soft or muddy, the wheel-track control module controls the front and rear axle wheels to reduce the tire pressure, and the middle axle wheels are switched to a crawler type walking mode to walk; when the road surface is not soft or muddy, the wheel-track control module controls the front and rear axle wheels to keep normal tire pressure, and the middle axle wheels are switched to a wheel type walking mode to walk.
Meanwhile, the parking space control module controls the height of the vehicle chassis to be raised to the highest position, and the vehicle runs according to the high-position running state.
After the steering is finished, the steering control module determines that the steering is quickly steered in a quick steering mode;
and finally, the driving control module controls the vehicle maneuvering mode to be a rapid straight-going mode, and rapid maneuvering is carried out by the straight-going trajectory line, so that adjustment of the whole external emergency three-axis unmanned vehicle to the vehicle is completed.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.

Claims (10)

1. The three-axis unmanned vehicle coping strategy method based on the external emergency is characterized by comprising the following steps of,
acquiring real-time environment information;
extracting target classification information of targets in external burst conditions in real-time environment information;
determining a type of the emergency condition based on the target classification information;
controlling the three-axis unmanned vehicle to adjust the vehicle body state and the driving state based on the determination result and the real-time environment information;
the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
2. The three-axis unmanned vehicle countermeasure method of claim 1, wherein the real-time environmental information includes at least driving environment information, vehicle driving information, vehicle structural parameter information, and external environment photoelectric information.
3. The tri-axial unmanned vehicle countermeasure method of claim 1, wherein the external emergency condition is determined by a smart recognition evaluation method, the smart recognition evaluation method comprising:
acquiring real-time environment information, and extracting target classification information of a target in a suspected emergency;
based on the target classification information, identifying suspected emergency conditions and evaluating the danger degree;
and determining whether the suspected emergency belongs to the external emergency based on the identification and the danger degree evaluation result.
4. The tri-axial unmanned vehicle countermeasure method of claim 3, wherein the determining of the emergency target type comprises: when the suspected emergency is determined to belong to the external emergency, determining the type of the emergency based on the target classification information and the risk degree evaluation;
the burst condition type comprises at least one of a far lateral or oblique lateral burst condition, a near lateral or oblique lateral burst condition, a vertical or near vertical upper burst condition, and a vertical or near vertical lower burst condition.
5. The tri-axial unmanned vehicle countermeasure method of claim 1, wherein the object classification information includes at least a position, a speed, a direction, and a height of an object in an external emergency.
6. The triaxial unmanned vehicle countermeasure method of claim 1, wherein the elevating tire pressure and switching wheel-track structure comprises:
if the road surface is soft or muddy, the front axle and the rear axle wheels of the three-axle unmanned vehicle reduce the tire pressure, and the middle axle switches the wheels to crawler-type running;
if the road surface is not soft or muddy, the tire pressure of the front axle and the rear axle of the three-axle unmanned vehicle is kept normal, and the middle axle switches the wheels into wheel type walking.
7. The three-axis unmanned vehicle countermeasure method of claim 6, wherein the method of determining a soft or muddy road comprises:
calculating the maximum horizontal shear force tau born by the intermediate shaft wheel when the intermediate shaft wheel runs on soft terrainmaxThe calculation formula is as follows:
Figure FDA0003186929310000021
wherein c is a constant, σ is a load borne by the ground,
Figure FDA0003186929310000022
is a shear angle;
obtaining the relation between the ground subsidence z and the load sigma borne by the ground, wherein the relation between the ground subsidence z and the load sigma borne by the ground is obtained by the following formula:
Figure FDA0003186929310000023
in the formula, b is the short side length of the contact area between the intermediate shaft wheel and the ground, namely the contact width, n is the index of soil deformation, kc is the cohesive force modulus of the soil deformation and k phi is the friction coefficient of the soil deformation;
obtaining a relation of the load sigma borne by the ground through the conversion of the formula (2):
Figure FDA0003186929310000024
based on the vertical direction force balance of the middle shaft wheel when the soft terrain advances, a vertical direction balance formula is obtained:
Figure FDA0003186929310000025
in the formula, G is a vertical acting force, delta is an integral variable, l is a contact length, and delta M is an included angle between a contact point and a vertical central line of the wheel;
r' is the radius of the part in real time contact with the ground, and has:
Figure FDA0003186929310000026
in the formula, RWRadius of parts for wheeled walking, RTThe equivalent radius is the equivalent radius when the crawler-type walking is carried out, and alpha is the deformation angle of the wheel rim;
obtaining the amount of subsidence Z of the intermediate shaft wheel on soft terrain under the same load condition through approximate processing based on the formulas (1) to (5)MAnd the rim deformation angle α:
Figure FDA0003186929310000027
calculating the horizontal traction force F of the intermediate shaft wheel when the intermediate shaft wheel travels on soft terrain to obtain:
Figure FDA0003186929310000031
combining the formulas (1), (2), (3) and (7), obtaining the relationship between the maximum traction force F provided by the intermediate shaft wheel on soft terrain and the rim deformation angle alpha under the same load condition:
Figure FDA0003186929310000032
based on the formulas (1) to (8), the settlement Z with the same traction force required when the intermediate shaft wheels are respectively tracked walking and wheeled walking is solvedt；
Solving the actual subsidence Z of the intermediate shaft wheel during actual walking based on the formulas (1) to (8)s；
And (3) comparison:
if Z iss＞ZtThen the road surface is judged to be softOr a muddy road surface, and the crawler type walking is adopted;
if Z iss＜ZtAnd judging that the road surface is a non-soft or non-muddy road surface, and adopting a wheel type to walk.
8. The three-axis unmanned vehicle countermeasure method of claim 1, wherein the adjusting vehicle chassis height comprises:
based on the type of emergency, the vehicle chassis height is raised or lowered to keep the vehicle body in high, medium or low drive.
9. The three-axis unmanned vehicle countermeasure method of claim 1, wherein the determining and switching steering modes comprises:
determining whether to adopt a center steering mode to quickly steer to steer a defensive surface of the side of the vehicle body to the direction of the emergency based on the type of the emergency; or, determining whether to assist the vehicle in maneuvering using the fast steering mode.
10. A three-axis unmanned vehicle response strategy system based on external emergency is characterized by comprising,
the acquisition module is used for acquiring real-time environment information;
the extraction module is used for extracting target classification information of targets in external burst conditions in the real-time environment information;
a determining module for determining a type of the emergency condition;
the control module is used for controlling the three-axis unmanned vehicle to adjust the vehicle body state and the running state;
the vehicle body state adjusting method comprises the steps of lifting the tire pressure of a wheel, switching the wheel track structure of the wheel and adjusting the height of a vehicle chassis; the adjusting the driving state comprises determining and switching a steering mode and adjusting a vehicle maneuvering mode.
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