143results about How to "Precise Navigation" patented technology

The invention provides an airway navigation system and method based on a bronchoscope view, and the system comprises a reconstruction module which obtains a bronchial tree 3D mask through CT image reconstruction; the model building module is used for obtaining a three-dimensional virtual map model comprising a 3D bronchial tree according to the 3D mask of the bronchial tree; the path extraction module is used for extracting all possible navigation paths from the bronchus entrance to the target part based on the 3D bronchus tree; the path selection module is used for selecting one navigation path as a target navigation path; the navigation module is used for guiding the bronchoscope to move along a target navigation path in the three-dimensional virtual map model based on a visual guide path; and the navigation auxiliary module maps the identified real-time part corresponding to the bronchoscope to the 3D bronchial tree for matching so as to realize dynamic synchronization of the real-time part corresponding to the bronchoscope and the target navigation path. According to the invention, reliable and convenient navigation in a complex airway network can be realized, misoperation is effectively avoided, time is saved, and operation difficulty is reduced.

The invention relates to a satellite / inertial integrated navigation anti-deception jamming method and system based on a multi-array-element antenna, and the method comprises the steps: receiving an inertial navigation measurement value through an inertial navigation measurement unit, carrying out the preprocessing of the inertial navigation measurement value, obtaining a processed inertial navigation measurement value, and receiving a navigation signal transmitted by a satellite through a master antenna and a slave antenna; whether a deception jamming signal exists or not is detected according to the received master and slave antenna signals, if the deception jamming signal exists, the incoming wave direction of the deception jamming signal is searched by a multi-array-element antenna, a null is aligned to the direction, meanwhile, the master antenna signal is switched into the multi-array-element antenna signal, detection is conducted, and the deception jamming signal is obtained. And taking the multi-array-element antenna signal as a GNSS (Global Navigation Satellite System) signal and optimizing the processed inertial navigation measurement value by adopting a factor graph until no deception jamming signal is detected, so as to obtain an anti-deception jamming satellite / inertial integrated navigation result. By adopting the method, accurate navigation can be carried out in a complex environment and a scene with deception jamming.

The invention discloses an autonomous navigation positioning system and method for an autonomous vehicle, and belongs to the technical field of automatic driving, and the method specifically comprises the steps: receiving a satellite signal through a GPS receiver, preliminarily determining the position of the vehicle, starting a vehicle sensor to carry out real-time measurement, and preprocessing a result; the preprocessed measurement result is converted into position information in a global coordinate system, and the position and attitude of the vehicle are calculated in combination with a sensor fusion algorithm; generating point cloud data by using a laser radar, matching the point cloud data with a high-precision map to determine the accurate position of a vehicle, and identifying obstacle and road features; a vehicle-mounted camera captures an environment image, extracts visual feature information and fuses the visual feature information with environment perception information; on the basis of fusion information and distance information, the obstacle and road conditions are sensed in real time, the optimal driving route is determined by adopting a path planning algorithm, visual navigation and automatic obstacle avoidance are realized, and the safety and reliability of automatic driving are improved.

The invention discloses a robot positioning and navigation method and device based on a large language model thinking chain, and belongs to the field of intelligent navigation, and the method comprises the steps: obtaining a target instruction, and collecting the current position of a robot and the image information of the current position; performing semantic analysis on the target instruction and the image information of the current position by using a visual language model to generate a navigation thinking chain; and determining the next position of the robot according to the navigation thinking chain, and generating a navigation route of the robot according to the next position and the current position. Therefore, the problems that an existing navigation method generally lacks a systematic reasoning process, and abundant semantic information contained in a model cannot be fully utilized to optimize a navigation task are solved.

The invention relates to the technical field of logistics navigation, and discloses a logistics park navigation method, device and equipment and a storage medium, and the method comprises the steps: obtaining logistics order information when it is detected that a vehicle enters a preset range of a logistics park, and generating path information according to the logistics order information; selecting navigation equipment in a navigation transceiving cabin according to the navigation equipment selection strategy to obtain target navigation equipment; importing the path information into the target navigation equipment to obtain started navigation equipment; and distributing the started navigation equipment to the vehicle so as to realize navigation control of the logistics park. According to the invention, accurate navigation of the logistics vehicle can be realized, and the operation efficiency of a logistics park is effectively improved.

