CN113867401A - Multi-unmanned aerial vehicle patrol scheduling method based on optical fiber disturbance monitoring system - Google Patents
Multi-unmanned aerial vehicle patrol scheduling method based on optical fiber disturbance monitoring system Download PDFInfo
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Abstract
The invention discloses a patrol scheduling method for multiple unmanned aerial vehicles based on an optical fiber disturbance monitoring system, which comprises the following steps: 1) laying unmanned aerial vehicles and unmanned aerial vehicle base stations thereof; 2) when the monitoring area is invaded, the optical fiber disturbance monitoring system gives an alarm and uploads alarm data to the optical fiber unmanned aerial vehicle dispatching system; 3) the optical fiber unmanned aerial vehicle dispatching system arranges the unmanned aerial vehicle to go to the site for duty, tracking and shooting according to the position of the alarm point; 4) the on-duty unmanned aerial vehicle transmits data back to the optical fiber unmanned aerial vehicle dispatching system; 5) the optical fiber unmanned aerial vehicle dispatching system finishes the prediction of the future invading travel route and outputs the predicted route to the next stage; 6) the optical fiber unmanned aerial vehicle dispatching system dispatches the unmanned aerial vehicle to relay on duty until the staff on duty goes out of the police, and the unmanned aerial vehicle dispatching system cancels the alarm and then ends the process; 7) the unmanned aerial vehicle that returns a journey charges and awaits the orders. The invention can realize all-weather duty of the unmanned aerial vehicle, and has simple construction and low investment cost.
Description
Technical Field
The invention belongs to the field of unmanned aerial vehicle security and protection, and particularly relates to a multi-unmanned aerial vehicle patrol scheduling method based on an optical fiber disturbance monitoring system.
Background
Along with the continuous improvement of the global economic level, the quality of life of people has changed greatly, and people pay more and more attention to material property and life safety and have higher and more high requirements on security protection. Meanwhile, the national infrastructure is more and more complete, such as schools, airports, gas stations, military bases and the like are increased remarkably. However, the development of science and technology also easily causes lawless persons to utilize higher-level technology to carry out illegal invasion, steal public property and even hurt the life safety of people, thus seriously interfering the life of people and destroying the stability of society, and the development of science and technology is a great challenge to security and protection work. The traditional video monitoring generally adopts the installation camera, but the observation scope of camera is limited, and the material cost and the construction cost of laying the point all can greatly increased.
Along with the development of unmanned aerial vehicle technology, the automatic patrol technology of unmanned aerial vehicle comes. When the unmanned aerial vehicle patrol system is used, the unmanned aerial vehicle patrol system has the advantages of low manufacturing cost, low flight cost, flight control personnel on duty safety, flexible patrol route, diversified monitoring angle, no dead angle, automatic cruise, hovering and target tracking, quick task deployment, no landform visibility and the like. Although there are many advantages to unmanned aerial vehicle patrol, nevertheless be subject to battery technology and wireless transmission technique, also there are many shortcomings that can't overcome: firstly, the endurance of the existing unmanned aerial vehicle is obviously insufficient, even the unmanned aerial vehicle with stronger endurance only supports 30km endurance mileage, and the monitoring range of a large security system (such as an airport, a military base and the like) or an ultra-large security system (such as a border line and the like) which is hundreds of kilometers often cannot be met; secondly, most of the existing unmanned aerial vehicles adopt 2.4G or 5.8G transmission, even if the power of a wireless module is increased and the wireless module is controlled by domestic electromagnetic environment and building shielding, 30km is the limit of image transmission, and the requirements of a large or ultra-large security system cannot be met; finally, even in a small security system, the battery technology is controlled, the endurance time of the unmanned aerial vehicle is only 30-40 minutes, and the unmanned aerial vehicle cannot be on duty all day long. Synthesize above problem, this is also the unable widely used leading reason of unmanned aerial vehicle patrol.
Disclosure of Invention
The invention provides a patrol scheduling method for multiple unmanned aerial vehicles based on an optical fiber disturbance monitoring system for solving the technical problems in the prior art, the method can realize all-weather duty of the unmanned aerial vehicles, and is simple and convenient to construct and low in investment cost.
