CN117201565A - Internet-connected unmanned aerial vehicle management cloud platform based on 5G transmission - Google Patents
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Abstract
The invention belongs to the technical field of unmanned aerial vehicle management, and particularly relates to a 5G transmission-based network-connected unmanned aerial vehicle management cloud platform, which comprises a position acquisition module, a cruising monitoring module, an alarm module, a prediction module, an exploration module, a forced landing module and a central control module. According to the invention, the cruising mileage of the unmanned aerial vehicle can be measured and calculated according to the electric quantity of the unmanned aerial vehicle, an alarm signal is sent out when the cruising ability is insufficient, the cruising can be selected or continued according to the alarm signal, a temporary forced landing point can be planned for the unmanned aerial vehicle in the process of continuing cruising, the duration of the cruising task is prolonged, the predicted mileage of the unmanned aerial vehicle can be predicted through the prediction module when the cruising ability is normal, an operator is assisted to plan the cruising task of the unmanned aerial vehicle in advance, and an early warning signal can be sent out in advance before the cruising ability of the unmanned aerial vehicle is insufficient, so that reasonable management of cruising of the unmanned aerial vehicle is realized, and the flexibility of cruising management of the unmanned aerial vehicle is improved.
Description
Technical Field
The invention belongs to the technical field of unmanned aerial vehicle management, and particularly relates to a network-connected unmanned aerial vehicle management cloud platform based on 5G transmission.
Background
Along with the rapid development of unmanned aerial vehicle technology, the unmanned aerial vehicle technology is gradually applied to various fields of people's daily life or work, such as geological exploration, inspection cruising, water rescue and other fields, but unmanned aerial vehicle's duration is relatively poor, generally its single cruising period can only keep at 30-60 min, in order to guarantee that it can return to the journey safely in the execution task, it is obviously necessary to manage its cruising ability, combine the transmission rate of 5G network, make unmanned aerial vehicle duration in time feed back to unmanned aerial vehicle management cloud platform, guarantee unmanned aerial vehicle cruising task's orderly execution.
In the prior art, the unmanned aerial vehicle management cloud platform is used for directly managing and scheduling the cruising unmanned aerial vehicle through the cruising ability, when the cruising ability is insufficient, the unmanned aerial vehicle is forcefully scheduled to a starting point, but the unmanned aerial vehicle is inevitably in emergency in the cruising process, the unmanned aerial vehicle is scheduled to the starting point at this moment obviously unreasonable, or the cruising area is explored to be completed to execute the cruising operation, the cruising task is required to be executed for the second time, and the resource waste can be caused undoubtedly.
Disclosure of Invention
The invention aims to provide a 5G transmission-based network-connected unmanned aerial vehicle management cloud platform which can assist an unmanned aerial vehicle in planning forced landing points, prolong the time for executing a cruising task and realize reasonable management on cruising of the unmanned aerial vehicle.
The technical scheme adopted by the invention is as follows:
a network-connected unmanned aerial vehicle management cloud platform based on 5G transmission comprises a position acquisition module, a cruising monitoring module, an alarm module, a prediction module, an exploration module, a forced landing module and a central control module;
the position acquisition module is used for acquiring position information of the unmanned aerial vehicle in real time;
the endurance monitoring module is used for acquiring the battery electric quantity of the unmanned aerial vehicle in real time and measuring and calculating the endurance mileage of the unmanned aerial vehicle according to the battery electric quantity of the unmanned aerial vehicle;
the alarm module is used for judging whether the unmanned aerial vehicle needs to return to the voyage or not according to the position information and the voyage mileage of the unmanned aerial vehicle;
if yes, an alarm signal is sent, and a return instruction is sent to the unmanned aerial vehicle flight control;
if not, indicating that the endurance capacity of the unmanned aerial vehicle is normal, constructing a monitoring period by taking a current node as an ending node, setting a plurality of sampling nodes in the monitoring period, and calibrating the battery electric quantity of the unmanned aerial vehicle under each sampling node as a parameter to be evaluated;
the prediction module is used for measuring and calculating the predicted electric quantity of the unmanned aerial vehicle under the prediction node and the predicted mileage of the unmanned aerial vehicle under the prediction node according to the parameters to be evaluated, and sending out an early warning signal when the predicted mileage is greater than or equal to the distance between the return point and the position of the unmanned aerial vehicle;
the exploration module is used for collecting image information in a navigation area and uploading the image information to a cloud for storage;
the forced landing module is used for searching a forced landing point according to the image information when an alarm signal is sent out, and measuring and calculating the distance between the forced landing point and the real-time position of the unmanned aerial vehicle after the forced landing point is determined;
the central control module is used for receiving and transmitting the circulation information among the position acquisition module, the cruising monitoring module, the alarm module, the prediction module, the exploration module and the forced landing module.