The invention belongs to a robot navigation method, and aims to solve the technical problems of difficulty in establishing a geometric map in a non-structural scene, dependence on tags from laser radar data, easiness in ignoring long-distance features and slow reasoning time in the conventional navigation or exploration method. According to the robot visual navigation method based on comparative learning and the related device, after current observation is obtained, the current observation is input into a trained observation encoder to obtain a corresponding feature vector, and then a pre-selected batch action sequence passes through an action encoder to extract the corresponding feature vector; and calculating the similarity between the current observation and each action sequence through a vector inner product, selecting the action sequence with the highest similarity, and inputting the selected action sequence into a robot controller for controlling the robot to execute corresponding actions. Compared with a method for directly generating the action sequence, the method has the advantages that the difficulty of selecting one action sequence is lower, and the expansibility and generalization are better.

The invention relates to a wall-climbing robot positioning system and method based on a space structure circular descriptor. A depth image sensor (RGB-D) camera outputs a depth image; collecting three-dimensional point cloud data of three-dimensional space wall surface points; and conformally mapping the contour of the wall-climbing robot to a minimum bounding ball (MBS). A space structure circular descriptor (SSCD) algorithm module maps the three-dimensional point cloud data to a two-dimensional positioning navigation plane, and an SSCD image is formed on the two-dimensional positioning navigation plane; and point cloud features of the SSCD images from the k-1 moment to the k moment are matched, and positioning of the wall-climbing robot on the three-dimensional space wall surface at the current moment is completed. An airborne inertial measurement unit (IMU) measurement module acquires the angular velocity and acceleration of the wall-climbing robot; the attitude information of the wall-climbing robot at the current moment is obtained by carrying out pre-integration on the collected angular velocity and acceleration. Therefore, three-dimensional data are mapped to a two-dimensional plane through a space structure circular descriptor (SSCD) algorithm, and the wall-climbing robot is accurately positioned and navigated.

The invention relates to the technical field of visual robots, and discloses a visual navigation mobile robot under a GPS signal denial condition, the visual navigation mobile robot comprises a robot body, the top of the robot body is fixedly connected with a control box body; by integrating a visual navigation system and an intelligent path planning algorithm, the navigation problem of the mobile robot under a GPS signal denial condition is solved, so that the robot has higher autonomy and adaptability, and accurate positioning and navigation can be realized in a complex environment; meanwhile, the cleaning brush is used for cleaning the wheel body, sundries and the like which are attached to the surface of the wheel body and affect advancing of the robot body are reduced, the transmission fan is used for generating wind power, the ventilation effect in the robot body is improved, and dust on the surfaces of the heat dissipation holes can be cleaned through the dust removal brush which continuously moves; the situation that dust is attached to the surfaces of the heat dissipation holes to affect air circulation in the robot body and consequently temperature rise is caused is reduced, and the stability of a circuit in the robot body is improved.

The invention relates to the technical field of robots, and discloses a method for generating a robot sensing map, which comprises the following steps: performing online mapping through a simultaneous positioning and mapping technology to obtain an initial sensing map under a robot coordinate system; according to the prior information of the robot, determining a target area needing to be complemented in the initial perception map and a space entity type corresponding to the target area; and complementing the target area according to the spatial entity type to obtain a target perception map. According to the method, an initial sensing map under a robot coordinate system is obtained by online mapping through a simultaneous positioning and mapping technology, a specific target area is complemented in combination with prior information, and the robot can obtain a more complete environment model by complementing missing data of a view limited area, so that the robot can more accurately perform navigation and obstacle avoidance, and the navigation efficiency of the robot is improved. And the accuracy of environment perception when the robot executes the task is improved. The invention further discloses a device for generating the robot perception map, the robot and a storage medium.

The invention discloses a self-propelled water and fertilizer irrigation device and method based on intelligent navigation and a multi-energy system, and relates to the field of agricultural irrigation.The self-propelled water and fertilizer irrigation device comprises a rear rack, a front rack is arranged on the front side of the rear rack, a machine body is connected to the upper portion of the rear rack and the upper portion of the front rack, and stability adjusting mechanisms are installed on the rear side wall of the rear rack and the rear side wall of the front rack correspondingly; the bottom of the stable adjusting mechanism is connected with a wheel carrier, wheels are installed below the wheel carrier, a wheel shaft is connected to the middle of each wheel in a penetrating mode, and a bearing is connected between each wheel shaft and the corresponding wheel carrier. By arranging the hybrid energy system, the dependency of device power supply on the environment can be reduced, the storage battery can be automatically switched to provide power in rainy days and windless days, continuous supply of energy is ensured, and the reliability of the system is greatly improved; and by arranging the stability adjusting mechanism, the movement stability of the device on the uneven ground or the muddy area can be improved, and the possibility of slipping is reduced.

