WO2023098164A1 - Système de patrouille de véhicule aérien sans pilote et procédé de nid de machine de maillage - Google Patents

Système de patrouille de véhicule aérien sans pilote et procédé de nid de machine de maillage Download PDF

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Publication number
WO2023098164A1
WO2023098164A1 PCT/CN2022/114397 CN2022114397W WO2023098164A1 WO 2023098164 A1 WO2023098164 A1 WO 2023098164A1 CN 2022114397 W CN2022114397 W CN 2022114397W WO 2023098164 A1 WO2023098164 A1 WO 2023098164A1
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WIPO (PCT)
Prior art keywords
nest
uav
inspection
machine
landing
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PCT/CN2022/114397
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English (en)
Chinese (zh)
Inventor
刘越
刘俍
孙晓斌
李春飞
张飞
黄振宁
刘天立
李敏
赵金龙
张海龙
高绍楠
孙磊
王涛
周长明
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国网智能科技股份有限公司
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Application filed by 国网智能科技股份有限公司 filed Critical 国网智能科技股份有限公司
Publication of WO2023098164A1 publication Critical patent/WO2023098164A1/fr

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    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
    • G05D1/12—Target-seeking control

Definitions

  • the invention relates to the technical field of electric power inspection, and in particular to a gridded machine nest UAV inspection system and method.
  • UAV nest As a UAV support transfer station, the role of UAV nest is self-evident.
  • the deployment position of UAV nest is very important for UAV, which is directly related to the flight inspection radius of UAV and Operational efficiency and results.
  • the position of the drone nest is set randomly, or only a few drone nests are arranged sporadically, which often cannot achieve full coverage of the targets to be inspected; moreover, in the inspection process, each A single flight inspection of the target to be inspected does not involve the coverage of the surrounding short-distance waypoints, resulting in a waste of range and power in the inspection.
  • the UAV smart machine nest can realize the interconnection with the background monitoring center. After the on-site monitoring of the flight environment, most of the operators in the background monitoring center subjectively judge the on-site flight conditions, which has a low degree of intelligence, strong subjectivity and existence There is a certain possibility of misjudgment; or the judgment of flight conditions is simply patchwork, lacking a comprehensive judgment of multi-source data, causing certain safety hazards to the flight mission.
  • the UAV When the UAV recognizes the coordinates of the landing position, it needs high-precision real-time positioning. Not only the cost of positioning components is high, but also the coordinate data of the preset point of the UAV airport must be obtained in real time.
  • the landing control is cumbersome; in the prior art, there are solutions to realize the landing by identifying the specific image of the landing point, but most of them only identify a single data source, and the landing accuracy cannot be guaranteed.
  • the existing technology discloses the solution of using binocular vision to realize hover positioning and ranging. It is still to control the UAV to arrive at the inspection target in sequence, brake and hover, and then accelerate to the next inspection after taking a fixed-point photo. The goal is that the braking, hovering and acceleration of the UAV consume a lot of battery power, and it is impossible to realize the non-hovering autonomous inspection.
  • the present invention provides a grid-based UAV inspection system and method for nests, which realizes efficient UAV collaborative inspection based on grid-based UAV nests. , which reduces labor costs and meets the needs of normalized or emergency inspections for multiple inspection targets across fields.
  • the first aspect of the present invention provides an unmanned aerial vehicle inspection system for a gridded machine nest, including a plurality of machine nests deployed in a grid, and each machine nest is used to accommodate at least one unmanned aerial vehicle;
  • the machine nest includes a machine nest controller communicating with the control terminal, the machine nest controller communicates with the UAV remote controller, and the UAV remote controller communicates with the UAV;
  • the control terminal is used to obtain the inspection target corresponding to each machine nest based on the current cruising range of the UAV and the distance between the inspection target and each nest, with the shortest inspection time as the optimization goal, and generate each inspection target according to the determined inspection target.
  • the optimal inspection path of the UAV is sent to the nest controller.
  • machine nest includes:
  • the carrying mechanism includes a retractable landing platform and a first motor, and the landing platform is driven by the first motor;
  • the vertical fixing mechanism includes a first centering rod, one end of the first centering rod is arranged on the side wall of the machine nest body through a rotating shaft, gears are provided on the first centering rod, and gears are provided on the landing platform.
  • the rack meshed with the gear drives the first center rod to rotate around the rotation axis through the meshing of the gear and the rack;
  • the horizontal fixing mechanism includes a rotating rod, a second centering rod and a second motor, the two ends of the rotating rod are arranged on the side wall of the machine nest main body, and the second centering rod is arranged on the rotating rod;
  • the rod is driven by the second motor to rotate in the opposite direction to the moving direction of the landing platform relative to the main body of the machine nest, thereby driving the second centering rod to move in the vertical direction to the moving direction of the landing platform.
  • the first centering rods provided on the two side walls rotate around the axis, so that the other ends of the two first centering rods move toward the middle position or move toward both sides. Open.
  • a second centering rod is provided at both ends of the rotating rod.
  • the first center rod on the two side walls is driven to move to the middle position to restrain the drone vertically.
  • a second centering rod is provided at both ends of the rotating rod.
  • the first center rods on the two side walls are driven to open to both sides, so as to release the vertical restraint on the drone.
  • machine nest includes:
  • the main body of the machine nest includes the drone seat, charging module and energy storage module;
  • the main body of the machine nest is equipped with an installation module, and the installation module adopts a screw-type automatic locking structure to fix the main body of the machine nest.
  • the controller communicates with the charging module and the installation module respectively.
  • the drone is equipped with a three-axis gimbal, an RTK positioning module and a front-end AI processing module;
  • a camera and a video camera are installed on the three-axis pan/tilt; the camera is a monocular zoom camera; the video camera is used to obtain video information of the tower; wherein the camera and the video camera are integrated into one lens.
  • the RTK positioning module is used to locate the 3D coordinate information of the UAV
  • the front-end AI processing module is configured as:
  • the position of the gimbal of the drone is adjusted through the Kalman filter algorithm, and the zoom camera is locked to the target viewing point of the tower by zooming ;
  • the second aspect of the present invention provides a gridded machine nest drone inspection method, including the following process:
  • each machine nest performs inspection task planning tasks, and the tasks include:
  • the number of the inspection target is set, and the farther the distance is, the larger the number is;
  • this inspection target is taken as the current inspection target, and judge the time from the machine nest to the current inspection target, the inspection time of the current inspection target, and the latest time from the current inspection target to the number less than the current inspection target. Whether the sum of the inspection time of the primary inspection target, the time from the current inspection target to the secondary inspection target, and the time from the secondary inspection target to the machine nest is greater than the total endurance time of the drone;
  • the inspection target is taken as the task of the single base tower; if not, the route task of the second base tower is executed, and the inspection of the current inspection target and the secondary inspection target is carried out in turn.
