6682results about "Launching weapons" patented technology

The invention relates to the technical field of artificial intelligence rescue, and discloses an unmanned aerial vehicle and robot dog rescue emergency system and method, and the system comprises an unmanned aerial vehicle cluster module which is used for air data collection, communication guarantee and emergency material distribution; the robot dog cluster module is used for ground environment detection, sample collection and special task execution; the communication cooperation module is used for ensuring information intercommunication and task cooperation between air-ground equipment; the central control module provides task instructions for the unmanned aerial vehicle cluster and the robot dog cluster; the human-computer interaction interface module is used for realizing effective communication between rescue workers and the system; the modules work cooperatively, multi-source data acquisition, three-dimensional scene reconstruction, semantic segmentation, risk assessment, fire spreading prediction and decision support information generation of a disaster site are realized, and a reliable basis is provided for rescue command decision.

An unmanned aerial vehicle (UAV) is disclosed that includes a retractable payload delivery system. The payload delivery system can lower a payload to the ground using a delivery device that secures the payload during descent and releases the payload upon reaching the ground. The location of the delivery device can be determined as it is lowered to the ground using image tracking. The UAV can include an imaging system that captures image data of the suspended delivery device and identifies image coordinates of the delivery device, and the image coordinates can then be mapped to a location. The UAV may also be configured to account for any deviations from a planned path of descent in real time to effect accurate delivery locations of released payloads.

The invention discloses an unmanned aerial vehicle-mechanical arm system cooperative control method for precise spraying. According to the method, through a depth camera and a point cloud reconstruction algorithm, three-dimensional modeling of a target surface and semantic recognition of a spraying area are achieved, and a spraying path and spraying posture data are generated. Based on spraying task requirements, a spraying film thickness experience estimation model is established, and path point-level spraying parameters are obtained. Load mass change, mechanical arm mass center change and spraying reaction force of each path point are calculated, and a coupling dynamic model is constructed in combination with the system state. And dynamic compensation control input is generated by using an adaptive sliding mode control algorithm. After spraying is completed, the actual spraying effect is collected through image and point cloud detection, color, film thickness and texture features are extracted and compared with task requirements, error feedback is generated, and control parameters are adjusted online. According to the method, the problems of dynamic change and error compensation in the spraying process are effectively solved, and the method is suitable for a high-precision spraying task in a complex environment.

An autonomous agricultural drone system for the precise spraying of pesticides, consisting of: an advanced image recognition camera integrated with an artificial intelligence (AI) module specifically trained on pest and plant health datasets, with the camera configured to detect specific pests, identify pest hotspots, and differentiate between healthy and stressed plants; a real-time decision processor that is operationally connected to the image recognition camera, the processor being configured to: Data received from the image recognition camera is interpreted to assess pest density and plant health. adjusts the pesticide output and spraying patterns of the drone based on real-time field conditions, determines the severity of pest infestation in order to avoid excessive use of pesticides and to apply pesticides precisely and only where they are needed; a multitude of intelligent spray nozzles equipped with sensors and actuators, each nozzle configured to dynamically adjust its spray rate based on pest density and plant species, as determined by the real-time decision processor, thereby minimizing chemical use and environmental impact; characterized by the fact that The drone system includes a multi-liquid injection nozzle system that allows the drone to carry and selectively apply multiple solutions, including pesticides and nutrients, in a single flight, with the system configured to switch between solutions in response to real-time data from the image recognition camera and decision processor.

A system and method for airborne dispensing. In some embodiments, the system includes a hopper and a metering wheel. The metering wheel may be configured to extract pellets, one at a time, from the hopper.

A system for delivering ordinance is disclosed. The system includes a flight capable drone having a lift capacity suitable for carrying a munition, a fire control module in communication with the munition, and a handheld device in remote communication with the fire control module. At least one encrypted firing code generated by the fire control module is received by the handheld device and the munition is armed in accordance with at least the location of the drone.

When a customer places an order for a first item and a second item, delivery systems utilize an aerial vehicle to transport the first item from a first source of the first item to a second source of the second item. At the second source, the first item and the second item are transferred into a carrier vehicle and transported toward a destination of the order. Once the carrier vehicle arrives within a vicinity of the destination, an autonomous ground vehicle departs the carrier vehicle with the first item and the second item, and delivers the first item and the second item to the destination. The delivery systems effectively expand the capacity of sources of items, and simplify processes for delivering orders for items, by enabling items from multiple sources to be combined at a single source prior to delivery, and transported to a destination from the single source.

