Intelligent unmanned aerial vehicle bomb delivery system and delivery method

Abstract

The application provides an intelligent unmanned aerial vehicle bomb dropping system and a dropping method, wherein a control part receives image information and position information fed back by a carrying part and a bomb dropping part, provides manual control information to control the flight track and the hiding place of the carrying part and the flight timing and the bomb dropping timing of the bomb dropping part; the carrying part carries the bomb dropping part, controls the flight state according to the self control information or the manual control information, autonomously plans the route, carries the bomb dropping part to the designated place, and feeds back the image information and the position information in real time, and supplies power for the carrying part and the bomb dropping part; the bomb dropping part executes the cruise attack task according to the self control information or the manual control information according to the set track, and feeds back the image information and the position information in real time; when the target is not found, the bomb dropping part returns to the carrying part to charge according to the control information, and waits for the next cruise attack task. The application improves the long time and long distance combat capability of the unmanned aerial vehicle bomb dropping system, and improves the target attack level.

Description

Technical Field

[0001] This invention relates to the field of unmanned aerial vehicle (UAV) coordinated control and precision guidance technology, specifically to an intelligent UAV bomb delivery system and method capable of long-duration, long-range, controllable, and automatically target-identifying operations. Background Technology

[0002] With the continuous development of drone technology, drone bomb delivery has been widely used in the military field. Compared with traditional bomb delivery systems, drone bomb delivery systems have advantages such as accuracy and flexibility. However, drones need to carry bombs, and with current battery capabilities and considering costs, their endurance is difficult to guarantee for completing long-duration or long-range combat missions.

[0003] The search revealed:

[0004] Chinese utility model patent CN206351780U, entitled "A Drone Carrier Based on a Ground Station and a Helium Balloon," describes a drone carrier that uses a helium balloon as a carrier to connect drones to the balloon. Power is supplied to the drones via a generator or power grid, enhancing their endurance and enabling long-endurance low-altitude flight operations. However, if this drone carrier is applied to a bomb delivery system, the following technical problems will arise:

[0005] First, the helium balloon and the ground station are connected together, and the balloon is bound to the ground station, making it unable to fly to distant places. The ground station is mounted on a vehicle, which is difficult to adapt to complex geographical environments, and it is impossible to carry the helium balloon and the drones it carries to the enemy and patrol.

[0006] Second, the drones on this drone carrier are connected to helium balloons and cannot stray far from the helium balloons, thus making it impossible to conduct long-distance patrols and launch precise attacks against designated targets.

[0007] Third, the drone carrier lacks remote control capabilities, making it unable to remotely operate or respond promptly to real-time changes in battlefield conditions. Summary of the Invention

[0008] To address the aforementioned shortcomings in existing technologies, this invention provides an intelligent unmanned aerial vehicle (UAV) bomb delivery system and method. This system uses a flying balloon as a carrier to transport UAVs for combat, enabling long-term concealment and remote control, allowing for precise target strikes and better completion of combat missions.

[0009] According to one aspect of the present invention, an intelligent unmanned aerial vehicle (UAV) bomb delivery system is provided, comprising: a control unit, a carrying unit, and a bomb delivery unit; wherein:

[0010] The control unit is used to receive image information and position information fed back by the transport unit and the bombing unit, and based on the image information and position information, to provide manual control information for controlling the flight trajectory and hiding place of the transport unit and the flight timing and bombing timing of the bombing unit.

[0011] The carrier unit is used to carry the bomb-dropping unit, controls its own flight status according to its own control information or received manual control information, autonomously plans its flight path, carries the bomb-dropping unit to the designated location, and provides real-time image and location information; at the same time, it supplies power to itself and the bomb-dropping unit.

[0012] The bomb-dropping unit, based on its own control information or received manual control information, reaches the target location according to its autonomously planned trajectory to perform a cruise attack mission, and provides real-time feedback of image and location information; when it fails to find the target, it returns to the carrier unit to recharge based on its own control information, waiting for the next cruise attack mission.

[0013] Preferably, the control unit is located at a ground station and includes a console; the console receives image and location information transmitted from the transport unit and the bombing unit in real time via wireless communication, generates manual control information based on the image and location information, and then transmits it to the transport unit and the bombing unit through the console.