  • the third aspect of the present invention provides a method for judging the environment of UAV task execution, using the above-mentioned UAV inspection system with gridded machine nests, including:
  • the selection of the target machine nest according to the position of the UAV includes: according to the position of the UAV, determine the perception range of the machine nest where the UAV is located, and use the machine nest that falls within the sensing range as the target machine nest; If more than one machine nest falls within the sensing range, the machine nest closest to the UAV is determined to be the target machine nest.
  • the fourth aspect of the present invention provides a precise landing control method for UAVs, using the above-mentioned UAV inspection system with gridded nests, including:
  • the UAV According to the acquired positioning data, it is judged whether the UAV is within the preset landing range; when the UAV is not within the preset landing range, the UAV is controlled to move until the position requirements are met;
  • the UAV When the precise landing range code is identified according to the acquired image data or video data, the UAV is controlled to descend to a position at a second preset distance from the landing point, and the image data or video data under the UAV is acquired again.
  • the acquired image data or video data recognizes the precise landing position code, the UAV is controlled to descend to a position at a fourth preset distance from the landing point, and the UAV is controlled to land.
  • the fifth aspect of the present invention provides a UAV inspection method based on visual movement tracking, using the above-mentioned UAV inspection system with gridded machine nests, including:
  • the image acquisition module on the gimbal is used to obtain a real-time wide-angle image of the inspection target;
  • step S2 Determine whether the inspection target is located in the real-time image captured by shooting, if so, go to step S3; otherwise, control the motion of the pan-tilt, change the posture, until the inspection target in the real-time image is searched;
  • the processing module uses the Kalman filter algorithm to fit the shooting position of the drone and the attitude of the gimbal according to the position of the inspection target in the real-time image, the shooting position of the UAV, and the attitude of the gimbal, and determines the focal length of the image acquisition module model;
  • S4 Control the unmanned aerial vehicle to fly at a constant speed to the shooting position obtained by fitting.
  • the processing module reversely adjusts the attitude of the gimbal in real time according to the three-dimensional direction of the uniform flying of the unmanned aerial vehicle, so as to achieve the real-time image setting of the image acquisition module. Lock the inspection target in a fixed area, and adjust the focal length mode of the image acquisition module;
  • the UAV arrives at the shooting position, confirms that the inspection target position is in the set area of the real-time image of the image acquisition module, and locks the inspection point for image acquisition;
  • S6 The processing module processes the collected pictures, controls the UAV to perform the next detection point task, and re-executes S1 until all detection point image collection tasks are completed.
  • the present invention innovatively designs a UAV inspection system for gridded nests, and proposes a UAV inspection method for gridded nests.
  • the distance between the inspection target and each machine nest is optimized by taking the shortest inspection time as the optimization goal, and the multi-type inspection targets corresponding to each machine nest are obtained, and the optimal inspection path of each UAV is generated according to the determined inspection target, which solves the problem of
  • the collaborative inspection optimization problem of single-base tower tasks and multi-base tower tasks realizes the optimization of the inspection path with the goal of minimum inspection time, and realizes the grid-based UAV nest for inspection targets in various fields
  • the high-efficiency UAV collaborative inspection reduces labor costs and meets the normalized or emergency inspection requirements for multiple inspection targets in various fields.
  • the invention innovatively proposes a UAV machine nest, designs a double-constraint technology for the UAV’s lateral and longitudinal constraints, and proposes a method for coordinating the centering rod group fixing mechanism with the rack and pinion mechanism
  • the UAV back-to-center solution solves the limitations of the single scene of the UAV nest and the problem of the stability of the UAV parking; improves the stability of the UAV landing in different inspection environments, and the UAV machine
  • the nest supports remote control operations, significantly improves the efficiency of inspection operations, realizes the diversification of application scenarios, and realizes the coverage of drones in a wider range.
  • the present invention innovatively proposes a method for judging the execution environment of UAV missions. According to different flight missions or return missions combined with different mission environment conditions, it is judged whether it is suitable to perform the mission, and it meets the logic requirements of the nest flight condition judgment. In complex flight situations, the judgment conclusion redundancy is realized through the nest self-judgment method, which improves the judgment accuracy and solves the limitations of single judgment conditions, subjective interference and low intelligence in the existing flight environment monitoring technology. With manual intervention, the autonomous prediction of flight conditions under different tasks is realized, which significantly improves the efficiency of UAV inspection and the safety of the machine nest system.
  • the present invention innovatively proposes a precise landing control method for UAVs. According to the positioning data of the UAV, the preliminary calibration of the UAV and the position to be landed is realized, and the real-time differential positioning data and the precise landing range code are integrated. And the precision landing position code, through continuous image recognition and distance approach, solves the problem of difficult drone landing control, realizes precise ladder control of drone landing, and improves the accuracy of drone landing control.
  • the present invention innovatively proposes a UAV inspection method based on visual movement tracking.
  • the UAV always follows the set Track flight, through the Kalman filter algorithm to fit the current position and speed data, adjust the gimbal attitude and camera zoom in real time to realize the camera's mobile tracking and locking shooting of the inspection target, and realize the non-hover inspection process of the drone
  • the automatic collection of the inspection target image greatly reduces the labor intensity of the inspection personnel
  • the present invention adopts the reverse movement tracking method to realize the relative stillness of the inspection target by dynamically adjusting the posture of the UAV and the pan-tilt camera; It greatly saves the power of the drone and the workload of a single flight; the acquisition of the inspection target in the present invention is completed based on a monocular camera, with a simple structure and low cost.
  • Fig. 1 is a schematic diagram of a drone inspection system for gridded machine nests provided by Embodiment 1 of the present invention.
  • Fig. 2 is a schematic diagram of the drone nest provided by Embodiment 1 of the present invention.
  • Fig. 3 is a schematic diagram of the main body of the drone nest provided by Embodiment 1 of the present invention.
  • Fig. 4 is a schematic diagram of driving the gear at the bottom of the first centering rod provided in Embodiment 1 of the present invention.
  • Fig. 5 is a schematic diagram of resetting the first centering rod and the second centering rod provided in Embodiment 1 of the present invention.
  • Figures 6(a)-6(b) are schematic diagrams of the centering of the drone provided by Embodiment 1 of the present invention.
  • FIG. 7(a)-7(b) are schematic diagrams of the landing of the drone provided by Embodiment 1 of the present invention.
  • Fig. 8 is a schematic diagram of the installation of the drone nest provided by Embodiment 1 of the present invention.
  • Fig. 9(a) is a schematic diagram of the internal structure of the mobile drone nest provided by Embodiment 2 of the present invention.