The technical scheme adopted by the invention for solving the technical problems in the prior art is as follows: a patrol scheduling method for multiple unmanned aerial vehicles based on an optical fiber disturbance monitoring system comprises the following steps:
1) calculating needed unmanned aerial vehicles according to the perimeter and the area of a monitoring area and the endurance mileage of the unmanned aerial vehicles, completing the layout, matching one unmanned aerial vehicle base station with each unmanned aerial vehicle, wherein the distance L between any two unmanned aerial vehicle base stations does not exceed the maximum endurance mileage S of one unmanned aerial vehicle, and each unmanned aerial vehicle base station is provided with a wireless data receiving module, a network data wired transmission module and an unmanned aerial vehicle wireless charging module;
2) when the monitoring area is invaded, the optical fiber disturbance monitoring system gives an alarm and uploads alarm data to the optical fiber unmanned aerial vehicle dispatching system;
3) the optical fiber unmanned aerial vehicle dispatching system inquires whether the nearest unmanned aerial vehicle is idle and has sufficient electric quantity according to the position of the alarm point, if so, the position of the alarm point is sent to an unmanned aerial vehicle base station to which the nearest unmanned aerial vehicle belongs through a wired network, the unmanned aerial vehicle base station is sent to the nearest unmanned aerial vehicle through a wireless network, and the nearest unmanned aerial vehicle goes to the site to perform duty, tracking and shooting; if not, the optical fiber unmanned aerial vehicle dispatching system inquires data of the next-nearest unmanned aerial vehicle, and arranges the next-nearest unmanned aerial vehicle to go to the site for duty, tracking and shooting;
4) the duty unmanned aerial vehicle carries out target tracking and video shooting, and transmits the video back to the affiliated unmanned aerial vehicle base station in real time through a wireless network, and then transmits the video back to the optical fiber unmanned aerial vehicle dispatching system through a wired network by the affiliated unmanned aerial vehicle base station;
5) the optical fiber unmanned aerial vehicle dispatching system carries out real-time intrusion travelling route prediction according to real-time coordinates and shooting data of the on-duty unmanned aerial vehicle, and firstly carries out linear regression prediction according to an intruder travelling route uploaded by the on-duty unmanned aerial vehicle to obtain an intrusion future travelling prediction route; then the optical fiber unmanned aerial vehicle dispatching system processes and stores the video data uploaded by the on-duty unmanned aerial vehicle frame by frame, and classifies the environmental data in front of the intruder into obstacles and non-obstacles by adopting image SVM classification; then, the fiber unmanned aerial vehicle dispatching system adopts a multi-mode fusion algorithm, the linear regression prediction weight is preset to be 0.2, the image SVM classification weight is 0.8, fusion is carried out, the future-invasion traveling prediction route is calculated after fusion, and the future-invasion traveling prediction route is output to the next stage;
6) judging whether the on-duty unmanned aerial vehicle continues to follow up on duty or not according to the calculated future invasion travelling prediction route and whether the remaining endurance mileage of the on-duty unmanned aerial vehicle can return to the affiliated unmanned aerial vehicle base station or the nearby base station, if so, continuing to follow up on duty, if not, the optical fiber unmanned dispatching system schedules the on-duty unmanned aerial vehicle to relay on duty nearby, and continuing to track and shoot the target; repeating the steps until the on-duty personnel gives an alarm, and ending the unmanned aerial vehicle dispatching system after the unmanned aerial vehicle dispatching system cancels the alarm;
7) judging whether the returning unmanned aerial vehicle can return to the unmanned aerial vehicle base station according to the remaining endurance mileage; if yes, returning to the unmanned aerial vehicle base station to charge for standby; if not, selecting a nearby unmanned aerial vehicle base station to land; if the unmanned aerial vehicle is charged in the nearby unmanned aerial vehicle base station, the returning unmanned aerial vehicle waits, the charging unmanned aerial vehicle enters the base station for charging after the charging of the charging unmanned aerial vehicle is finished, and the returning unmanned aerial vehicle flies to the unmanned aerial vehicle base station to charge for standby after the charging is finished; and finishing the alarm processing at one time.
And 5) in the operation process of the optical fiber unmanned aerial vehicle dispatching system, the image SVM classification parameters and the weight of the multi-mode fusion algorithm are optimized according to the increase of the data volume of the system.
