CN112731921A - Military path planning support system based on parallel simulation - Google Patents
Military path planning support system based on parallel simulation Download PDFInfo
- Publication number
- CN112731921A CN112731921A CN202011436294.4A CN202011436294A CN112731921A CN 112731921 A CN112731921 A CN 112731921A CN 202011436294 A CN202011436294 A CN 202011436294A CN 112731921 A CN112731921 A CN 112731921A
- Authority
- CN
- China
- Prior art keywords
- module
- path planning
- marching
- path
- map
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000004088 simulation Methods 0.000 title claims abstract description 53
- 238000012544 monitoring process Methods 0.000 claims abstract description 31
- 238000000034 method Methods 0.000 claims abstract description 30
- 238000004891 communication Methods 0.000 claims abstract description 26
- 230000008569 process Effects 0.000 claims abstract description 23
- 230000007613 environmental effect Effects 0.000 claims abstract description 13
- 238000005457 optimization Methods 0.000 claims abstract description 8
- 238000004422 calculation algorithm Methods 0.000 claims description 7
- 230000004888 barrier function Effects 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 4
- 238000006243 chemical reaction Methods 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 7
- 238000005516 engineering process Methods 0.000 description 4
- 238000010276 construction Methods 0.000 description 3
- 238000007726 management method Methods 0.000 description 3
- 241000257303 Hymenoptera Species 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 2
- 230000007123 defense Effects 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 239000003016 pheromone Substances 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000000470 constituent Substances 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012821 model calculation Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 239000012466 permeate Substances 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000001681 protective effect Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
Abstract
The invention discloses a military path planning support system based on parallel simulation, which comprises a communication module, an environmental information identification module, a path planning module, a monitoring module and a control system, wherein the communication module is used for receiving environmental information; the communication module is used for transmitting data information among the environment information identification module, the path planning module, the monitoring module and the control system; the environment information identification module is used for collecting map information of a marching area; the route planning module is used for realizing map modeling according to the map information obtained by the environment information identification module, abstracting the transportation process into a constraint optimization problem of a two-dimensional space, and obtaining an optimal marching route; the monitoring module is used for detecting obstacles along the transportation path in the marching process; the control system module marks the obstacles detected by the monitoring module to complete map information updating, and the updated map information is acted on the path planning module through the communication module to obtain a new marching simulation route. The invention can avoid obstacles and greatly improve the transportation efficiency.
Description
Technical Field
The invention belongs to the technical field of simulation and control management in command decision, and particularly relates to a military path planning support system based on parallel simulation.
Background
The simulation technology is a modified object which is formed by combining a computer system with physical effect simulation equipment and tools, establishing and operating a model according to a research target and based on comprehensive interdisciplinary disciplines and knowledge through the existing research. With the continuous development of computer information technology, the parallel simulation technology has important practical significance in the process of national defense and military construction development, and even gradually begins to permeate into various fields in our daily life. A military path planning application based on a parallel simulation system is designed, and aims to solve the problems that a commander is assisted to know forward environment information in time and corresponding military transportation routes are adjusted under different situations in the military transportation process, the combat efficiency is improved, the transportation cost is reduced and the like.
The military path planning has the function of ensuring that troops can complete established tasks safely and efficiently. The precondition of the method is to ensure the execution of the task to have high efficiency and high reliability. In the face of more extensive field command and complex task execution, the related path planning technical solution faces higher requirements. How to deal with the avoidance of the emergent threats on the planned transportation route and how to rapidly carry out the path planning again is the key point for solving the military path planning problem.
Disclosure of Invention
The invention aims to provide a military path planning support system based on parallel simulation, which can rapidly update and share data information and solve the problems of high transportation cost and casualties caused by sudden threats in the marching process.