An artificial intelligence (AI) entry management (EM) security system includes a camera, a microphone, a motion detector, a speaker, and a software platform. Geofences are utilized to create boundaries around physical areas, such as locations for package delivery or property boundaries. The EM device and other devices connected to the software platform are configured to monitor the geofences and detect a presence of an activity, an event, an object, or a device. At least one license plate reader is utilized to read license plate characters. Voice recognition and voice identification are used to grant or deny permissions for individuals on a property

The present invention relates to a method for remotely and / or autonomously harvesting a tree from air. The method comprises detecting by at least one sensor on a UAV (100) a tree to be harvested, positioning a harvesting tool (105) comprising delimbing means (114) carried by the UAV (100), by using information from the at least one sensor, at a predetermined distance above a canopy of the tree to be harvested, releasing the harvesting tool (105) in a first mode from the UAV (100) from the predetermined distance above the canopy of the tree to be harvested, setting the harvesting tool (105) in a second mode when the harvesting tool (105) has the tree top (131) within its tree receiving area (177). At least a portion of the harvesting tool (105) is below the tree top (131) of the tree to be harvested while the harvesting tool (105) has a certain speed >0 in a downward direction. The first and second mode differ with respect to the tree receiving area (177) of the delimbing means (114) in the harvesting tool (105). The tree receiving area (177) refers to the area in between open and closed delimbing means (114).

Load stability systems and methods for stabilizing swinging motions of suspended loads. The load stability systems include a fully automated, self-powered device that employs thrust to counteract and control lateral and rotational motion of an external load. The device is a temporary installment on the load, cable, or boom, and is agnostic to the platform from which it is suspended.

Provided are: an aircraft that can fly stably even when water is discharged from a hose installed on the airframe thereof; and an aircraft system that uses the aircraft. This aircraft system comprises: a master aircraft 10; three slave aircrafts 20; and a remote control device 30 that is for making the aircraft fly as a unit. Each slave aircraft 20 has: four rotary blade portions that have propellers 221; and a suspending means 23 that is for suspending a prescribed part of a hose 50 that is for discharging water. The master aircraft has: four first rotary blade portions that have first propellers 121 that have been arranged to rotate in a horizontal plane; four second rotary blade portions that have second propellers 131 that have been arranged to rotate in a vertical plane; and a nozzle 15 on which a tip end part of the hose 50 is installed. The direction of the center axis of the nozzle 15 is parallel to the direction of the rotational axes of the second propellers 131.

A suppression device for a rotary machine gun includes a body; and a core configured to fit inside the body, wherein the core includes: a plurality of suppression tubes symmetrically oriented around the core with one each of the plurality of suppression tubes corresponding to one of a plurality of barrels of the rotary machine gun, and a redirector at a distal end of the core and including an angled surface to direct propellant gas emitted through a central channel of the core radially outward.

An unmanned aerial vehicle includes: a mooring member capable of mooring an article; a linear member connected to the mooring member; a reel around which the linear member is wound. The unmanned aerial vehicle acquires information relating to wind strength around the article when the article is to be lowered from the unmanned aerial vehicle by controlling the reel; and controls the reel so as to provide a feeding amount of the linear member in dependence on the wind strength, on the basis of the acquired information.

The invention relates to the technical field of image recognition, and discloses a multispectral image and deep learning-based forest disease and insect pest automatic recognition method, which comprises the following steps of 1, carrying a multispectral camera containing a red edge wave band through an unmanned aerial vehicle to obtain a forest region image; 2, calculating a red edge normalized vegetation index of the image; 3, performing time sequence modeling on the red edge normalized vegetation index data of more than five consecutive periods, and inputting a time sequence convolutional network to generate an early lesion probability graph; 4, detecting a pest and disease damage target by adopting a multi-scale adaptive feature pyramid network; 5, outputting a disease and pest distribution thermodynamic diagram; and 6, driving the unmanned aerial vehicle cluster to execute precise pesticide spraying. According to the method, through the high sensitivity of the red-edge wave band to chlorophyll degradation and in combination with sequential convolutional network dynamic modeling, an initial lesion area can be recognized 7-10 days before disease development, the early disease recognition capability is remarkably improved, the disease discovery period is shortened, and large-scale disease diffusion is effectively avoided.

The invention relates to the technical field of unmanned aerial vehicles, in particular to a wind speed correction method and system for an unmanned aerial vehicle, and the method comprises the steps: controlling the unmanned aerial vehicle to be in a hovering state, and obtaining the first position information of the unmanned aerial vehicle; acquiring second position information of the target position; obtaining a target distance based on the first position information and the second position information; acquiring wind condition information and material information; based on the first position information and the wind condition information, obtaining a material putting time length; based on the target distance, the material putting duration, the wind condition information and the material information, obtaining an offset; position correction is carried out based on the offset, and a target putting position is obtained; and based on the target delivery position, carrying out material delivery operation. The method is beneficial for reducing errors of unmanned aerial vehicle hovering material putting.

