CN112947549A - Unmanned aerial vehicle-based emergency material delivery method and system and readable storage medium - Google Patents
Unmanned aerial vehicle-based emergency material delivery method and system and readable storage medium Download PDFInfo
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Abstract
The invention relates to an unmanned aerial vehicle-based emergency material delivery method, an unmanned aerial vehicle-based emergency material delivery system and a readable storage medium, wherein the method comprises the following steps: acquiring target area information and generating material configuration information; acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy; calculating the optimal throwing point position according to the traffic strategy to obtain the optimal throwing position information; acquiring real-time position information of the unmanned aerial vehicle, and comparing the real-time position information with the optimal throwing position information to obtain a deviation rate; judging whether the deviation rate is greater than a preset threshold value or not, if so, generating correction information, and correcting the traffic strategy through the correction information; if the quantity is smaller than the preset value, the materials are thrown in a preset throwing mode.
Description
Technical Field
The invention relates to an emergency material delivery method, in particular to an emergency material delivery method and system based on an unmanned aerial vehicle and a readable storage medium.
Background
In recent years, various natural disasters occur frequently in countries around the world. And with the development and progress of social economic science and technology, various artificial disasters or technical disasters are increasing day by day, and more serious terrorist attack events also occur frequently. The emergencies not only cause great loss of lives and properties, but also influence social stability, even endanger national security, and have great influence on the development of the economic society. Meanwhile, the level of human beings predicting and forecasting natural disasters is continuously improved, but the information such as the occurrence time, the occurrence place and the occurrence intensity of many natural disasters still cannot be accurately forecasted up to now. How to deal with emergencies and how to reduce the loss of the emergencies to human beings are one of the powerful challenges facing countries or social organizations all over the world. The method has the advantages that the strengthening of emergency management, particularly the emergency material guarantee work management is the key of effective rescue after disasters, and the time utility values of different emergency materials are different due to different requirements of the emergency materials in different time stages in the emergency rescue process; and the capacity is often not enough in emergency rescue, especially for large-scale emergency rescue, and all needed emergency materials can not be allocated and supplied at the same time, so that the demand urgency degree of the emergency materials is determined by considering the demand urgency classification of the emergency materials according to the time utility value of the emergency materials, and the emergency materials are put in at fixed points according to the material demands.
In order to realize accurate control on material delivery, a system matched with the system needs to be developed for control, and the system acquires target area information and generates material configuration information; acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy; the optimal throwing point position is calculated according to the traffic strategy, the optimal throwing position information is obtained, and the accurate throwing of the materials is realized.
Disclosure of Invention
The invention overcomes the defects of the prior art and provides an emergency material releasing method and system based on an unmanned aerial vehicle and a readable storage medium.
In order to achieve the purpose, the invention adopts the technical scheme that: an emergency material releasing method based on an unmanned aerial vehicle comprises the following steps:
acquiring target area information and generating material configuration information;
acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy;
calculating the optimal throwing point position according to the traffic strategy to obtain the optimal throwing position information;
acquiring real-time position information of the unmanned aerial vehicle, and comparing the real-time position information with the optimal throwing position information to obtain a deviation rate;
determining whether the deviation ratio is greater than a predetermined threshold,
if the traffic policy is larger than the preset threshold, generating correction information, and correcting the traffic policy through the correction information;
if the quantity is smaller than the preset value, the materials are thrown in a preset throwing mode.
In a preferred embodiment of the present invention, the method further comprises:
classifying the materials, and respectively loading the materials to different unmanned aerial vehicles;
obtaining the position information of the unmanned aerial vehicle, establishing an unmanned aerial vehicle formation model,
generating unmanned aerial vehicle formation keeping information according to the unmanned aerial vehicle formation model;
generating an unmanned aerial vehicle formation mode according to the unmanned aerial vehicle formation keeping information;
forming unmanned aerial vehicles according to the unmanned aerial vehicle forming mode to obtain result information;
comparing the result information with actual detection information; obtaining unmanned aerial vehicle formation deviation information;
judging whether the deviation information is larger than a preset threshold value,
and if so, generating correction information to correct the unmanned aerial vehicle formation mode.