  • Fig. 9(b) is a schematic diagram of the structure of the mobile UAV nest hatch provided by Embodiment 2 of the present invention.
  • FIG. 10 is a schematic structural diagram of a charging module provided by Embodiment 2 of the present invention.
  • Fig. 11 is a schematic structural diagram of the drone seat fixing device provided by Embodiment 2 of the present invention.
  • FIG. 12 is a schematic diagram of a partial structure of the drone seat fixing device provided by Embodiment 2 of the present invention.
  • Fig. 13(a) is a schematic structural diagram of the installation module provided by Embodiment 2 of the present invention.
  • Fig. 13(b) and Fig. 13(c) are schematic diagrams of the partial structure of the installation module provided by Embodiment 2 of the present invention.
  • Fig. 14 is a workflow diagram of the UAV system provided by Embodiment 2 of the present invention.
  • FIG. 15 is a schematic diagram of the route planning process provided by Embodiment 3 of the present invention.
  • FIG. 16 is a first schematic diagram of mission planning provided by Embodiment 3 of the present invention.
  • FIG. 17 is a second schematic diagram of mission planning provided by Embodiment 3 of the present invention.
  • FIG. 18 is a schematic diagram of division of task instructions and corresponding environmental factors provided by Embodiment 4 of the present invention.
  • Fig. 19 is a schematic diagram of judging the execution environment of the drone storage task provided by Embodiment 4 of the present invention.
  • FIG. 20 is a schematic flowchart of a method for controlling a precise landing of a drone provided in Embodiment 5 of the present invention.
  • FIG. 21 is a schematic flow chart of the autonomous inspection method for drones provided by Embodiment 6 of the present invention.
  • pole tower 2. machine nest bottom support, 3. machine nest, 4. landing platform, 5. top cover, 6. machine nest main body, 7. rotating rod, 8. second motor, 9. first motor , 10, the second center pole, 11, the charging pole, 12, the charging port, 13, the first center pole, 14, the rack, 15, the fixing seat; 16, the charging module; 17, the drone seat; 18. Energy storage module; 19. Display module; 20. Charging port; 21. BMS control board; 22. Cooling fan; 23. Communication interface; 24. Charging indicator light; 25. First clamping part; 26.
  • Elastic part ;27 the second clamping piece; 27-1, the handle; 27-2, the first sleeve; 27-3, the first telescopic rod; 27-4, the fixed end; 27-5, the first spring; 28 , the second sleeve; 29, the double shaft motor; 30, the second telescopic rod; 31, the spring slider; 31-1, the first slider; 31-2, the second spring; 31-3, the second slider block; 32, lead screw; 33, unmanned aerial vehicle; 34, machine nest.
  • Embodiment 1 of the present invention provides an unmanned aerial vehicle inspection system for a gridded machine nest, as shown in Figure 1, including a plurality of machine nests 34 deployed in a grid, each machine nest is used to accommodate at least one Drone 33;
  • the machine nest includes a machine nest controller communicating with the control terminal, the machine nest controller communicates with the UAV remote controller, and the UAV remote controller communicates with the UAV;
  • the control terminal is used to obtain the inspection target corresponding to each machine nest based on the current cruising range of the UAV and the distance between the inspection target and each nest, with the shortest inspection time as the optimization goal, and generate each inspection target according to the determined inspection target.
  • the optimal inspection path of the UAV is sent to the nest controller.
  • the substation is selected as the main deployment point of the UAV machine nest, and the UAV can first conduct inspections on the nearby substation equipment; the surrounding area of the substation is the main intersection of power lines, and it is also an area that needs to be inspected.
  • the inspection around the substation can inspect the power lines to the greatest extent; the drone nest is deployed in the substation, and can also be used as a part of the maintenance of the substation to facilitate operation and maintenance.
  • the UAV nest can also be properly deployed in places such as 5G base stations or mountaintop photovoltaics, and can also take targets in other fields as inspection targets, such as the communication field, fire protection field, etc. , as long as there is electricity, the drone nest can be deployed.
  • the drone nest described in this embodiment is a miniaturized drone nest, including: a nest main body, a bearing mechanism, a vertical A fixing mechanism and a lateral fixing mechanism; the carrying mechanism includes a retractable landing platform and a first motor, and the landing platform is driven by the first motor;
  • the vertical fixing mechanism includes a first centering rod, one end of the first centering rod is arranged on the side wall of the machine nest body through a rotating shaft, gears are provided on the first centering rod, and gears are provided on the landing platform.
  • the rack meshed with the gear drives the first center rod to rotate around the rotation axis through the meshing of the gear and the rack;
  • the horizontal fixing mechanism includes a rotating rod, a second centering rod and a second motor, the two ends of the rotating rod are arranged on the side wall of the machine nest main body, and the second centering rod is arranged on the rotating rod;
  • the rod is driven by the second motor to rotate in the opposite direction to the moving direction of the landing platform relative to the main body of the machine nest, thereby driving the second centering rod to move in the vertical direction to the moving direction of the landing platform.
  • the machine nest main body 6 is a rectangular frame structure
  • the top of the machine nest main body 6 is provided with a top cover 5
  • the top cover 5 is provided with a solar photovoltaic panel to absorb light energy through the solar photovoltaic panel , and convert light energy into electrical energy storage, as the power support of the machine nest.
  • the top cover 5 is sloped to prevent water accumulation on the top of the machine nest.
  • the nest body 6 is provided with a retractable landing platform 4.
  • the landing platform 4 When the drone lands, the landing platform 4 is pushed out inside the nest body 6 to carry the drone, and the drone lands. Finally, the landing platform 4 is recovered into the machine nest main body 6; when the drone performs inspection tasks, the landing platform 4 is pushed out inside the machine nest main body 6, the drone takes off, and then the landing platform 4 is recovered to the machine nest main body within 6.
  • the three sides of the machine nest main body 6 are closed, and the forward surface forms a closed surface with the landing platform 4 to ensure the overall protective performance of the machine nest.
  • the first motor 9 is connected to the landing platform 4 through a rod, so as to drive the landing platform 4 to push out of the machine nest main body 6 or to be recovered into the machine nest main body 6 .
  • first motors 9 there are two first motors 9 .
  • slide rails are provided at both ends of the machine nest main body 6, and the two ends of the rotating rod 7 are arranged on the slide rails of the machine nest main body 6 through rolling pulleys, and the first Two motors 8 control the rotation of the rotating rod 7; the rotating direction of the rotating rod 7 is opposite to the moving direction of the landing platform 4.
  • the end of the second back center rod 10 is provided with a chute, and a second back center rod 10 is respectively set at the two ends of the rotating rod 7, and the second back center rod 10 is arranged on the rotating rod 7 through the chute.
  • the rotating rod 7 is provided with a screw thread, and the second centering rod 10 moves in one direction along the screw thread with the rotation of the rotating rod 7 through the chute.
