Intelligent control method and device for rescue unmanned aerial vehicle carrying rescue net

Abstract

This invention discloses an intelligent control method and device for a rescue drone carrying a rescue net. The method includes: acquiring the position parameters of the object to be rescued, and performing flight control on the target drone carrying the rescue net based on its position parameters; during the flight control process, determining the position parameters of each target drone, and judging whether all target drones meet the hovering control conditions. If so, hovering control is performed on all target drones to receive the object to be rescued through the rescue net, and controlling all target drones to land the object to be rescued at the target location. Therefore, implementing this invention enables close-range rescue of the object to be rescued using rescue equipment through automatic drone control, which improves the reliability and accuracy of drone control, thereby improving the reliability and effectiveness of rescue operations, reducing the impact of rescue efforts, and ultimately ensuring the personal safety of the object to be rescued.

Description

Technical Field

[0001] This invention relates to the field of intelligent unmanned aerial vehicle (UAV) technology, and in particular to an intelligent control method and device for a rescue UAV carrying a rescue net. Background Technology

[0002] Rescue is the entire process by which people are rescued when they encounter disasters or emergencies. Timely and reliable rescue operations can minimize the consequences of accidents and protect the lives and property of those being rescued.

[0003] Currently, in rescue operations involving multi-story buildings, rescuers often place inflatable airbags at the base of the building to cushion the impact of rescuers jumping onto them. However, as building height increases, the cushioning effect of the airbags diminishes significantly during high-rise rescues. Furthermore, it becomes increasingly difficult for rescuers to accurately jump into the airbag's protective range, increasing the risk of injury and hindering the effective execution of the rescue operation. Therefore, providing a new rescue method to ensure the safety of those being rescued is crucial. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and device for intelligent control of a rescue drone carrying a rescue net, which can improve the reliability and accuracy of drone control, thereby improving the reliability and effectiveness of rescue of the target, reducing the impact of rescue, and thus helping to protect the personal safety of the target.

[0005] To address the aforementioned technical problems, the first aspect of this invention discloses an intelligent control method for a rescue drone carrying a rescue net, the method comprising:

[0006] When it is necessary to rescue a target, the first position parameter of the target is obtained, and flight control operations are performed on at least one target UAV used for rescue based on the first position parameter; all the target UAVs are equipped with rescue equipment.

[0007] During the execution of the flight control operation, the second position parameters of each target UAV are determined, and based on the second position parameters of all target UAVs, it is determined whether all target UAVs meet the preset hovering control conditions.

[0008] When the judgment result is yes, hovering control operation is performed on all the target drones so that the rescue equipment can receive the object to be rescued when all the target drones are in a hovering state.

[0009] Upon receiving the object to be rescued, all target drones are controlled to land at the target location according to preset placement parameters, so as to place the object to be rescued at the target location.

[0010] As an optional implementation, in the first aspect of the invention, the rescue equipment carried by all the target drones includes a rescue net;

[0011] Furthermore, the method further includes:

[0012] During the execution of the flight control operation, all the target drones are controlled to pull apart the rescue net;

[0013] During the process of opening the rescue net, the flight environment parameters of all the target UAVs and the target parameters of the rescue net are acquired; the flight environment parameters include at least one of the types of flight environment obstacles, the movement of flight environment obstacles, and the position parameters of flight environment obstacles; the target parameters of the rescue net include at least one of the mesh size parameters, the number of meshes parameters, the area of ​​the net opening surface parameters, and the relative position between the net opening surface and the flight environment obstacles.

[0014] Based on the flight environment parameters of all the target drones and the target parameters of the rescue network, obstacle avoidance operations are performed on all the target drones.

[0015] As an optional implementation, in the first aspect of the present invention, determining whether all the target drones meet the preset hovering control conditions based on the second position parameters of all the target drones includes:

[0016] Based on the second position parameters of all the target drones, determine the net opening surface of all the target drones relative to the rescue net; the net opening surface condition includes the net opening surface area parameter, the net opening surface tilt parameter, the net opening surface height position parameter, and the net opening surface horizontal position parameter;

[0017] Based on the net opening status of all the target drones towards the rescue network, determine whether the rescue network meets the preset object reception conditions for the object to be rescued;

[0018] When it is determined that the rescue network meets the object reception conditions for the object to be rescued, all the target drones are determined to meet the preset hovering control conditions.

[0019] As an optional implementation, in the first aspect of the present invention, determining whether the rescue network meets the preset object reception conditions for the object to be rescued based on the net opening status of all the target drones includes:

[0020] Based on the net opening surface area parameter and the net opening surface tilt parameter, it is determined whether the opening surface of the rescue net meets the preset opening surface receiving conditions; the opening surface receiving conditions include the opening surface area parameter threshold condition and the opening surface tilt parameter threshold condition;

[0021] When it is determined that the net opening surface meets the opening surface receiving conditions, the rescue environment parameters of the object to be rescued are determined, and based on the rescue environment parameters, it is determined whether the object to be rescued is located at a preset protruding building position;

[0022] When it is determined that the object to be rescued is not located at the protruding building, a first distance parameter between the object to be rescued and the first receiving position of the rescue net is determined based on the height position parameter of the net opening surface, the horizontal position parameter of the net opening surface, and the first position parameter; the first distance parameter includes a first horizontal distance parameter and / or a first vertical distance parameter.

[0023] Determine whether the first distance parameter is less than or equal to a preset first distance parameter threshold;

[0024] When it is determined that the first distance parameter is less than or equal to the first distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0025] As an optional implementation, in the first aspect of the present invention, the method further includes:

[0026] When it is determined that the object to be rescued is located at the protruding building, the position parameters of the bottom protruding edge of the protruding building where the object to be rescued is located are determined;

[0027] Based on the height position parameter of the net opening surface, the horizontal position parameter of the net opening surface, and the position parameter of the bottom protruding edge, a second distance parameter is determined between the position of the bottom protruding edge of the protruding building and the second receiving position of the rescue net for the object to be rescued; the second distance parameter includes a second horizontal distance parameter and / or a second vertical distance parameter;

[0028] Determine whether the second distance parameter is less than or equal to a preset second distance parameter threshold;

[0029] When it is determined that the second distance parameter is less than or equal to the second distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0030] As an optional implementation, in a first aspect of the invention, before performing flight control operations on at least one target UAV for rescue based on the first position parameter, the method further includes:

[0031] Determine the networking parameters corresponding to all target drones used for networking, and perform networking operations on the pre-loaded rescue network based on the networking parameters corresponding to all target drones;

[0032] The step of determining the networking parameters corresponding to all target drones used for networking, and performing networking operations on the pre-loaded rescue network based on the networking parameters corresponding to all target drones, includes:

[0033] The weight parameters of the object to be rescued are obtained, and the number of first drones used for networking is determined based on the weight parameters and the preset first drone load-bearing parameters; all first drones are drones that need to have load-bearing capabilities.

[0034] Based on the quantity parameters of all the first UAVs and the size parameters of the pre-loaded rescue network, determine the network spacing distance parameter between every two first UAVs, and determine whether the network spacing distance parameter is greater than or equal to a preset spacing distance parameter threshold.