[0014] Preferably, in the control section, generating manual control information based on the image information and location information includes:

[0015] The image information and location information are processed; wherein, the processing of the image information includes: image denoising, enhancement, and feature extraction; the processing of the location information includes: coordinate transformation and coordinate system matching;

[0016] The processed image information and location information are fused together to associate the position of the target object in the image with its position in the real world;

[0017] The fused information is analyzed, including target recognition, target classification, trajectory prediction, and environmental perception, to obtain the analysis results;

[0018] Based on the analysis results, corresponding manual control information is generated, including path planning, flight attitude adjustment, and target tracking commands, to guide the behavior of the delivery and bombing components.

[0019] Preferably, the carrying unit includes: a flight unit, a navigation unit, a communication unit, a computing unit, a power supply unit, and a docking unit; wherein:

[0020] The flight unit includes a flight balloon and a propulsion device; wherein the flight balloon is used to provide the buoyancy required for flight; and the propulsion device is used to provide the power required for traveling along a trajectory.

[0021] The navigation unit includes a GPS, an inertial navigation system, and a camera; wherein, the GPS is used for real-time positioning; the inertial navigation system is used to control the stability and accuracy of the flight of the flight unit; and the camera is used to obtain real-time image information.

[0022] The communication section includes a wireless communication module; wherein the wireless communication module is used to transmit information with the control section in real time.

[0023] The computing unit includes a small computing unit; wherein the small computing unit is used to control the flight status of the flight unit through its own control information or manual control information transmitted from the control unit, and to automatically plan the flight path based on the target information and the built-in atmospheric circulation data.

[0024] The power supply unit includes a solar panel and a battery, which are used to supply power to the carrier section and the bomb-dropping section.

[0025] The docking unit includes a drone nest for storing and releasing drones; the drone nest is equipped with a charging interface that is connected to the power supply unit and used for charging the drones.

[0026] Preferably, the computing unit generates its own control information and target information based on the acquired real-time image information and location information, including:

[0027] The acquired real-time image and location information are preprocessed;

[0028] The preprocessed image information and location information are fused to associate the position of the target object in the image with its position in the real world;

[0029] The fused information is analyzed, including target recognition, target classification, trajectory prediction, and environmental perception, to obtain the analysis results;

[0030] Based on the analysis results, corresponding self-control information and target information are generated;

[0031] Automatic flight path planning based on the target information and built-in atmospheric circulation data, including:

[0032] Based on built-in atmospheric circulation data and target information, the optimal flight path is determined; at the same time, an optimization algorithm is used to update the flight path in real time according to weather changes.

[0033] Preferably, the bomb-dropping section includes: a drone and a bomb-dropper unit; wherein:

[0034] The drone includes a GPS, a camera, and a wireless communication module; wherein, the GPS is used for real-time positioning; the camera is used to obtain real-time image information; and the wireless communication module is used to transmit information with the control unit in real time.

[0035] The bomber unit is used to load bombs and execute attack missions against target information based on its own control information or manual control information transmitted from the control unit.

[0036] Preferably, in the bomber unit, self-control information and target information are generated based on the acquired real-time image information and location information, including: initiating AI visual guidance to find the target based on the acquired real-time image information and location information, obtaining target information, and generating first self-control information to control the bomber part to carry out the attack mission based on the found target information; when the AI ​​visual guidance to find the target fails, second self-control information is generated to control the bomber part to return to the carrier part for charging, waiting for the next cruise attack mission.

[0037] Preferably, the step of initiating AI visual guidance to find the target based on the acquired real-time image information and location information includes:

[0038] The acquired real-time image information is preprocessed, including: resizing, denoising, and contrast enhancement;

[0039] The YOLOv8 model is used to identify target objects in the preprocessed image information and classify them to obtain target information;

[0040] A target tracking algorithm is used to track the movement trajectory of the target information, and path planning is performed based on the acquired real-time location information, the detected target information, and the target location;

[0041] Based on the path planning results, a corresponding first self-control command is generated to guide and track the target.

[0042] Preferably, it further includes:

[0043] The generated first self-control command is fed back to the carrier unit as a reference for the carrier unit to readjust its course, speed, or attitude.

[0044] According to another aspect of the present invention, a method for delivering intelligent drone bombs is provided, comprising:

[0045] The control section of the intelligent drone bomb delivery system acquires image and location information from the carrying and bomb-dropping sections of the intelligent drone bomb delivery system, and provides manual control information.