In a preferred scheme, the endurance monitoring module comprises a monitoring unit and a measuring and calculating unit, wherein the monitoring unit is used for collecting the battery electric quantity of the unmanned aerial vehicle in real time, the measuring and calculating unit is used for measuring and calculating the endurance mileage of the unmanned aerial vehicle, and a measuring and calculating function is preset in the measuring and calculating unit;
the battery electric quantity and the endurance coefficient of the unmanned aerial vehicle are input into an measuring and calculating function, and the endurance mileage of the unmanned aerial vehicle can be output in real time;
and the endurance coefficient is the travel mileage of the unmanned aerial vehicle under the unit electricity quantity.
In a preferred scheme, when the alarm module is executed, the distance between the position coordinates and the return point coordinates of the unmanned aerial vehicle is acquired in real time, and is calibrated to be the mileage to be evaluated;
performing difference processing on the mileage to be evaluated and the endurance mileage of the unmanned aerial vehicle to obtain a deviation mileage;
an evaluation threshold value used for comparing with the deviation mileage is arranged in the alarm module;
when the deviation mileage is greater than or equal to an evaluation threshold value, the unmanned aerial vehicle endurance capability is indicated to be normal;
and when the deviation mileage is smaller than an evaluation threshold, indicating that the unmanned aerial vehicle has insufficient endurance.
In a preferred scheme, the prediction module comprises a trend analysis unit and a prediction unit, wherein the trend analysis unit is used for measuring and calculating a battery power consumption trend value of the unmanned aerial vehicle according to parameters to be evaluated, and the prediction unit is used for measuring and calculating the predicted power of the unmanned aerial vehicle according to the actual power of the unmanned aerial vehicle under the current node, the battery power consumption trend value and the period between the prediction node and the current node;
wherein, the execution priority of the trend analysis unit is higher than the execution priority of the prediction unit.
In a preferred scheme, a trend analysis function is preset in the trend analysis unit, and after the parameter to be evaluated is input into the trend analysis function, the output result is calibrated as a battery power consumption trend value;
the prediction unit is internally preset with a prediction function, and after the actual electric quantity of the unmanned aerial vehicle under the current node, the battery electric quantity loss trend value and the period between the prediction node and the current node are input into the prediction function, the output result is calibrated to be the predicted electric quantity.
In a preferred scheme, the exploration module comprises a shooting unit and a measuring unit, wherein the shooting unit is used for acquiring image information in a cruising area, and the measuring unit is used for picking up edge coordinates of a cruising area and measuring the cruising area;
the measuring unit is internally provided with a measuring function, and the measuring function is used for measuring and calculating the area of the cruising area according to the edge coordinates of the cruising area.
In a preferred scheme, the shooting unit is a sampling camera, and the sampling camera is used for shooting environmental information in a continuous navigation area of the unmanned aerial vehicle;
wherein the sampling camera is a binocular camera.
In a preferred scheme, the forced landing module determines the safe landing area of the unmanned aerial vehicle according to the measurement unit, and splits the cruising area according to the safe landing area to obtain a plurality of areas to be evaluated;
the forced landing module comprises a screening unit for performing screening treatment on an area to be evaluated, wherein a standard image corresponding to a safe landing area is arranged in the screening unit, and when the screening unit is performed, the image corresponding to the area to be evaluated is calibrated to be the image to be evaluated, and then the image to be evaluated is compared with the standard image to obtain the image similarity;
the screening unit is internally provided with a screening threshold value for comparing with the image similarity;
when the image similarity is greater than or equal to a screening threshold value, the corresponding region to be evaluated is marked as a temporary forced landing point;
and when the image similarity is smaller than a screening threshold value, the corresponding region to be evaluated is marked as a non-forced landing point.