  • the rotating rod 7 adopts a lead screw.
  • the rotating rod 7 rotates on the slide rail under the drive of the second motor 8, and controls the movement direction of the second centering rod 10 according to the rotating direction of the rotating rod 7;
  • the second centering rods 10 on both sides move back to the center, that is, move to the middle position; when the rotating rod 7 rotates reversely, the second centering rods 10 on both sides move toward Move in the opposite direction, that is, open to both sides; through the rotation of the rotating rod 7 on the slide rail and the movement of the second centering rod 10 through the chute, the force of the reciprocating movement of the second centering rod 10 with the rotating rod 7 is balanced. It is ensured that the second back center rod 10 is a displacement of one-way degree of freedom.
  • the second centering rod 10 on both sides moves in the opposite direction, that is, opens to both sides; at this time, it is also used for the second returning centering rod 10 to open After that, the unmanned aerial vehicle on the landing platform 4 can fly out;
  • the second center rod 10 on both sides will move back to the center, that is, move to the middle position; at this time, it is also used for the lateral movement of the drone on the landing platform. Reset, lateral constraints immobilize the drone.
  • first centering rods 13 are provided on the two opposite side walls of the main body 6 of the machine nest. Under the engagement of the gear and the rack, the first centering rods 13 on both sides rotate around the axis. So that the other end of the first centering rod 13 moves to the middle position or opens to both sides.
  • the first centering rod 13 is provided with a gear, and the landing platform 4 is connected to the rack 14 by screws, and the rack 14 is engaged with the gear; , the gear rotates, and by the meshing of the rack and pinion, it drives the first return middle rod 13 to rotate around the axis; when the first return middle rod 13 rotates around the axis, the moving power is converted into the rotational power moment by the rack and pinion transmission.
  • the first return middle rod 13 is used for vertical reset of the drone, the first return middle rod 13 makes a circular rotation around the axis through the rotating shaft, and the other end rotates around the axis to the middle position through the rotation, so as to Fixed drone.
  • the reset of the UAV is completed through the joint push of the second back middle rod 10 and the first back middle rod 13. As shown in FIG. The promotion of the centering rod 10 resets horizontally, and a part completes the vertical reset by the rotation of the first centering rod 13 .
  • the first motor 9 pushes the landing platform 4 to open the front side of the nest body 6, and during the opening process, the second center lever 10 is opened, and the reverse direction of the rotation lever 7 Rotate, the second back center rod 10 on both sides moves in the opposite direction, that is, open to both sides, and release the lateral fixation to the drone; at the same time, the rack connected to the landing platform 4 is pushed forward synchronously with the landing platform 4, through The meshing of the gear rack 14 in the landing platform 4 and the gear in the first center rod 13 drives the rotation of the first center rod 13, and the first center rod 13 on both sides rotates around the axis, and also opens to both sides, releasing The vertical fixation of the UAV allows the UAV to take off autonomously according to the planned route for inspection operations.
  • charging rods 11 are also provided at both ends of the nest main body 6, and several charging ports 12 are provided on the charging rods. After the UAV is reset, the charging contact plate at the bottom of the UAV contacts the charging ports. 12. Charging is carried out through the machine nest control command.
  • the unmanned aerial vehicle When the unmanned aerial vehicle performs an inspection mission, first detect the remaining power of the battery, and when the power is insufficient, charge the power battery of the unmanned aerial vehicle through the charging port 12; The plane took off.
  • the above-mentioned unmanned aerial vehicle nest as a general-purpose unmanned aerial vehicle nest, can be applied to a pole tower.
  • the installation process is shown in Figure 8.
  • the nest 3 is installed on the On the pole tower 1, the machine nest 3 is connected with the machine nest bottom support by screws, and the machine nest bottom support 2 is fixedly installed on the pole tower 1 by bolts. In different terrains, it can rely on pole tower settings, which can realize diversified scenes.
  • the above-mentioned drone nest can be used with a vehicle-mounted drone, and the drone nest is installed on the roof of the vehicle through the bottom support of the nest.
  • Embodiment 2 of the present invention provides a drone inspection system for gridded nests, including multiple nests deployed in a grid, and each nest is used to accommodate at least one drone;
  • the machine nest includes a machine nest controller communicating with the control terminal, the machine nest controller communicates with the UAV remote controller, and the UAV remote controller communicates with the UAV;
  • the control terminal is used to obtain the inspection target corresponding to each machine nest based on the current cruising range of the UAV and the distance between the inspection target and each nest, with the shortest inspection time as the optimization goal, and generate each inspection target according to the determined inspection target.
  • the optimal inspection path of the UAV is sent to the nest controller.
  • the machine nest described in this embodiment is a mobile drone machine nest, including a main controller and a machine nest body, and the inside of the machine nest body includes a charging module 16 , unmanned aerial vehicle machine position 17, energy storage module 18 and display module 19;
  • described machine nest main body is provided with installation module, and described installation module adopts lead screw type automatic locking structure to machine nest main body is fixed;
  • Said The UAV stand is provided with a UAV fixing device for autonomous shock absorption in the horizontal and vertical directions, and the main controller is respectively connected with the charging module and the installation module.
  • the charging module includes several charging ports 20, BMS (BATTERY MANAGEMENT SYSTEM) control board 21, charging cooling fan 22, communication interface 23 and charging indicator light 24;
  • BMS BATTERY MANAGEMENT SYSTEM
  • the UAV position of the main body of the machine nest can place mainstream RTK (Real-time kinematic) UAVs in the market. Since the application scene of the present invention corresponds to the mobile UAV machine nest, it is often faced with random situations in different terrain environments.
  • the car moves, so a fixing device is provided at the position of the drone for fixing the drone.
  • the fixing device includes a first clamping part 25 and a second clamping part 28, and the first clamping part and the second clamping part are connected by an elastic part 27 to form a clamping structure (Similar clip structure).
  • the first clamping part 25 is fixed on the surface of the drone stand, as shown in Figure 12,
  • the second clamping part includes a handle 27-1, a first sleeve 27-2, a first spring 27-5.
  • the two telescopic rods 27-3 located at both ends of the sleeve and the fixed end, the first spring is located in the middle of the sleeve, and the two ends of the first spring are respectively fixedly connected to one end of the two telescopic rods , through the first spring, the pulling force is applied to the center of the sleeve on the two telescopic rods, and the horizontal direction of the UAV is fixed through the fixed end.
  • the fixed end is based on the clip formed by the fixing device.
  • the holding structure realizes the vertical fixation of the UAV. Based on the spring of the fixing device in the horizontal direction and the elastic member in the vertical direction, the fixing device can be better fixed on the one hand, and on the other hand, the spring and the elastic member serve as damping absorption The force in the horizontal and vertical directions of the UAV realizes vibration reduction protection and further ensures the safety of the UAV.