The invention discloses an unmanned aerial vehicle control method, a storage medium, a processor and an electronic device. The method comprises the following steps: acquiring image information, and determining a first relative position relationship between a mounting point and an unmanned aerial vehicle based on the image information; obtaining point cloud information, wherein the point cloud information is obtained by performing radar scanning on the target area by the unmanned aerial vehicle; determining a second relative position relationship between the mounting point and the unmanned aerial vehicle based on the point cloud information; determining positioning information based on the first relative position relation and the second relative position relation; and generating a control strategy based on the positioning information, wherein the control strategy is used for controlling the unmanned aerial vehicle to move into the installation area of the installation point. The technical problem that an existing unmanned aerial vehicle is inaccurate in positioning when positioning a power transmission tower installation point is solved.

The invention relates to a power transmission line inspection unmanned aerial vehicle navigation method and device, an unmanned aerial vehicle, equipment and a medium, and relates to the technical field of unmanned aerial vehicles. The method comprises the following steps: acquiring a first electric field intensity collected by a first electric field sensor and a second electric field intensity collected by a second electric field sensor of the unmanned aerial vehicle in an inspection process; the first electric field sensor and the second electric field sensor are vertically arranged; according to the first electric field intensity and the second electric field intensity, determining the synthetic electric field intensity of the position of the unmanned aerial vehicle; and determining a flight strategy of the unmanned aerial vehicle according to the synthesized electric field intensity, a preset electric field intensity range, the first electric field intensity, the second electric field intensity and a preset electric field proportion range to control the unmanned aerial vehicle to fly relative to the power transmission line according to a preset safety distance. The method can improve the navigation accuracy of the unmanned aerial vehicle.

The invention relates to an environment self-adaptive deformation robot end device and a preparation method and application thereof, and belongs to the field of bionic robots. According to the device, the load of the robot is reduced by adopting the lightweight sensor, the movement efficiency of the robot is improved, and the cost is reduced; by arranging the flexible shell, the feet of the robot can be subjected to self-adaptive deformation when the robot is loaded, the stability of the robot is improved, it is ensured that the robot can stably move under various terrains and postures, accurate sensing data are provided, and the adaptability and operation performance of the robot under different scenes are greatly improved through the flexibility.

The invention relates to the technical field of three-dimensional modeling, in particular to a human blood vessel mapping guide plate automatic generation method based on three-dimensional modeling. The method comprises the following steps: acquiring a patient focus tissue CT image and a patient focus tissue MRI image; fuzzy blood vessel area radiography optimization is carried out on the patient focus tissue CT image, and a standard patient focus tissue optimization CT image is generated; soft tissue identification is carried out on the patient focus tissue MRI image, and an MRI image soft tissue area image is generated; performing image merging on the standard patient focus tissue optimization CT image and the patient focus tissue MRI image to generate a patient focus tissue feature image; and performing preoperative plan image simulation based on the lesion tissue feature image of the patient to generate a preoperative plan image. Through multi-modal image fusion, AI automatic segmentation and function testing, the automatic generation precision and reliability of the three-dimensional blood vessel mapping guide plate are improved.

The invention discloses a vehicle navigation method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: acquiring a road image acquired by an image acquisition device in a vehicle; recognizing a building in the road image, and recognizing the road type of the road where the vehicle is located according to the building; under the condition that the road type is an urban road, identifying a target object in the road image by using a first-stage target detection algorithm; under the condition that the road type is a rural road, identifying a target object in the road image by using a two-stage target detection algorithm; and generating virtual navigation information based on the target object, and displaying the virtual navigation information at a preset position. The technical problem that a related augmented reality-based navigation technology cannot select recognition algorithms adapted to different roads according to the environment where the vehicle is located so as to recognize important objects around the vehicle is solved.