In a preferred scheme, after the alarm signal is sent out and the unmanned aerial vehicle executes the return voyage, an execution instruction is not sent to the forced landing module;
when the forced landing module receives an execution instruction, synchronously calculating the distances between all temporary forced landing points and the unmanned aerial vehicle, and calibrating the distances as mileage to be checked;
comparing the mileage to be checked with the endurance mileage in real time;
if the mileage to be checked is greater than or equal to the endurance mileage, the corresponding temporary forced landing point is marked as an unexecutable forced landing point;
if the mileage to be checked is smaller than the endurance mileage, the corresponding temporary forced landing point is marked as an executable forced landing point.
The invention also provides an internet-connected unmanned aerial vehicle management terminal based on 5G transmission, which comprises:
at least one processor;
and a memory communicatively coupled to the at least one processor;
the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor, so that the at least one processor can execute the internet-connected unmanned aerial vehicle management cloud platform based on 5G transmission.
The invention has the technical effects that:
according to the invention, the cruising mileage of the unmanned aerial vehicle can be measured and calculated according to the electric quantity of the unmanned aerial vehicle, an alarm signal is sent out when the cruising ability is insufficient, the cruising can be selected or continued according to the alarm signal, a temporary forced landing point can be planned for the unmanned aerial vehicle in the process of continuing cruising, the duration of the cruising task is prolonged, the predicted mileage of the unmanned aerial vehicle can be predicted through the prediction module when the cruising ability is normal, an operator is assisted to plan the cruising task of the unmanned aerial vehicle in advance, and an early warning signal can be sent out in advance before the cruising ability of the unmanned aerial vehicle is insufficient, so that reasonable management of cruising of the unmanned aerial vehicle is realized, and the flexibility of cruising management of the unmanned aerial vehicle is improved.
Drawings
FIG. 1 is a block diagram of a cloud platform provided by the present invention;
fig. 2 is a cloud platform operation diagram provided by the invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one preferred embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Referring to fig. 1 and 2, the invention provides a 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform, which comprises a position acquisition module, a cruising monitoring module, an alarm module, a prediction module, an exploration module, a forced landing module and a central control module;
the position acquisition module is used for acquiring position information of the unmanned aerial vehicle in real time;
the endurance monitoring module is used for acquiring the battery electric quantity of the unmanned aerial vehicle in real time and measuring and calculating the endurance mileage of the unmanned aerial vehicle according to the battery electric quantity of the unmanned aerial vehicle;
the alarm module is used for judging whether the unmanned aerial vehicle needs to return to the voyage according to the position information and the voyage mileage of the unmanned aerial vehicle;
if yes, an alarm signal is sent, and a return instruction is sent to the unmanned aerial vehicle flight control;
if not, indicating that the endurance capacity of the unmanned aerial vehicle is normal, constructing a monitoring period by taking the current node as an ending node, setting a plurality of sampling nodes in the monitoring period, and calibrating the battery electric quantity of the unmanned aerial vehicle under each sampling node as a parameter to be evaluated;
the prediction module is used for measuring and calculating the predicted electric quantity of the unmanned aerial vehicle under the prediction node and the predicted mileage of the unmanned aerial vehicle under the prediction node according to the parameters to be evaluated, and sending out an early warning signal when the predicted mileage is greater than or equal to the distance between the return point and the position of the unmanned aerial vehicle;
the exploration module is used for collecting image information in the navigation area and uploading the image information to the cloud for storage;
the forced landing module is used for searching a forced landing point according to image information when an alarm signal is sent out, and measuring and calculating the distance between the forced landing point and the real-time position of the unmanned aerial vehicle after the forced landing point is determined;
the central control module is used for receiving and transmitting the circulation information among the position acquisition module, the cruising monitoring module, the alarm module, the prediction module, the exploration module and the forced landing module.