Said step 1), L should not be greater than 90% of S.
The invention has the advantages and positive effects that: based on a fusion neural network, the unmanned aerial vehicle is on duty in all weather by combining an optical fiber disturbance detection system; the problems of short endurance mileage, short endurance time and limited wireless signal transmission distance of the unmanned aerial vehicle are solved; the unmanned aerial vehicle monitoring system is used for monitoring in a large-scale and long-distance monitoring system, compared with a camera, dead-angle-free monitoring is realized, the cost of a large number of cameras is reduced, and due to the convenience of unmanned aerial vehicle deployment, the construction difficulty is greatly reduced.
Drawings
FIG. 1 is a block diagram of a structure to which the present invention is applied;
FIG. 2 is a flow chart of intrusion future travel route prediction;
FIG. 3 is a flow chart of the present invention.
Detailed Description
In order to further understand the contents, features and effects of the present invention, the following embodiments are illustrated and described in detail with reference to the accompanying drawings:
referring to fig. 1 to 3, a patrol scheduling method for multiple drones based on an optical fiber disturbance monitoring system includes the following steps:
1) the unmanned aerial vehicle that needs is calculated according to control area girth and area and unmanned aerial vehicle continuation of the journey mileage and accomplish and lay, every unmanned aerial vehicle collocation an unmanned aerial vehicle basic station, the distance L of two arbitrary unmanned aerial vehicle basic stations must not exceed an unmanned aerial vehicle' S the biggest continuation of the journey mileage S, every unmanned aerial vehicle basic station all is equipped with wireless data receiving module, network data wired transmission module and the wireless module of charging of unmanned aerial vehicle. Considering factors such as weather, wind speed, unmanned aerial vehicle battery attenuation, L should be no more than 90% of S.
2) When the monitoring area is invaded, the optical fiber disturbance monitoring system gives an alarm and uploads alarm data to the optical fiber unmanned aerial vehicle dispatching system;
3) the optical fiber unmanned aerial vehicle dispatching system inquires whether the nearest unmanned aerial vehicle is idle and has sufficient electric quantity according to the position of the alarm point, if so, the position of the alarm point is sent to an unmanned aerial vehicle base station to which the nearest unmanned aerial vehicle belongs through a wired network, the unmanned aerial vehicle base station is sent to the nearest unmanned aerial vehicle through a wireless network, and the nearest unmanned aerial vehicle goes to the site to perform duty, tracking and shooting; if not, the optical fiber unmanned aerial vehicle dispatching system inquires data of the next-nearest unmanned aerial vehicle, and arranges the next-nearest unmanned aerial vehicle to go to the site for duty, tracking and shooting;
4) the duty unmanned aerial vehicle carries out target tracking and video shooting, and transmits the video back to the affiliated unmanned aerial vehicle base station in real time through a wireless network, and then transmits the video back to the optical fiber unmanned aerial vehicle dispatching system through a wired network by the affiliated unmanned aerial vehicle base station;
5) the optical fiber unmanned aerial vehicle dispatching system carries out real-time intrusion travelling route prediction according to real-time coordinates and shooting data of the on-duty unmanned aerial vehicle, and firstly carries out linear regression prediction according to an intruder travelling route uploaded by the on-duty unmanned aerial vehicle to obtain an intrusion future travelling prediction route; then the optical fiber unmanned aerial vehicle dispatching system processes and stores the video data uploaded by the on-duty unmanned aerial vehicle frame by frame, and classifies the environmental data in front of the intruder into obstacles and non-obstacles by adopting image SVM classification; and then the fiber unmanned aerial vehicle dispatching system adopts a multi-mode fusion algorithm, the linear regression prediction weight is preset to be 0.2, the image SVM classification weight is 0.8, fusion is carried out, the intrusion future traveling prediction route is calculated after fusion, and the intrusion future traveling prediction route is output to the next stage. In the operation process of the optical fiber unmanned aerial vehicle dispatching system, parameter optimization is carried out on the image SVM classification parameters and the weight of the multi-mode fusion algorithm according to the increase of the data volume of the system.