[0035] When the judgment result is negative, the pre-loaded rescue network is networked according to the networking interval distance parameter between every two first UAVs;

[0036] When the judgment result is yes, the networking requirement parameters for all second drones used for networking are determined according to the networking interval distance parameter, the preset first drone rotation range parameter and the second drone rotation range parameter; all second drones are drones that do not need to have load-bearing function, and the networking requirement parameters include networking requirement quantity parameter and networking requirement interval parameter.

[0037] The pre-loaded rescue network is configured based on the networking interval distance parameter between every two first UAVs and the networking requirement parameters corresponding to all second UAVs.

[0038] As an optional implementation, in the first aspect of the present invention, after determining that the rescue network meets the object reception conditions for the object to be rescued, and before determining that all the target drones meet the preset hovering control conditions, the method further includes:

[0039] Determine the pre-hovering environment parameters for each target UAV; the pre-hovering environment parameters for each target UAV include the hovering distance parameter between the pre-hovering position of the target UAV and the building surface of the preset building and / or the object structure of the building surface;

[0040] Based on the pre-hovering environmental parameters of each target UAV and the rotation range of each target UAV, the pre-hovering hazard index corresponding to each target UAV is predicted, and it is determined whether the pre-hovering hazard index corresponding to all target UAVs is less than or equal to the preset hazard index threshold.

[0041] When it is determined that the pre-hovering hazard index of all the target drones is less than or equal to the hazard index threshold, it is determined that all the target drones meet the preset hovering control conditions.

[0042] A second aspect of the present invention discloses an intelligent control device for a rescue drone carrying a rescue net, the device comprising:

[0043] The acquisition module is used to acquire the first location parameters of the object to be rescued when it is necessary to rescue the object.

[0044] A control module is configured to perform flight control operations on at least one target drone for rescue purposes based on the first position parameters; all said target drones are equipped with rescue equipment.

[0045] The determination module is used to determine the second position parameters of each target UAV during the flight control operation performed by the control module;

[0046] The judgment module is used to determine whether all the target drones meet the preset hovering control conditions based on the second position parameters of all the target drones;

[0047] The control module is further configured to perform hovering control operations on all the target drones when the judgment module determines that the object to be rescued is in a hovering state, so as to receive the object to be rescued through the rescue equipment when all the target drones are in a hovering state; after receiving the object to be rescued, the control module controls all the target drones to land at the target position according to the preset placement position parameters, so as to place the object to be rescued at the target position.

[0048] As an optional implementation, in the second aspect of the invention, the rescue equipment carried by all the target drones includes a rescue net;

[0049] Furthermore, the control module is also used for:

[0050] During the execution of the flight control operation, all the target drones are controlled to pull apart the rescue net;

[0051] The acquisition module is further configured to acquire flight environment parameters of all target UAVs and target parameters of the rescue net during the process of the control module performing the opening operation on the rescue net; the flight environment parameters include at least one of the types of flight environment obstacles, the movement of flight environment obstacles, and the position parameters of flight environment obstacles; the target parameters of the rescue net include at least one of the mesh size parameters, the number of meshes, the area of ​​the net opening surface, and the relative position between the net opening surface and the flight environment obstacles.

[0052] The control module is also used to perform obstacle avoidance operations on all the target drones based on the flight environment parameters of all the target drones and the target parameters of the rescue network.

[0053] As an optional implementation, in a second aspect of the present invention, the determining module includes:

[0054] The determination submodule is used to determine the net opening surface of all the target drones relative to the rescue net based on the second position parameters of all the target drones; the net opening surface condition includes the net opening surface area parameter, the net opening surface tilt parameter, the net opening surface height position parameter, and the net opening surface horizontal position parameter;

[0055] The judgment submodule is used to determine whether the rescue network meets the preset object reception conditions for the object to be rescued based on the net opening status of all the target drones.

[0056] The determining submodule is further configured to determine that all target drones meet preset hovering control conditions when the judging module determines that the rescue network meets the object receiving conditions for the object to be rescued.

[0057] As an optional implementation, in a second aspect of the invention, the method by which the determining submodule determines whether the rescue network meets the preset object reception conditions for the object to be rescued based on the net opening status of all the target drones includes:

[0058] Based on the net opening surface area parameter and the net opening surface tilt parameter, it is determined whether the opening surface of the rescue net meets the preset opening surface receiving conditions; the opening surface receiving conditions include the opening surface area parameter threshold condition and the opening surface tilt parameter threshold condition;

[0059] When it is determined that the net opening surface meets the opening surface receiving conditions, the rescue environment parameters of the object to be rescued are determined, and based on the rescue environment parameters, it is determined whether the object to be rescued is located at a preset protruding building position;

[0060] When it is determined that the object to be rescued is not located at the protruding building, a first distance parameter between the object to be rescued and the first receiving position of the rescue net is determined based on the height position parameter of the net opening surface, the horizontal position parameter of the net opening surface, and the first position parameter; the first distance parameter includes a first horizontal distance parameter and / or a first vertical distance parameter.

[0061] Determine whether the first distance parameter is less than or equal to a preset first distance parameter threshold;

[0062] When it is determined that the first distance parameter is less than or equal to the first distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0063] As an optional implementation, in the second aspect of the present invention, the method by which the judging submodule judges whether the rescue network meets the preset object reception conditions for the object to be rescued based on the net opening status of all the target drones on the rescue network specifically includes:

[0064] When it is determined that the object to be rescued is located at the protruding building, the position parameters of the bottom protruding edge of the protruding building where the object to be rescued is located are determined;

[0065] Based on the height position parameter of the net opening surface, the horizontal position parameter of the net opening surface, and the position parameter of the bottom protruding edge, a second distance parameter is determined between the position of the bottom protruding edge of the protruding building and the second receiving position of the rescue net for the object to be rescued; the second distance parameter includes a second horizontal distance parameter and / or a second vertical distance parameter;

[0066] Determine whether the second distance parameter is less than or equal to a preset second distance parameter threshold;

[0067] When it is determined that the second distance parameter is less than or equal to the second distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0068] As an optional implementation, in a second aspect of the invention, the apparatus further includes:

[0069] The networking module is used to determine the networking parameters corresponding to all target drones for networking before the control module performs flight control operations on at least one target drone for rescue based on the first position parameters, and to perform networking operations on the pre-loaded rescue network based on the networking parameters corresponding to all the target drones.

[0070] The networking module determines the networking parameters corresponding to all target drones used for networking, and performs networking operations on the pre-loaded rescue network based on the networking parameters corresponding to all target drones in the following specific manner:

[0071] The weight parameters of the object to be rescued are obtained, and the number of first drones used for networking is determined based on the weight parameters and the preset first drone load-bearing parameters; all first drones are drones that need to have load-bearing capabilities.

[0072] Based on the quantity parameters of all the first UAVs and the size parameters of the pre-loaded rescue network, determine the network spacing distance parameter between every two first UAVs, and determine whether the network spacing distance parameter is greater than or equal to a preset spacing distance parameter threshold.

[0073] When the judgment result is negative, the pre-loaded rescue network is networked according to the networking interval distance parameter between every two first UAVs;

[0074] When the judgment result is yes, the networking requirement parameters for all second drones used for networking are determined according to the networking interval distance parameter, the preset first drone rotation range parameter and the second drone rotation range parameter; all second drones are drones that do not need to have load-bearing function, and the networking requirement parameters include networking requirement quantity parameter and networking requirement interval parameter.