Along with the rapid development of unmanned aerial vehicle technology, the unmanned aerial vehicle technology is gradually applied to various fields of daily life or work of people, such as geological exploration, cruising and water rescue, but the unmanned aerial vehicle has poor cruising ability, generally has a single cruising period which can only be kept at 30-60 min, the cruising ability management is obviously necessary for ensuring that the unmanned aerial vehicle can safely return to the navigation during the task execution, the cruising ability of the unmanned aerial vehicle can be timely fed back to an unmanned aerial vehicle management cloud platform by combining with the transmission rate of a 5G network, so that the phenomenon of falling of the unmanned aerial vehicle caused by insufficient cruising ability during the task execution or the returning process of the unmanned aerial vehicle can be effectively avoided, in the embodiment, the position information of the unmanned aerial vehicle is firstly acquired in real time through a position acquisition module, the position information can be used for obtaining the required flight mileage of the unmanned aerial vehicle during the returning process, and then the battery electric quantity of the unmanned aerial vehicle is obtained in real time through the continuous voyage monitoring module, so that the continuous voyage mileage of the unmanned aerial vehicle can be calculated according to the battery electric quantity, the continuous voyage mileage of the unmanned aerial vehicle is judged and processed through the alarm module, whether a return instruction is sent to the unmanned aerial vehicle in a flying mode or not is determined, after the return instruction is sent, an alarm signal is sent synchronously to prompt an operator, but the operator can select whether to continue to cruise according to actual requirements, but before the operator selects to continue to cruise, the forced landing module can mark a plurality of temporary forced landing points in a cruising area, so that the situation that the unmanned aerial vehicle continues to cruise is ensured, the phenomenon that the unmanned aerial vehicle falls due to insufficient voyage capability is avoided, the determination of the temporary forced landing points is required to be executed according to the image information obtained by the exploration module, in the normal cruising process of the unmanned aerial vehicle, a monitoring period is constructed according to the cruising period, a plurality of sampling nodes are arranged in the monitoring period, the electric quantity of the unmanned aerial vehicle battery under the sampling nodes is calibrated as a parameter to be evaluated, after the parameter to be evaluated is determined, the predicted electric quantity of the unmanned aerial vehicle under the predicting node and the predicted mileage of the unmanned aerial vehicle under the predicting node can be calculated through the action of the predicting module, the cruising ability of the unmanned aerial vehicle can be judged in advance based on the predicted mileage, and when the predicted mileage is greater than or equal to the distance between the returning point and the unmanned aerial vehicle position, an early warning signal is sent to remind an operator that the cruising ability of the unmanned aerial vehicle tends to be insufficient, so that the operator can plan and adjust the cruising task in advance, and reasonable management of cruising of the unmanned aerial vehicle is realized.
In a preferred embodiment, the endurance monitoring module comprises a monitoring unit and a measuring and calculating unit, wherein the monitoring unit is used for collecting the battery electric quantity of the unmanned aerial vehicle in real time, the measuring and calculating unit is used for measuring and calculating the endurance mileage of the unmanned aerial vehicle, and a measuring and calculating function is preset in the measuring and calculating unit;
the battery electric quantity and the endurance coefficient of the unmanned aerial vehicle are input into the measuring and calculating function, and the endurance mileage of the unmanned aerial vehicle can be output in real time;
the endurance coefficient is the travel mileage of the unmanned aerial vehicle under the unit electricity quantity.
