Unmanned aerial vehicle safety monitoring method and system

Abstract

The invention relates to an unmanned aerial vehicle safety monitoring method and system. The method comprises the steps of obtaining a flight route of an unmanned aerial vehicle; collecting a ground image in the route; acquiring flight information of the unmanned aerial vehicle; obtaining the current power consumption and the residual electric quantity of a main battery of the unmanned aerial vehicle; determining the endurance mileage of the unmanned aerial vehicle; and determining a safe flight strategy. Therefore, the flight efficiency and safety of the unmanned aerial vehicle are guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of unmanned aerial vehicles, and in particular to a safety monitoring method and system for unmanned aerial vehicles. Background Art

[0002] During the flight of a drone, if the battery power is low, from the perspective of the drone, it may malfunction or unexpectedly shut down. From the perspective of the battery, it may cause the battery to work abnormally and its life span to be reduced.

[0003] However, in the prior art, when the battery is insufficient, the drone is usually simply ordered to return or make an emergency landing. This method has low working efficiency and poor safety. Summary of the invention

[0004] The present invention aims at the technical problems existing in the prior art and provides a method and system for safety monitoring of unmanned aerial vehicles.

[0005] The technical solution of the present invention to solve the above technical problems is as follows: A method for safety monitoring of an unmanned aerial vehicle, the method comprising: Get the flight route of the drone; collecting ground images in the flight route; Obtaining flight information of the drone; the flight information includes current flight mileage, current location, flight speed, and remaining mileage; Obtaining the current power consumption and remaining power of the main battery of the drone; Determining the range of the drone; Determine safe flight strategies.

[0006] Optionally, determining the cruising range of the drone includes: Determine the loss rate according to the current flight mileage and the current power consumption; The cruising range of the drone is determined according to the loss rate and the remaining power.

[0007] Optionally, determining the loss rate according to the current flight mileage and the current power consumption includes: Calculate the actual unit energy consumption, where the actual unit energy consumption = current power consumption / current flight mileage; Get theoretical unit energy consumption; The loss rate is calculated, where the loss rate=actual unit energy consumption / theoretical unit energy consumption.

[0008] Optionally, determining the cruising range of the drone according to the loss rate and the remaining power includes: Endurance mileage = remaining power / theoretical unit energy consumption*loss rate.

[0009] Optionally, determining a safe flight strategy includes: If the remaining mileage is greater than the endurance mileage, the total power of the backup battery of the drone is obtained; Determining the standby mileage according to the total power of the standby battery; Determining whether a temporary landing point needs to be selected according to the remaining mileage, the endurance mileage, and the spare mileage; If so, a temporary landing point is selected and a battery switching strategy is formulated.

[0010] Optionally, determining the standby mileage according to the total power of the standby battery includes: Reserve mileage = total reserve battery capacity / theoretical unit energy consumption*loss rate.

[0011] Optionally, the determining whether a temporary landing point needs to be selected according to the remaining mileage, the endurance mileage, and the spare mileage includes: If the remaining mileage is greater than the sum of the endurance mileage and the reserve mileage, a temporary landing point needs to be selected.

[0012] Optionally, selecting a temporary landing point includes: Inputting the current position, the flight speed and the ground image into a landing point screening model to obtain a possible landing point position; The possible landing point locations are screened to determine a temporary landing point.

[0013] Optionally, after determining the temporary landing point, the following steps are performed: Genetic algorithm is used to formulate battery switching strategy.

[0014] The present invention also provides a drone safety monitoring system, the system comprising: A first data acquisition module is used to acquire the UAV route; A data acquisition module, used for acquiring ground images in the route; A second data acquisition module is used to acquire the flight information of the UAV; the flight information includes the current flight mileage, current position, flight speed and remaining mileage; A third data acquisition module is used to obtain the current power consumption and remaining power of the main battery of the drone; A mileage calculation module, used to determine the cruising range of the drone; Strategy formulation module, used to determine safe flight strategies.