6) According to the predicted route of the future invasion and the remaining continuation of the journey mileage of the unmanned aerial vehicle on duty calculated in the step 5), whether the unmanned aerial vehicle on duty can return to the base station of the unmanned aerial vehicle or the nearby base station is judged, whether the unmanned aerial vehicle on duty continues to follow up on duty is judged, if yes, the unmanned aerial vehicle continues to follow up on duty, and if not, the unmanned aerial vehicle is dispatched nearby by the optical fiber unmanned dispatching system to continue target tracking and shooting; repeating the steps until the on-duty personnel gives an alarm, and ending the unmanned aerial vehicle dispatching system after the unmanned aerial vehicle dispatching system cancels the alarm;
7) judging whether the returning unmanned aerial vehicle can return to the unmanned aerial vehicle base station according to the remaining endurance mileage; if yes, returning to the unmanned aerial vehicle base station to charge for standby; if not, selecting a nearby unmanned aerial vehicle base station to land, wherein the base station is usually a base station to which the relay unmanned aerial vehicle belongs; if the unmanned aerial vehicle is charged in the nearby unmanned aerial vehicle base station, the returning unmanned aerial vehicle waits, the charging unmanned aerial vehicle enters the base station for charging after the charging of the charging unmanned aerial vehicle is finished, and the returning unmanned aerial vehicle flies to the unmanned aerial vehicle base station to charge for standby after the charging is finished; and finishing the alarm processing at one time.
In conclusion, when the method is applied, the allocation quantity and the deployment position of the unmanned aerial vehicles are calculated according to the perimeter and the area of the security area, the endurance mileage of the unmanned aerial vehicles and the time; meanwhile, the unmanned aerial vehicle is matched with an unmanned aerial vehicle base station, and the unmanned aerial vehicle base station has the functions of wireless data receiving, network data wired transmission, unmanned aerial vehicle wireless charging and the like; the optical fiber disturbance monitoring system carries out all-weather and dead-angle-free perimeter security monitoring, when the monitoring system finds intrusion behavior, the remaining endurance mileage and the intrusion point position of each unmanned aerial vehicle are integrated, and the unmanned aerial vehicles are intelligently scheduled to carry out on-site duty and target tracking; when the unmanned aerial vehicle tracks a target, flight data including coordinates, electric quantity, endurance mileage, endurance time, shooting video and the like are reported to an unmanned aerial vehicle base station in real time, and the unmanned aerial vehicle base station uploads the information to an optical fiber unmanned aerial vehicle dispatching system through a wired network so that the optical fiber unmanned aerial vehicle dispatching system can regulate and deploy each unmanned aerial vehicle in real time; the optical fiber unmanned aerial vehicle dispatching system predicts the future travel route in real time according to the current travel route of the monitored target by combining with the terrain information; when the optical fiber unmanned aerial vehicle dispatching system finds that an intrusion target is about to cross from one unmanned aerial vehicle on-duty area to another unmanned aerial vehicle on-duty area according to a predicted route, or the remaining endurance mileage of the current unmanned aerial vehicle on duty is not enough to return to the unmanned aerial vehicle base station or land to the nearest unmanned aerial vehicle base station, arranging nearby unmanned aerial vehicles in advance to take over duty; the process is circulated in such a way, the unmanned aerial vehicle finishes the duty on duty until security personnel carry out on-site duty and cancel the alarm, and the unmanned aerial vehicle returns to the affiliated unmanned aerial vehicle base station for charging.
Although the preferred embodiments of the present invention have been described above with reference to the accompanying drawings, the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and those skilled in the art can make many modifications without departing from the spirit and scope of the present invention as defined in the appended claims.