  • the nest body is provided with an installation module for installing the drone nest, wherein the installation module runs through the nest body and is fixedly connected to the nest body, as shown in Figure 13(a)- As shown in Figure 13(c), the installation module uses a screw type automatic locking structure to fix the main body of the machine nest;
  • the screw type automatic locking structure includes a second sleeve 28 and a sleeve fixed at the center Double output shaft motor 29, the two ends of the rotor of the double output shaft motor are respectively fixedly connected with a section of the lead screw 32, the other end of the lead screw 32 is connected with an end of the spring slider 31 through a threaded hole, and the spring slider 31 moves horizontally and linearly with the rotation of the lead screw, and drives the expansion and contraction of the second telescopic rod 30 fixedly connected with the other end of the spring slider.
  • the spring slider 31 includes a first slider 31-1 and a second slider 31-3, and the first slider 31-1 and the second slider 31-3 are connected by a second spring 31-2 .
  • the first slider 31-1 of the spring slider 31 is provided with a threaded hole matching the lead screw 32, and the second slider 31-3 is at a position corresponding to the first slider 31-1.
  • a circular hole is provided, and the diameter of the circular hole is larger than the outer diameter of the lead screw.
  • one end of the fixed rod fixedly connected with the second slider is also provided with a hole of a preset length, and the diameter of the hole is also larger than that of the screw. The outer diameter of the bar.
  • a pressure sensor is provided on the first slider 31-1, and the pressure sensor is connected to the main controller; at the same time, the main controller is connected to the double output shaft motor, And based on the comparison result of the obtained pressure value of the pressure sensor and the preset threshold value, the operation of the double output shaft motor is controlled.
  • the working mechanism of the installation module is as follows:
  • the double output shaft motor is used as the power core to drive the lead screw to rotate, and the rotation of the lead screw will cause the power block to displace in the horizontal direction, and the power block will transmit the thrust through the spring to make the fixed end gradually contact with the cargo box (the compartment of the pickup truck in this embodiment)
  • the power block is equipped with a pressure sensor. When the sensor receives the reaction force from the carriage and reaches a predetermined value, it forms a feedback, and the double output shaft motor stops rotating and locks automatically. When the vehicle is bumped, the spring acts as a damper to absorb the vibration and maintain the self-stable state of the mobile nest.
  • the UAV performs operations according to the inspection tasks.
  • the autonomous inspection software of the UAV is equipped in the machine nest, and the refined inspection operation is carried out according to the track planning plan prepared in advance.
  • the current state of the man-machine and the specific working mode After the drone operation is completed, the staff will manually replace the battery of the drone to give full play to the subjective initiative of the operator.
  • the main controller is also connected with a display module for displaying the status of the battery in the charging port of the charging module, and issuing commands through the display module.
  • the issuing of the order includes an installation order (that is, installing the UAV nest in the vehicle) and issuing an operation task to the UAV.
  • the energy storage module 18 is used as the mobile operation energy supply module of the machine nest, and is equipped with a special charging gun to charge it.
  • the energy storage module supports the machine Various power supplies in the nest, including charging modules, display modules, and main control modules.
  • the personnel operate the installation module through the display module to automatically lock it with the pickup truck; when the UAV is performing inspection operations, the vehicle Bring the mobile nest to the vicinity of the work site.
  • the personnel open the aircraft fixing device, take out the drone, select the battery recommended by the charging module for installation, and select a suitable inspection route through the autonomous flight software in the nest.
  • the human-machine completes the inspection operation independently. After the task is completed, the staff replaces the battery and puts the aircraft back into the nest.
  • Embodiment 3 of the present invention provides a method for inspecting drones in gridded nests, specifically including:
  • this embodiment takes the tower as the inspection target as an example.
  • the position coordinates of several poles and towers are (X1, Y1, Z1), (X2, Y2, Z2), ..., (Xn, Yn, Zn), taking the position of the machine nest as the center of the sphere or plane, and moving in three directions X, Y , Z-axis extension, assuming the coordinates (Xn, Yn, Zn) of the tower N, the straight line is the shortest between two points, so the straight-line distance of the UAV flying from the machine nest to the tower N is
  • the inspection complexity of a single tower is determined according to the tower type (strain tower, straight tower, corner tower, etc.), and the inspection complexity can be determined according to the three-dimensional point cloud model of the tower.
  • the time Tn is used to represent the complexity of the tower N, where The physical meaning is the time it takes for the UAV to inspect the power tower.
  • the number of the towers from near to far from the origin of the machine nest is 1, 2, 3, ..., n, provide the basis for the follow-up planning method, the cruise capability of the UAV is T, the inspection speed of the UAV is V, and the coordinates of the nest position are (0, 0, 0).
  • route autonomous planning The method and steps of route autonomous planning are as follows: the basic principle of route planning is to first plan the tower far from the origin of the machine nest, that is, Start with the largest and decrease in turn for judgment.
  • the plan confirms that only one base tower can be inspected.
  • This task satisfies the condition that the towers within the coverage of the machine nest, far away from the origin of the machine nest, and with high tower complexity are screened out and executed as a single base tower task. , expressed as:
  • the complexity of the tower N is denoted as Tn, and the unit is seconds.
  • the three-dimensional coordinates of the tower N are denoted as (Xn, Yn, Zn), and the unit is meters.
  • the cruising capability of the drone is denoted as T, and the unit is seconds.
  • Man-machine inspection speed V in meters per second, and machine nest position (0, 0, 0), in meters.
  • the judgment principle of the above formula is: after the UAV has inspected a certain base tower alone, the remaining battery life is less than the complexity T of all other towers within the coverage of the machine nest, that is, the basic tower can only be completed by a single inspection task. These towers are considered to be the furthest line missions covered by the nest.
  • T n-1 is the surrounding tower that is closer to Tn straight-line distance, because its number is n-1, so it is closer to the origin of the machine nest; so far, the routes of all single-base tower missions have been planned.
  • the judgment principle is that after the drone has inspected a base tower alone, the remaining battery life is only enough to continue the inspection of a base tower near the tower, and the drone will fly straight to the nearby tower.
  • the tower continues to patrol, and then returns to the machine nest in a straight line, and its route path forms a triangle.
  • the order of route planning is from far to near, that is, the number is from large to small. After the inspection of a certain tower is completed, there is still endurance. When searching for nearby towers, only the towers with a smaller number than the current tower can be searched. No., to ensure the clarity of the method.
  • the route task that includes the three base towers.
  • the route task constitutes a quadrilateral.
  • the tower 3-2-1 on the left side of Figure 16 is a clockwise search method, which can avoid overlapping routes and optimize the route path, because Tower 3 is farther away from the origin of the machine nest than tower 1, and the route planning is calculated from tower 3.