An example system includes a vehicle having a platform, a linear slide configured on the platform, a robotic retrieval system configured on the linear slide, a shelf configured adjacent to the linear slide and a control system that controls a reception of a first item and a second item by the robotic retrieval system and a placement of the first item and the second item, by the robotic retrieval system, on the shelf. A drone can be configured to retrieve the first item or the second item from the robotic retrieval system on the vehicle and deliver the first item or the second item to a destination location. The vehicle can thereby enable delivery of many items without the vehicle stopping or even driving to a specific destination location.

An artificial intelligence (AI) entry management (EM) security system includes a camera, a microphone, a motion detector, a speaker, and a software platform. Geofences are utilized to create boundaries around physical areas, such as locations for package delivery or property boundaries. The EM device and other devices connected to the software platform are configured to monitor the geofences and detect a presence of an activity, an event, an object, or a device. At least one license plate reader is utilized to read license plate characters. Voice recognition and voice identification are used to grant or deny permissions for individuals on a property.

A device (4200) for an Unmanned Aerial Vehicle, UAV (100), said device (4200) comprising a first pivot point (4212) and a second pivot point (4214) being spaced apart from each other, said first pivot point (4212) is connectable a UAV (100) and said second pivot point (4214) is connectable the UAV (100), said device (4200) is configured to be tilted / rotated around said first pivot point (4212) by adjusting a length of a second cord (4204) and / or tilted / rotated around said second pivot point (4214) by adjusting a length of a first cord (4202), wherein said device (4200) has a first winch motor (4292) and a second winch motor (4294), said first and second winch motors (4292, 4294) are configured for adjusting the length of said first and second cords (4202, 4204) respectively. Also provided is a harvesting tool (105, 110) comprising a base structure (650), said base structure having attached to it at least one cutting means for delimbing a tree (114a, 114b), at least one means for communicating with a UAV and / or a remote base station, at least one cutting means for cutting a tree trunk (116), at least one attaching means to be attachable to the UAV (660), at least one holding means for holding a tree trunk (105,107a, 107b, 114a, 114b). Also provided is a method for controlling the relative rotation between a UAV and a device, where the device is attached to said UAV via at least two cords, said method comprising the steps of: a. determining a reference rotational position of said device relative to said UAV, b. detecting an angular rotation R in a horizontal plane of said device relative to said reference position, c. compensating said angular rotation in said horizontal plane of said device by rotating said UAV in said horizontal plane in the same direction and by the same angular rotation R as said device for prohibiting twisting of said cords.

The invention relates to an aircraft high-speed throwing control method and device and electronic equipment, and relates to the technical field of aircraft flight control, and the method comprises the steps: calculating an optimal control instruction sequence in a preset time domain in a rolling manner based on an expected throwing trajectory, a predicted throwing trajectory model and a multi-objective optimization function, and generating a main control quantity, the main control quantity is a control instruction in the optimal control instruction sequence; performing feedforward compensation on the main control quantity based on the disturbance observation result, and performing superposition processing of the sliding mode control quantity on the main control quantity after feedforward compensation based on the disturbance observation result to obtain a superposed main control quantity; high speed throwing of the aircraft cargo is performed based on the superimposed master control quantity. Through application of the scheme, the problem of throwing track deviation caused by posture change and airflow disturbance is effectively solved, it is ensured that the goods can accurately reach the target position according to expectation, and the accuracy of goods throwing is remarkably improved.

The invention relates to the technical field of desertification control, in particular to a sand barrier aerial seeding collaborative layout optimization system and method based on an unmanned aerial vehicle cluster game, which constructs a microenvironment digital model of terrain, wind field, humidity and temperature through a multi-mode desert microenvironment sensing module and combines with a sand barrier-vegetation coupling dynamic model. Space-time correlation between sand barrier configuration and vegetation growth is achieved, the self-adaptive sand barrier parameter optimization module and the precise seed aerial seeding control module work cooperatively, seed putting is optimized, the sand stabilization efficiency and the vegetation survival rate are remarkably improved to 60%-75%, the treatment period is shortened to 1.5-2.5 years, and the control cost is reduced. The closed-loop feedback and dynamic optimization module further ensures continuous improvement of the treatment effect, a traditional'sand blocking 'strategy is converted into'ecological microenvironment engineering', a complete microenvironment regulation and control mechanism is constructed, the treatment efficiency is improved by 35%-50%, and fundamental change of the treatment concept is achieved.