[0046] The control unit sends the manual control information to the transport unit and the bombing unit to control the flight trajectory and ambush location of the transport unit, as well as the flight timing and bombing timing of the bombing unit.

[0047] The carrier unit controls its own flight status based on its own control information or the manual control information it receives, autonomously plans its route, carries the bombing unit to the designated location, and provides real-time feedback of image and location information, while supplying power to itself and the bombing unit.

[0048] The bombing unit executes cruise attack missions according to its own control information or received manual control information, following an autonomously planned trajectory, and provides real-time feedback of image and location information. When it fails to find a target, it returns to the carrier unit to recharge based on its own control information, awaiting the next cruise attack mission.

[0049] By adopting the above technical solution, the present invention has at least one of the following beneficial effects compared with the prior art:

[0050] The intelligent drone bomb delivery system and method provided by this invention uses a flying balloon as a transport device, which can realize long-range attack of the bomb delivery system.

[0051] The intelligent drone bomb delivery system and method provided by this invention uses solar power for the carrier and has the function of charging the drone, which solves the problem of short drone endurance in bomb delivery systems and enables long-term cruise strikes.

[0052] The intelligent drone bomb delivery system and method provided by this invention uses solar power for the carrier and also has the functions of target detection and communication with ground stations, which can enable long-term reconnaissance and lurking in enemy territory.

[0053] The intelligent drone bomb delivery system and method provided by this invention have built-in atmospheric circulation data in the carrying unit, which can autonomously plan the flight path and accurately reach the target point based on the given GPS coordinates.

[0054] The intelligent unmanned aerial vehicle (UAV) bomb delivery system and method provided by this invention can add manual control function to the control part on the basis of autonomous control of the carrying part and the bomb delivery part, thereby enhancing the mobility of the bomb delivery system. Attached Figure Description

[0055] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0056] Figure 1 This is a schematic diagram of the architecture of an intelligent drone bomb delivery system in a preferred embodiment of the present invention.

[0057] Figure 2 This is a schematic diagram of the operation of an intelligent drone bomb delivery system in a preferred embodiment of the present invention.

[0058] Figure 3 This is a flowchart illustrating the process of a preferred embodiment of the intelligent drone bomb delivery method of the present invention.

[0059] Figure 4 This is a schematic diagram of the carrier unit detecting the target and deploying a drone to perform an attack mission in a preferred embodiment of the present invention.

[0060] Figure 5 This is a schematic diagram of a preferred embodiment of the present invention, showing the deployment of a drone by the carrier unit to perform a patrol and attack mission. Detailed Implementation

[0061] The embodiments of the present invention are described in detail below: These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention.

[0062] Given the current level of battery and drone technology, drone-based bomb delivery systems generally suffer from poor endurance due to cost considerations, making long-range operations difficult and hindering their ability to remain infiltrated near enemy territory to find suitable opportunities for attack. To address this issue, one embodiment of this invention provides an intelligent drone bomb delivery system. This system uses a balloon as the drone's transport vehicle, with the drone carrying missiles to strike targets. The balloon transports the drone over long distances, and based on given GPS signals and built-in atmospheric circulation data, it autonomously plans its flight path, accurately reaching the designated target location. It can also remain infiltrated near enemy territory for extended periods to find opportunities, while a ground station controls the drone to launch the attack. This significantly enhances the long-range, long-duration combat capability of the drone bomb delivery system and improves target engagement effectiveness.

[0063] Specifically, such as Figure 1 As shown, the intelligent drone bomb delivery system provided in this embodiment may include: a control unit, a carrying unit, and a bomb delivery unit; wherein:

[0064] The control section is used to receive image and position information from the transport and bombing sections. Based on the image and position information, the personnel can provide manual control information (which may include manual control commands and / or manual target information) to control the flight trajectory and hiding place of the transport section and the flight and bombing timing of the bombing section.

[0065] The transport unit carries the bomb-dropping unit. It controls its own flight status based on its own control information or received manual control information, autonomously plans its flight path, carries the bomb-dropping unit to the designated location, and provides real-time image and location information; at the same time, it supplies power to itself and the bomb-dropping unit.

[0066] The bombing section, based on its own control information or received manual control information, reaches the target location according to its autonomously planned trajectory to carry out the cruise attack mission, and provides real-time feedback of image and location information; when it fails to find the target, it returns to the carrier section to recharge based on its own control information, and waits for the next cruise attack mission.