In this embodiment, when the cruise monitoring module is executed, the monitoring unit is executed first to collect the battery power of the unmanned aerial vehicle, and then the measuring and calculating function is called from the measuring and calculating unit, where the expression of the measuring and calculating function is:wherein->Represents the endurance mileage of the unmanned aerial vehicle, +.>Representing the endurance coefficient, < >>Representing battery power of unmanned aerial vehicle, +.>The buffer mileage is represented, that is, the flight resistance of the unmanned aerial vehicle may be increased due to the influence of weather environment and the like, so that the endurance mileage is correspondingly reduced, the buffer mileage is set to avoid the phenomenon, and the specific numerical value of the buffer mileage is set according to the actual environment and the specification of the unmanned aerial vehicle, which is not the technical core point of the scheme, and will not be detailed hereAnd in detail, based on the above formula, the endurance mileage of the unmanned aerial vehicle can be obtained, and corresponding data support is provided for the execution of the subsequent alarm module.
In a preferred embodiment, when the alarm module executes, the distance between the position coordinates and the return point coordinates of the unmanned aerial vehicle is obtained in real time, and is calibrated to be the mileage to be evaluated;
performing difference processing on mileage to be evaluated and the endurance mileage of the unmanned aerial vehicle to obtain a deviation mileage;
an evaluation threshold value used for comparing with the deviation mileage is arranged in the alarm module;
when the deviation mileage is greater than or equal to the evaluation threshold, the unmanned aerial vehicle endurance is normal;
and when the deviation mileage is smaller than the evaluation threshold, indicating that the unmanned aerial vehicle has insufficient endurance.
In this embodiment, when the alarm module executes, the distance between the current position of the unmanned aerial vehicle and the return point needs to be acquired, the present embodiment marks the distance as the mileage to be evaluated, then performs difference processing on the distance and the cruising mileage obtained by the duration detection module, so as to obtain the deviation mileage, then compares the deviation mileage with the evaluation threshold, and can definitely judge whether the duration of the unmanned aerial vehicle is normal, when the distance is judged to be normal, the period that the unmanned aerial vehicle cruises is constructed as the monitoring period, a plurality of sampling nodes are set in the monitoring period, and corresponding data support is provided for the execution of the follow-up prediction module by acquiring the battery power of the unmanned aerial vehicle under each sampling node, otherwise, when the duration of the unmanned aerial vehicle is judged to be abnormal, an alarm signal is sent out synchronously, and a return instruction is sent to the unmanned aerial vehicle flight control synchronously, after the unmanned aerial vehicle is determined, the return point can be executed by the unmanned aerial vehicle, and when the alarm signal is sent out, the forced landing module synchronously calculates the landing point, so that the operator can select the temporary cruising of the unmanned aerial vehicle to continue to the forced landing point according to the actual requirement, and the temporary landing point is lifted, and the unmanned aerial vehicle is directly managed, and the landing is also flexible.
In a preferred embodiment, the prediction module includes a trend analysis unit and a prediction unit, the trend analysis unit is used for measuring and calculating a battery power consumption trend value of the unmanned aerial vehicle according to parameters to be evaluated, and the prediction unit is used for measuring and calculating a predicted power of the unmanned aerial vehicle according to an actual power of the unmanned aerial vehicle at a current node, the battery power consumption trend value and a period between the prediction node and the current node;
wherein, the execution priority of the trend analysis unit is higher than the execution priority of the prediction unit.
In this embodiment, when the prediction module executes, the parameters to be evaluated need to be collected in advance, then the parameters to be evaluated are directly input into the trend analysis unit, the battery power consumption trend value of the unmanned aerial vehicle is derived, the actual power of the unmanned aerial vehicle under the current node and the duration between the prediction node and the current node are obtained, the prediction power of the unmanned aerial vehicle can be derived by combining the battery power consumption trend value and inputting the prediction power into the prediction unit together, it is required that the energy consumption required by the unmanned aerial vehicle in the starting and rising processes is large, and when the parameters to be evaluated are collected, the collection can be started after the unmanned aerial vehicle rises to the required height, so that the accuracy of the output result of the prediction unit is ensured.
In a preferred embodiment, a trend analysis function is preset in the trend analysis unit, and after the parameter to be evaluated is input into the trend analysis function, the output result is calibrated as a battery power consumption trend value;
the prediction unit is preset with a prediction function, and the actual electric quantity of the unmanned aerial vehicle under the current node, the battery electric quantity loss trend value and the period between the prediction node and the current node are input into the prediction function, and then the output result is calibrated to be the predicted electric quantity.