In a preferred embodiment of the present invention, the method further comprises:
establishing a constraint model through big data, and generating a navigation time constraint condition through the constraint model;
acquiring an initial position and a target position of the unmanned aerial vehicle;
calculating standard navigation time from the starting position of the unmanned aerial vehicle to the target position according to the reference flight path;
collecting dynamic track information and calculating and predicting navigation time;
comparing the standard voyage time with the predicted voyage time to obtain a deviation ratio;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the unmanned aerial vehicle node is larger than the target node, the navigation speed of the unmanned aerial vehicle node is adjusted.
In a preferred embodiment of the present invention, the calculating an optimal drop position according to the traffic policy to obtain information of the optimal drop position further includes:
the real-time position information of the unmanned aerial vehicle is obtained,
comparing the real-time position information of the unmanned aerial vehicle with the optimal throwing position;
if the unmanned aerial vehicle reaches the optimal throwing position, acquiring ground image information below the unmanned aerial vehicle;
comparing the image information with preset information to obtain the information of obstacles below the unmanned aerial vehicle;
obtaining distance compensation information according to the obstacle information;
and adjusting the optimal throwing position according to the distance compensation.
In a preferred embodiment of the present invention, the traffic policy includes one or a combination of two or more of the driving speed of the drone, the driving angle of the drone, the driving time of the drone, and the formation information of the drone.
In a preferred embodiment of the present invention, the formation mode of the unmanned aerial vehicles includes formation of the types of materials loaded on the unmanned aerial vehicles or formation according to material configuration information in the target area.
The second aspect of the present invention further provides an emergency material delivery system based on an unmanned aerial vehicle, the system comprising: the emergency material releasing method based on the unmanned aerial vehicle comprises a storage and a processor, wherein the storage comprises an emergency material releasing method program based on the unmanned aerial vehicle, and when the emergency material releasing method program based on the unmanned aerial vehicle is executed by the processor, the following steps are realized:
acquiring target area information and generating material configuration information;
acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy;
calculating the optimal throwing point position according to the traffic strategy to obtain the optimal throwing position information;
acquiring real-time position information of the unmanned aerial vehicle, and comparing the real-time position information with the optimal throwing position information to obtain a deviation rate;
determining whether the deviation ratio is greater than a predetermined threshold,
if the traffic policy is larger than the preset threshold, generating correction information, and correcting the traffic policy through the correction information;
if the quantity is smaller than the preset value, the materials are thrown in a preset throwing mode.
In a preferred embodiment of the present invention, the method further comprises:
classifying the materials, and respectively loading the materials to different unmanned aerial vehicles;
obtaining the position information of the unmanned aerial vehicle, establishing an unmanned aerial vehicle formation model,
generating unmanned aerial vehicle formation keeping information according to the unmanned aerial vehicle formation model;
generating an unmanned aerial vehicle formation mode according to the unmanned aerial vehicle formation keeping information;
forming unmanned aerial vehicles according to the unmanned aerial vehicle forming mode to obtain result information;
comparing the result information with actual detection information; obtaining unmanned aerial vehicle formation deviation information;
judging whether the deviation information is larger than a preset threshold value,
and if so, generating correction information to correct the unmanned aerial vehicle formation mode.
In a preferred embodiment of the present invention, the calculating an optimal drop position according to the traffic policy to obtain information of the optimal drop position further includes:
the real-time position information of the unmanned aerial vehicle is obtained,
comparing the real-time position information of the unmanned aerial vehicle with the optimal throwing position;
if the unmanned aerial vehicle reaches the optimal throwing position, acquiring ground image information below the unmanned aerial vehicle;
comparing the image information with preset information to obtain the information of obstacles below the unmanned aerial vehicle;
obtaining distance compensation information according to the obstacle information;
and adjusting the optimal throwing position according to the distance compensation.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of an emergency material delivery method based on a drone, and when the program of the emergency material delivery method based on the drone is executed by a processor, the method implements any one of the steps of the emergency material delivery method based on the drone.