  • the route task when the route task is determined, it can be inspected in reverse order, such as tower 3-2-1 or 1-2-3. It is feasible, because the distance of the inspection path is equal.
  • the reason why the planned route here is 3-2-1 follows the planning principle of the tower from far to near. This principle is calculated in the opposite way from near to far. The path out is shorter.
  • the plan of the four-base route is an irregular pentagon, and the sum of the lengths of the five sides is the total length of the route.
  • the towers that are farther away from the origin of the machine nest have been planned into the route. The closer the towers are to the origin of the machine nest, the wider the range of the search for nearby towers will be. This is because the distance The closer the origin of the machine nest, the remaining battery life of the tower will be greater and greater.
  • the difference between the two diagrams is the route planning of towers 6, 1, 2, and 3.
  • tower 6 is planned first, and towers in the nearby range are searched according to the endurance capability. If the search range does not include tower 1, then the left As shown in the figure, tower 6 can only be planned as a single-base route task, and as shown in the right figure, if the planning range of tower 6 includes tower 1, then calculate the triangular route formed by tower 6, tower 1 and the origin of the machine nest To meet the endurance capability of the UAV, the tower 6 and the tower 1 are planned as a dual-base route.
  • the grid is embodied in the deployment of multiple machine nests based on substations in an area all over the power towers, and the staggered deployment in this area like a grid.
  • the optimal path generation method is:
  • the power towers within the coverage of the machine nest are numbered from near to far from small to large, and the initial towers of the route planning are numbered from the largest number that is the distance to the UAV machine nest. Starting from the farthest tower, it is enough to judge whether the tower is a single-base route mission or a multi-base route mission from far to near.
  • the machine nest deployed in the substation is not limited to one.
  • a substation can deploy multiple machine nests to complete line inspections with different requirements such as different directions or different voltage levels.
  • the grid deployment in such a substation further increases the significance and feasibility of the grid grid.
  • each tower only exists in a certain route mission of a certain drone nest, ensuring that there is no repeated inspection path.
  • the background control terminal issues only the routes owned by the nest to ensure the one-to-one correspondence between each route and the UAV nest.
  • Embodiment 4 of the present invention provides a method for judging the execution environment of a UAV task, using the UAV inspection system of the gridded machine nest described in Embodiment 1 or Embodiment 2, the method includes:
  • Select the target machine nest according to the position of the drone determine the corresponding flight influencing factors according to the flight instructions, and retrieve the corresponding flight environment data from the external environment information of the selected target machine nest; judge the flight conditions according to the flight environment data, If the flight environment data does not meet the flight conditions, control the UAV to return;
  • the data controls the landing method of the drone, and adjusts the environment in the machine nest according to the return environment data until the drone returns to the target machine nest.
  • the environmental information in the machine nest includes: temperature in the machine nest, humidity in the machine nest, and smoke concentration in the machine nest;
  • the environmental information in the machine nest is collected by temperature sensors, humidity sensors and smoke sensors;
  • the temperature sensor is used to collect the ambient temperature in the machine nest.
  • the temperature in the machine nest can reach the normal working range by controlling the heating function of the air conditioner.
  • the temperature is higher than the upper limit of the set temperature range, Turn on the cooling function of the air conditioner to make the ambient temperature inside the machine nest reach the normal working range;
  • the humidity sensor is used to detect the ambient humidity in the machine nest, and when the humidity in the machine nest is higher than the set threshold, the dehumidification function of the air conditioner is turned on;
  • the smoke sensor is used to detect Smoke concentration in the machine nest.
  • the environment information outside the machine nest includes: wind speed, wind direction, temperature outside the machine nest, humidity outside the machine nest, rainfall, air pressure, light intensity and visibility;
  • the environmental information outside the machine nest is collected by wind speed sensors, wind direction sensors, temperature sensors, humidity sensors, rain gauges, barometers, photosensitive sensors and visibility sensors;
  • the wind speed sensor is used to measure the wind speed at the location of the machine nest;
  • the wind direction sensor is used to measure the wind direction;
  • the temperature sensor is used to measure the ambient temperature;
  • the humidity sensor is used to measure the ambient humidity;
  • the barometer is used to measure the local air pressure;
  • the photosensitive sensor is used to measure the current light intensity;
  • the visibility sensor can continuously output the atmospheric visibility.
  • the above-mentioned several sensors transmit the collected data through wireless communication.
  • wireless communication can adopt UWB wireless communication technology, which has the characteristics of low power consumption, high data transmission rate, strong anti-interference ability, and strong penetrating ability.
  • UWB wireless communication is only an achievable implementation method given in this embodiment, but it is not limited to this wireless communication method.
  • other wireless communication methods can also be used according to the actual situation on site. , such as 4G, 5G, etc.
  • various types of sensors are used to collect the internal and external environmental data of the machine nest, and the collected sensory data are preprocessed, and the preprocessing includes: preprocessing the sensor data through a moving average low-pass filter Processing, filtering out jumps or abnormal environmental information, and obtaining relatively stable environmental information after preprocessing;
  • the influencing factors are divided according to the mission instructions, so as to judge the flight conditions according to different mission instructions combined with the required influencing factors;
  • the task instruction includes UAV storage, UAV charging, UAV inspection, machine nest self-inspection, machine nest switch action, machine nest open state, UAV flight task, wireless Man-machine precise landing, unmanned aerial vehicle backup landing, etc.;
  • the main influencing factors of UAV storage, UAV charging and machine nest self-inspection are the environmental information in the machine nest, including the temperature in the machine nest, the humidity in the machine nest, and the smoke concentration in the machine nest;
  • the main influencing factors of drone inspection include: wind speed, wind direction, temperature outside the machine nest, rainfall, barometer, light intensity, and visibility;
  • the main factors affecting the switch action of the machine nest are the rainfall and the smoke concentration in the machine nest;
  • the main influencing factors in UAV flight missions are wind speed, wind direction, barometer, and visibility;
  • the main factors affecting UAV precision landing are wind speed, wind direction, light intensity, and visibility;
  • the main factors affecting the drone landing are wind speed and wind direction.
  • Preset temperature threshold, humidity threshold and smoke threshold Preset temperature threshold, humidity threshold and smoke threshold
  • the current judgment result and abnormal factors are packaged into message information for push, and the output of the corresponding task uses U8 type data to represent the current judgment result and abnormal factors, where 01 is the task number, and the following 8-bit data It is used to indicate the judgment result, where the judgment conclusion is the comprehensive environment judgment result, 0 is abnormal, 1 is suitable; the following is the sensor judgment conclusion, 0 is the current environment item is abnormal, otherwise the environment is suitable, when the environment judgment result is 1, the sensor judgment The results are all 1, otherwise, judge which environment does not meet the current task requirements through the register data at the location of the sensor, and so on to form message information under different tasks, and directly call the judgment result according to the current task status, and decide whether to execute task decision.
