CN117132128A - Intelligent army system capable of achieving autonomous engagement and operation flow - Google Patents
Intelligent army system capable of achieving autonomous engagement and operation flow Download PDFInfo
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Abstract
The invention discloses an intelligent army system capable of autonomous engagement and an operation flow thereof. The invention uses digital twin, intelligent task planning, unmanned cluster AI control and other technologies to realize that the red army can independently fight by adopting live ammunition striking and intelligent blue army, thereby greatly reducing the additional equipment of the red army, reducing the potential safety hazard and improving the training quality.
Description
Technical Field
The invention relates to the field of training, in particular to an intelligent army system capable of achieving autonomous engagement and an operation flow.
Background
The army is a knife stone for checking the battle ability of the army, and with the development of big data, artificial intelligence, unmanned technology and the like, the intelligent army based on unmanned equipment gradually walks into a training field. The biggest advantage brought by adopting the intelligent blue army is that the red army can adopt the live ammunition to develop the countermeasure training, is closer to the live combat, and achieves the aim of 'how to play in the time of combat and how to exercise in ordinary times'. The current intelligent army construction is still in the starting stage, and in use, there are a plurality of defects:
(1) Insufficient autonomous engagement capacity
The current intelligent army-related unmanned equipment (personnel targets, equipment targets and the like) is mainly remotely controlled by personnel in the background to realize tactical actions such as maneuver, striking and the like, has weak autonomous engagement capacity, is influenced by human factors, and has larger gap in simulating army combat ideas, command modes, tactical application and the like.
(2) The additional equipment of the red army is numerous
The existing intelligent army-based countermeasure training system, no matter laser or digital ammunition is adopted for striking, additional equipment such as a laser receiver, a weapon efficiency device, pose measuring equipment and the like are additionally arranged on army personnel and equipment, each equipment needs to be connected to the network for running, and the system is complex in composition and inconvenient to use.
(3) The safety risk management and control means is not enough
The training quality can be greatly improved by adopting live ammunition training, but potential safety hazards such as accidental injury and the like are also easily brought, and the safety risk in training is urgently required to be reduced by technical means.
Disclosure of Invention
The invention aims to solve the technical problem of providing a system and a method for measuring the explosion point by using an infrared image, which adopt trajectory simulation to calculate the explosion point and then determine the explosion point through data fusion, so that the accuracy and the precision of explosion point detection can be greatly improved.
The invention aims to solve the technical problem of providing an intelligent army system capable of achieving autonomous engagement and an operation flow thereof, so that the 'the army can achieve autonomous engagement by adopting live ammunition striking and intelligent army', the additional equipment of the army is greatly reduced, the potential safety hazard is reduced, and the training quality is improved.
The technical scheme for realizing the purpose of the invention is as follows:
an intelligent army system capable of autonomous engagement comprises a guiding control system, a physical space, a twin space, army command information system software, army unmanned cluster control software and a basic supporting environment;
the pilot control system is used for completing training task planning, data acquisition and distribution, situation display, arbitration evaluation, pilot intervention and report generation;
the physical space comprises a red army entity, a blue army entity, an intermittent explosion point measuring system and a physical battlefield environment, wherein the red army entity strikes the blue army entity by using a live ammunition, the blue army entity can collect the impact point of a direct aiming weapon, the intermittent explosion point measuring system can collect the explosion point of the ammunition shot by the intermittent aiming weapon, and the direct aiming weapon impact point information collected by the blue army entity is combined for the damage calculation and evaluation of the red army to the blue army;
the twin space comprises a maroon twin body, a blue army twin body, a damage calculation module, a marching safety early warning module, a pose resolving module and a twin battlefield environment, wherein after the marching twin body is hit by the blue army twin body, the damage effect can be displayed according to the output result of the damage calculation module, the blue army twin body is driven by blue army unmanned cluster control software, the red army twin body is hit by adopting digital ammunition, the damage calculation module combines a physical space, the twin space and a damage evaluation model with a vulnerability model, the pose resolving module can realize pose resolving of red army personnel and equipment for digital twin of the red army entity, and the red army safety early warning module utilizes an artificial intelligent algorithm to predict and remind in real time;
the Lan Jun command information system software realizes command control and task planning for the army, and comprises a command control module and a task planning module, wherein the command control module receives training tasks, guiding and adjusting intervention and fight judging information issued by a guiding and adjusting control system, and the task planning module completes fight task allocation, task sequence generation, fight resource allocation and fight action coordination according to fight tasks issued by the command control module according to the army fight thought weapon force resource allocation and initialization deployment;
the blue army unmanned cluster control software comprises an unmanned cluster system control module, a battlefield situation awareness module, an unmanned cluster AI decision module and a deep learning module, wherein the battlefield situation awareness module can acquire battlefield situation information from the twin space 3 in real time, and under the support of the unmanned cluster AI decision module, a blue army combat action decision is carried out, the unmanned cluster system control module is combined with a decision instruction to complete unmanned cluster cooperative control calculation and control a blue army twin body to complete actions, and the unmanned cluster AI decision module can complete tactical actions of blue army and intelligent decisions of tactical actions; the deep learning module can form a cluster intelligent body through a group game data driving method and a deep reinforcement learning algorithm;
the base support environment is configured to provide data services, computing services, storage services, communication services, positioning services, timing services, weather services, and crawler services.