The invention solves the defects in the background technology, and has the following beneficial effects:
(1) the required emergency goods and materials are loaded on the unmanned aerial vehicle in a classified mode through the goods and materials configuration information, then the unmanned aerial vehicle is formed into a team according to the goods and materials configuration information, the traffic capacity index is calculated according to the big data of the traffic flow of a target area, a traffic passing strategy is generated, the optimal throwing point position is calculated according to the passing strategy, the unmanned aerial vehicle flies to the optimal throwing point to carry out goods and materials fixed-point throwing, the throwing efficiency is high, and the throwing point is accurate.
(2) Acquire unmanned aerial vehicle real-time position information, when unmanned aerial vehicle reachd best input position, gather unmanned aerial vehicle below ground image information, acquire unmanned aerial vehicle below barrier information, when detecting there is the barrier, when the analysis was put in goods and materials, the distance between ground point and the barrier, when the distance is nearer, the best input position of adjustment guarantees that partial goods and materials put in the security.
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The invention is further illustrated with reference to the following figures and examples.
Fig. 1 shows a flow chart of an emergency material delivery method based on an unmanned aerial vehicle according to the invention;
FIG. 2 shows a flow chart of a method for correcting a formation mode of unmanned aerial vehicles;
FIG. 3 shows a flow chart of a method of adjusting the speed of flight of an unmanned aerial vehicle;
FIG. 4 is a flow chart illustrating a method for adjusting an optimal delivery location;
fig. 5 shows a block diagram of an emergency material delivery system based on a drone.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.
Fig. 1 shows a flow chart of an emergency material delivery method based on an unmanned aerial vehicle according to the invention.
As shown in fig. 1, a first aspect of the present invention provides an emergency material delivery method based on a drone, including:
s102, acquiring target area information and generating material configuration information;
s104, acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy;
s106, calculating the optimal throwing point position according to the traffic strategy to obtain the optimal throwing position information;
s108, acquiring real-time position information of the unmanned aerial vehicle, and comparing the real-time position information with the optimal throwing position information to obtain a deviation rate;
s110, judging whether the deviation ratio is larger than a preset threshold value,
s112, if the traffic policy is larger than the preset traffic policy, generating correction information, and correcting the traffic policy through the correction information;
and S114, if the quantity is smaller than the preset value, throwing the materials according to a preset throwing mode.
It should be noted that a rescue goods and materials dispatching command center is established, and rescue goods and materials in a target area are classified; acquiring the type of the emergency and judging the level of the emergency; generating an emergency plan according to the type and the level of the emergency, and obtaining material demand information; generating a corresponding material financing decision according to the rescue material demand information, and establishing a material storage center; and carrying out material conveying sequencing according to the emergency level, generating conveying sequence information, and carrying out rescue material conveying in sequence according to the conveying sequence information. On the basis of the prediction of the demand of emergency materials, the emergency material dispatching command center inquires the specific conditions such as the reserve, distribution, variety and specification of the emergency materials through an emergency material information system, and the demand of emergency demand points on the quantity and the type of the emergency materials is met as much as possible by adopting conventional planning modes such as reserve utilization, material collection and collection, domestic donation and the like, international assistance, organization assault production and other unconventional planning modes.