In this embodiment, when the trend analysis unit performs, the parameter to be evaluated may be input into a trend analysis function, where the expression of the trend analysis function is:wherein->Representing a battery power consumption trend value, < >>Time length representing monitoring period, +.>Representing the number of parameters to be evaluated, +.>And->And (3) representing the battery power under the adjacent sampling nodes, and based on the above formula, after the battery power loss trend value is determined, executing a prediction unit, wherein the expression of a prediction function in the prediction unit is as follows: />Wherein->Representing predicted power,/->Representing the actual power under the current node, +.>The method has the advantages that the time period between the prediction node and the current node is represented, after the predicted electric quantity is obtained, the predicted electric quantity is input into the measuring and calculating unit, and the predicted mileage can be obtained, so that early warning can be carried out in advance before the unmanned aerial vehicle has insufficient endurance, a certain response time is provided for an operator to plan a cruising task and the like, and the flexibility of the unmanned aerial vehicle cruising management is enhanced.
In a preferred embodiment, the exploration module comprises a shooting unit and a measuring unit, wherein the shooting unit is used for acquiring image information in a cruising area, and the measuring unit is used for picking up edge coordinates of a cruising area and measuring the cruising area;
the measuring unit is internally provided with a measuring function, and the measuring function is used for measuring and calculating the area of the cruising area according to the edge coordinates of the cruising area.
In this embodiment, after the cruising region is photographed, it may be classified into video data and picture data, the coordinates of the cruising region edge inflection point can be determined for the picture data, and after these inflection point coordinates are determined, they are input into a measurement function to measure the area of the cruising region, where the expression of the measurement function is:wherein->Indicating the area of the cruise zone>Representing the number of coordinates of the inflection point>Number indicating coordinates of inflection point>Represents the abscissa of inflection point, ++>Representing the ordinate of the inflection point, based on the above, may provide computational support when the forced landing module selects a temporary forced landing point.
In addition, the recording unit mentioned in the present embodiment is a sampling camera, and the sampling camera is used for recording environmental information in the navigation area of the unmanned aerial vehicle;
the sampling camera is a binocular camera, and the measurement result is more accurate compared with a monocular camera.
In a preferred embodiment, the forced landing module determines the safe landing area of the unmanned aerial vehicle according to the measurement unit, and splits the cruising area according to the safe landing area to obtain a plurality of areas to be evaluated;
the forced landing module comprises a screening unit for performing screening treatment on the area to be evaluated, wherein a standard image corresponding to the safe landing area is arranged in the screening unit, and when the screening unit is performed, the image corresponding to the area to be evaluated is calibrated to be the image to be evaluated, and then the image to be evaluated is compared with the standard image to obtain the image similarity;
the screening unit is also internally provided with a screening threshold value for comparing with the image similarity;
when the image similarity is greater than or equal to the screening threshold value, the corresponding region to be evaluated is marked as a temporary forced landing point;
and when the image similarity is smaller than the screening threshold value, the corresponding region to be evaluated is marked as a non-forced landing point.
In this embodiment, when the temporary forced landing point is calibrated, firstly, the safe landing area required by the unmanned aerial vehicle during safe landing needs to be determined, then the cruising area is split according to the safe landing area, so that a plurality of areas to be evaluated can be obtained, then the images corresponding to the areas to be evaluated are calibrated into images to be evaluated, and compared with the standard image, so that the image similarity between the images to be evaluated and the standard image can be calculated, wherein the calculation formula of the image similarity is as follows:
wherein->Representing image similarity>Representing the number of pixels in the image to be evaluated and in the standard image, < >>Representing pixel coordinates in the image to be evaluated, for example>And the coordinates of the pixel points in the standard image are represented, and after the image similarity is determined, the coordinates are compared with a preset screening threshold value, so that whether the region to be evaluated can be calibrated as a temporary forced landing point or not can be determined, and corresponding data support is provided for the subsequent operator forced landing unmanned aerial vehicle.