[0075] The pre-loaded rescue network is configured based on the networking interval distance parameter between every two first UAVs and the networking requirement parameters corresponding to all second UAVs.

[0076] As an optional implementation, in a second aspect of the invention, the determining submodule is further configured to:

[0077] After the judgment submodule determines that the rescue network meets the object reception conditions for the object to be rescued, and before determining that all the target drones meet the preset hovering control conditions, the pre-hovering environment parameters of each target drone are determined; the pre-hovering environment parameters of each target drone include the hovering distance parameter between the pre-hovering position of the target drone and the building surface of the preset building and / or the object structure of the building surface;

[0078] Furthermore, the determination module also includes:

[0079] The prediction submodule is used to predict the pre-hovering hazard index of each target UAV based on the pre-hovering environmental parameters of each target UAV and the rotation range of each target UAV.

[0080] The judgment submodule is also used to determine whether the pre-hovering danger index corresponding to all the target drones is less than or equal to the preset danger index threshold.

[0081] The determining submodule is further configured to determine that all target drones meet the preset hovering control conditions when the judging submodule determines that the pre-hovering hazard index of all target drones is less than or equal to the hazard index threshold.

[0082] A third aspect of the present invention discloses another intelligent control device for a rescue drone carrying a rescue net, the device comprising:

[0083] Memory containing executable program code;

[0084] A processor coupled to the memory;

[0085] The processor calls the executable program code stored in the memory to execute the intelligent control method for a rescue drone carrying a rescue network disclosed in the first aspect of the present invention.

[0086] The fourth aspect of the present invention discloses a computer storage medium storing computer instructions, which, when invoked, are used to execute the intelligent control method for a rescue drone carrying a rescue network disclosed in the first aspect of the present invention.

[0087] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:

[0088] In this embodiment of the invention, when a rescue operation is required for a target, its first position parameter is acquired, and flight control is performed on the target drone carrying the rescue net based on the first position parameter. During flight control, a second position parameter is determined for each target drone, and it is used to determine whether all target drones meet preset hovering control conditions. If so, hovering control is performed on all target drones to receive the target through the rescue net they carry, and all target drones are controlled to land and place the target at the target location. Therefore, implementing this invention enables close-range rescue of targets using rescue equipment through the automatic control of drones. This improves the reliability and accuracy of controlling drones carrying rescue nets, thereby improving the reliability and effectiveness of rescue operations, reducing the impact of rescue efforts, and ultimately ensuring the safety of the target. Simultaneously, it also improves the efficiency of rescue operations, facilitating timely rescue and ensuring the smooth progress of rescue work. Attached Figure Description

[0089] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0090] Figure 1 This is a schematic diagram of a networking method for a rescue drone disclosed in an embodiment of the present invention;

[0091] Figure 2 This is a schematic diagram of a rescue process using a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention.

[0092] Figure 3 This is a flowchart illustrating an intelligent control method for a rescue drone carrying a rescue network, as disclosed in an embodiment of the present invention.

[0093] Figure 4 This is a flowchart illustrating another intelligent control method for a rescue drone carrying a rescue network, as disclosed in an embodiment of the present invention.

[0094] Figure 5 This is a schematic diagram of the structure of an intelligent control device for a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention.

[0095] Figure 6 This is a schematic diagram of another intelligent control device for a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention.

[0096] Figure 7This is a schematic diagram of the structure of another intelligent control device for a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention;

[0097] Figure 8 This is a schematic diagram of the networking connection of a rescue drone disclosed in an embodiment of the present invention. Detailed Implementation

[0098] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0099] The terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, apparatus, product, or end that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or ends.

[0100] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0101] This invention discloses an intelligent control method and device for a rescue drone carrying a rescue net, which can improve the reliability and accuracy of drone control, thereby improving the reliability and effectiveness of rescue of the target, reducing the impact of rescue, and thus helping to protect the personal safety of the target.

[0102] Example 1

[0103] Please see Figure 3 , Figure 3 This is a flowchart illustrating an intelligent control method for a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention. Figure 3The described intelligent control method for rescue drones carrying rescue nets can be applied to rescue targets at preset heights, such as people in buildings, mountains, etc., and this embodiment of the invention is not limited to this. Optionally, this method can be implemented by a drone control system, which can be integrated into a drone control device, or it can be a local server or cloud server used to process the rescue control process of the drone carrying rescue equipment, etc., and this embodiment of the invention is not limited to this. Figure 3 As shown, the intelligent control method for the rescue drone carrying the rescue net can include the following operations:

[0104] 101. When it is necessary to rescue a target, obtain the first position parameters of the target and perform flight control operations on at least one target UAV used for rescue based on the first position parameters.

[0105] In this embodiment of the invention, all target drones carry rescue equipment. Optionally, the object to be rescued may be a person, animal, or other person at a height. Further optionally, the first position parameter of the object to be rescued may include its altitude and / or horizontal position parameters. Still further optionally, all target drones may include multiple load-bearing drones, or multiple load-bearing drones and multiple obstacle-avoiding drones specifically designed to assist in pulling rescue equipment (which do not have load-bearing capabilities). It should be noted that the load-bearing drones can also be used to pull rescue equipment and also have obstacle-avoidance capabilities, and the sum of the load-bearing parameters of all load-bearing drones must be greater than or equal to the weight parameter of the object to be rescued.

[0106] 102. During the execution of flight control operations, determine the second position parameters of each target UAV, and based on the second position parameters of all target UAVs, determine whether all target UAVs meet the preset hovering control conditions.

[0107] In this embodiment of the invention, all target drones can be controlled to move up and down or left and right in a cluster manner. Optionally, the second position parameter of each target drone may include its altitude position parameter and / or horizontal position parameter. Further, determining whether all target drones meet the preset hovering control conditions based on the second position parameters of all target drones can be understood as predicting whether the rescue equipment carried by all target drones can be used to safely receive the object to be rescued when they are hovering, and whether all target drones are in a safe hovering environment, based on the second position parameters of all target drones. Similarly, the second position parameters of all target drones can be determined by using a cluster algorithm to calculate the relative positions of other target drones after the binocular camera on one of the target drones detects its own position; at the same time, the relative position between each target drone and the object to be rescued can also be calculated.

[0108] 103. When the judgment result is yes, perform hovering control operation on all target drones so that the rescue equipment can receive the target to be rescued when all target drones are in a hovering state.

[0109] In this embodiment of the invention, the object to be rescued can be brought to safety by carrying rescue equipment while all target drones are hovering. Optionally, the rescue equipment may include rescue nets, rescue bags, rescue rope ladders, etc., and the number of rescue equipment can be determined based on the weight parameters of the object to be rescued, and there may be one or more (e.g., using two overlapping rescue nets to receive the object to be rescued to increase the stress on the nets). Furthermore, when it is determined that all target drones do not meet the preset hovering control conditions, flight control operations are continued for all target drones. Furthermore, during the hovering control operation for all target drones, if it is necessary to ensure that all target drones are at the same horizontal altitude, RTK (Real-time kinematic) carrier phase differential technology can be used.

[0110] 104. Upon receiving the object to be rescued, control all target drones to land at the target location according to the preset placement parameters, so as to place the object to be rescued at the target location.