The utility model provides wearable fitness positioning equipment, which relates to the technical field of fitness equipment and comprises a main body and a working mechanism, the upper end of the main body is fixedly connected with the working mechanism, and the working mechanism comprises a basic component, an auxiliary component, a positioning component, a motion power generation component and a heat dissipation component. By integrating the basic assembly, the auxiliary assembly, the positioning assembly, the exercise power generation assembly and the heat dissipation assembly, multiple functions such as exercise data monitoring, health index detection, accurate positioning navigation, self-power generation and effective heat dissipation are achieved, and through combination of the functions, the performance of the equipment is optimized, and the fitness experience of a user is improved; by means of the self-power-generation function of the motion power generation assembly, the cruising ability of the equipment is remarkably prolonged by converting motion kinetic energy of a user into electric energy, in addition, the safety of outdoor sports is guaranteed through the precise positioning and navigation functions, and the stability and reliability of the equipment in various environments are guaranteed through the efficient heat dissipation design.

The invention discloses an intelligent inspection device of a new energy automobile ordered charging guide rail type robot. The intelligent inspection device comprises a control system, a communication interface, an I / O interface, an ultrasonic sensor, a driving system, a photoelectric switch and a walking mechanism. The control system performs information interaction with the ultrasonic sensor through the communication interface and is used for detecting whether a vehicle is parked in a parking space or not and sensing the running state of the robot through the I / O interface and the photoelectric switch; the control system controls the driving system to drive the robot to move on the walking mechanism according to detected and sensed information so as to achieve intelligent inspection of parking spaces and upload inspection results to the operation platform, and the intelligent inspection technology of the guide rail type charging robot and the implementation method are provided. And the vehicle parking condition of the charging parking space in the charging station is dynamically sensed and uploaded to the operation management platform to assist in operation decision making, so that the operation efficiency is improved.

The invention discloses a sensing system and method for humanoid robot joints, and belongs to the technical field of humanoid robots, the system comprises humanoid robot four limbs and joints, a camera, a processor and a calibration board, the joints comprise shoulder joints, elbow joints, wrist joints and end actuators, and / or hip joints, knee joints, ankle joints and end actuators; the camera is composed of a binocular camera module and a TOF module, the camera and the processor are located on joints of the humanoid robot, and the processor calibrates the position, processes data obtained by the camera and outputs a control instruction to control the end effector. According to the invention, environment perception in a wider range can be realized, and the camera on the joint can freely adjust the visual angle and direction along with the movement of the joint, so that more flexible environment perception and operation are realized; camera data processing and motor control are integrated, the communication delay between the sensor and the controller is reduced, and the response speed and the processing efficiency of the system are improved.

The invention discloses a self-walking unmanned aerial vehicle nest bridge steel box girder internal detection system and method. The system is composed of a track traveling chassis, a laser radar subunit, an image monitoring subunit, an unmanned aerial vehicle cable laying and collecting mechanism, one or more unmanned aerial vehicle carrying tables, a communication unit, a storage unit, a calculation unit, a control unit and a power supply unit. The laser radar subunit realizes position positioning of the self-walking nest in a bridge, and realizes position positioning and attitude calculation of the unmanned aerial vehicle in a steel box girder; through the cooperation of the self-walking nest and the mooring unmanned aerial vehicle, crack and defect detection by using the unmanned aerial vehicle in the steel box girder has establishment conditions; and tracking and monitoring of the unmanned aerial vehicle and image and video acquisition of the internal environment of the steel box girder are realized through the image monitoring subunit. According to the system and the method, autonomous driving of the nest in the bridge and autonomous flight of the unmanned aerial vehicle are ensured, and the internal patrol and crack and defect detection efficiency of the steel box girder is greatly improved.

The invention discloses a navigation signal enhancement system and method, and relates to the technical field of navigation. The navigation signal enhancement system comprises a timing system control unit, a signal processing unit and a signal enhancement unit which are connected in sequence, wherein the timing system control unit is used for receiving a first navigation signal transmitted by a navigation satellite and unifying the time frequency of a base station according to the first navigation signal; the signal processing unit is used for generating a second navigation signal according to the first navigation signal and the working mode of the base station, and the second navigation signal at least comprises a position signal, a time delay signal and a clock correction signal; the signal enhancement unit is used for generating a third navigation signal according to the first navigation signal and the second navigation signal, and the third navigation signal is a navigation enhancement signal for accurately positioning the terminal. The navigation signal enhancement system and the navigation signal enhancement method provided by the invention can be used for accurately positioning and navigating the low-altitude traffic tool under low-altitude economy.