The technical solution for realizing the purpose of the invention is as follows:
a military path planning support system based on parallel simulation comprises a communication module, an environmental information identification module, a path planning module, a monitoring module and a control system;
the communication module is used for transmitting data information among the environment information identification module, the path planning module, the monitoring module and the control system;
the environment information identification module is used for collecting map information of a marching area;
the path planning module is used for realizing map modeling according to the map information obtained by the environment information identification module, abstracting the transportation process into a constraint optimization problem of a two-dimensional space, and simulating according to an ant colony algorithm to obtain an optimal marching path;
the monitoring module is used for detecting the transportation path along the way in the marching process and detecting the obstacles in the marching route;
the control system module marks the obstacles detected by the monitoring module to complete map information updating, and further acts the updated map information on the path planning module through the communication module to obtain a new marching simulation route through simulation.
Compared with the prior art, the invention has the following remarkable advantages:
all modules are networked and interconnected, and data information can be updated and shared rapidly; by optimizing the path planning result, the problems of high transportation cost and casualties caused by sudden threats in the marching process are solved; through the integration of a parallel simulation technology and path planning, uninterrupted circulating parallel simulation is realized, the feasibility of a path scheme is deduced, the path replacement scheduling time is shortened, obstacles are avoided, the transportation efficiency is greatly improved, auxiliary monitoring protective measures are matched, the influence caused by sudden threats in the transportation process is further reduced, and the transportation safety is enhanced.
Drawings
FIG. 1 is a schematic diagram of the constituent modules of the present invention.
FIG. 2 is a marching region map display in accordance with an embodiment of the present invention.
Fig. 3 is a marching route planning diagram according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a monitoring module prompting risk information according to an embodiment of the present invention.
Fig. 5 is a diagram showing the structure of the control system of the present invention.
Fig. 6 is a flowchart of implementation of parallel simulation path planning in the embodiment of the present invention.
Fig. 7 is a diagram illustrating a result of calculating a simulation route according to an embodiment of the present invention.
Detailed Description
The invention is further described with reference to the following figures and embodiments.
The invention will now be further described with reference to a certain embodiment and the accompanying drawings.
A certain march wants to determine a process that a certain team in a certain real environment starts from the area A, passes along the enemy position and reaches the area B according to the simulation path planning route. The departure points of the area A are named as Wangcun 1 and Wangcun 2 respectively, the destination points of the area B are named as Wangcun 3 and Wangcun 4 respectively, and the army mission is completed through a military path planning support system based on parallel simulation.
The specific cases planned by the march in the embodiment of the present invention are described as follows:
the basic cases include: the unit for executing the marching tasks is a light vehicle power-driven connecting team which is divided into two longitudinal teams, each longitudinal team comprises a sub-team echelon, the lowest equipment standard of the echelon is 10 persons, 10 sets of person matching equipment and 75 liters of oil, and one light vehicle is used. The known conditions of marching regions include unknown high lands, cannon battle fields, enemy defense fields, enemy command centers, enemy control areas and the like.
And (3) marching target formulation: when the vehicle arrives at the destination B from the destination A, enemy obstacles need to be avoided in the marching process, the enemy fire hitting range is avoided, and the vehicle can arrive at the destination without casualties and the like.
Referring to fig. 1, the military path planning support system based on parallel simulation of the present invention includes a communication module 1, a monitoring module 3, an environmental information identification module 4, a path planning module 5, and a control system 2. The communication module 1, the monitoring module 3, the environmental information identification module 4 and the path planning module 5 are respectively connected with the control system 2.
The communication module 1 is used for realizing data information transmission between the environment information identification module 4, the path planning module 5, the monitoring module 3 and the control system 2. The communication module transmits data to the environment information identification module, the path planning module, the monitoring module and the control system through networking, so that information interconnection and intercommunication are realized, and a marching route model calculation result is updated in real time. The communication module 1 of the present embodiment is a wireless communication module, but is not limited to a wireless communication system. The wireless communication module comprises one or more of a GSM module, a 3G module, a 4G module, a 5G module, a WIFI module, a PTR2000 wireless transmission module, a ZigBee module or a Bluetooth module.
Referring to fig. 2, the environment information recognition module 4 acquires map information of the marching region through situation sensing means such as satellite map positioning and radar, and draws a topographic map of the region, including information of the unknown high land, the peaceful enemy control region, the enemy communication hub, the enemy tank cluster, the enemy cannon battle position and the like.