As shown in fig. 2, the invention discloses a flow chart of a method for correcting a formation mode of unmanned aerial vehicles;
according to the embodiment of the invention, the method further comprises the following steps:
s202, classifying the materials and respectively loading the materials to different unmanned aerial vehicles;
s204, obtaining the position information of the unmanned aerial vehicles, establishing an unmanned aerial vehicle formation model,
s206, generating unmanned aerial vehicle formation keeping information according to the unmanned aerial vehicle formation model;
s208, generating an unmanned aerial vehicle formation mode according to the unmanned aerial vehicle formation keeping information, and performing unmanned aerial vehicle formation according to the unmanned aerial vehicle formation mode to obtain result information;
s210, comparing the result information with the actual detection information; obtaining unmanned aerial vehicle formation deviation information;
s212, judging whether the deviation information is larger than a preset threshold value,
and S214, if the number of the unmanned aerial vehicles is larger than the preset number, generating correction information and correcting the unmanned aerial vehicle formation mode.
It should be noted that required emergency materials are loaded on the unmanned aerial vehicle in a classified mode through material configuration information, then the unmanned aerial vehicle is formed into a team according to the material configuration information, a traffic capacity index is calculated according to the target area traffic flow big data, a traffic passing strategy is generated, an optimal throwing point position is calculated according to the passing strategy, the unmanned aerial vehicle flies to the optimal throwing point to carry out material fixed-point throwing, throwing efficiency is high, and the throwing point is accurate.
As shown in fig. 3, the invention discloses a flow chart of a method for adjusting the navigation speed of an unmanned aerial vehicle;
according to the embodiment of the invention, the method further comprises the following steps:
s302, establishing a constraint model through big data, and generating a navigation time constraint condition through the constraint model;
s304, acquiring an initial position and a target position of the unmanned aerial vehicle;
s306, calculating the standard navigation time from the starting position of the unmanned aerial vehicle to the target position according to the reference track;
s308, collecting dynamic track information and calculating and predicting navigation time;
s310, comparing the standard navigation time with the predicted navigation time to obtain a deviation rate;
s312, judging whether the deviation rate is larger than a preset deviation rate threshold value or not;
and S314, if the navigation speed is larger than the target navigation speed, adjusting the navigation speed of the unmanned aerial vehicle node.
The unmanned aerial vehicle formation is carried out according to the material types on the unmanned aerial vehicle by acquiring the material demand information of the target area; acquiring a current flight path of the unmanned aerial vehicle, determining a collaborative path plan of the unmanned aerial vehicle, and generating dynamic path information; comparing the dynamic path information with a reference path to obtain a deviation rate; and judging whether the deviation rate is greater than a preset threshold value, if so, generating correction information, re-forming the unmanned aerial vehicles according to the correction information, generating a new planned path, updating the current flight path according to the new planned path, and controlling the unmanned aerial vehicle to form a formation to fly along the new planned path.
As shown in fig. 4, the present invention discloses a flow chart of a method for adjusting an optimal delivery position;
according to the embodiment of the invention, the optimal throwing position is calculated according to the traffic strategy to obtain the optimal throwing position information, and the method further comprises the following steps:
s402, acquiring real-time position information of the unmanned aerial vehicle,
s404, comparing the real-time position information of the unmanned aerial vehicle with the optimal throwing position;
s406, if the unmanned aerial vehicle reaches the optimal throwing position, acquiring ground image information below the unmanned aerial vehicle;
s408, comparing the image information with preset information to obtain the information of the obstacles below the unmanned aerial vehicle;
s410, obtaining distance compensation information according to the obstacle information;
and S412, adjusting the optimal throwing position according to the distance compensation.
It should be noted that, acquire unmanned aerial vehicle real-time position information, when unmanned aerial vehicle reachd the best position of puting in, gather unmanned aerial vehicle below ground image information, acquire unmanned aerial vehicle below barrier information, when detecting there is the barrier, when the analysis is put in goods and materials, the distance between ground point and the barrier, when the distance is nearer, the best position of puting in of adjustment guarantees that partial goods and materials put in the security.
According to the embodiment of the invention, the traffic strategy comprises one or more than two combinations of unmanned aerial vehicle running speed, unmanned aerial vehicle running navigation angle, unmanned aerial vehicle running time and unmanned aerial vehicle formation information.