The invention discloses a path planning method combined with three-dimensional modeling, comprising: obtaining a GPS covered road network of a target scene, dividing a non-GPS covered road network area into a VPS custom area, performing real scene three-dimensional reconstruction on the VPS custom area, and obtaining a real scene model of the VPS custom area; defining a transition area between the GPS covered road network area and the VPS custom area, and selecting an optimal path connection point in the transition area; connecting a path in the GPS covered road network area and a path in the VPS custom area through the optimal path connection point, planning the path of the VPS custom area through the real scene model of the VPS custom area, and forming a fused navigation path; navigating according to the fused navigation path, performing navigation point deviation detection, and if deviation occurs, performing new starting point planning to generate a new fused navigation path.

The present invention proposes a method for indoor navigation of a robot, the method comprising: obtaining indoor environment information and obstacle information through sensors; classifying the obstacle information; formulating a coping strategy for each obstacle according to the classification results of the obstacles; the robot performs path planning on an established environment map according to a current position, a target position, the obstacle information and the coping strategy; the robot moves along the planned path, senses changes in the environment in real time, and dynamically adjusts the path according to new environmental information. Through this method, the robot can obtain and process surrounding environment information in a timely manner, the robot can perform more intelligent and optimized path planning, thereby providing more accurate navigation and obstacle avoidance, and improving navigation efficiency; by identifying obstacle types and selecting appropriate obstacle avoidance strategies, the robot can avoid collisions with obstacles, thereby improving navigation safety.

The application discloses a three-dimensional terrain modeling analysis and adaptive navigation system and method, and relates to the technical field of navigation.The laser radar is used for acquiring point cloud data of the region where the device to be navigated is located in real time; the IMU is used for measuring the acceleration and angular velocity of the device to be navigated in real time; the data fusion sub-module is used for pre-processing the point cloud data, acceleration and angular velocity in real time, and fusing the pre-processed data; the three-dimensional map modeling sub-module is used for constructing a three-dimensional map model according to the point cloud data in real time by using a SLAM algorithm; the three-dimensional terrain analysis module is used for determining the terrain features of each point in the three-dimensional map model in real time; and the adaptive navigation module is used for planning a path for the device to be navigated according to the three-dimensional map model and the terrain features of each point, so that navigation is realized.The application can improve the precision of original data, and then improve the positioning precision, and realize accurate navigation.

The invention discloses a vehicle control method and device, a vehicle and a readable storage medium. The method comprises the steps of obtaining a planned path obtained by performing path planning on the vehicle; selecting a plurality of road adsorption points adsorbed by the planned path from the road points according to the distance between the planned path and the road points in each road of the target electronic map; determining a target road interval indicated by the plurality of road adsorption points in the road; controlling the vehicle to run according to the semantic description information of the target road interval in the target electronic map and the planned path; the semantic description information of the target road interval is used for indicating the road attribute of the target road interval. According to the method provided by the invention, accurate navigation in the vehicle driving process is realized.

The present invention provides a flatbed carriage detection method, device and unmanned guided vehicle based on an unmanned guided vehicle. The method uses an image retrieval network to extract the front reference image and the rear reference image that are closest to the real-time monitored RGB data stream from the flatbed graphics library that is updated and maintained in real time, and then matches the feature point pairs with the front image and the rear image in the RGB data stream to locate the pixel coordinates, and then converts them into the front space coordinates and the rear space coordinates in the absolute space coordinate system, and fits the linear equation that matches the first length side to guide the loading operation position according to each position of the first length side. In complex scenarios such as the unfixed parking position of the truck and the various types and specifications of the goods, the position of the flatbed carriage can be accurately identified, and the cargo specifications are combined to provide a basis for the cargo position division, which is convenient for accurate navigation to the designated cargo position and realizes flexible loading.