[0015] Optionally, the mileage calculation module is further used for: Determine the loss rate according to the current flight mileage and the current power consumption; The cruising range of the drone is determined according to the loss rate and the remaining power.

[0016] Optionally, determining the loss rate according to the current flight mileage and the current power consumption includes: Calculate the actual unit energy consumption, where the actual unit energy consumption = current power consumption / current flight mileage; Get theoretical unit energy consumption; The loss rate is calculated, where the loss rate=actual unit energy consumption / theoretical unit energy consumption.

[0017] Optionally, determining the cruising range of the drone according to the loss rate and the remaining power includes: Endurance mileage = remaining power / theoretical unit energy consumption*loss rate.

[0018] Optionally, the policy formulation module is further used to: If the remaining mileage is greater than the endurance mileage, the total power of the backup battery of the drone is obtained; Determining the standby mileage according to the total power of the standby battery; Determining whether a temporary landing point needs to be selected according to the remaining mileage, the endurance mileage, and the spare mileage; If so, a temporary landing point is selected and a battery switching strategy is formulated.

[0019] Optionally, determining the standby mileage according to the total power of the standby battery includes: Reserve mileage = total reserve battery capacity / theoretical unit energy consumption*loss rate.

[0020] Optionally, the determining whether a temporary landing point needs to be selected according to the remaining mileage, the endurance mileage, and the spare mileage includes: If the remaining mileage is greater than the sum of the endurance mileage and the reserve mileage, a temporary landing point needs to be selected.

[0021] Optionally, selecting a temporary landing point includes: Inputting the current position, the flight speed and the ground image into a landing point screening model to obtain a possible landing point position; The possible landing point locations are screened to determine a temporary landing point.

[0022] Optionally, after determining the temporary landing point, the following steps are performed: Genetic algorithm is used to formulate battery switching strategy.

[0023] In addition, to achieve the above-mentioned purpose, the present invention also proposes an electronic device, comprising: a memory for storing a computer software program; a processor for reading and executing the computer software program, thereby implementing a drone safety monitoring method as described above.

[0024] In addition, to achieve the above-mentioned purpose, the present invention also proposes a non-transitory computer-readable storage medium, in which a computer software program is stored. When the computer software program is executed by a processor, a drone safety monitoring method as described above is implemented.

[0025] The beneficial effects of the present invention are: (1) The present invention obtains the flight route of the drone; collects ground images in the flight route; obtains the flight information of the drone; obtains the current power consumption and remaining power of the main battery of the drone; determines the endurance mileage of the drone; and determines a safe flight strategy, thereby ensuring the flight efficiency and safety of the drone.

[0026] (2) Considering that the battery power of the drone will be depleted due to environmental factors during flight, the present invention introduces the loss rate to calculate the cruising range of the main battery and the standby range of the backup battery; specifically, actual unit energy consumption = current power consumption / current flight mileage; loss rate = actual unit energy consumption / theoretical unit energy consumption; then cruising range = remaining power / theoretical unit energy consumption*loss rate; standby mileage = total power of the backup battery / theoretical unit energy consumption*loss rate. This method improves the accuracy of mileage calculation.

[0027] (3) A convolutional neural network model is introduced to screen possible landing points. The current position of the drone, the flight speed and the ground image are used as the input of the model. After the convolution layer, pooling layer, activation layer and fully connected layer, the possible landing point position is output. The possible landing point whose distance from the current position is less than the endurance mileage + spare mileage and whose distance from the end point of the flight route is the smallest is screened out as a temporary landing point. This improves the flight efficiency of the drone.