[0067] In some preferred embodiments, the control unit is located at a ground station and includes a control console. The control console receives image and location information transmitted from the transport unit and the bombing unit in real time via wireless communication. The staff can generate manual control information based on the image and location information and then transmit it to the transport unit and the bombing unit through the control console.

[0068] In some preferred embodiments, the above-mentioned control console, which generates manual control information based on image information and location information, may further include:

[0069] The analysis of image and location information includes: processing the acquired image information, including image denoising, enhancement, and feature extraction; and processing the acquired location information, including coordinate transformation and coordinate system matching.

[0070] The processed image information and location information are fused together to associate the position of the target object in the image with its position in the real world;

[0071] Further analysis is performed using the fused information, including target recognition, target classification, trajectory prediction, and environmental perception, to obtain deeper information and analytical results.

[0072] Finally, based on the analysis results of image and position information, corresponding manual control information is generated. This control information includes manual control commands, such as path planning, flight attitude adjustment, target tracking commands, and / or manual target information, which are used to guide the behavior of the delivery and bombing sections.

[0073] In some preferred embodiments, the aforementioned carrying unit includes: a flight unit, a navigation unit, a communication unit, a computing unit, a power supply unit, and a docking unit; wherein:

[0074] The flight unit includes a flight balloon and a propulsion system; the flight balloon provides the buoyancy required for flight; and the propulsion system provides the power required for following the trajectory.

[0075] The navigation unit includes GPS, an inertial navigation system, and a camera; GPS is used for real-time positioning; the inertial navigation system is used to control the stability and accuracy of the flight unit's flight; and the camera is used to obtain real-time video information (and thus real-time image information) to help the ground station make decisions.

[0076] The communication section includes a wireless communication module; the wireless communication module is used to transmit information with the control section in real time, thereby better controlling the activities of the carrier section.

[0077] The computing unit includes a small computing unit; wherein, the small computing unit is used to control the flight status of the flight unit through its own control information or manual control information transmitted from the control unit, and automatically plan the route based on the target information and the built-in atmospheric circulation data.

[0078] The power supply unit includes solar panels and batteries, which are used to power the carrier and bomb-dropping sections.

[0079] The docking unit includes a drone nest for storing and releasing drones, and a built-in charging interface that connects to the power supply unit to charge the drones.

[0080] In some preferred embodiments, the above-mentioned computing unit, which generates its own control information and target information based on the acquired real-time image information and location information, may further include:

[0081] The acquired real-time image information and location information are preprocessed; the preprocessing of the acquired image information includes operations such as image denoising, enhancement, and feature extraction, and the preprocessing of the acquired location information includes operations such as coordinate transformation and coordinate system matching.

[0082] The preprocessed image information and location information are fused to associate the position of the target object in the image with its position in the real world;

[0083] The fused information is analyzed, including target recognition, target classification, trajectory prediction, and environmental perception, to obtain the analysis results;

[0084] Based on the analysis results, corresponding self-control information and target information are generated. Self-control information includes commands such as path planning, flight attitude adjustment, and target tracking.

[0085] In some preferred embodiments, the above-mentioned calculation unit, which automatically plans the flight path based on the target information and built-in atmospheric circulation data, may further include:

[0086] The system automatically plans flight routes based on atmospheric circulation data and target information to determine the optimal route. Simultaneously, it utilizes optimization algorithms to update the flight path in real time according to weather changes.

[0087] Furthermore, the automatic route planning, based on atmospheric circulation data and target information, determines the optimal route and can further include steps such as acquiring meteorological information, setting targets, preprocessing data, selecting planning algorithms, generating routes, evaluating and adjusting, and outputting results. Simultaneously, optimization algorithms can be used to update the route path in real time according to weather changes. Among these steps:

[0088] Meteorological Information Acquisition: Utilizing data from the built-in atmospheric circulation model (global weather model or local weather station), meteorological variables, including wind speed, wind direction, temperature, humidity, and air pressure, are acquired in real time. This step provides environmental background data for the entire system, and subsequent target setting and data processing rely on this information. Meteorological data serves as an important reference when planning flight routes, influencing target setting and the criteria for route selection.