The operation flow is as follows:
(1) According to the fight assumption, the director part issues training tasks to the red army and the intelligent blue army through the guiding control system;
(2) After receiving the training task, the red army commander completes the initial deployment, task delivery and the like of personnel, ground equipment and land navigation equipment through the integrated command platform, and the blue army entity is hit by the live ammunition in the process of engagement;
(3) After receiving the training task, the bluing command personnel develop the initialization deployment, task planning and the like of bluing twins through bluing command information system software to complete combat task allocation, task sequence generation, combat resource allocation, combat action coordination and the like;
(4) The unmanned blue army cluster control software collects battlefield situations in real time, under the decision support of the unmanned cluster AI, unmanned cluster cooperative control is carried out according to task planning information, a blue army twin body is driven to strike a red army twin body by adopting digital ammunition, and the step (2) is combined to form the antagonism relationship between the red army and the intelligent blue army, so that the functions of 'the red army is struck by live ammunition and the intelligent blue army can be independently battled' are realized;
(5) In the process of fighting with the red army and the intelligent blue army, acquiring the explosion point position of aiming the weapon between red army entities, the impact point position of aiming the weapon and the digital ammunition information of the blue army twins in real time, and carrying out damage calculation by combining a damage evaluation model and a vulnerability model;
(6) The guiding control system performs fight arbitration according to the damage calculation result, controls the damaged personnel and equipment of both red and blue parties to reduce fight capability, withdraw from fight and the like;
(7) The director part controls the training process according to the fight thinking, fight results and the like, and automatically generates an evaluation report according to the acquired data after the training is finished so as to allow the red and blue parties to review and review the returnable; meanwhile, related data are also used for machine learning of the deep learning module, so that the decision capability of the unmanned cluster AI decision module is improved, and the autonomous engagement capability of intelligent army is continuously improved.
The invention has the technical effects that:
(1) Realizing autonomous engagement of intelligent army
The technologies of digital twinning, intelligent task planning, unmanned cluster AI control and the like are utilized, so that autonomous engagement of intelligent blue army is realized; meanwhile, through data such as combat warfare, course teaching materials, combat experiments, exercise training, actual combat summarization and the like of the blue army which is crawled in real time, and red and blue countermeasure data and the like generated by the system, the autonomous combat capability of the intelligent blue army is stronger and stronger through deep learning training.
(2) Additional equipment for greatly simplifying red army
In the invention, firstly, equipment such as a laser receiver, a weapon efficacy device and the like does not need to be additionally arranged when the countermeasure is simulated; secondly, when in digital twinning, pose measuring equipment is not required to be additionally arranged, the system synthesizes the position information and the characteristic information of the red army personnel and equipment and the elevation information of the battlefield environment, and the pose of the red army personnel and the equipment is resolved through pattern recognition, so that the digital twinning is realized, and the additional equipment of the red army is greatly simplified.
(3) Can effectively reduce the safety risk during live ammunition training
The red army safety early warning module is designed, the action or the behavior of the red army twin body is predicted by using an artificial intelligent algorithm, the action or the behavior which possibly brings potential safety hazards such as accidental injury can be predicted in real time, the red army entity is timely reminded to avoid, and the safety risk in real-time bullet training is reduced.
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Fig. 1: system composition and schematic diagram
Detailed Description
The present invention will now be described in detail with reference to the drawings, wherein the examples are set forth only to facilitate an understanding of the invention, and are not to be construed as limiting the scope of the invention, since modifications and alterations of the invention may be made by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Referring to FIG. 1, the invention comprises a guiding control system 1, a physical space 2, a twin space 3, a blue army command information system software 4, a blue army unmanned cluster control software 5 and a basic supporting environment 6;
the pilot control system 1 is used for completing training task planning, data acquisition and distribution, situation display, decision evaluation, pilot intervention and report generation;
the physical space 2 includes a red army entity 21, a blue army entity 22, an intermittent explosion point measuring system 23 and a physical battlefield environment 24 (natural environment, electromagnetic environment, network communication environment, etc.).