[0028] (4) To avoid failures, drones are usually equipped with backup batteries. The present invention takes into account the impact of the remaining battery power on the flight efficiency of the drone and adopts a genetic algorithm to formulate a battery switching strategy to improve the efficiency and safety of drone use. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 A scene diagram of a drone safety monitoring method provided by the present invention; Figure 2 A flowchart of a drone safety monitoring method provided by the present invention; Figure 3 A flow chart of another drone safety monitoring method provided by the present invention; Figure 4 A schematic diagram of the structure of a drone safety monitoring system provided by the present invention; Figure 5 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention; Figure 6 A schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. DETAILED DESCRIPTION

[0030] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0031] In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0032] In the description of the present invention, the term "for example" is used to mean "used as an example, illustration or explanation". Any embodiment described as "for example" in the present invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is given to enable any technician in the field to implement and use the present invention. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present invention can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present invention with unnecessary details. Therefore, the present invention is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present invention.

[0033] See also Figure 1 , Figure 1 This is a scene diagram of a drone safety monitoring method provided by the present invention. Figure 1 As shown, the terminal and the server are connected via a network, such as a wired or wireless network connection. The terminal may include but is not limited to portable terminals such as mobile phones and tablets installed with various network platform applications, as well as fixed terminals such as computers, query machines, and advertising machines. The server provides users with various business services, including service push servers, user recommendation servers, etc.

[0034] It should be noted that Figure 1 The scenario diagram of a drone safety monitoring method shown is only an example. The terminal, server, and application scenario described in the embodiment of the present invention are intended to more clearly illustrate the technical solution of the embodiment of the present invention, and do not generate limitations on the technical solution provided by the embodiment of the present invention. A person of ordinary skill in the art can know that with the evolution of the system and the emergence of new business scenarios, the technical solution provided by the embodiment of the present invention is also applicable to similar technical problems.

[0035] Among them, the terminal can be used for: Get the flight route of the drone; collecting ground images in the flight route; Obtaining flight information of the drone; the flight information includes current flight mileage, current location, flight speed, and remaining mileage; Obtaining the current power consumption and remaining power of the main battery of the drone; Determining the range of the drone; Determine safe flight strategies.

[0036] See also Figure 2 , provides a flow chart of a wind UAV safety monitoring method of the present invention, comprising the following steps: Step 201: Obtain the flight route of the drone.

[0037] Optionally, the flight route can be pre-planned or adjusted in real time by the drone and returned to the control center.

[0038] Step 202: Collect ground images in the flight route.

[0039] Optionally, ground images are collected through satellite images, GIS systems, field measurements, etc.

[0040] Step 203: Obtain flight information of the UAV.

[0041] The flight information includes the current flight mileage, current location, flight speed and remaining mileage.

[0042] Step 204: Obtain the current power consumption and remaining power of the main battery of the drone.

[0043] Among other things, the drone may contain a main battery and multiple backup batteries.

[0044] Step 205: Determine the cruising range of the UAV.

[0045] In one embodiment, if Figure 3 As shown, step 205 may further include the following steps: Step 2051: determine the loss rate according to the current flight mileage and current power consumption.

[0046] Optionally, this step includes: calculating actual unit energy consumption; obtaining theoretical unit energy consumption; and calculating loss rate. Wherein, the actual unit energy consumption = current power consumption / current flight mileage; and the loss rate = actual unit energy consumption / theoretical unit energy consumption.

[0047] Step 2052: Determine the cruising range of the UAV according to the loss rate and the remaining power.

[0048] Among them, cruising range = remaining power / theoretical unit energy consumption*loss rate.

[0049] This will provide a more accurate mileage estimate.

[0050] Step 206: Determine a safe flight strategy.

[0051] In one embodiment, if Figure 3 As shown, step 206 may further include the following steps: Step 2061: If the remaining mileage is greater than the endurance mileage, the total power of the backup battery of the drone is obtained.

[0052] Step 2062: Determine the standby mileage according to the total power of the standby battery.

[0053] Among them, the reserve mileage = total reserve battery power / theoretical unit energy consumption*loss rate.

[0054] Therefore, applying the previously obtained loss rate of the main battery during the flight to the mileage calculation of the backup battery can obtain a more accurate backup mileage.