  • the packet information is sent out at a rate not lower than a set rate.
  • the above method can be applied to a single-machine nest and an unmanned aerial vehicle that performs flight tasks within the range of perception of a single-machine nest, specifically including:
  • one nest and one machine are adopted, and the flight missions of the UAV are all within the perception range of the nest, so the nest can collect the environmental information of the UAV during the flight mission and the return flight in real time. So as to judge the condition.
  • the specific methods include :
  • the target machine nest selected by the position of the UAV, determine the corresponding flight influencing factors according to the flight instructions, and retrieve the corresponding flight environment data from the environmental information outside the machine nest; judge the flight conditions according to the flight environment data, if the flight environment When the data does not meet the flight conditions, control the UAV to return;
  • the landing method is to adjust the environment in the machine nest according to the return environment data until the drone returns to the target machine nest.
  • the distance between the nests does not exceed its sensing distance, that is, if the drone flies out of the sensing range of one nest, it will fall into the sensing range of the other nest, so according to the The position of the drone is judged whether the UAV falls within the sensing range of the nest, and the nest that falls into the sensing range is used as the target nest, and the target nest collects the environmental information of the drone during the flight mission and the return flight;
  • the closest nest will be used as the target nest according to the distance between the drone and the nest.
  • the UAV flight condition judgment process of the above method specifically includes:
  • the drone takes off and performs inspection tasks
  • the UAV will return and judge whether the current environment meets the precision landing conditions
  • the UAV will be executed as an alternate landing
  • the UAV will be forced to land, and the forced landing status and unfavorable factors will be uploaded.
  • the process of adjusting the environment in the machine nest includes:
  • the temperature in the machine nest can reach the normal working range by controlling the heating function of the air conditioner;
  • the air conditioner cooling function is turned on to make the ambient temperature inside the nest reach the normal working range
  • the UAV will be executed as an alternate landing.
  • Embodiment 5 of the present invention provides a precise landing control method for UAVs, using the UAV inspection system for gridded machine nests described in Embodiment 1 or Embodiment 2, including the following process :
  • the UAV According to the acquired positioning data, it is judged whether the UAV is within the preset landing range, and when the UAV is not within the preset landing range, the UAV is controlled to move until the location requirements are met;
  • the UAV When the precise landing range code is identified according to the acquired image data or video data, the UAV is controlled to descend to a position at a second preset distance from the landing point, and the image data or video data under the UAV is acquired again.
  • the acquired image data or video data recognizes the precise landing position code, the UAV is controlled to descend to a position at a fourth preset distance from the landing point, and the UAV is controlled to land.
  • the fine-falling range code and the fine-falling position code are next to each other, one big and one small, and the big one is called the fine-falling range code, which is used at high altitude and is mainly used to determine the approximate location of the drone’s landing. Landing, adjust posture.
  • the small one is called the precision landing position code. When it reaches low altitude, the UAV starts to recognize it, constantly adjusts its posture and finally lands on this small UAV precision landing position code.
  • the method described in this embodiment first utilizes the UAV RTK technology to enable the UAV to quickly and accurately return to the top of the landing point after performing the task.
  • the RTK technology can make the error of the UAV flight reach the centimeter level, so that no one
  • the drone can quickly return to the landing point without updating the coordinates multiple times; when it reaches the landing range, turn on the camera to search the landing range code, receive the image and complete the recognition within 0.7s Return to the drone to adjust its posture and land to a height of 20 cm to achieve Blind landing, to realize the complete automation of drone inspection tasks.
  • Embodiment 6 is a diagrammatic representation of Embodiment 6
  • Embodiment 6 of the present invention provides a UAV inspection method based on visual movement tracking, using the UAV inspection system of gridded machine nest described in Embodiment 1 or Embodiment 2, wherein:
  • the UAV is equipped with a three-axis gimbal, an RTK positioning module and a front-end AI processing module, and a camera and a video camera are installed on the three-axis gimbal; the camera is a monocular zoom camera; the camera is used to obtain video information of the tower; , the camera and video camera are integrated in one lens.
  • the RTK positioning module is used to locate the 3D coordinate information of the UAV
  • the front-end AI processing module is used to fit the UAV flight control data, RTK positioning module data and zoom camera to collect images, issue flight control commands to control the flight of the UAV, control the gimbal to adjust the camera angle and zoom, and lock the inspection target And take pictures; use the visual zoom wide-angle camera to take photos during the flight approaching the hovering point, calculate the coordinate value (GPS value) and the attitude of the gimbal of the photo, and identify the inspection target in the photo through the camera imaging principle; according to The current GPS position and three-dimensional velocity of the UAV and the roll angle, pitch angle and yaw angle of the attitude of the gimbal are adjusted by the Kalman filter algorithm to adjust the position of the gimbal of the UAV, and the zoom camera is locked to the target inspection point of the tower through zooming; Finally, take pictures to complete the information collection of the tower target inspection point, thereby improving the accuracy of the inspection target information collection and the quality of the collected images.
  • the UAV During the flight process between the UAV entering the inspection target and leaving the inspection target, the UAV always flies according to the set track, and adjusts the attitude of the gimbal and the camera in real time by fitting the current position and speed data through the Kalman filter algorithm Zooming realizes the camera's mobile tracking and locking shooting of the inspection target.
  • the subscript cw represents the abbreviation for converting the earth coordinate system to the camera coordinate system
  • R cwx ( ⁇ ), R cwy ( ⁇ ), and R cwz ( ⁇ ) represent the need to go around x, y
  • the matrix of z-axis rotation, ⁇ , ⁇ They are the roll angle, pitch angle, and yaw angle of the camera gimbal attitude respectively.
  • an initial rotation R cw0 needs to be multiplied to the left.
  • R cw R cw0 ⁇ (R cwx ( ⁇ ) ⁇ R cwy ( ⁇ ) ⁇ R cwz ( ⁇ ))
  • the specific steps include:
  • S2 Determine whether the inspection target is located in the real-time image captured by shooting, if so, go to S4; otherwise, the "O" shape controls the pan-tilt attitude to search for the inspection target in the real-time image, and enters the next step after finding it;
  • the front-end AI processing module uses the Kalman filter algorithm to fit the position of the drone, the position of the gimbal and the camera that need to be adjusted according to the position of the inspection target in the real-time image, the shooting position of the drone, and the attitude of the three-axis gimbal.