Referring to fig. 3, the path planning module 5 abstracts the transportation process into a constraint optimization problem of a two-dimensional space according to the information in the topographic map obtained by the environment information identification module 4, wherein the constraint condition is to avoid contact with obstacles such as the unknown region, the healthy and enemy control region, the enemy communication hub, the enemy tank cluster, the enemy cannon battlefield and the like, the optimization function is composed of a path length function and an obstacle penalty function, and the mathematical modeling problem of the path planning can be described as solving the minimum value of the following expression:
min F＝μ1Fs+μ2Fc
wherein Fs is a path length function, Fc is an obstacle point penalty function consisting of obstacles encountered in the path point, and μ1And mu2Is a weighted value, and μ1+μ2＝1。
Dividing the marching route into N path points, the path length of marching is FsThe calculation formula is as follows:
wherein, Pi( i 1, 2.. N) denotes the position of the ith waypoint, SiRepresents the distance between the i-th and i + 1-th position points;
barrier penalty function FcThe calculation formula is as follows:
wherein the content of the first and second substances,
for ith waypoint to jth obstacle Qj(j ═ 1, 2.., K). m (i, j) is the distance between the ith path point and the jth obstacle, N is the number of path points, and K is the number of obstacles. The ant colony algorithm is designed according to the behavior of simulating ants to find the shortest path of food, so that the embodiment of the invention selects the ant colony algorithm to perform simulation optimization function min F ═ mu1Fs+μ2Fc。
Setting initialization parameters of an ant colony algorithm, setting the number of ants as 50, setting the pheromone importance degree factor as 1, setting the heuristic function importance degree factor as 7, setting the pheromone volatilization factor as 0.3, setting the constant coefficient as 1 and setting the iteration number as 100. And then two line segments used for representing the optimal marching path needing to complete the marching task in the graph 3 are obtained through ant colony algorithm simulation and respectively represent the transport route 0 column and the transport route 1 column.
Referring to fig. 3, with the map situation of the area as a reference, two line segments represent predetermined lines calculated by two marching columns through simulation, such as the graphic representation represents marching proposed routes of the column 1 and the column 2 respectively, and when the two columns start to depart, a trapezoid close to the starting position point on the left represents the position of the actual position of the marching column; the trapezoid far away from the initial position point on the left represents a position point where a marching longitudinal team of the simulation result is located, and the position point is obtained by simulating the detection data along the way by the monitoring module 3 and serves as a marching suggested position point of the longitudinal team.
Referring to fig. 4, the monitoring module 3 is composed of a photoelectric sensor and an infrared sensor, and is used for functions of front road detection, radiation and distance measurement, infrared image presentation, and the like. The method comprises the steps of detecting the transport path along the way in the marching process, detecting that the marching path has nuclear biochemical risk, feeding back the nuclear biochemical risk to a control system 2 through a communication module 1, carrying out obstacle marking processing on returned information through the control system 2 module, completing map information updating, further acting the updated map information on a path planning module 5 through the communication module 1, and obtaining a new marching simulation path through simulation. And the monitored road condition information is used as a reference element influencing the efficiency of the road maneuvering and marching equipment and the avoidance of the marching obstacles in the marching route.