According to the embodiment of the invention, the unmanned aerial vehicle formation mode comprises formation of the types of goods loaded on the unmanned aerial vehicles or formation according to goods configuration information in the target area.
As shown in fig. 5, the invention discloses a block diagram of an emergency material delivery system based on an unmanned aerial vehicle;
the second aspect of the present invention further provides an emergency material delivery system based on an unmanned aerial vehicle, the system comprising: the emergency material releasing method based on the unmanned aerial vehicle comprises a storage and a processor, wherein the storage comprises an emergency material releasing method program based on the unmanned aerial vehicle, and when the emergency material releasing method program based on the unmanned aerial vehicle is executed by the processor, the following steps are realized:
acquiring target area information and generating material configuration information;
acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy;
calculating the optimal throwing point position according to the traffic strategy to obtain the optimal throwing position information;
acquiring real-time position information of the unmanned aerial vehicle, and comparing the real-time position information with the optimal throwing position information to obtain a deviation rate;
determining whether the deviation ratio is greater than a predetermined threshold,
if the traffic policy is larger than the preset threshold, generating correction information, and correcting the traffic policy through the correction information;
if the quantity is smaller than the preset value, the materials are thrown in a preset throwing mode.
It should be noted that a rescue goods and materials dispatching command center is established, and rescue goods and materials in a target area are classified; acquiring the type of the emergency and judging the level of the emergency; generating an emergency plan according to the type and the level of the emergency, and obtaining material demand information; generating a corresponding material financing decision according to the rescue material demand information, and establishing a material storage center; and carrying out material conveying sequencing according to the emergency level, generating conveying sequence information, and carrying out rescue material conveying in sequence according to the conveying sequence information. On the basis of the prediction of the demand of emergency materials, the emergency material dispatching command center inquires the specific conditions such as the reserve, distribution, variety and specification of the emergency materials through an emergency material information system, and the demand of emergency demand points on the quantity and the type of the emergency materials is met as much as possible by adopting conventional planning modes such as reserve utilization, material collection and collection, domestic donation and the like, international assistance, organization assault production and other unconventional planning modes. The traffic capacity index refers to the maximum number of traffic entities which can pass through in unit time in an airspace, the traffic entities comprise unmanned aerial vehicles, when the actual traffic volume of the airspace is smaller than the traffic capacity, the unmanned aerial vehicles in the road airspace are in a free state, the traffic density is smaller, the time-distance distribution rule of the unmanned aerial vehicles is in negative index distribution, when the actual traffic volume of the airspace is larger than the traffic capacity, the density of the unmanned aerial vehicles in the airspace is increased, traffic jam or blockage occurs, a proper traffic path is selected according to different traffic capacity indexes, a corresponding traffic strategy is generated, and the high efficiency of material transportation is ensured. The traffic capacity calculation formula is as follows:
wherein κ represents traffic capacity; λ represents a correction coefficient; l1Representing the length of the drone; l2Representing a safe distance; l3Indicating a braking distance; v represents the traffic speed;
the calculation formula of the braking distance is as follows:
f, air resistance coefficient; t brake reaction time; gamma-shaped1,Γ2Representing front and rear drone braking systems; v represents the traffic speed.
According to the embodiment of the invention, the method further comprises the following steps:
classifying the materials, and respectively loading the materials to different unmanned aerial vehicles;
obtaining the position information of the unmanned aerial vehicle, establishing an unmanned aerial vehicle formation model,
generating unmanned aerial vehicle formation keeping information according to the unmanned aerial vehicle formation model;
generating an unmanned aerial vehicle formation mode according to the unmanned aerial vehicle formation keeping information;
forming unmanned aerial vehicles according to the unmanned aerial vehicle forming mode to obtain result information;
comparing the result information with actual detection information; obtaining unmanned aerial vehicle formation deviation information;
judging whether the deviation information is larger than a preset threshold value,
and if so, generating correction information to correct the unmanned aerial vehicle formation mode.