[0089] Setting Objectives: Based on mission requirements, clearly define the destination and specific requirements (flight altitude, time constraints, energy consumption, etc.). Setting clear objectives helps with subsequent data preprocessing and planning steps, ensuring that the route design meets mission requirements. Objective setting will influence subsequent route selection and planning schemes. For example, the urgency of the mission may necessitate prioritizing faster routes.

[0090] Data preprocessing: The acquired meteorological data and target information are cleaned, standardized, and filtered. Noise and irrelevant data are removed to better facilitate subsequent analysis. Data quality is optimized to improve the effectiveness of data analysis and model application in later steps. Preprocessed data directly impacts the quality of route generation decisions; poor data can lead to inaccurate planning.

[0091] Choosing a planning scheme: Based on meteorological conditions and mission requirements, select an appropriate route planning model or algorithm (such as shortest path solution, genetic algorithm, particle swarm optimization, etc.). The chosen algorithm will affect the efficiency and effectiveness of route generation. It is closely related to meteorological data and target information, ensuring that the selected method can reflect the impact of meteorological changes on the route in real time.

[0092] Flight Route Generation: Using the selected planning algorithm, preprocessed meteorological data and set target information are input into the model to generate the optimal flight route. The output flight route in this stage directly depends on all previous data and planning steps, and the generated route should meet the set targets and meteorological conditions. The generated flight route should have a certain degree of flexibility to allow for improvement in subsequent evaluation and adjustments.

[0093] Evaluation and Adjustment: The generated flight routes are evaluated, taking into account multiple factors such as weather conditions, flight safety, energy consumption, and mission completion. Adjustments or replanning may be made as necessary. Evaluation results may lead to route optimization, and feedback information will be used to improve the accuracy of the algorithm model, thereby enhancing future planning efficiency. Adjustments to flight routes based on evaluation results can be fed back to the data source, providing a reference for future weather analysis and target setting.

[0094] Execution Results: The payload unit executes the flight path based on the final route and related information. The output route provides the payload unit with a clear flight path, guiding it to complete the mission. The output route can also be stored as data for subsequent analysis and model improvement.

[0095] Real-time updates: By combining weather changes with real-time data stream monitoring, optimization algorithms (such as dynamic programming and reinforcement learning) are used to update flight paths. Real-time updates enable the system to respond quickly to environmental changes, ensuring flight safety and mission efficiency. Timely adjustments to flight paths will affect the execution of subsequent flight missions. The update results can be compared with historical data to analyze the impact of weather changes on flight path selection and further optimize the planning model.

[0096] In some preferred embodiments, the bombing portion includes: a drone and a bomber unit; wherein:

[0097] The drone includes GPS, a camera, and a wireless communication module; GPS is used for real-time positioning; the camera is used to obtain real-time video information (and thus real-time image information); and the wireless communication module is used to transmit information with the control unit in real time.

[0098] The bomber unit is used to load bombs and execute attack missions based on control information or manual input from the control unit, targeting specific targets.

[0099] In some preferred embodiments, the bomb dispenser unit generates its own control information and target information based on the acquired real-time image information and position information, including:

[0100] Based on the real-time video (image) information fed back by the bomb-dropping unit's camera and the real-time location information fed back by GPS, the AI ​​vision guidance is activated to find the target, obtain the target information, and generate the first self-control information to control the bomb-dropping unit to carry out the attack mission based on the found target information; if the AI ​​vision guidance fails to find the target, the second self-control information is generated to control the bomb-dropping unit to return to the carrier unit for charging, waiting for the next cruise attack mission.

[0101] In some preferred embodiments, the above-mentioned activation of AI visual guidance to find the target based on the acquired real-time image information and location information may further include:

[0102] The acquired real-time image information is preprocessed, including resizing, noise reduction, and contrast enhancement, to ensure that the image quality is good enough for subsequent processing.

[0103] The YOLOv8 algorithm model is used to identify target objects in images and classify them to obtain target information.

[0104] The target tracking algorithm is used to track the movement trajectory of the target information, and to make decisions based on the acquired real-time location information, detected target information and target position, including path planning, such as determining the next action or path planning, so as to guide the device or robot to move towards the target;

[0105] Based on the decision results, corresponding first self-control commands are generated, including steering angle, speed control, obstacle avoidance strategies, etc., to guide and track the target.