The red-army entity 21 comprises an integrated command platform 211, personnel 212, ground equipment 213 and land equipment 214.
The integrated command platform 211 is an actual command system for the red army, and receives information such as training tasks, guiding and adjusting interventions, and engagement decisions issued by the guiding and adjusting control system 1 on one hand, and realizes command control for the red army on the other hand.
Personnel 212, ground equipment 213 and land equipment 214 are actual personnel and equipment to which a positioning module is added for digital twinning.
The bluing entity 22 includes a robot 221, a drone 222, a drone 223, and an industrial obstacle 224.
The robot 221, the unmanned vehicle 222 and the unmanned vehicle 223 are used for simulating the personnel and equipment of the army, and are composed of a stay wire chassis, a target, an acousto-optic smoke electric simulation device and a bullet information acquisition device, and the army is highly simulated in the aspects of appearance, infrared characteristics, acousto-optic smoke characteristics, tactical actions, operational capacity and the like.
The work obstacle 224 is used to simulate a blutroy array ground layout and obstacle system, wherein the work adopts simulated work to facilitate deployment and the obstacle adopts actual obstacle to facilitate assessment of obstacle breaking capability.
The intermittent aiming explosion point measuring system 23 is used for measuring explosion points of the red army intermittent aiming weapon for transmitting ammunition, and is used for the damage evaluation of the red army to the blue army by combining the direct aiming weapon explosion point information acquired by the robot 221, the unmanned vehicle 222 and the unmanned vehicle 223.
The twin space 3 comprises a marvelous twin body 31, a bluous twin body 32, a damage calculation module 33, a marvelous safety early warning module 34, a pose solving module 35 and a twin battlefield environment 36.
The marching twins 31 include a personnel twinning body 311, a ground equipment twinning body 312 and a land equipment twinning body 313, and after being hit by the marching twinning body 32, the marching effect can be displayed according to the output result of the marching calculation module 33.
The blue army twin 32 comprises a robot twin 321, an unmanned vehicle twin 322, an unmanned vehicle twin 323 and an engineering obstacle twin 324, and is driven by blue army unmanned cluster control software 5 to strike the red army twin 31 by digital ammunition.
The damage calculation module 33 collects the information of the intermittent explosion point and the direct impact point of the physical space on one hand, and collects the digital ammunition information of the twin space on the other hand, combines the damage evaluation model and the vulnerability model to carry out damage calculation, and transmits the damage result to the guiding control system 1 for the arbitration evaluation of the director part, guiding intervention and the like; the damage results are transmitted to the marching twin 31 and the marching twin 32 for the display of the damage effect.
The red army safety early warning module 34 predicts the action or the behavior of the red army twin 31 by using an artificial intelligence algorithm, can predict the action or the behavior possibly bringing about potential safety hazards such as accidental injury and the like in real time, and timely reminds the red army entity 21 to avoid, so that the safety risk in training is reduced.
The pose resolving module 35 combines the position information, the feature information and the elevation information of the battlefield environment 36 of the red army entity 21 to achieve resolving of the pose (the orientation and speed of personnel, the pose such as standing, squatting and creeping, the orientation and speed of equipment, and the like) of red army personnel and equipment for digital twin of the red army entity 21.
Lan Jun the command and information system software 4 includes a command and control module 41 and a mission planning module 42.
The command control module 41 is deployed according to the blue force command seat, operated by the blue force command personnel, receives the information of training tasks, guiding and adjusting interventions, engagement decisions and the like which are issued by the guiding and adjusting control system, and initiates deployment and the like according to the blue force operational thought weapon force resource allocation.
The task planning module 42 includes a cooperative task analysis unit 421, a hit target analysis unit 422, a combat force application unit 423, and a combat action planning unit 424, and completes combat task allocation, task sequence generation, combat resource allocation, combat action coordination, and the like according to combat tasks issued by the command control module.
The blue army unmanned cluster control software 5 mainly comprises an unmanned cluster system control module 51, a battlefield situation awareness module 52, an unmanned cluster AI decision module 53 and a deep learning module 54, and is a core for realizing intelligent blue army autonomous engagement, the blue army twin 32 is driven to engage in autonomous engagement with the red army twin 31 by using an AI algorithm, and an entity in the physical space 2 is synchronized with the twin in the twin space 3 in real time, so that autonomous engagement between the blue army entity 22 and the red army entity 21 is realized.