It should be noted that required emergency materials are loaded on the unmanned aerial vehicle in a classified mode through material configuration information, then the unmanned aerial vehicle is formed into a team according to the material configuration information, a traffic capacity index is calculated according to the target area traffic flow big data, a traffic passing strategy is generated, an optimal throwing point position is calculated according to the passing strategy, the unmanned aerial vehicle flies to the optimal throwing point to carry out material fixed-point throwing, throwing efficiency is high, and the throwing point is accurate.
According to the embodiment of the invention, the optimal throwing position is calculated according to the traffic strategy to obtain the optimal throwing position information, and the method further comprises the following steps:
the real-time position information of the unmanned aerial vehicle is obtained,
comparing the real-time position information of the unmanned aerial vehicle with the optimal throwing position;
if the unmanned aerial vehicle reaches the optimal throwing position, acquiring ground image information below the unmanned aerial vehicle;
comparing the image information with preset information to obtain the information of obstacles below the unmanned aerial vehicle;
obtaining distance compensation information according to the obstacle information;
and adjusting the optimal throwing position according to the distance compensation.
It should be noted that, acquire unmanned aerial vehicle real-time position information, when unmanned aerial vehicle reachd the best position of puting in, gather unmanned aerial vehicle below ground image information, acquire unmanned aerial vehicle below barrier information, when detecting there is the barrier, when the analysis is put in goods and materials, the distance between ground point and the barrier, when the distance is nearer, the best position of puting in of adjustment guarantees that partial goods and materials put in the security.
In a preferred embodiment of the present invention, the method further comprises:
establishing a constraint model through big data, and generating a navigation time constraint condition through the constraint model;
acquiring an initial position and a target position of the unmanned aerial vehicle;
calculating standard navigation time from the starting position of the unmanned aerial vehicle to the target position according to the reference flight path;
collecting dynamic track information and calculating and predicting navigation time;
comparing the standard voyage time with the predicted voyage time to obtain a deviation ratio;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the unmanned aerial vehicle node is larger than the target node, the navigation speed of the unmanned aerial vehicle node is adjusted.
The unmanned aerial vehicle formation is carried out according to the material types on the unmanned aerial vehicle by acquiring the material demand information of the target area; acquiring a current flight path of the unmanned aerial vehicle, determining a collaborative path plan of the unmanned aerial vehicle, and generating dynamic path information; comparing the dynamic path information with a reference path to obtain a deviation rate; and judging whether the deviation rate is greater than a preset threshold value, if so, generating correction information, re-forming the unmanned aerial vehicles according to the correction information, generating a new planned path, updating the current flight path according to the new planned path, and controlling the unmanned aerial vehicle to form a formation to fly along the new planned path.
In a preferred embodiment of the present invention, the traffic policy includes one or a combination of two or more of the driving speed of the drone, the driving angle of the drone, the driving time of the drone, and the formation information of the drone.
In a preferred embodiment of the present invention, the formation mode of the unmanned aerial vehicles includes formation of the types of materials loaded on the unmanned aerial vehicles or formation according to material configuration information in the target area.
A third aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium includes a program of an emergency material delivery method based on a drone, and when the program of the emergency material delivery method based on the drone is executed by a processor, the method implements any one of the steps of the emergency material delivery method based on the drone.
The required emergency goods and materials are loaded on the unmanned aerial vehicle in a classified mode through the goods and materials configuration information, then the unmanned aerial vehicle is formed into a team according to the goods and materials configuration information, the traffic capacity index is calculated according to the big data of the traffic flow of a target area, a traffic passing strategy is generated, the optimal throwing point position is calculated according to the passing strategy, the unmanned aerial vehicle flies to the optimal throwing point to carry out goods and materials fixed-point throwing, the throwing efficiency is high, and the throwing point is accurate.