[0055] Step 2063: Determine whether a temporary landing point needs to be selected based on the remaining mileage, the endurance mileage, and the spare mileage; if so, proceed to step 2064.

[0056] Among them, if the remaining mileage is greater than the sum of the endurance mileage and the backup mileage, it can be seen that the existing battery on the drone cannot support the entire route, and a temporary landing point needs to be selected.

[0057] Step 2064: Select a temporary landing point and formulate a battery switching strategy.

[0058] In yet another embodiment, step 2064 may further include the following steps: Step A: input the current position, the flight speed and the ground image into a landing point screening model to obtain a landing point position.

[0059] The landing point screening model may be a convolutional neural network model (CNN). Specifically, the current position of the drone, the flight speed and the ground image are used as inputs of the model, and the coordinates of the landing point, i.e., the landing point position, are output through a convolutional layer, a pooling layer, an activation layer and a fully connected layer.

[0060] Step B: screening the possible landing point locations and determining a temporary landing point.

[0061] Optionally, a landing point whose distance from the current position is less than the endurance mileage+the spare mileage and whose distance from the end point of the flight route is the shortest is selected as a temporary landing point.

[0062] The temporary landing points selected in this way can improve the flight efficiency of the drone.

[0063] Step C: Develop a battery switching strategy using a genetic algorithm.

[0064] Among them, since the battery life will be reduced when used when the remaining power is too low, in order to optimize the battery life while completing the temporary landing mission, a genetic algorithm is introduced to formulate a battery switching strategy.

[0065] Specifically, initialize the population: randomly generate different switching strategies, each switching strategy consists of a battery type (i.e., main battery / backup battery) and a flight mileage (the flight mileage between the current location and the temporary landing point); calculate the fitness score of each switching strategy according to the fitness function; select a population with higher fitness from the current population; perform crossover and mutation operations on the new population; repeat the above process of calculating fitness scores, selecting, crossover, and mutation until the stopping condition is reached (such as fitness convergence or reaching the maximum number of iterations); select the individual with the highest fitness from the final population as the optimal battery switching strategy.

[0066] Optionally, assuming that the drone has one main battery and two backup batteries, and the distance between the current position and the temporary landing point is 160, the randomly generated switching strategy can be expressed as {[main battery, 80], [backup battery 1, 40], [backup battery 2, 40]}. The fitness function is: F=1 / |a*main battery remaining power+b*backup battery 1 remaining power+c*backup battery 2 remaining power-d*battery switching times|, where a, b, c represent the weight coefficients of the remaining power of the main battery, backup battery 1, and backup battery 2, and d represents the weight coefficient of the battery switching times.

[0067] Therefore, a reasonable battery switching strategy is formulated to improve the efficiency and safety of drone use.

[0068] See also Figure 4 , Figure 4A schematic structural diagram of a UAV safety monitoring system provided by the present invention.

[0069] like Figure 4 As shown, an unmanned aerial vehicle safety monitoring system proposed in an embodiment of the present invention includes: The first data acquisition module 301 is used to acquire the drone route; A data acquisition module 302 is used to acquire ground images in the route; The second data acquisition module 303 is used to acquire the flight information of the UAV; the flight information includes the current flight mileage, current position, flight speed and remaining mileage; The third data acquisition module 304 is used to obtain the current power consumption and remaining power of the main battery of the drone; A mileage calculation module 305 is used to determine the cruising range of the drone; The strategy formulation module 306 is used to determine the safe flight strategy.

[0070] See also Figure 5 , Figure 5 Schematic diagram of an electronic device provided by an embodiment of the present invention. Figure 5 As shown, an embodiment of the present invention provides an electronic device 400, including a memory 410, a processor 420, and a computer program 411 stored in the memory 410 and executable on the processor 420. When the processor 420 executes the computer program 411, the following steps are implemented: Get the flight route of the drone; collecting ground images in the flight route; Obtaining flight information of the drone; the flight information includes current flight mileage, current location, flight speed, and remaining mileage; Obtaining the current power consumption and remaining power of the main battery of the drone; Determining the range of the drone; Determine safe flight strategies.