[0106] In the preferred embodiments described above, the following may further be included:

[0107] The generated first self-control command is transmitted to the bombing section to execute corresponding actions, such as adjusting the course, speed, or attitude to guide and track the target; or, the generated first self-control command is transmitted to the delivery section as a reference for the delivery section to readjust its course, speed, or attitude.

[0108] In the preferred embodiment described above, the transport unit carries the bombing unit, which can reach a designated location to release the bombing unit to launch an attack mission, or fly a long distance to the vicinity of the target area to carry out ambush or patrol missions, thereby reconnoitering the enemy's situation and waiting for an opportunity to launch an attack.

[0109] In this preferred embodiment, the UAV can receive control information and target information from the control unit, and conduct flight patrol and reconnaissance according to a set trajectory. Based on the target found by AI vision guidance, it will carry out an attack mission on the target. If the AI ​​vision guidance fails to find the target, it will return to the carrier unit to recharge according to the control information and wait for the next patrol and attack mission.

[0110] like Figure 2As shown, the intelligent drone bomb delivery system provided in the above embodiments of the present invention has a control unit, i.e., a ground station, that remains on our side. The transport unit flies to or near the target area, and the bombing unit performs a patrol and attack mission in the target area. Under the control of the ground station or its own program, and in conjunction with atmospheric circulation data, the transport unit's balloon can autonomously plan its route, carry the bombing drone to the target area and directly release the drone to perform the attack mission, or patrol near the target area, release the drone to the target point for reconnaissance, use a camera to detect the target, and launch a precise and rapid attack once the target is found or controlled by the ground station. If the drone does not find the target, it can return to the balloon to recharge. The balloon can then carry the drone to other target areas for patrol and ambush under the control of the ground station, and release the drone to launch the next round of attacks.

[0111] Based on the same inventive concept, an embodiment of the present invention also provides a method for intelligent drone bomb delivery.

[0112] Specifically, such as Figure 3 As shown, the intelligent drone bomb delivery method provided in this embodiment may include the following operations:

[0113] S1, the carrier unit controls its own flight status according to its own control commands or received manual control information, autonomously plans its route, carries the bombing unit to the designated location, and provides real-time feedback of image and location information, while supplying power to itself and the bombing unit.

[0114] S2: The bombing unit executes the cruise attack mission according to its own control information or the received manual control information, and provides real-time feedback of image and position information; if it fails to find the target, it returns to the carrier unit to recharge according to its own control information and waits for the next cruise attack mission.

[0115] S3, the control unit acquires image and position information from the transport and bombing units and provides manual control information;

[0116] S4, the control unit sends manual control information to the transport and bombing units to manually intervene and control the flight trajectory and ambush location of the transport unit, as well as the flight and bombing timing of the bombing unit.

[0117] It should be noted that the steps in the method provided by the present invention can be implemented using corresponding modules, devices, units, etc. in the system. Those skilled in the art can refer to the technical solution of the system to implement the steps and flow of the method. That is, the embodiments in the system can be understood as preferred examples of the method, and will not be elaborated here.

[0118] The technical solution provided by the above embodiments of the present invention will be further described in detail below with reference to a specific application example.

[0119] Specific application example 1

[0120] like Figure 4 As shown, after the delivery unit reaches the target point based on the built-in atmospheric circulation data, when the camera of the delivery unit detects the target, it dispatches a corresponding drone carrying bombs to launch a precise and rapid attack mission on the target. The drone is equipped with a camera that can detect and follow the target. The ground station can also issue commands to control the drone to launch an attack on the target.

[0121] Specific application example 2:

[0122] like Figure 5 As shown, the delivery unit lies in wait near the enemy. The drone cruises along a certain trajectory according to the instructions of the ground station. If a target is detected, it tracks and approaches the target to launch a suicide attack. If no target is detected, it returns to the delivery unit to recharge and waits for the next opportunity to cruise and attack.

[0123] The intelligent drone bomb delivery system and delivery method provided in the above embodiments of the present invention equip the bomb delivery part based on the drone with a transport device, which can bring the drone to the vicinity of the target area at a low cost and realize long-distance strike missions.

[0124] The intelligent drone bomb delivery system and method provided in the above embodiments of the present invention have a carrier device powered by solar energy and capable of charging drones, similar to a flying drone nest. This allows drones to cruise and operate in the target area for extended periods. If no target is found, the drone can return to the carrier device to recharge before launching the next cruise and attack mission.