[0111] In an embodiment of the present invention, for example, if the rescue equipment carried by all target drones is a rescue net, after the object to be rescued falls into the rescue net, all target drones can be controlled to retract the rescue net to maximize the load-bearing capacity of all load-bearing drones. According to the preset placement parameters, all target drones can be controlled to perform landing operations to place the object to be rescued in a safe location.

[0112] It is evident that implementing the embodiments of the present invention enables the use of rescue equipment at close range through the automatic control of drones to rescue those in need of rescue. This improves the reliability and accuracy of controlling drones carrying rescue nets, thereby enhancing the reliability and effectiveness of rescue efforts, reducing the impact of rescue operations, and ultimately ensuring the personal safety of those in need of rescue. Simultaneously, it also improves the efficiency of rescue operations, facilitating timely rescue and ensuring the smooth progress of rescue work.

[0113] In an optional embodiment, the method further includes:

[0114] During the flight control operation, control all target drones to pull apart the rescue network;

[0115] During the deployment of the rescue network, flight environment parameters of all target drones and target parameters of the rescue network are acquired.

[0116] Based on the flight environment parameters of all target drones and the target parameters of the rescue network, perform obstacle avoidance operations on all target drones.

[0117] In this optional embodiment, the rescue equipment carried by all target drones may include a rescue net. That is, during the ascent phase of remote control of rescue from a high-rise building, all target drones can fully extend the net together to achieve the maximum rescue reception area. At the same time, it is also necessary to control all target drones to avoid obstacles in the flight environment to prevent the rescue net from colliding with the building surface or structural objects (such as windowsills, green plants, etc.) or other flying objects in the flight environment.

[0118] Optionally, the flight environment parameters include at least one of the following: obstacle type, obstacle movement, and obstacle position. The identification of these parameters can be achieved using technologies such as obstacle avoidance radar, structured light scanning, ultrasonic ranging, TOF ranging (time-of-flight ranging), and binocular ranging possessed by the target UAV. Further, the target parameters of the rescue net include at least one of the following: net mesh size, mesh count, net open area, and the relative position of the net open area to the obstacle. In other words, by combining the target parameters of the rescue net, all-around obstacle avoidance control of the target UAV can be achieved, preventing the rescue net from colliding with obstacles.

[0119] As can be seen, this optional embodiment can perform obstacle avoidance operations on the target UAV carrying the rescue net based on the flight environment parameters of the target UAV and the target parameters of the rescue net. In this way, obstacle avoidance can be performed in all directions during the flight control of the target UAV, which helps to improve the reliability and accuracy of the obstacle avoidance operation of the target UAV, thereby reducing the occurrence of accidents during the flight of the target UAV and improving the safety of the flight control of the target UAV, thus facilitating the smooth progress of the target UAV rescue operation.

[0120] In another optional embodiment, step 102 above, determining whether all target drones meet the preset hovering control conditions based on the second position parameters of all target drones, includes:

[0121] Based on the second position parameters of all target drones, determine the net opening of all target drones relative to the rescue net;

[0122] Based on the deployment of the rescue network by all target drones, determine whether the rescue network meets the preset target reception conditions for the target being rescued;

[0123] When it is determined that the rescue network meets the conditions for receiving the target drone, it determines that all target drones meet the preset hovering control conditions.

[0124] In this optional embodiment, hovering conditions are issued once all target drones have towed the rescue net to a safe altitude and the rescue net can safely receive the object to be rescued. Optionally, the net opening surface status includes parameters such as net opening surface area, net opening surface tilt, net opening surface height, and net opening surface horizontal position. The net opening surface area and tilt parameters can be used to determine whether the rescue net has sufficient receiving area and whether it can stably receive the object to be rescued, preventing the object from falling. The net opening surface height and horizontal position parameters can be used to determine whether the rescue net is close enough to receive the object to be rescued. Furthermore, if it is determined that the rescue net does not meet the object receiving conditions, then it is determined that all target drones do not meet the preset hovering control conditions, and flight control of all target drones continues.

[0125] As can be seen, this optional embodiment can intelligently determine whether the rescue net can receive the target object based on the net's deployment status (i.e., traction status) of the target UAV. This helps improve the reliability and accuracy of the rescue net's object reception condition determination operation, which in turn helps improve the reliability and accuracy of the target UAV's hovering control operation. This, in turn, helps improve the reliability, accuracy, and effectiveness of the rescue net in receiving the target object, thus ensuring the smooth reception of the target object by the rescue net.

[0126] In another optional embodiment, the step of determining whether the rescue network meets the preset target reception conditions based on the net deployment status of all target drones includes:

[0127] Based on the net opening area parameters and net opening inclination parameters, determine whether the net opening surface of the rescue net meets the preset opening surface receiving conditions;

[0128] When it is determined that the net opening surface meets the opening surface receiving conditions, the rescue environment parameters of the object to be rescued are determined, and based on the rescue environment parameters, it is determined whether the object to be rescued is located at the preset protruding building position;

[0129] When it is determined that the object to be rescued is not located in a protruding building, the first distance parameter between the object to be rescued and the first receiving position of the rescue net is determined based on the height position parameter of the net opening face, the horizontal position parameter of the net opening face, and the first position parameter.

[0130] Determine whether the first distance parameter is less than or equal to a preset first distance parameter threshold;

[0131] When it is determined that the first distance parameter is less than or equal to the first distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0132] In this optional embodiment, when the object to be rescued is on a rooftop rather than in a protruding structure such as a balcony, the target drone can be controlled to pull the rescue net to a position close to the rooftop below the object. Optionally, the opening surface reception conditions include an opening surface area parameter threshold condition and an opening surface tilt parameter threshold condition. Further, the determination of the first distance parameter between the object to be rescued and the first reception position of the rescue net can be achieved by target tracking and positioning of the object to be rescued using a binocular camera or a TOF camera configured on the target drone, wherein the first distance parameter may include a first horizontal distance parameter and / or a first vertical distance parameter. Furthermore, when it is determined that the opening surface of the net does not meet the opening surface reception conditions, or when it is determined that the first distance parameter is greater than a preset first distance parameter threshold, it can be determined that the rescue net does not meet the preset object reception conditions for the object to be rescued.

[0133] Specifically, the tracking process for the object to be rescued can be as follows: The target (i.e., the object to be rescued) is outlined using the camera configured on the target drone, and the target features are calculated using a deep learning target recognition network (such as RCNN, YOLO, etc.). Then, a target tracking network (such as optical flow, Deep Sort, etc.) is used to track the target. Taking a binocular camera as an example, assuming the binocular camera is mounted on the load-bearing drone 1, the coordinates of the load-bearing drone 1 are defined as the origin of a three-dimensional coordinate system. Based on this, the target's coordinate position and the first distance parameter between the target and the first receiving position of the rescue net are calculated. Furthermore, this first receiving position can be understood as the middle position of the rescue net edge near the object to be rescued (i.e., the side against the wall), to ensure that the object to be rescued is unlikely to fall out of the rescue net's range.

[0134] As can be seen, this optional embodiment can determine whether the target drone is close enough to receive the target by considering the rescue environment in which the target is located. This enriches the intelligent rescue control method for the target drone, improves the reliability and accuracy of the operation to determine the target receiving conditions of the rescue network, and thus improves the reliability and effectiveness of subsequent rescue of the target, thereby ensuring the personal safety of the target.