The unmanned cluster system control module 51 combines the combat mission information and combat action decision instructions to complete unmanned cluster cooperative control calculation, and issues control commands to the bluing army twin 32 to control the bluing army twin 32 to complete actions such as gathering, reconnaissance, maneuver, concealing, striking, combat withdrawal and the like.
The battlefield situation awareness module 52 acquires battlefield situation information from the twin space 3 in real time, and performs a army combat action decision under the support of the unmanned cluster AI decision module 53.
The unmanned cluster AI decision module 53 includes an AI behavior model unit 531, an AI decision model 532, an AI rule model 533, and an AI influence model 534, and is a basis for realizing autonomous engagement, and completes intelligent decisions of tactical actions, and the like of the army.
The deep learning module 54 adopts a group game data driving method, fuses a deep reinforcement learning algorithm, continuously learns knowledge data such as a blue army combat command, a course teaching material and the like, influence data of environmental elements on army equipment and combat actions, and practical data such as combat experiments, exercise training, actual combat summarization and the like, and forms a group intelligent body with strong perception capability, decision making capability and execution capability, so that support is provided for autonomous combat.
The base support environment 6 mainly provides data services, computing services, storage services, communication services, positioning services, time services, weather services, crawler services, etc. Wherein the crawler service utilizes technologies such as big data, deep learning, etc., and crawls data such as the combat command, course teaching material, combat experiment, exercise training, actual combat summarization, etc. of the army in real time on the internet, ensures the freshness of the data, and is used for the learning training of the deep learning module 54.
The operation flow of the system of the invention is as follows:
(1) According to the fight assumption, the director part issues training tasks to the red army and the intelligent blue army through the guiding control system 1;
(2) After receiving the training task, the red army commander completes the initial deployment, task delivery and the like of personnel 212, ground equipment 213 and land equipment 214 through the integrated command platform 211, and the blue army entity is hit by the live ammunition in the process of engagement;
(3) After receiving the training task, the bluing command personnel completes the initialized deployment and task planning of the bluing twin body 32 through the bluing command information system software 4, and completes the fight task allocation, the task sequence generation, the fight resource allocation, the fight action coordination and the like;
(4) The unmanned blue army cluster control software 5 collects battlefield situations in real time, under the decision support of the unmanned cluster AI, unmanned cluster cooperative control is carried out according to task planning information, the twin 32 of blue army is driven to strike the twin 31 of red army by adopting digital ammunition, and the fighting relation between the red army and the intelligent blue army is formed by combining the step (2), so that the functions of 'the red army is struck by live ammunition and the intelligent blue army can be independently battled' are realized;
(5) In the process of fighting with the red army and the intelligent blue army, acquiring the explosion point position of aiming the weapon between red army entities, the impact point position of aiming the weapon and the digital ammunition information of the blue army twins in real time, and carrying out damage calculation by combining a damage evaluation model and a vulnerability model;
(6) The guiding control system 1 performs fight arbitration according to the damage calculation result, and controls the damaged personnel and equipment of the red and blue parties to reduce fight capability, exit fight and the like;
(7) The director part controls the training process according to the fight thinking, fight results and the like, and automatically generates an evaluation report according to the acquired data after the training is finished so as to allow the red and blue parties to review and review the returnable; and the related data is also used for machine learning of the deep learning module 54, so as to continuously intelligent autonomous engagement capacity of the army.