Claims (3)
1. A patrol scheduling method for multiple unmanned aerial vehicles based on an optical fiber disturbance monitoring system is characterized by comprising the following steps:
1) calculating needed unmanned aerial vehicles according to the perimeter and the area of a monitoring area and the endurance mileage of the unmanned aerial vehicles, completing the layout, matching one unmanned aerial vehicle base station with each unmanned aerial vehicle, wherein the distance L between any two unmanned aerial vehicle base stations does not exceed the maximum endurance mileage S of one unmanned aerial vehicle, and each unmanned aerial vehicle base station is provided with a wireless data receiving module, a network data wired transmission module and an unmanned aerial vehicle wireless charging module;
2) when the monitoring area is invaded, the optical fiber disturbance monitoring system gives an alarm and uploads alarm data to the optical fiber unmanned aerial vehicle dispatching system;
3) the optical fiber unmanned aerial vehicle dispatching system inquires whether the nearest unmanned aerial vehicle is idle and has sufficient electric quantity according to the position of the alarm point, if so, the position of the alarm point is sent to an unmanned aerial vehicle base station to which the nearest unmanned aerial vehicle belongs through a wired network, the unmanned aerial vehicle base station is sent to the nearest unmanned aerial vehicle through a wireless network, and the nearest unmanned aerial vehicle goes to the site to perform duty, tracking and shooting; if not, the optical fiber unmanned aerial vehicle dispatching system inquires data of the next-nearest unmanned aerial vehicle, and arranges the next-nearest unmanned aerial vehicle to go to the site for duty, tracking and shooting;
4) the duty unmanned aerial vehicle carries out target tracking and video shooting, and transmits the video back to the affiliated unmanned aerial vehicle base station in real time through a wireless network, and then transmits the video back to the optical fiber unmanned aerial vehicle dispatching system through a wired network by the affiliated unmanned aerial vehicle base station;
5) the optical fiber unmanned aerial vehicle dispatching system carries out real-time intrusion travelling route prediction according to real-time coordinates and shooting data of the on-duty unmanned aerial vehicle, and firstly carries out linear regression prediction according to an intruder travelling route uploaded by the on-duty unmanned aerial vehicle to obtain an intrusion future travelling prediction route;
then the optical fiber unmanned aerial vehicle dispatching system processes and stores the video data uploaded by the on-duty unmanned aerial vehicle frame by frame, and classifies the environmental data in front of the intruder into obstacles and non-obstacles by adopting image SVM classification;
then, the fiber unmanned aerial vehicle dispatching system adopts a multi-mode fusion algorithm, the linear regression prediction weight is preset to be 0.2, the image SVM classification weight is 0.8, fusion is carried out, the future-invasion traveling prediction route is calculated after fusion, and the future-invasion traveling prediction route is output to the next stage;
6) the optical fiber unmanned aerial vehicle dispatching system judges whether the on-duty unmanned aerial vehicle continues to follow up on duty or not according to the calculated future invasion travel prediction route and whether the remaining continuation of the journey mileage of the on-duty unmanned aerial vehicle can return to the affiliated unmanned aerial vehicle base station or the nearby base station, if so, the on-duty unmanned aerial vehicle continues to follow up on duty, and if not, the optical fiber unmanned aerial vehicle dispatching system dispatches the unmanned aerial vehicle to carry out relay on duty nearby and continues to track and shoot targets; repeating the steps until the on-duty personnel gives an alarm, and ending the unmanned aerial vehicle dispatching system after the unmanned aerial vehicle dispatching system cancels the alarm;
7) judging whether the returning unmanned aerial vehicle can return to the unmanned aerial vehicle base station according to the remaining endurance mileage; if yes, returning to the unmanned aerial vehicle base station to charge for standby; if not, selecting a nearby unmanned aerial vehicle base station to land; if the unmanned aerial vehicle is charged in the nearby unmanned aerial vehicle base station, the returning unmanned aerial vehicle waits, the charging unmanned aerial vehicle enters the base station for charging after the charging of the charging unmanned aerial vehicle is finished, and the returning unmanned aerial vehicle flies to the unmanned aerial vehicle base station to charge for standby after the charging is finished; and finishing the alarm processing at one time.
2. The multi-unmanned-aerial-vehicle patrol scheduling method based on the optical fiber disturbance monitoring system according to claim 1, wherein in the step 5), in the operation process of the optical fiber unmanned-vehicle scheduling system, the image SVM classification parameters and the weight of the multi-modal fusion algorithm are optimized according to the increase of the system data volume.
3. The multi-unmanned aerial vehicle patrol scheduling method based on the optical fiber disturbance monitoring system according to claim 1, wherein in the step 1), L is not more than 90% of S.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116631134A (en) * | 2023-07-26 | 2023-08-22 | 海南至元科技有限公司 | Intelligent monitoring anti-theft device |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116631134A (en) * | 2023-07-26 | 2023-08-22 | 海南至元科技有限公司 | Intelligent monitoring anti-theft device |
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Application publication date: 20211231 |