Acquire unmanned aerial vehicle real-time position information, when unmanned aerial vehicle reachd best input position, gather unmanned aerial vehicle below ground image information, acquire unmanned aerial vehicle below barrier information, when detecting there is the barrier, when the analysis was put in goods and materials, the distance between ground point and the barrier, when the distance is nearer, the best input position of adjustment guarantees that partial goods and materials put in the security.
In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of a unit is only one logical function division, and there may be other division ways in actual implementation, such as: multiple units or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units; can be located in one place or distributed on a plurality of network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, all the functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately regarded as one unit, or two or more units may be integrated into one unit; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
Those of ordinary skill in the art will understand that: all or part of the steps for realizing the method embodiments can be completed by hardware related to program instructions, the program can be stored in a computer readable storage medium, and the program executes the steps comprising the method embodiments when executed; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An emergency material releasing method based on an unmanned aerial vehicle is characterized by comprising the following steps:
acquiring target area information and generating material configuration information;
acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy;
calculating the optimal throwing point position according to the traffic strategy to obtain the optimal throwing position information;
acquiring real-time position information of the unmanned aerial vehicle, and comparing the real-time position information with the optimal throwing position information to obtain a deviation rate;
determining whether the deviation ratio is greater than a predetermined threshold,
if the traffic policy is larger than the preset threshold, generating correction information, and correcting the traffic policy through the correction information;
if the quantity is smaller than the preset value, the materials are thrown in a preset throwing mode.
2. The unmanned aerial vehicle-based emergency material delivery method of claim 1, further comprising:
classifying the materials, and respectively loading the materials to different unmanned aerial vehicles;
obtaining the position information of the unmanned aerial vehicle, establishing an unmanned aerial vehicle formation model,
generating unmanned aerial vehicle formation keeping information according to the unmanned aerial vehicle formation model;
generating an unmanned aerial vehicle formation mode according to the unmanned aerial vehicle formation keeping information;
forming unmanned aerial vehicles according to the unmanned aerial vehicle forming mode to obtain result information;
comparing the result information with actual detection information; obtaining unmanned aerial vehicle formation deviation information;
judging whether the deviation information is larger than a preset threshold value,
and if so, generating correction information to correct the unmanned aerial vehicle formation mode.
3. The unmanned aerial vehicle-based emergency material delivery method of claim 2, further comprising:
establishing a constraint model through big data, and generating a navigation time constraint condition through the constraint model;
acquiring an initial position and a target position of the unmanned aerial vehicle;
calculating standard navigation time from the starting position of the unmanned aerial vehicle to the target position according to the reference flight path;
collecting dynamic track information and calculating and predicting navigation time;
comparing the standard voyage time with the predicted voyage time to obtain a deviation ratio;
judging whether the deviation rate is greater than a preset deviation rate threshold value or not;
if the unmanned aerial vehicle node is larger than the target node, the navigation speed of the unmanned aerial vehicle node is adjusted.
4. The unmanned aerial vehicle-based emergency material delivery method of claim 1, wherein the optimal delivery position is calculated according to a traffic policy to obtain optimal delivery position information, and further comprising:
the real-time position information of the unmanned aerial vehicle is obtained,
comparing the real-time position information of the unmanned aerial vehicle with the optimal throwing position;
if the unmanned aerial vehicle reaches the optimal throwing position, acquiring ground image information below the unmanned aerial vehicle;
comparing the image information with preset information to obtain the information of obstacles below the unmanned aerial vehicle;
obtaining distance compensation information according to the obstacle information;
and adjusting the optimal throwing position according to the distance compensation.
5. The unmanned aerial vehicle-based emergency material delivery method of claim 4, wherein the traffic policy comprises one or more of unmanned aerial vehicle traveling speed, unmanned aerial vehicle traveling angle, unmanned aerial vehicle traveling time, and unmanned aerial vehicle formation information.