Claims (6)
1. An intelligent army system capable of achieving autonomous engagement is characterized by comprising a guiding control system (1), a physical space (2), a twin space (3), army command information system software (4), army unmanned cluster control software (5) and a basic supporting environment (6);
the pilot control system (1) is used for completing training task planning, data acquisition and distribution, situation display, decision evaluation, pilot intervention and report generation;
the physical space (2) comprises a red army entity (21), a blue army entity (22), an intermittent explosion point measuring system (23) and a physical battlefield environment (24), wherein the red army entity (21) uses a real bullet to strike the blue army entity (22), the Lan Jun entity (22) can collect the explosion point of a direct aiming weapon, the intermittent explosion point measuring system (23) can collect the explosion point of the intermittent weapon for transmitting ammunition, and the direct aiming weapon explosion point information collected by the blue army entity (22) is combined for the damage calculation and evaluation of the red army on the blue army;
the twin space 3 comprises a maroon twin body (31), a blue army twin body (32), a damage calculation module (33), a maroon safety early warning module (34), a pose calculation module (35) and a twin battlefield environment (36), wherein after the maroon twin body (31) is hit by the blue army twin body (32), the damage effect can be displayed according to the output result of the damage calculation module (33), the blue army twin body (32) can be driven by a blue army unmanned cluster control software (4), the maroon twin body (31) is hit by adopting digital ammunition, the damage calculation module (33) combines a physical space (2), the twin space (3) and a damage evaluation model and a damage model to develop the transmission and the damage effect display of the damage result, the pose calculation module (35) can realize the pose calculation of red army and equipment for digital twin of the red entity (21), and the maroon safety early warning module (34) utilizes an artificial intelligent prediction and a real-time reminding algorithm;
the Lan Jun command information system software (4) realizes command control and task planning of the army, and comprises a command control module (41) and a task planning module (42), wherein the command control module (41) receives training tasks, guiding and adjusting intervention and fight arbitration information issued by the guiding and adjusting control system (1), and the task planning module (42) completes fight task allocation, task sequence generation, fight resource allocation and fight action coordination according to the fight tasks issued by the command control module (41) according to the force resource allocation and the initialized deployment of the army fight ideas;
the unmanned blue army cluster control software (5) comprises an unmanned cluster system control module (51), a battlefield situation awareness module (52), an unmanned cluster AI decision module (53) and a deep learning module (54), wherein the battlefield situation awareness module (52) can acquire battlefield situation information from a twin space (3) in real time, and a blue army combat action decision is carried out under the support of the unmanned cluster AI decision module (53), the unmanned cluster system control module (51) combines with a decision instruction to complete unmanned cluster cooperative control calculation and control a blue army twin body (32) to complete actions, and the unmanned cluster AI decision module (53) can complete tactical actions of blue army and intelligent decisions of tactical actions; the deep learning module (54) can form a cluster intelligent agent through a group game data driving method and a deep reinforcement learning algorithm;
the base support environment (6) is for providing data services, computing services, storage services, communication services, positioning services, timing services, weather services and crawler services.
2. The intelligent army system capable of achieving autonomous engagement according to claim 1, wherein the army entity (21) comprises an integrated command platform (211), personnel (212), ground equipment (213) and land equipment (214), the integrated command platform (211) is an actual army command system, receives information such as training tasks, guiding and adjusting interventions and engagement decisions and the like issued by the guiding and adjusting control system, achieves command control of the army, and is provided with positioning modules on the personnel (212), the ground equipment (213) and the land equipment (214) for digital twin.
3. An autonomously engageable intelligent navy system according to claim 2, wherein the personnel (212), ground equipment (213) and land equipment (214) are actual personnel and equipment.
4. The autonomous battle intelligent navy system of claim 1, wherein the Lan Jun entity (22) comprises a robot (221), an unmanned vehicle (222), an unmanned vehicle (223), and a work obstacle (224), the robot (221), unmanned vehicle (222), and unmanned vehicle (223) are used to simulate navy personnel and equipment, and the work obstacle (224) is used to simulate navy battle ground mating, obstacle system.
5. An autonomous competitive intelligent navy system as claimed in claim 4, wherein the work in the work barrier (224) is a simulated work and the barrier is an actual barrier.
6. The intelligent army system operation flow capable of achieving autonomous engagement is characterized in that a director part issues training tasks to the army and the intelligent army through the guiding control system (1), the army commander completes personnel (212), initial deployment of ground equipment (213) and land and air equipment (214) through the integrated command platform (211), the army commander hits a army entity (22) in the task issuing and engagement process, the army commander completes initial deployment of the army twinning body (32), task planning, task allocation, task sequence generation, operational resource allocation and operational action coordination through the Lan Jun command information system software (4), the army unmanned cluster control software (5) collects battlefield situations in real time, unmanned cluster cooperative control is performed, the army twinning body (32) is driven to achieve a combat fighting relationship of the army twinning body (31) by adopting digital ammunition, the position of the army twinning body and the intelligent army is collected, the position of the army twinning body is reported by the army twinning body in real time, the position of the army twinning body and the intelligent army is subjected to a combat fighting body, the position of the army is reported by the training aid is carried out by the training aid of the training control system, and the training aid is evaluated according to a digital training model (1), and the vulnerable result is evaluated according to the training data of the training model (1).
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| CN117930868A (en) * | 2024-03-14 | 2024-04-26 | 湖南星河云程信息科技有限公司 | Mobile self-scheduling design method, device, equipment and medium for air formation |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117930868A (en) * | 2024-03-14 | 2024-04-26 | 湖南星河云程信息科技有限公司 | Mobile self-scheduling design method, device, equipment and medium for air formation |
| CN117930868B (en) * | 2024-03-14 | 2024-05-24 | 湖南星河云程信息科技有限公司 | Mobile self-scheduling design method, device, equipment and medium for air formation |
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