Fig. 5 is a block diagram of the control system 2. The control system 2 is configured to process information transmitted by the environmental information identification module 4, the monitoring module 3, and the path planning module 5, and specifically includes: the method comprises the steps of converting a marching area topographic map drawn by an environment information identification module 4 into a grid map through a grid method, calling a path planning module 5 to solve the shortest path in the grid map in a simulation mode to serve as a marching route, updating map information in real time according to an obstacle marked by a monitoring module 3, carrying out grid map conversion on a new map, updating the grid map required to be solved by the path planning module 5 in a simulation mode, and realizing real-time simulation of path planning. Fig. 5 is explained in connection with the control system 2: the control system 2 comprises a transportation state sensing, a transportation state construction, a transportation state evolution, a transportation state prediction and a simulation engine. The above parts, the environmental information identification module 4, the monitoring module 3, and the path planning module 5 are connected through the communication module 1 to realize data communication. The transportation state sensing part of the control system 2 controls the monitoring module 3 to detect the transportation path along the way, transmits monitoring information of the photoelectric sensor and the infrared sensor in a state flow mode to obtain barrier information in marching transportation, and acts the barrier information on the path planning module 5 to complete the construction of the transportation state. After the path planning module 5 obtains the simulated marching path, the risk deviation setting continuously updates the obstacles in the topographic map through the monitoring module 3, modifies the transportation map information, completes the transportation state evolution, and enables the modeling data to continuously approach the real situation in the transportation process, thereby reducing the error of the model in the aspect of obstacle prediction. With the advancing of the marching process, the marching transportation path obtained by the simulation of the path planning module 5 is continuously deduced to the situation of the optimal path by the transportation state prediction function, and the optimal marching path is obtained according to the situation evaluation standard of the shortest marching path. The Matlab simulation engine provides the functions of clock propulsion, operation control, scheduling management, data distribution management and the like, and supports the normal operation of the control system 2.
Fig. 6 is a flowchart of implementation of parallel simulation path planning in the embodiment of the present invention.
The military path planning support system based on parallel simulation ensures that the communication module 1 runs and checks whether the environmental information input of the environmental information identification module 4 is correct or not and obtains an accurate environmental information condition; further, the control system 2 receives a marching transportation plan; further, the format of the data packet transmitted by the communication module 1 is ensured to be correct, and the data is ensured to be accurate; further, the path planning module 5 executes path planning simulation; furthermore, the monitoring module 3 processes the obstacle situation encountered in the actual marching process, and the photoelectric sensor and the infrared sensor detect the marching route, and the obtained information is subjected to obstacle information data storage and reported to the control system 2; further, the control system 2 updates the map information in real time according to the obstacles to complete the environmental information processing work; further, the control system 2 performs raster image conversion on the new map, realizes raster image update of simulation solution required by the path planning module 5, and realizes route adjustment through real-time simulation of path planning.
Fig. 7 is a diagram illustrating a result of calculating a simulation route according to an embodiment of the present invention.
In the transportation process, the parallel simulation military path planning support system continuously inputs and updates the current environment state information, and a two-dimensional map based on a grid method is drawn according to the environment information obtained at the current moment. The points represented by each grid make up a traversable transportation space or point obstacles that need to be avoided. In this embodiment, a black grid represents an obstacle needing to avoid a point, a white grid represents a passable area, and a broken line represents a simulation route result in fig. 7. Fig. 7 is a path planning result obtained by selecting a certain military transportation time in a certain area with the length of 20 kilometers and the width of 20 kilometers, and performing simulation on the condition that the coverage rate of obstacles in the area is 30% through the ant colony algorithm. The iteration number is set to 100, the ant number is set to 50, the upper left corner is the starting point of the transportation path, and the lower right corner is the end point of the transportation path.
As the transport state continues to advance, the obstacles represented by the black grid and the accessible areas represented by the white grid in fig. 7 change accordingly if the environmental state changes accordingly. The path planning result obtained by the control system 2 is therefore updated accordingly.
The present invention provides a military path planning support system based on parallel simulation, and the method and the way for implementing the technical solution are many, and the above description is only the preferred embodiment of the present invention, it should be noted that, for those skilled in the art, many modifications and embellishments can be made without departing from the principle of the present invention, and these modifications and embellishments should also be regarded as the protection scope of the present invention. The components not specified in the embodiments of the present invention can be implemented by the prior art.