[0125] The intelligent drone bomb delivery system and method provided in the above embodiments of the present invention have a delivery device that provides power to the drone, detects targets, and communicates with a ground station. It is itself a continuously operating cruise device, which is something other cruise drones cannot do. If the delivery device detects a target, it can dispatch the drone to launch a precise and rapid attack mission.

[0126] The intelligent drone bomb delivery system and delivery method provided in the above embodiments of the present invention allow the carrier equipment to automatically plan its flight path to the target point based on the given GPS signal location and the built-in atmospheric circulation data, release the drone to find the target, and perform the attack mission.

[0127] The intelligent drone bomb delivery system and method provided in the above embodiments of the present invention have a control section that can provide remote manual operation function, thereby improving the mobility of the bomb delivery system.

[0128] In summary, the intelligent drone bomb delivery system and method provided in the above embodiments of the present invention can achieve functions such as long-range attack, long-term patrol or ambush, background control, and automatic target recognition, overcoming the problems of existing drone bomb delivery systems having short attack range, short endurance, and inability to conduct long-term reconnaissance.

[0129] Any matters not covered in the above embodiments of the present invention are well-known in the art.

[0130] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various modifications or variations within the scope of the claims, which do not affect the essence of the present invention.

Claims

1. An intelligent unmanned aerial vehicle (UAV) bomb delivery system, characterized in that, include: The system comprises a control section, a transport section, and a bombing section; among which: The control unit is used to receive image information and position information fed back by the transport unit and the bombing unit, and based on the image information and position information, to provide manual control information for controlling the flight trajectory and hiding place of the transport unit and the flight timing and bombing timing of the bombing unit. The carrier unit is used to carry the bomb-dropping unit, controls its own flight status according to its own control information or received manual control information, autonomously plans its flight path, carries the bomb-dropping unit to the designated location, and provides real-time image and location information; at the same time, it supplies power to itself and the bomb-dropping unit. The bomb-dropping unit, based on its own control information or received manual control information, reaches the target location according to its autonomously planned trajectory to perform a cruise attack mission, and provides real-time feedback of image and location information; when it fails to find the target, it returns to the carrier unit to recharge based on its own control information, waiting for the next cruise attack mission. The carrier unit uses a computing unit to control its own flight status through its own control information or manual control information transmitted from the control unit, and automatically plans its flight path based on target information and built-in atmospheric circulation data. In the computing unit: Based on the acquired real-time image and location information, it generates its own control information and target information; including: The acquired real-time image and location information are preprocessed; The preprocessed image information and location information are fused to associate the position of the target object in the image with its position in the real world; The fused information is analyzed, including target recognition, target classification, trajectory prediction, and environmental perception, to obtain the analysis results; Based on the analysis results, corresponding self-control information and target information are generated; Automatic flight path planning based on the target information and built-in atmospheric circulation data, including: Based on built-in atmospheric circulation data and target information, the optimal flight path is determined; at the same time, an optimization algorithm is used to update the flight path in real time according to weather changes.

2. The intelligent unmanned aerial vehicle (UAV) bomb delivery system according to claim 1, characterized in that, The control unit, located at the ground station, includes a console. The console receives image and location information transmitted from the transport unit and the bombing unit in real time via wireless communication, generates manual control information based on the image and location information, and then transmits it to the transport unit and the bombing unit through the console.

3. The intelligent unmanned aerial vehicle (UAV) bomb delivery system according to claim 1, characterized in that, In the control section, manual control information is generated based on the image information and location information, including: The image information and location information are processed; wherein, the processing of the image information includes: image denoising, enhancement, and feature extraction; the processing of the location information includes: coordinate transformation and coordinate system matching; The processed image information and location information are fused together to associate the position of the target object in the image with its position in the real world; The fused information is analyzed, including target recognition, target classification, trajectory prediction, and environmental perception, to obtain the analysis results; Based on the analysis results, corresponding manual control information is generated, including path planning, flight attitude adjustment, and target tracking commands, to guide the behavior of the delivery and bombing components.