[0135] In yet another optional embodiment, the method further includes:

[0136] When it is determined that the object to be rescued is located in the position of a protruding building, determine the position parameters of the bottom protruding edge of the protruding building where the object to be rescued is located;

[0137] Based on the height position parameters of the net opening face, the horizontal position parameters of the net opening face, and the position parameters of the bottom protruding edge, determine the second distance parameter between the position of the bottom protruding edge of the protruding building and the second receiving position of the rescue net for the object to be rescued;

[0138] Determine whether the second distance parameter is less than or equal to a preset second distance parameter threshold;

[0139] When it is determined that the second distance parameter is less than or equal to the second distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0140] In this optional embodiment, such as Figure 2 As shown, Figure 2This is a schematic diagram of a rescue process using a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention. When the person to be rescued is located in a protruding building such as a balcony, the target drone can be controlled to pull the rescue net to the area below the balcony (as shown in the position of rescue net 2). This ensures that the person to be rescued can land in the second receiving position of the rescue net (i.e., the center position of the rescue net). Compared to the receiving position of rescue net 1 (i.e., pulled to the edge near the balcony), the receiving position of rescue net 2 better ensures that the person to be rescued will not fall out of the rescue net's range. The second receiving position of the rescue net can be understood as the center position of the rescue net, and the parameter of the protruding edge position of the bottom of the protruding building can be understood as, for example, the edge of the balcony is 1.5 meters away from the wall of the building, etc.

[0141] Optionally, the second distance parameter includes a second horizontal distance parameter and / or a second vertical distance parameter. Further, when it is determined that the second distance parameter is greater than a preset second distance parameter threshold, the camera on the target drone can automatically identify and locate it, and fine-tune its flight position to accurately position the rescue net directly below the protruding building where the object to be rescued is located, until the second distance parameter is less than or equal to the second distance parameter threshold, thereby ensuring that the object to be rescued is unlikely to fall out of the rescue net's range. Further, when it is determined that the second distance parameter is greater than the second distance parameter threshold, it can be determined that the rescue net does not meet the preset object reception conditions for the object to be rescued.

[0142] As can be seen, this optional embodiment can control the target drone to pull the rescue net to a safer receiving position based on the rescue environment of the object to be rescued. This helps to improve the reliability and accuracy of the rescue net pulling control operation of the target drone, thereby improving the reliability and effectiveness of the rescue of the object to be rescued, and thus helping to achieve safe rescue work for the object to be rescued.

[0143] In yet another optional embodiment, after determining that the rescue network meets the target reception conditions for the target drones, and before determining that all target drones meet the preset hovering control conditions, the method further includes:

[0144] Determine the pre-hovering environment parameters for each target drone;

[0145] Based on the pre-hovering environmental parameters and rotation range of each target drone, predict the pre-hovering hazard index corresponding to each target drone, and determine whether the pre-hovering hazard index corresponding to all target drones is less than or equal to the preset hazard index threshold.

[0146] When it is determined that the pre-hovering hazard index of all target drones is less than or equal to the hazard index threshold, it is determined that all target drones meet the preset hovering control conditions.

[0147] In this optional embodiment, the pre-hovering environment parameters for each target UAV may include the hovering distance parameter between the pre-hovering position of the target UAV and the building surface of a preset building and / or the object structure of the building surface. The object structure of the building surface can be understood as whether the building wall has windowsills, potted plants, curtains, etc.

[0148] Furthermore, when it is determined that the pre-hovering hazard index of all target drones is not less than or equal to the hazard index threshold, all drones to be adjusted whose pre-hovering hazard index is greater than the hazard index threshold are selected from all target drones. Based on the pre-hovering environmental parameters and rotation range of each drone to be adjusted, the pre-hovering position of all drones to be adjusted is adjusted until the pre-hovering hazard index of all target drones is less than or equal to the hazard index threshold.

[0149] For example, to ensure the normal operation of the rescue net, it is necessary to hover the target drone close to the building wall while preventing other objects on the building from contacting the rescue net or the target drone. This can be illustrated using binocular stereo imaging technology: all target drones are equipped with binocular cameras to acquire real-time images of the outer edge of the rescue net and calculate stereo images in real time. When the image predicts that the distance between the target drone hovering and the edge of the rescue net is too small (i.e., the pre-hovering danger index exceeds a preset danger index threshold), a surface fitting can be performed on the distance to the outer edge of the wall (at the same height as the rescue net), and one or more target drones in the rescue net can be moved towards the outer edge of the wall to ensure that the outer edge of the rescue net does not rub against or collide with the outer edge of the wall when the target drone hovers.

[0150] As can be seen, this optional embodiment can further determine whether the target UAV meets the hovering control conditions based on the pre-hovering environment parameters of the target UAV, which can further improve the reliability and accuracy of the hovering control condition determination operation of the target UAV, so as to ensure the subsequent hovering safety of the target UAV, thereby improving the reliability and effectiveness of the rescue work for the rescued object, so as to enable the rescue work to proceed smoothly and ensure the personal safety of the rescued object.

[0151] Example 2

[0152] Please see Figure 4 , Figure 4 This is a flowchart illustrating an intelligent control method for a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention. Figure 4The described intelligent control method for rescue drones carrying rescue nets can be applied to rescue targets at preset heights, such as people in buildings, mountains, etc., and this embodiment of the invention is not limited to this. Optionally, this method can be implemented by a drone control system, which can be integrated into a drone control device, or it can be a local server or cloud server used to process the rescue control process of the drone carrying rescue equipment, etc., and this embodiment of the invention is not limited to this. Figure 4 As shown, the intelligent control method for the rescue drone carrying the rescue net can include the following operations:

[0153] 201. When it is necessary to rescue a person, obtain the first location parameters of the person to be rescued.

[0154] 202. Determine the networking parameters for all target drones used for networking, and perform networking operations on the pre-loaded rescue network based on the networking parameters for all target drones.

[0155] In this embodiment of the invention, the rescue net towing position corresponding to each target drone is determined.

[0156] As an optional implementation, the networking parameters corresponding to all target drones used for networking are determined, and the pre-loaded rescue network is networked based on the networking parameters corresponding to all target drones, including:

[0157] Obtain the weight parameters of the object to be rescued, and determine the number of all first drones used for networking based on the weight parameters and the preset first drone load-bearing parameters;

[0158] Based on the number parameters of all first UAVs and the size parameters of the pre-loaded rescue network, determine the network spacing distance parameter between every two first UAVs, and determine whether the network spacing distance parameter is greater than or equal to the preset spacing distance parameter threshold.

[0159] When the judgment result is negative, the pre-loaded rescue network is networked according to the networking interval distance parameter between every two first UAVs;

[0160] When the judgment result is yes, the networking requirement parameters corresponding to all second drones used for networking are determined based on the networking interval distance parameter, the preset first drone rotation range parameter and the second drone rotation range parameter.

[0161] The pre-loaded rescue network is configured based on the networking interval distance between every two first UAVs and the networking requirement parameters corresponding to all second UAVs.

[0162] In this optional embodiment, specifically, all first drones are drones that need to have load-bearing capabilities, and all second drones are drones that do not need to have load-bearing capabilities (i.e., obstacle avoidance drones specifically used for towing rescue nets). Optionally, the networking requirement parameters include networking requirement quantity parameters and networking requirement interval parameters. It should be noted that, as Figure 8 As shown, Figure 8 This is a schematic diagram of a network connection for a rescue drone disclosed in an embodiment of the present invention. The networking operation of the pre-bearing rescue network can be understood as a physical connection, that is, all target drones are connected to the intermediate rescue network; at the same time, it can also be understood as an algorithmic or communication connection, that is, the interaction process between all networked target drones during networking.