Claims (6)
1. A military path planning support system based on parallel simulation is characterized by comprising a communication module, an environmental information identification module, a path planning module, a monitoring module and a control system;
the communication module is used for transmitting data information among the environment information identification module, the path planning module, the monitoring module and the control system;
the environment information identification module is used for collecting map information of a marching area;
the path planning module is used for realizing map modeling according to the map information obtained by the environment information identification module, abstracting the transportation process into a constraint optimization problem of a two-dimensional space, and simulating according to an ant colony algorithm to obtain an optimal marching path;
the monitoring module is used for detecting the transportation path along the way in the marching process and detecting the obstacles in the marching route;
the control system module marks the obstacles detected by the monitoring module to complete map information updating, and further acts the updated map information on the path planning module through the communication module to obtain a new marching simulation route through simulation.
2. The military path planning support system based on parallel simulation of claim 1, wherein the control system performs the following specific processes:
and converting a marching area topographic map drawn by the environment information identification module into a grid map by a grid method, calling a path planning module to solve the shortest path in the grid map in a simulation mode to serve as a marching route, updating map information in real time according to the obstacles marked by the monitoring module, and performing grid map conversion on a new map to update the grid map required to be solved by the path planning module and realize real-time simulation of path planning.
3. The military path planning support system based on parallel simulation of claim 1, wherein the path planning module abstracts the transportation process into a constrained optimization problem in two-dimensional space, the constraint condition is to avoid contact with the obstacle, the optimization function is composed of a path length function and an obstacle penalty function, and the mathematical modeling problem of the path planning can be described as solving the minimum of the following expression:
minF＝μ1Fs+μ2Fc
wherein Fs is a path length function, Fc is an obstacle point penalty function consisting of obstacles encountered in the path point, and μ1And mu2Is a weighted value, and μ1+μ2＝1。
4. The military path planning support system based on parallel simulation of claim 3, wherein the path length F of the marchsThe calculation formula is as follows:
wherein, Pi(i 1, 2.. N) denotes the position of the ith waypoint, SiRepresents the distance between the i-th and i + 1-th position points;
barrier penalty function FcThe calculation formula is as follows:
wherein the content of the first and second substances,
for ith waypoint to jth obstacle Qj(j ═ 1, 2,..., K) barrier penalty function; m (i, j) is the distance between the ith path point and the jth obstacle, N is the number of path points, and K is the number of obstacles.
5. The military path planning support system based on parallel simulation of claim 1, wherein the environment information identification module collects map information of a marching region through situational awareness means such as satellite map positioning, radar and the like.
6. The military path planning support system based on parallel simulation of claim 1, wherein the transportation state sensing part of the control system controls the monitoring module to monitor the transportation path along the way, and transmits the monitoring information of the monitoring module in a state flow manner to obtain the obstacle information in the marching transportation.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011436294.4A CN112731921A (en) | 2020-12-11 | 2020-12-11 | Military path planning support system based on parallel simulation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011436294.4A CN112731921A (en) | 2020-12-11 | 2020-12-11 | Military path planning support system based on parallel simulation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112731921A true CN112731921A (en) | 2021-04-30 |
Family
ID=75598810
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011436294.4A Pending CN112731921A (en) | 2020-12-11 | 2020-12-11 | Military path planning support system based on parallel simulation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112731921A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116069045A (en) * | 2023-04-06 | 2023-05-05 | 武汉大学 | Radiation environment detection method and system based on mobile robot |