Unmanned systems, and primarily vehicles, and in most embodiments unmanned aerial systems (UAS), as well as novel guided and unguided munitions are presented herein. to the two combine to present unmanned weaponized systems that not only carry weapons functionality, but allow for advanced observation and reconnaissance. These unmanned systems are largely directed toward military applications where the weaponized unmanned system may be forward deployed to allow human warfighters to remain at long range distances from the potential targets, and to provide surveillance, target identification and tracking, general reconnaissance information, and the like, while also providing weaponized attack capabilities. The unmanned systems may, in some embodiments, include advanced command and control capabilities for communication between the system and the remote, rear-positioned warfighter, and between separate elements of the unmanned system. Many embodiments also include weapons systems, munitions, or rounds with guidance and real-time maneuverability capabilities as well.

The invention relates to the technical field of leaf bee prevention and control, and particularly discloses a leaf bee pest adult prevention and control method, which comprises the steps of S1, data collection, S2, climate prediction model establishment, S3, precise monitoring, S4, precise prevention and control, S5, dynamic adjustment and S6, monitoring optimization. By using the unmanned aerial vehicle and the remote sensing technology, a gathering area of the adult leafbees can be accurately identified, a high-risk area can be intensively prevented and treated, blind large-area pesticide spraying is avoided, the prevention and treatment effect is remarkably improved, the climate prediction model can predict the activity peak period of the adult leafbees in advance, farmers are helped to take prevention and treatment measures at the best opportunity, and the prevention and treatment efficiency is improved. Through real-time analysis of a climate prediction model and remote sensing data, a farmer can formulate a scientific prevention and control strategy according to the data, dependence on experience and subjective judgment is reduced, the decision accuracy is improved, and according to feedback of real-time monitoring data and the prediction model, changes of pests are coped with in time, so that the prevention and control effect is improved. The continuous optimization of the control effect is ensured.

The invention discloses an intelligent forest fire prevention method and system, and aims at solving the problems of monitoring failure, information updating lag and low prediction precision of a traditional method in a severe environment by integrating multi-source real-time data and adopting deep learning and a dynamic probability model to realize accurate identification of a fire disaster and fire spreading prediction. Through an intelligent path planning algorithm and an unmanned aerial vehicle autonomous fire extinguishing technology, real-time response to dynamic changes of a fire scene and flexible adjustment of a fire extinguishing strategy are realized, the fire extinguishing efficiency and safety are improved, a fire extinguishing effect data acquisition and feedback mechanism is established, and the defect that a traditional system lacks effect evaluation after fire extinguishing is overcome. And a reliable basis is provided for subsequent model optimization and decision improvement, so that the forest fire early warning and emergency response capabilities are integrally improved.

The invention discloses a three-dimensional space self-adaptive unmanned aerial vehicle accurate spraying method and system and an unmanned aerial vehicle. The method relates to the technical field of unmanned aerial vehicle spraying, and comprises the following steps: scanning a spraying area on the bottom surface of a viaduct through an unmanned aerial vehicle to obtain unmanned aerial vehicle spraying quality data, and analyzing, optimizing and adjusting the unmanned aerial vehicle spraying quality data. The method comprises the following steps: scanning a spraying area on the bottom surface of a viaduct through an unmanned aerial vehicle to obtain three-dimensional point cloud data, adaptively generating a flight path and a spraying track of the unmanned aerial vehicle based on the data, flying according to a planned path and spraying, collecting spraying quality data through a sensor, analyzing the spraying quality data, and determining the spraying quality of the viaduct. The dynamic liquid level monitoring error quantized value and the unmanned aerial vehicle precise spraying method stability quantized value are obtained and analyzed with threshold values in a database, the unmanned aerial vehicle precise spraying method is optimized and adjusted, the stability of the unmanned aerial vehicle precise spraying method is improved, and the problem that in the prior art, an unmanned aerial vehicle precise spraying method is insufficient in stability is solved.

The invention discloses an unmanned aerial vehicle and unmanned vehicle joint distribution method and system, a terminal and a medium. The method comprises the steps of obtaining a task allocation scheme of cargo distribution of an unmanned aerial vehicle and an unmanned vehicle; according to the task allocation scheme, controlling the unmanned aerial vehicle carrying the goods to sail into a target area; the unmanned aerial vehicle is controlled to throw the goods into the unmanned vehicle located in the target area; according to the task allocation scheme, the unmanned vehicle is controlled to run to a goods receiving position, and goods receiving notification information is generated; and sending the goods receiving notification information to a target device corresponding to a recipient, and when it is detected that the goods are taken out, marking that delivery of the goods is completed. According to the invention, the distribution efficiency is improved through a distribution mode of combining the unmanned aerial vehicle and the unmanned vehicle.