In a preferred embodiment, after the alarm signal is sent out and the unmanned aerial vehicle performs the return voyage, no execution instruction is sent to the forced landing module;
when the forced landing module receives an execution instruction, synchronously calculating the distances between all temporary forced landing points and the unmanned aerial vehicle, and calibrating the distances as mileage to be checked;
comparing the mileage to be checked with the endurance mileage in real time;
if the mileage to be checked is greater than or equal to the endurance mileage, the corresponding temporary forced landing point is marked as an unexecutable forced landing point;
if the mileage to be checked is smaller than the endurance mileage, the corresponding temporary forced landing point is marked as an executable forced landing point.
In this embodiment, after the alarm signal is sent, if the operator executes the unmanned aerial vehicle to return, it indicates that forced landing is not required, so that the forced landing module is not required to be executed any more, and then an execution instruction is not required to be sent to the forced landing module.
The invention also provides an internet-connected unmanned aerial vehicle management terminal based on 5G transmission, which comprises:
at least one processor;
and a memory communicatively coupled to the at least one processor;
the memory stores a computer program executable by the at least one processor, so that the at least one processor can execute the 5G transmission-based internet access unmanned aerial vehicle management cloud platform.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, apparatus, article or method that comprises the element.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention. Structures, devices and methods of operation not specifically described and illustrated herein, unless otherwise indicated and limited, are implemented according to conventional means in the art.
Claims (10)
1. The utility model provides a network allies oneself with unmanned aerial vehicle management cloud platform based on 5G transmission, includes position acquisition module, continuation of journey monitoring module, alarm module, prediction module, exploration module, forced landing module and central control module, its characterized in that:
the position acquisition module is used for acquiring position information of the unmanned aerial vehicle in real time;
the endurance monitoring module is used for acquiring the battery electric quantity of the unmanned aerial vehicle in real time and measuring and calculating the endurance mileage of the unmanned aerial vehicle according to the battery electric quantity of the unmanned aerial vehicle;
the alarm module is used for judging whether the unmanned aerial vehicle needs to return to the voyage or not according to the position information and the voyage mileage of the unmanned aerial vehicle;
if yes, an alarm signal is sent, and a return instruction is sent to the unmanned aerial vehicle flight control;
if not, indicating that the endurance capacity of the unmanned aerial vehicle is normal, constructing a monitoring period by taking a current node as an ending node, setting a plurality of sampling nodes in the monitoring period, and calibrating the battery electric quantity of the unmanned aerial vehicle under each sampling node as a parameter to be evaluated;
the prediction module is used for measuring and calculating the predicted electric quantity of the unmanned aerial vehicle under the prediction node and the predicted mileage of the unmanned aerial vehicle under the prediction node according to the parameters to be evaluated, and sending out an early warning signal when the predicted mileage is greater than or equal to the distance between the return point and the position of the unmanned aerial vehicle;
the exploration module is used for collecting image information in a navigation area and uploading the image information to a cloud for storage;
the forced landing module is used for searching a forced landing point according to the image information when an alarm signal is sent out, and measuring and calculating the distance between the forced landing point and the real-time position of the unmanned aerial vehicle after the forced landing point is determined;
the central control module is used for receiving and transmitting the circulation information among the position acquisition module, the cruising monitoring module, the alarm module, the prediction module, the exploration module and the forced landing module.
2. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 1, wherein: the cruising monitoring module comprises a monitoring unit and a measuring and calculating unit, wherein the monitoring unit is used for collecting the battery electric quantity of the unmanned aerial vehicle in real time, the measuring and calculating unit is used for measuring and calculating the cruising mileage of the unmanned aerial vehicle, and a measuring and calculating function is preset in the measuring and calculating unit;
the battery electric quantity and the endurance coefficient of the unmanned aerial vehicle are input into an measuring and calculating function, and the endurance mileage of the unmanned aerial vehicle can be output in real time;
and the endurance coefficient is the travel mileage of the unmanned aerial vehicle under the unit electricity quantity.
3. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 1, wherein: when the alarm module is executed, the distance between the position coordinates and the return point coordinates of the unmanned aerial vehicle is obtained in real time, and the distance is calibrated to be the mileage to be evaluated;
performing difference processing on the mileage to be evaluated and the endurance mileage of the unmanned aerial vehicle to obtain a deviation mileage;
an evaluation threshold value used for comparing with the deviation mileage is arranged in the alarm module;
when the deviation mileage is greater than or equal to an evaluation threshold value, the unmanned aerial vehicle endurance capability is indicated to be normal;
and when the deviation mileage is smaller than an evaluation threshold, indicating that the unmanned aerial vehicle has insufficient endurance.
4. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 1, wherein: the prediction module comprises a trend analysis unit and a prediction unit, wherein the trend analysis unit is used for measuring and calculating a battery power consumption trend value of the unmanned aerial vehicle according to parameters to be evaluated, and the prediction unit is used for measuring and calculating the predicted power of the unmanned aerial vehicle according to the actual power of the unmanned aerial vehicle under the current node, the battery power consumption trend value and the period between the prediction node and the current node;
wherein, the execution priority of the trend analysis unit is higher than the execution priority of the prediction unit.
5. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 4, wherein: a trend analysis function is preset in the trend analysis unit, and after the parameter to be evaluated is input into the trend analysis function, the output result is calibrated as a battery electric quantity loss trend value;
the prediction unit is internally preset with a prediction function, and after the actual electric quantity of the unmanned aerial vehicle under the current node, the battery electric quantity loss trend value and the period between the prediction node and the current node are input into the prediction function, the output result is calibrated to be the predicted electric quantity.
6. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 1, wherein: the exploration module comprises a shooting unit and a measuring unit, wherein the shooting unit is used for collecting image information in a cruising area, and the measuring unit is used for picking up edge coordinates of a cruising area and measuring the area of the cruising area;
the measuring unit is internally provided with a measuring function, and the measuring function is used for measuring and calculating the area of the cruising area according to the edge coordinates of the cruising area.
7. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 6, wherein: the shooting unit is a sampling camera and the sampling camera is used for shooting environmental information in a continuous navigation area of the unmanned aerial vehicle;
wherein the sampling camera is a binocular camera.
8. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 6, wherein: the forced landing module determines the safe landing area of the unmanned aerial vehicle according to the measuring unit, and splits the cruising area according to the safe landing area to obtain a plurality of areas to be evaluated;
the forced landing module comprises a screening unit for performing screening treatment on an area to be evaluated, wherein a standard image corresponding to a safe landing area is arranged in the screening unit, and when the screening unit is performed, the image corresponding to the area to be evaluated is calibrated to be the image to be evaluated, and then the image to be evaluated is compared with the standard image to obtain the image similarity;
the screening unit is internally provided with a screening threshold value for comparing with the image similarity;
when the image similarity is greater than or equal to a screening threshold value, the corresponding region to be evaluated is marked as a temporary forced landing point;
and when the image similarity is smaller than a screening threshold value, the corresponding region to be evaluated is marked as a non-forced landing point.
9. The 5G transmission-based internet-connected unmanned aerial vehicle management cloud platform of claim 1, wherein: after the alarm signal is sent out, and the unmanned aerial vehicle executes return, an execution instruction is not sent to the forced landing module;
when the forced landing module receives an execution instruction, synchronously calculating the distances between all temporary forced landing points and the unmanned aerial vehicle, and calibrating the distances as mileage to be checked;
comparing the mileage to be checked with the endurance mileage in real time;
if the mileage to be checked is greater than or equal to the endurance mileage, the corresponding temporary forced landing point is marked as an unexecutable forced landing point;
if the mileage to be checked is smaller than the endurance mileage, the corresponding temporary forced landing point is marked as an executable forced landing point.
10. An internet-connected unmanned aerial vehicle management terminal based on 5G transmission, its characterized in that: comprising the following steps:
at least one processor;
and a memory communicatively coupled to the at least one processor;
wherein the memory stores a computer program executable by the at least one processor to enable the at least one processor to execute the 5G transmission-based networked unmanned aerial vehicle management cloud platform of any of claims 1 to 9.
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