| CN116976144A (en) * | 2023-09-20 | 2023-10-31 | 北京数易科技有限公司 | Weapon force deployment exercise method, system and medium based on simulation platform |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109945881A (en) * | 2019-03-01 | 2019-06-28 | 北京航空航天大学 | A kind of method for planning path for mobile robot of ant group algorithm |
| CN110032212A (en) * | 2019-03-13 | 2019-07-19 | 浙江工业大学 | A kind of automatic follower method of wheeled robot neural network based |
| CN110632931A (en) * | 2019-10-09 | 2019-12-31 | 哈尔滨工程大学 | Mobile robot collision avoidance planning method based on deep reinforcement learning in dynamic environment |
| CN110887484A (en) * | 2019-10-14 | 2020-03-17 | 重庆邮电大学 | Mobile robot path planning method based on improved genetic algorithm and storage medium |
| CN111413965A (en) * | 2020-03-11 | 2020-07-14 | 西安工程大学 | UGV (Unigraphics Virus) driving path planning method based on UAV (unmanned aerial vehicle) cooperative sensing |
-
2020
- 2020-12-11 CN CN202011436294.4A patent/CN112731921A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109945881A (en) * | 2019-03-01 | 2019-06-28 | 北京航空航天大学 | A kind of method for planning path for mobile robot of ant group algorithm |
| CN110032212A (en) * | 2019-03-13 | 2019-07-19 | 浙江工业大学 | A kind of automatic follower method of wheeled robot neural network based |
| CN110632931A (en) * | 2019-10-09 | 2019-12-31 | 哈尔滨工程大学 | Mobile robot collision avoidance planning method based on deep reinforcement learning in dynamic environment |
| CN110887484A (en) * | 2019-10-14 | 2020-03-17 | 重庆邮电大学 | Mobile robot path planning method based on improved genetic algorithm and storage medium |
| CN111413965A (en) * | 2020-03-11 | 2020-07-14 | 西安工程大学 | UGV (Unigraphics Virus) driving path planning method based on UAV (unmanned aerial vehicle) cooperative sensing |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116069045A (en) * | 2023-04-06 | 2023-05-05 | 武汉大学 | Radiation environment detection method and system based on mobile robot |
| CN116976144A (en) * | 2023-09-20 | 2023-10-31 | 北京数易科技有限公司 | Weapon force deployment exercise method, system and medium based on simulation platform |
| CN116976144B (en) * | 2023-09-20 | 2023-12-26 | 北京数易科技有限公司 | Weapon force deployment exercise method, system and medium based on simulation platform |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Coutinho et al. | The unmanned aerial vehicle routing and trajectory optimisation problem, a taxonomic review | |
| Lazarowska | A new deterministic approach in a decision support system for ship’s trajectory planning | |
| CN106970648A (en) | Unmanned plane multi-goal path plans combined method for searching under the environment of city low latitude | |
| US9520066B2 (en) | Determining landing sites for aircraft | |
| CN111044052B (en) | Unmanned aerial vehicle self-adaptive navigation system and method based on intelligent sensing | |
| AU2014360672A1 (en) | Method and apparatus for developing a flight path | |
| Stodola et al. | Tactical decision support system to aid commanders in their decision-making | |
| CN112731921A (en) | Military path planning support system based on parallel simulation | |
| CN109656264A (en) | For being generated to the method implemented by computer and system in the path 3D in landing site for aircraft | |
| KR20170087156A (en) | Differential Reward Typed Cooperative Mapdata Providing System for Driver free vehicle based on Cloud Computing | |
| CN113406968B (en) | Unmanned aerial vehicle autonomous take-off and landing cruising method based on digital twin | |
| CN109960148A (en) | A kind of the independence appraisal procedure and system of intelligent Unmanned Systems | |
| CN114355967B (en) | Aircraft, method for controlling an aircraft, and computer-aided system | |
| Seraj et al. | Safe coordination of human-robot firefighting teams | |
| CN113552867B (en) | Planning method for motion trail and wheeled mobile device | |
| Drozd et al. | Experiments with the UAS reconnaissance model in the real environment | |
| Politi et al. | The future of safe BVLOS drone operations with respect to system and service engineering | |
| CN112396298B (en) | Unmanned helicopter multi-machine collaborative task planning method | |
| Khachumov et al. | Optimization Models of UAV Route Planning For Forest Fire Monitoring | |
| Honghong et al. | Risk assessment framework for low-altitude UAV traffic management | |
| US20200192405A1 (en) | Method and device for generating an optimum vertical trajectory intended to be followed by an aircraft | |
| Chen et al. | Integrated air-ground vehicles for uav emergency landing based on graph convolution network | |
| Li et al. | A path planning for one UAV based on geometric algorithm | |
| Chen et al. | Modelling of unmanned aerial vehicle deliveries in populated urban areas for risk management | |
| Childers et al. | Assessing unmanned ground vehicle tactical behaviors performance |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20210430 |