[0163] For example, when rescuing an 80kg target, the total load capacity of all first drones (i.e., the load-bearing drones) must exceed 80kg. This might require four or more drones with a load capacity of 20kg each. After determining the number of first drones, it's necessary to assess whether the distance between any two drones is too large. If so, second drones are needed to assist in traction within the rescue network, maximizing its coverage area and ensuring the safety of the target. Simultaneously, the safe distance between each second drone and other drones (i.e., the distance between any two drones must be greater than the drone's rotation range, such as 1 meter) and the required number of second drones between any two first drones must be determined. The specific networking method can be as follows: Figure 1 -A is shown ( Figure 1 This is a schematic diagram of a network formation method for rescue drones disclosed in an embodiment of the present invention; if the interval between any two first drones is not too large, then the rescue network towing assistance of the second drones is not required, and the first drones can be used entirely for network towing (e.g., Figure 1 -B shows that each first drone has a load capacity of 6.7 kg. In summary, based on the weight parameters of the object to be rescued, multiple first drones for load-bearing can be determined first. The more drones there are, the smaller the required load capacity can be. Then, based on the networking of the first drones, it can be determined whether additional second drones are needed for rescue network towing assistance. If so, multiple second drones specifically for towing can be added between every two networked first drones to achieve a safer networking method. If not, the first drones can be used directly for networking.

[0164] 203. Based on the first position parameters, perform flight control operations on all target UAVs used for rescue.

[0165] 204. During the execution of flight control operations, determine the second position parameters of each target UAV, and based on the second position parameters of all target UAVs, determine whether all target UAVs meet the preset hovering control conditions.

[0166] 205. When the judgment result is yes, perform hovering control operation on all target drones so that the rescue target can be received through the rescue network it carries while all target drones are in a hovering state.

[0167] 206. After receiving the object to be rescued, control all target drones to land at the target location according to the preset placement parameters, so as to place the object to be rescued at the target location.

[0168] In this embodiment of the invention, for other descriptions of steps 201 and steps 203-206, please refer to the detailed description of steps 101-104 in Embodiment 1. This embodiment of the invention will not repeat them.

[0169] As can be seen, implementing the embodiments of the present invention can determine the networking method for rescue in a targeted manner based on the weight parameters of the object to be rescued and the networking status of the first UAV. This can improve the reliability and accuracy of the networking operation of the rescue network, thereby improving the networking security performance of the rescue network. As a result, the rescue network can be used to achieve reliable, effective and safe reception of the object to be rescued.

[0170] Example 3

[0171] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of an intelligent control device for a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention. Figure 5 As shown, the intelligent control device for the rescue drone carrying the rescue net may include:

[0172] The acquisition module 301 is used to acquire the first position parameters of the object to be rescued when it is necessary to rescue the object.

[0173] Control module 302 is used to perform flight control operations on at least one target drone for rescue purposes based on the first position parameters;

[0174] The determination module 303 is used to determine the second position parameters of each target UAV during the flight control operation performed by the control module;

[0175] The judgment module 304 is used to determine whether all target drones meet the preset hovering control conditions based on the second position parameters of all target drones.

[0176] The control module 302 is also used to perform hovering control operations on all target drones when the judgment result of the judgment module 304 is yes, so as to receive the object to be rescued through the rescue equipment when all target drones are in a hovering state; after receiving the object to be rescued, it controls all target drones to land at the target position according to the preset placement position parameters, so as to place the object to be rescued at the target position.

[0177] In this embodiment of the invention, all target drones are equipped with rescue equipment.

[0178] It is evident that implementation Figure 5 The described intelligent control device for rescue drones carrying rescue nets enables close-range rescue operations using rescue equipment via automatic drone control. This improves the reliability and accuracy of controlling the drones carrying rescue nets, thereby enhancing the reliability and effectiveness of rescue efforts, reducing the impact of rescue operations, and ultimately ensuring the safety of those in need. Simultaneously, it also increases the efficiency of rescue operations, facilitating timely rescue and ensuring the smooth progress of rescue work.

[0179] In an optional embodiment, the control module 302 is further configured to:

[0180] During the flight control operation, control all target drones to pull apart the rescue network;

[0181] The acquisition module 301 is also used to acquire the flight environment parameters of all target UAVs and the target parameters of the rescue network during the process of the control module 302 performing the opening operation on the rescue network;

[0182] The control module 302 is also used to perform obstacle avoidance operations on all target drones based on the flight environment parameters of all target drones and the target parameters of the rescue network.

[0183] In this optional embodiment, the rescue equipment carried by all target UAVs includes a rescue net; the flight environment parameters include at least one of the following: the type of flight environment obstacle, the movement of the flight environment obstacle, and the position parameters of the flight environment obstacle; the target parameters of the rescue net include at least one of the following: the mesh size parameter, the number of meshes parameter, the area parameter of the net opening surface, and the relative position of the net opening surface with respect to the flight environment obstacle.

[0184] It is evident that implementation Figure 6The described intelligent control device for rescue drones carrying rescue nets can perform obstacle avoidance operations on the target drones based on the flight environment parameters of the target drones and the target parameters of the rescue nets. This allows for all-round obstacle avoidance during the flight control of the target drones, which helps improve the reliability and accuracy of the obstacle avoidance operations, reduces the occurrence of accidents during flight, and improves the safety of flight control, thus facilitating the smooth progress of the rescue work.

[0185] In another optional embodiment, the determination module 304 includes:

[0186] The determination submodule 3041 is used to determine the net opening of all target drones to the rescue net based on the second position parameters of all target drones;

[0187] The judgment submodule 3042 is used to determine whether the rescue network meets the preset object reception conditions based on the net opening status of all target drones to the rescue network.

[0188] The determination submodule 3041 is also used to determine that all target drones meet the preset hovering control conditions when the judgment module determines that the rescue network meets the object reception conditions for the target drones to be rescued.

[0189] In this optional embodiment, the net opening surface parameters include net opening surface area parameters, net opening surface tilt parameters, net opening surface height position parameters, and net opening surface horizontal position parameters.

[0190] It is evident that implementation Figure 6 The described intelligent control device for rescue drones carrying rescue nets can intelligently determine whether the rescue net can receive the target drone based on the net's opening position (i.e., its traction). This improves the reliability and accuracy of the rescue net's target drone reception condition determination, which in turn improves the reliability and accuracy of the target drone's hovering control. Ultimately, this enhances the reliability, accuracy, and effectiveness of the rescue net in receiving the target drone, ensuring its successful reception.

[0191] In another optional embodiment, the determination submodule 3042 determines whether the rescue network meets the preset object reception conditions based on the net deployment status of all target drones. Specifically, this includes:

[0192] Based on the net opening area parameters and net opening inclination parameters, determine whether the net opening surface of the rescue net meets the preset opening surface receiving conditions;

[0193] When it is determined that the net opening surface meets the opening surface receiving conditions, the rescue environment parameters of the object to be rescued are determined, and based on the rescue environment parameters, it is determined whether the object to be rescued is located at the preset protruding building position;

[0194] When it is determined that the object to be rescued is not located in a protruding building, the first distance parameter between the object to be rescued and the first receiving position of the rescue net is determined based on the height position parameter of the net opening face, the horizontal position parameter of the net opening face, and the first position parameter.