The invention relates to an unmanned aerial vehicle intelligent path planning method and system based on visual signals, and belongs to the field of path planning. The method comprises the following steps: optimizing a neural network through progressive pruning; fuzzy coordinates and scene types are provided for the unmanned aerial vehicle, the unmanned aerial vehicle flies to a fuzzy coordinate area, and when the unmanned aerial vehicle is close to the fuzzy coordinate area, the unmanned aerial vehicle is switched to a pure vision mode to perform environment perception through a neural network, and a three-dimensional semantic map is constructed; performing real-time path planning based on the three-dimensional semantic map to obtain a flight path; the method comprises the following steps: performing autonomous flight along a flight path, when approaching an operation target, performing autonomous operation to obtain real-time monitoring data, storing the real-time monitoring data in airborne storage equipment, and returning the real-time monitoring data after returning. And an unmanned aerial vehicle intelligent path planning system with high robustness, high autonomy and high task adaptability is constructed.

The invention discloses a circular small FOV magnetic resonance three-dimensional real-time imaging method applying a dynamic keyhole method, and the method comprises the steps: S1, selecting an out-of-region suppression pulse 2DRF and a 180-degree selection layer refocusing pulse 3D coding sequence as an imaging sequence, and achieving the imaging of a circular small FOV; s2, determining a scanning positioning line of an intervention process according to the intervention program, and obtaining pre-scanned reference image data; s3, a dynamic keyhole method is applied to two phase codes of the three-dimensional image, the number of phase codes in a keyhole is calculated according to reference image data, the phase codes of the sequence are modified accordingly, and keyhole data scanning is achieved; s4, performing registration on reference data and keyhole data obtained by real-time scanning by utilizing an image similarity function and a respiration monitoring method; and S5, performing rapid image reconstruction according to the registered data, and performing real-time imaging display on a display of the interventional image. The magnetic resonance real-time imaging method can give consideration to both the imaging quality and the imaging speed during interventional application.

This invention relates to the technical field of concealed pipeline mapping, and in particular to an auxiliary device for rapid three-dimensional coordinate positioning of concealed pipelines in installation projects. The invention includes a mother drone equipped with a probe and camera mounted on it. A marking nozzle is connected to the mother drone, and the marking nozzle is connected to and installed on a daughter drone. The mother drone connects the marking nozzle and the daughter drone via a flexible hose and power cable. The device uses a mother drone integrating a probe and camera, enabling multi-angle, omnidirectional spatial scanning and image acquisition of concealed pipelines. This achieves rapid and accurate three-dimensional coordinate positioning of the concealed pipelines, significantly improving the accuracy and reliability of the positioning. The mother drone connects the marking nozzle and the daughter drone via a flexible hose and power cable, enabling remote synchronous control. The daughter drone can flexibly move to the pipeline positioning point and automatically complete on-site marking, avoiding errors associated with traditional manual line drawing and improving the accuracy and consistency of the marking.

The utility model discloses an unmanned aerial vehicle visual navigation system which comprises a shell, and an MCU, a barometer, an RTK module, a 4G module, a UWB, a TTL-to-USB, a USB HUB, a PC, a visual module and a power supply system are integrally installed on the shell. The MCU communicates with the RTK module, the barometer and the TTL to USB chip; the 4G module is communicated with the USB HUB through one path of USB; the UWB is communicated with the TTL to USB through one path of UART; the PC is communicated with the USB HUB through one path of USB; the visual module communicates with the PC through a USB and is connected with the first camera and the second camera. According to the utility model, the structural design is scientific and reasonable, and the capability of accurate positioning and navigation can still be realized under the condition that GPS signals are lost; the system can provide more stable navigation performance in a dynamically changing environment; and positioning data are uploaded in real time and a cloud computing result is received through the 4G communication module, so that the flexibility and the expandability of the system are improved.

This invention belongs to the field of power technology, specifically disclosing a method, device, equipment, and medium for autonomous charging and navigation of unmanned aerial vehicles (UAVs). It includes the following steps: scanning environmental information to obtain LiDAR data; identifying charging station landmarks from the LiDAR data and establishing a coordinate system; processing the coordinate system using the ICP method to obtain pose gain; acquiring the odometer information corresponding to the pose gain; fusing the odometer information and pose gain using the extended Kalman filter method to obtain an estimated pose; and using the estimated pose as input for a PID control method to complete navigation. This invention, by applying landmark recognition and positioning navigation technology, replaces the traditional manual charging method, greatly reducing the need for human resources, lowering UAV charging costs, and improving charging efficiency.