4. The intelligent unmanned aerial vehicle (UAV) bomb delivery system according to claim 1, characterized in that, The carrier unit further includes: a flight unit, a navigation unit, a communication unit, a power supply unit, and a docking unit; wherein: The flight unit includes a flight balloon and a propulsion device; wherein the flight balloon provides buoyancy required for flight; the propulsion device provides power required for following a trajectory; and the flight state of the flight unit is controlled by the computing unit. The navigation unit includes a GPS, an inertial navigation system, and a camera; wherein, the GPS is used for real-time positioning; the inertial navigation system is used to control the stability and accuracy of the flight of the flight unit; and the camera is used to obtain real-time image information. The communication section includes a wireless communication module; wherein the wireless communication module is used to transmit information with the control section in real time. The power supply unit includes a solar panel and a battery, which are used to supply power to the carrier section and the bomb-dropping section. The docking unit includes a drone nest for storing and releasing drones; the drone nest is equipped with a charging interface that is connected to the power supply unit and used for charging the drones.

5. The intelligent unmanned aerial vehicle (UAV) bomb delivery system according to claim 1, characterized in that, The bombing component includes: a drone and a bomber unit; wherein: The drone includes a GPS, a camera, and a wireless communication module; wherein, the GPS is used for real-time positioning; the camera is used to obtain real-time image information; and the wireless communication module is used to transmit information with the control unit in real time. The bomber unit is used to load bombs and execute attack missions against target information based on its own control information or manual control information transmitted from the control unit.

6. The intelligent unmanned aerial vehicle (UAV) bomb delivery system according to claim 5, characterized in that, The bomber unit generates its own control information and target information based on the acquired real-time image information and location information. This includes: initiating AI vision guidance to find a target based on the acquired real-time image information and location information, obtaining target information, and generating first self-control information to control the bomber unit to carry out the attack mission based on the found target information; if the AI ​​vision guidance fails to find the target, generating second self-control information to control the bomber unit to return to the carrier unit for charging, waiting for the next cruise attack mission.

7. The intelligent unmanned aerial vehicle (UAV) bomb delivery system according to claim 6, characterized in that, The step of initiating AI visual guidance to find the target based on the acquired real-time image information and location information includes: The acquired real-time image information is preprocessed, including: resizing, denoising, and contrast enhancement; The YOLOv8 algorithm is used to identify target objects in the preprocessed image information and classify them to obtain target information; A target tracking algorithm is used to track the movement trajectory of the target information, and path planning is performed based on the acquired real-time location information, the detected target information, and the target location; Based on the path planning results, a corresponding first self-control command is generated to guide and track the target.

8. The intelligent unmanned aerial vehicle (UAV) bomb delivery system according to claim 7, characterized in that, Also includes: The generated first self-control command is fed back to the carrier unit as a reference for the carrier unit to readjust its course, speed, or attitude.

9. A method for delivering bombs using an intelligent unmanned aerial vehicle (UAV), characterized in that, include: The control section of the intelligent drone bomb delivery system acquires image and location information from the carrying and bomb-dropping sections of the intelligent drone bomb delivery system, and provides manual control information. The control unit sends the manual control information to the transport unit and the bombing unit to manually intervene and control the flight trajectory and ambush location of the transport unit, as well as the flight timing and bombing timing of the bombing unit. The carrier unit controls its own flight status based on its own control information or the manual control information it receives, autonomously plans its route, carries the bombing unit to the designated location, and provides real-time feedback of image and location information, while supplying power to itself and the bombing unit. The bombing unit executes cruise attack missions according to its own control information or received manual control information, following an autonomously planned trajectory, and provides real-time image and location information. When it fails to find a target, it returns to the carrier unit to recharge based on its own control information, waiting for the next cruise attack mission. The carrier unit uses a computing unit to control its own flight status through its own control information or manual control information transmitted from the control unit, and automatically plans its flight path based on target information and built-in atmospheric circulation data. In the computing unit: Based on the acquired real-time image and location information, it generates its own control information and target information; including: The acquired real-time image and location information are preprocessed; The preprocessed image information and location information are fused to associate the position of the target object in the image with its position in the real world; The fused information is analyzed, including target recognition, target classification, trajectory prediction, and environmental perception, to obtain the analysis results; Based on the analysis results, corresponding self-control information and target information are generated; Automatic flight path planning based on the target information and built-in atmospheric circulation data, including: Based on built-in atmospheric circulation data and target information, the optimal flight path is determined; at the same time, an optimization algorithm is used to update the flight path in real time according to weather changes.

Images