[0195] Determine whether the first distance parameter is less than or equal to a preset first distance parameter threshold;

[0196] When it is determined that the first distance parameter is less than or equal to the first distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0197] In this optional embodiment, the face-opening receiving conditions include a face-opening area parameter threshold condition and a face-opening tilt parameter threshold condition; the first distance parameter includes a first horizontal distance parameter and / or a first vertical distance parameter.

[0198] It is evident that implementation Figure 6 The described intelligent control device for rescue drones carrying rescue nets can determine whether the target drone is close enough to receive the target by considering the rescue environment. This enriches the intelligent rescue control methods for target drones, improves the reliability and accuracy of the operation to determine the target's reception conditions, and thus improves the reliability and effectiveness of subsequent rescue efforts, thereby ensuring the personal safety of the target.

[0199] In another optional embodiment, the method by which the judgment submodule 3041 determines whether the rescue network meets the preset object reception conditions based on the net deployment status of all target drones to the rescue network specifically includes:

[0200] When it is determined that the object to be rescued is located in the position of a protruding building, determine the position parameters of the bottom protruding edge of the protruding building where the object to be rescued is located;

[0201] Based on the height position parameters of the net opening face, the horizontal position parameters of the net opening face, and the position parameters of the bottom protruding edge, determine the second distance parameter between the position of the bottom protruding edge of the protruding building and the second receiving position of the rescue net for the object to be rescued;

[0202] Determine whether the second distance parameter is less than or equal to a preset second distance parameter threshold;

[0203] When it is determined that the second distance parameter is less than or equal to the second distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

[0204] In this optional embodiment, the second distance parameter includes a second horizontal distance parameter and / or a second vertical distance parameter.

[0205] It is evident that implementation Figure 6 The described intelligent control device for rescue drones carrying rescue nets can selectively control the target drone to pull the rescue net to a safer receiving position based on the rescue environment of the target. This improves the reliability and accuracy of the rescue net pulling control operation of the target drone, thereby improving the reliability and effectiveness of the rescue of the target and facilitating the safe rescue of the target.

[0206] In yet another optional embodiment, the device further includes:

[0207] The networking module 305 is used to determine the networking parameters corresponding to all target drones for networking before the control module 302 performs flight control operations on at least one target drone for rescue based on the first position parameters, and to perform networking operations on the pre-loaded rescue network based on the networking parameters corresponding to all target drones.

[0208] Specifically, the networking module 305 determines the networking parameters corresponding to all target UAVs used for networking, and performs networking operations on the pre-loaded rescue network based on the networking parameters corresponding to all target UAVs as follows:

[0209] Obtain the weight parameters of the object to be rescued, and determine the number of all first drones used for networking based on the weight parameters and the preset first drone load-bearing parameters;

[0210] Based on the number parameters of all first UAVs and the size parameters of the pre-loaded rescue network, determine the network spacing distance parameter between every two first UAVs, and determine whether the network spacing distance parameter is greater than or equal to the preset spacing distance parameter threshold.

[0211] When the judgment result is negative, the pre-loaded rescue network is networked according to the networking interval distance parameter between every two first UAVs;

[0212] When the judgment result is yes, the networking requirement parameters corresponding to all second drones used for networking are determined based on the networking interval distance parameter, the preset first drone rotation range parameter and the second drone rotation range parameter.

[0213] The pre-loaded rescue network is configured based on the networking interval distance between every two first UAVs and the networking requirement parameters corresponding to all second UAVs.

[0214] In this optional embodiment, all first drones are drones that need to have load-bearing capabilities; all second drones are drones that do not need to have load-bearing capabilities; and the networking requirement parameters include networking requirement quantity parameters and networking requirement interval parameters.

[0215] It is evident that implementation Figure 6 The described intelligent control device for rescue drones carrying a rescue network can determine the appropriate networking method for rescue based on the weight parameters of the object to be rescued and the networking status of the first drone. This improves the reliability and accuracy of the network operation of the rescue network, thereby enhancing the network security performance of the rescue network. As a result, the rescue network enables reliable, effective, and safe reception of the object to be rescued.

[0216] In yet another optional embodiment, the determining submodule 3041 is further configured to:

[0217] After the judgment submodule 3042 determines that the rescue network meets the target reception conditions, and before determining that all target drones meet the preset hovering control conditions, the pre-hovering environment parameters of each target drone are determined.

[0218] In addition, the judgment module 304 also includes:

[0219] The prediction submodule 3043 is used to predict the pre-hovering hazard index of each target UAV based on the pre-hovering environmental parameters of each target UAV and the rotation range of each target UAV.

[0220] The judgment submodule 3042 is also used to determine whether the pre-hovering hazard index corresponding to all target drones is less than or equal to the preset hazard index threshold.

[0221] The determining submodule 3041 is also used to determine that all target drones meet the preset hovering control conditions when the judging submodule 3042 determines that the pre-hovering hazard index of all target drones is less than or equal to the hazard index threshold.

[0222] In this optional embodiment, the pre-hovering environment parameters for each target UAV include the hovering distance parameter between the pre-hovering position of the target UAV and the building surface of a preset building and / or the object structure of the building surface.

[0223] It is evident that implementation Figure 6The described intelligent control device for rescue drones carrying rescue nets can further determine whether the target drone meets the hovering control conditions based on the pre-hovering environment parameters. This can further improve the reliability and accuracy of the hovering control condition determination operation for the target drone, thereby ensuring the subsequent hovering safety of the target drone. In turn, it can improve the reliability and effectiveness of the rescue work for the rescued object, so that the rescue work can be carried out smoothly and the personal safety of the person to be rescued can be guaranteed.

[0224] Example 4

[0225] Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of another intelligent control device for a rescue drone carrying a rescue net, as disclosed in an embodiment of the present invention. Figure 7 As shown, the intelligent control device for the rescue drone carrying the rescue net may include:

[0226] Memory 401 storing executable program code;

[0227] Processor 402 coupled to memory 401;

[0228] The processor 402 calls the executable program code stored in the memory 401 to execute the steps in the intelligent control method for a rescue drone carrying a rescue net as described in Embodiment 1 or Embodiment 2 of the present invention.

[0229] Example 5

[0230] This invention discloses a computer storage medium storing computer instructions. When these computer instructions are invoked, they are used to execute the steps in the intelligent control method for a rescue drone carrying a rescue net, as described in Embodiment 1 or Embodiment 2 of this invention.

[0231] Example 6

[0232] This invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the steps in the intelligent control method for a rescue drone carrying a rescue net as described in Embodiment 1 or Embodiment 2.