6. The unmanned aerial vehicle-based emergency material delivery method of claim 1, wherein the unmanned aerial vehicle formation mode comprises formation of material types loaded on the unmanned aerial vehicles or formation according to material configuration information in a target area.
7. The utility model provides an emergent material dispensing system based on unmanned aerial vehicle which characterized in that, this system includes: the emergency material releasing method based on the unmanned aerial vehicle comprises a storage and a processor, wherein the storage comprises an emergency material releasing method program based on the unmanned aerial vehicle, and when the emergency material releasing method program based on the unmanned aerial vehicle is executed by the processor, the following steps are realized:
acquiring target area information and generating material configuration information;
acquiring big data of traffic flow in a target area, calculating a traffic capacity index, and generating a traffic strategy;
calculating the optimal throwing point position according to the traffic strategy to obtain the optimal throwing position information;
acquiring real-time position information of the unmanned aerial vehicle, and comparing the real-time position information with the optimal throwing position information to obtain a deviation rate;
determining whether the deviation ratio is greater than a predetermined threshold,
if the traffic policy is larger than the preset threshold, generating correction information, and correcting the traffic policy through the correction information;
if the quantity is smaller than the preset value, the materials are thrown in a preset throwing mode.
8. The unmanned aerial vehicle-based emergency material delivery system of claim 7, further comprising:
classifying the materials, and respectively loading the materials to different unmanned aerial vehicles;
obtaining the position information of the unmanned aerial vehicle, establishing an unmanned aerial vehicle formation model,
generating unmanned aerial vehicle formation keeping information according to the unmanned aerial vehicle formation model;
generating an unmanned aerial vehicle formation mode according to the unmanned aerial vehicle formation keeping information;
forming unmanned aerial vehicles according to the unmanned aerial vehicle forming mode to obtain result information;
comparing the result information with actual detection information; obtaining unmanned aerial vehicle formation deviation information;
judging whether the deviation information is larger than a preset threshold value,
and if so, generating correction information to correct the unmanned aerial vehicle formation mode.
9. The unmanned aerial vehicle-based emergency material delivery system of claim 7, wherein the optimal delivery point position is calculated according to a traffic policy to obtain optimal delivery point position information, further comprising:
the real-time position information of the unmanned aerial vehicle is obtained,
comparing the real-time position information of the unmanned aerial vehicle with the optimal throwing position;
if the unmanned aerial vehicle reaches the optimal throwing position, acquiring ground image information below the unmanned aerial vehicle;
comparing the image information with preset information to obtain the information of obstacles below the unmanned aerial vehicle;
obtaining distance compensation information according to the obstacle information;
and adjusting the optimal throwing position according to the distance compensation.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium includes a program of the unmanned aerial vehicle-based emergency material delivery method, and when the program of the unmanned aerial vehicle-based emergency material delivery method is executed by a processor, the steps of the unmanned aerial vehicle-based emergency material delivery method according to any one of claims 1 to 6 are implemented.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115907333A (en) * | 2022-10-26 | 2023-04-04 | 江苏领悟信息技术有限公司 | Regional resource scheduling system and method in public emergency event |
| CN116402426A (en) * | 2023-04-20 | 2023-07-07 | 南京交通职业技术学院 | Unmanned aerial vehicle intelligent logistics distribution method, system and medium based on big data |
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2021
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115907333A (en) * | 2022-10-26 | 2023-04-04 | 江苏领悟信息技术有限公司 | Regional resource scheduling system and method in public emergency event |
| CN115907333B (en) * | 2022-10-26 | 2023-09-15 | 江苏领悟信息技术有限公司 | Regional resource scheduling system and method in public emergency event |
| CN116402426A (en) * | 2023-04-20 | 2023-07-07 | 南京交通职业技术学院 | Unmanned aerial vehicle intelligent logistics distribution method, system and medium based on big data |
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