[0071] See also Figure 6 , Figure 6 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present invention. Figure 6 As shown, this embodiment provides a computer-readable storage medium 500, on which a computer program 411 is stored. When the computer program 411 is executed by a processor, the following steps are implemented: Get the flight route of the drone; collecting ground images in the flight route; Obtaining flight information of the drone; the flight information includes current flight mileage, current location, flight speed, and remaining mileage; Obtaining the current power consumption and remaining power of the main battery of the drone; Determining the range of the drone; Determine safe flight strategies.

[0072] It should be noted that in the above embodiments, the description of each embodiment has its own emphasis, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0073] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded computer, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A system that specifies the functions of a box or boxes.

[0075] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction system, which is implemented in the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0077] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0078] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A drone safety monitoring method, characterized in that: The method comprises: Get the flight route of the drone; collecting ground images in the flight route; Obtaining flight information of the drone; the flight information includes current flight mileage, current location, flight speed, and remaining mileage; Obtaining the current power consumption and remaining power of the main battery of the drone; Determining the range of the drone; Determine safe flight strategies.

2. The drone safety monitoring method according to claim 1, characterized in that: Determining the cruising range of the drone includes: Determine the loss rate according to the current flight mileage and the current power consumption; The cruising range of the drone is determined according to the loss rate and the remaining power.

3. The drone safety monitoring method according to claim 2, characterized in that: The determining the loss rate according to the current flight mileage and the current power consumption includes: Calculate the actual unit energy consumption, where the actual unit energy consumption = current power consumption / current flight mileage; Get theoretical unit energy consumption; The loss rate is calculated, where the loss rate=actual unit energy consumption / theoretical unit energy consumption.

4. The drone safety monitoring method according to claim 3, characterized in that: Determining the cruising range of the drone according to the loss rate and the remaining power includes: Endurance mileage = remaining power / theoretical unit energy consumption*loss rate.

5. The drone safety monitoring method according to claim 1, characterized in that: The determining of the safe flight strategy includes: If the remaining mileage is greater than the endurance mileage, the total power of the backup battery of the drone is obtained; Determining the standby mileage according to the total power of the standby battery; Determining whether a temporary landing point needs to be selected according to the remaining mileage, the endurance mileage, and the spare mileage; If so, a temporary landing point is selected and a battery switching strategy is formulated.

6. The drone safety monitoring method according to claim 5, characterized in that: The step of determining the standby mileage according to the total power of the standby battery includes: Reserve mileage = total reserve battery capacity / theoretical unit energy consumption*loss rate.

7. The drone safety monitoring method according to claim 5, characterized in that: The determining whether a temporary landing point needs to be selected according to the remaining mileage, the endurance mileage, and the spare mileage includes: If the remaining mileage is greater than the sum of the endurance mileage and the reserve mileage, a temporary landing point needs to be selected.

8. The drone safety monitoring method according to claim 5, characterized in that: The step of selecting a temporary landing point comprises: Inputting the current position, the flight speed and the ground image into a landing point screening model to obtain a possible landing point position; The possible landing point locations are screened to determine a temporary landing point.

9. The drone safety monitoring method according to claim 8, characterized in that: After the temporary landing point is determined, the following steps are performed: Genetic algorithm is used to formulate battery switching strategy.

10. A drone safety monitoring system, characterized in that: The system comprises: A first data acquisition module is used to acquire the UAV route; A data acquisition module, used for acquiring ground images in the route; A second data acquisition module is used to acquire the flight information of the UAV; the flight information includes the current flight mileage, current position, flight speed and remaining mileage; A third data acquisition module is used to obtain the current power consumption and remaining power of the main battery of the drone; A mileage calculation module, used to determine the cruising range of the drone; Strategy formulation module, used to determine safe flight strategies.

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