[0233] The device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0234] Through the detailed description of the above embodiments, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0235] Finally, it should be noted that the intelligent control method and device for a rescue drone carrying a rescue net disclosed in the embodiments of the present invention are merely preferred embodiments of the present invention and are only used to illustrate the technical solutions of the present invention, not to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for intelligent control of a rescue drone carrying a rescue net, characterized in that, The method includes: When it is necessary to rescue a target, the first position parameter of the target is obtained, and flight control operations are performed on at least one target UAV used for rescue based on the first position parameter; all the target UAVs are equipped with rescue equipment. During the execution of the flight control operation, the second position parameters of each target UAV are determined, and based on the second position parameters of all target UAVs, it is determined whether all target UAVs meet the preset hovering control conditions. When the judgment result is yes, hovering control operation is performed on all the target drones so that the rescue equipment can receive the object to be rescued when all the target drones are in a hovering state. Upon receiving the object to be rescued, all the target drones are controlled to land at the target location according to the preset placement parameters, so as to place the object to be rescued at the target location; Before performing flight control operations on at least one target UAV for rescue based on the first position parameter, the method further includes: The weight parameters of the object to be rescued are obtained, and the number of first drones used for networking is determined based on the weight parameters and the preset first drone load-bearing parameters; all first drones are drones that need to have load-bearing capabilities. Based on the quantity parameters of all the first UAVs and the size parameters of the pre-loaded rescue network, determine the network spacing distance parameter between every two first UAVs, and determine whether the network spacing distance parameter is greater than or equal to a preset spacing distance parameter threshold. If not, then the pre-loaded rescue network is networked according to the networking interval distance parameter between every two first UAVs; If so, then based on the network interval distance parameter, the preset first UAV rotation range parameter and the second UAV rotation range parameter, determine the network requirement parameters corresponding to all second UAVs used for networking; all second UAVs are UAVs that do not need to have load-bearing function, and the network requirement parameters include the network requirement quantity parameter and the network requirement interval parameter. The pre-loaded rescue network is configured based on the networking interval distance parameter between every two first UAVs and the networking requirement parameters corresponding to all second UAVs.

2. The intelligent control method for a rescue drone carrying a rescue net according to claim 1, characterized in that, The rescue equipment carried by all the target drones includes rescue nets; Furthermore, the method further includes: During the execution of the flight control operation, all the target drones are controlled to pull apart the rescue net; During the process of opening the rescue net, the flight environment parameters of all the target UAVs and the target parameters of the rescue net are acquired; the flight environment parameters include at least one of the types of flight environment obstacles, the movement of flight environment obstacles, and the position parameters of flight environment obstacles; the target parameters of the rescue net include at least one of the mesh size parameters, the number of meshes parameters, the area of ​​the net opening surface parameters, and the relative position between the net opening surface and the flight environment obstacles. Based on the flight environment parameters of all the target drones and the target parameters of the rescue network, obstacle avoidance operations are performed on all the target drones.

3. The intelligent control method for a rescue drone carrying a rescue net according to claim 2, characterized in that, The step of determining whether all the target drones meet the preset hovering control conditions based on the second position parameters of all the target drones includes: Based on the second position parameters of all the target drones, determine the net opening surface of all the target drones relative to the rescue net; the net opening surface condition includes the net opening surface area parameter, the net opening surface tilt parameter, the net opening surface height position parameter, and the net opening surface horizontal position parameter; Based on the net opening status of all the target drones towards the rescue network, determine whether the rescue network meets the preset object reception conditions for the object to be rescued; When it is determined that the rescue network meets the object reception conditions for the object to be rescued, all the target drones are determined to meet the preset hovering control conditions.

4. The intelligent control method for a rescue drone carrying a rescue net according to claim 3, characterized in that, The step of determining whether the rescue network meets the preset object reception conditions for the object to be rescued based on the net deployment status of all the target drones includes: Based on the net opening surface area parameter and the net opening surface tilt parameter, it is determined whether the opening surface of the rescue net meets the preset opening surface receiving conditions; the opening surface receiving conditions include the opening surface area parameter threshold condition and the opening surface tilt parameter threshold condition; When it is determined that the net opening surface meets the opening surface receiving conditions, the rescue environment parameters of the object to be rescued are determined, and based on the rescue environment parameters, it is determined whether the object to be rescued is located at a preset protruding building position; When it is determined that the object to be rescued is not located at the protruding building, a first distance parameter between the object to be rescued and the first receiving position of the rescue net is determined based on the height position parameter of the net opening surface, the horizontal position parameter of the net opening surface, and the first position parameter; the first distance parameter includes a first horizontal distance parameter and / or a first vertical distance parameter. Determine whether the first distance parameter is less than or equal to a preset first distance parameter threshold; When it is determined that the first distance parameter is less than or equal to the first distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

5. The intelligent control method for a rescue drone carrying a rescue net according to claim 4, characterized in that, The method further includes: When it is determined that the object to be rescued is located at the protruding building, the position parameters of the bottom protruding edge of the protruding building where the object to be rescued is located are determined; Based on the height position parameter of the net opening surface, the horizontal position parameter of the net opening surface, and the position parameter of the bottom protruding edge, a second distance parameter is determined between the position of the bottom protruding edge of the protruding building and the second receiving position of the rescue net for the object to be rescued; the second distance parameter includes a second horizontal distance parameter and / or a second vertical distance parameter; Determine whether the second distance parameter is less than or equal to a preset second distance parameter threshold; When it is determined that the second distance parameter is less than or equal to the second distance parameter threshold, it is determined that the rescue network meets the preset object reception conditions for the object to be rescued.

6. The intelligent control method for a rescue drone carrying a rescue net according to any one of claims 3-5, characterized in that, After determining that the rescue network meets the target reception conditions for the object to be rescued, and before determining that all the target drones meet the preset hovering control conditions, the method further includes: Determine the pre-hovering environment parameters for each target UAV; the pre-hovering environment parameters for each target UAV include the hovering distance parameter between the pre-hovering position of the target UAV and the building surface of the preset building and / or the object structure of the building surface; Based on the pre-hovering environmental parameters of each target UAV and the rotation range of each target UAV, the pre-hovering hazard index corresponding to each target UAV is predicted, and it is determined whether the pre-hovering hazard index corresponding to all target UAVs is less than or equal to the preset hazard index threshold. When it is determined that the pre-hovering hazard index of all the target drones is less than or equal to the hazard index threshold, it is determined that all the target drones meet the preset hovering control conditions.

7. An intelligent control device for a rescue drone carrying a rescue net, characterized in that, The device is used to execute the intelligent control method for a rescue drone carrying a rescue net as described in any one of claims 1-6, and the device comprises: The acquisition module is used to acquire the first location parameters of the object to be rescued when it is necessary to rescue the object. A control module is configured to perform flight control operations on at least one target drone for rescue purposes based on the first position parameters; all said target drones are equipped with rescue equipment. The determination module is used to determine the second position parameters of each target UAV during the flight control operation performed by the control module; The judgment module is used to determine whether all the target drones meet the preset hovering control conditions based on the second position parameters of all the target drones; The control module is further configured to perform hovering control operations on all the target drones when the judgment module determines that the object to be rescued is in a hovering state, so as to receive the object to be rescued through the rescue equipment when all the target drones are in a hovering state; after receiving the object to be rescued, the control module controls all the target drones to land at the target position according to the preset placement position parameters, so as to place the object to be rescued at the target position.

8. An intelligent control device for a rescue drone carrying a rescue net, characterized in that, The device includes: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the intelligent control method for a rescue drone carrying a rescue net as described in any one of claims 1-6.

9. A computer storage medium, characterized in that, The computer storage medium stores computer instructions, which, when invoked, are used to execute the intelligent control method for a rescue drone carrying a rescue net as described in any one of claims 1-6.

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