The invention provides an integrated fire fighting truck for high-rise building fire fighting and a rescue system and a fire extinguishing method.The integrated fire fighting truck comprises a carriage, a standing workbench is arranged at the front end of a carriage body of the carriage, a vehicle-mounted multimedia display screen is arranged at the rear end of the carriage body, the standing workbench comprises a bottom supporting frame, and a standing platform is arranged at the upper end of the bottom supporting frame; a fence is arranged at the upper end of the bottom supporting frame around the standing platform, a control system of the vehicle-mounted multimedia display screen is connected with a vehicle-mounted electric control system, a fire-fighting ammunition storage frame is arranged on a bottom plate in the compartment body, a plurality of unmanned aerial vehicle lifting platforms are arranged above the fire-fighting ammunition storage frame, and a support for installing the unmanned aerial vehicle lifting platforms is arranged in the compartment body. A sliding door set matched with the unmanned aerial vehicle lifting platform to be opened and closed is arranged at the top of the compartment body. Through the unmanned aerial vehicle attitude and heading steady state control technology, the precise jet fire extinguishing technology and the body safety guarantee technology under the multi-source disturbance load based on artificial intelligence, and in combination with the high-rise building fire unmanned aerial vehicle cluster intelligent fire extinguishing system operation tactical and tactical method, the problem of fire extinguishing and rescue of urban high-rise buildings is solved.

The invention relates to the technical field of unmanned aerial vehicle inspection, and provides an unmanned aerial vehicle-based forest fire prevention inspection and disposal method, device and system. When an inspection unmanned aerial vehicle equipped with a multi-modal sensor is deployed to cruise according to a preset route, a visible light camera of the inspection unmanned aerial vehicle continuously collects forest region videos and transmits the videos to edge computing equipment of an inspection airport; fire hazards are analyzed in real time through a target recognition algorithm, and when a fire source is detected, position information is reported to a background terminal immediately; the system automatically dispatches the nearest fire extinguishing airport to dispatch the fire extinguishing unmanned aerial vehicle, and secondary accurate positioning is performed on a fire source by using the airborne infrared vision module, so that accurate throwing of the fire extinguishing bomb is ensured. The whole system enhances the real-time analysis capability through the edge computing device, breaks through the single-machine computing power limitation, also realizes the full-process automation from fire behavior recognition to fire extinguishing treatment, and significantly improves the response efficiency and treatment safety of forest fire prevention.

The invention relates to an autonomous flight unmanned aerial vehicle interception system carrying an anti-riot capture net gun, and aims to realize intelligent identification and accurate interception of a high-dynamic target. The sensing module collects multi-source data such as images, laser radar, air pressure and wind speed and fuses the multi-source data to generate a flight space topological graph, and the recognition module extracts target position, speed and deformation information according to the graph and outputs target motion parameters and deformation characteristics. The control unit constructs a target trajectory prediction model and a risk level incidence matrix based on the information, and dynamically generates an interception path, a posture adjustment instruction and a capture trigger strategy. The propulsion assembly adjusts the three-dimensional pose of the aircraft in real time according to the pose adjustment instruction, has anti-interference stability and is suitable for flight in a complex environment. The launching assembly is integrated in the aircraft structure and completes anti-riot net gun launching and target capturing according to a triggering strategy. The system has autonomous perception, dynamic prediction and accurate execution capabilities, and is suitable for target interception and control tasks in complex scenes.

The invention discloses an intelligent low-altitude unmanned aerial vehicle cluster air-ground cooperative detection fire extinguishing system and method, a patrol plan is made by determining the patrol time interval of a patrol area of an unmanned aerial vehicle and the density of patrol routes, the system can dynamically adapt to the change of seasons and human activities, and the system and method are more accurate and more efficient. Fire missing detection can be effectively avoided; identifying a fire source by adopting a multi-source data fusion technology, determining whether the fire source exists in the forest region through the infrared image and the actual image of the forest region, and determining the intensity and the position of the fire source according to the smoke concentration when determining that the fire source exists in the forest region. The problem that the accuracy of infrared thermal imaging is affected and the detection precision is low due to the temperature difference of different vegetation, the change of the sunlight irradiation angle, water vapor in the atmosphere and the like can be solved. The fire trend prediction module and the fire extinguishing scheme generation module are adopted to automatically realize fire extinguishing of the forest area, the prediction result is efficient and accurate, and missing of the optimal fire extinguishing opportunity can be avoided.