  • focal length mode go to S2;
  • the drone arrives at the hovering point, that is, the frontal direction of the inspection target, confirms the central position of the real-time image of the monocular zoom camera, locks the inspection point and takes a photo, and enters the next step;
  • the Faster-RCNN algorithm is used to input the picture into CNN for feature extraction; and then judge whether there is an inspection target in the picture.
  • This step assumes that the inspection target object has been identified in the image through S2;
  • the rotation direction of the gimbal is the direction that makes the tower offset to the center of the image; first rotate the gimbal by the smallest unit to obtain the tower at the current position image, and extract its features;

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Abstract

Système de patrouille de véhicule aérien sans pilote (33) et procédé d'un nid de machine de maillage (3, 34). Le système comprend une pluralité de nids de machine (3, 34) déployés dans un mode de maillage, chaque nid de machine (3, 34) étant utilisé pour recevoir au moins un véhicule aérien sans pilote (33) ; le nid de machine (3, 34) comprend un dispositif de commande de nid de machine qui communique avec un terminal de commande ; le dispositif de commande de nid de machine communique avec un dispositif de commande à distance de véhicule aérien sans pilote ; le dispositif de commande à distance de véhicule aérien sans pilote communique avec le véhicule aérien sans pilote (33) ; et le terminal de commande est utilisé pour générer, en fonction du kilométrage d'endurance actuel du véhicule aérien sans pilote (33) et d'une distance entre une cible de patrouille et chaque nid de machine (3, 34) en utilisant un temps de patrouille le plus court comme cible d'optimisation, un trajet de patrouille optimal du véhicule aérien sans pilote (33) et en envoyant le trajet de patrouille optimal au dispositif de commande de nid de machine. La présente invention présente les effets bénéfiques suivants : la réalisation d'une patrouille collaborative efficace du véhicule aérien sans pilote (33) sur la base des nids de machine de véhicule aérien sans pilote (3, 34) qui sont agencés dans le mode de maillage, la réduction du coût de main-d'œuvre et la satisfaction d'exigences de patrouille normalisées ou émergentes pour une pluralité de cibles de patrouille dans des champs.
PCT/CN2022/114397 2021-12-03 2022-11-02 Système de patrouille de véhicule aérien sans pilote et procédé de nid de machine de maillage WO2023098164A1 (fr)

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116614377A (zh) * 2023-07-20 2023-08-18 北京邮电大学 无人机集群服务功能链动态配置方法和装置
CN117082214A (zh) * 2023-09-18 2023-11-17 国网山东省电力公司高唐县供电公司 变电站巡检作业系统及通讯方法
CN117148871A (zh) * 2023-11-01 2023-12-01 中国民航管理干部学院 一种多无人机协同电力巡检方法及系统
CN117311381A (zh) * 2023-09-20 2023-12-29 中国农业大学 一种基于车载移动机巢的多无人机智能巡检系统及方法
CN117615304A (zh) * 2023-11-30 2024-02-27 北京中科医信科技有限公司 一种应用于医院安保的巡更管理方法、装置及电子设备

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* Cited by examiner, † Cited by third party
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CN114253300B (zh) * 2021-12-03 2023-04-07 国网智能科技股份有限公司 一种网格化机巢的无人机巡检系统及方法
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CN116126030B (zh) * 2023-04-17 2023-06-20 众芯汉创（北京）科技有限公司 一种基于人工智能的无人机机巢覆盖方法
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Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108622432A (zh) * 2018-04-27 2018-10-09 内蒙古工业大学 一种皮卡型车载无人机智能起降和自主续航系统
CN109018413A (zh) * 2018-09-13 2018-12-18 张欣 一种车载无人机机巢及其使用方法
WO2019077006A1 (fr) * 2017-10-18 2019-04-25 Uvue Ltd Système et procédé de détermination de trajets optimaux pour des drones
CN210473942U (zh) * 2019-08-20 2020-05-08 青岛大地新能源技术研究院 一种示踪剂制备装置
CN111176331A (zh) * 2020-03-12 2020-05-19 江苏蓝鲸智慧空间研究院有限公司 一种无人机精准降落控制方法
CN112164015A (zh) * 2020-11-30 2021-01-01 中国电力科学研究院有限公司 单目视觉自主巡检图像采集方法、装置及电力巡检无人机
CN112960132A (zh) * 2021-03-26 2021-06-15 中国能源建设集团江苏省电力设计院有限公司 分布式共享机巢及其电力线路无人机巡检方法
CN113552900A (zh) * 2021-07-23 2021-10-26 中国科学院地理科学与资源研究所 一种无人机智能机库
CN114253300A (zh) * 2021-12-03 2022-03-29 国网智能科技股份有限公司 一种网格化机巢的无人机巡检系统及方法

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10839699B2 (en) * 2016-10-18 2020-11-17 International Business Machines Corporation Methods and systems for managing aerial drones in regulated spaces with ground vehicle assist
CN111652460A (zh) * 2020-04-10 2020-09-11 安徽继远软件有限公司 多无人机协同巡检多杆塔的智能优化方法和系统
CN214474627U (zh) * 2021-03-02 2021-10-22 戈昊(台州)自动化有限公司 一种无人机不间断巡检系统
CN113110587B (zh) * 2021-04-28 2023-02-03 天津云圣智能科技有限责任公司 无人机的降落控制方法、装置以及电子设备
CN113359823A (zh) * 2021-05-31 2021-09-07 国网山东省电力公司滨州供电公司 基于图像识别的无人机通信光缆巡检方法
CN113625748A (zh) * 2021-07-27 2021-11-09 国家电网有限公司 一种变电站无人机巡检航线规划方法
CN113658350A (zh) * 2021-08-26 2021-11-16 广东电网有限责任公司佛山供电局 机巢巡检作业管理方法、装置、计算机设备和存储介质
CN113724415A (zh) * 2021-09-01 2021-11-30 国网福建省电力有限公司龙岩供电公司 一种配电线路无人机交互式自动巡检方法及设备

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019077006A1 (fr) * 2017-10-18 2019-04-25 Uvue Ltd Système et procédé de détermination de trajets optimaux pour des drones
CN108622432A (zh) * 2018-04-27 2018-10-09 内蒙古工业大学 一种皮卡型车载无人机智能起降和自主续航系统
CN109018413A (zh) * 2018-09-13 2018-12-18 张欣 一种车载无人机机巢及其使用方法
CN210473942U (zh) * 2019-08-20 2020-05-08 青岛大地新能源技术研究院 一种示踪剂制备装置
CN111176331A (zh) * 2020-03-12 2020-05-19 江苏蓝鲸智慧空间研究院有限公司 一种无人机精准降落控制方法
CN112164015A (zh) * 2020-11-30 2021-01-01 中国电力科学研究院有限公司 单目视觉自主巡检图像采集方法、装置及电力巡检无人机
CN112960132A (zh) * 2021-03-26 2021-06-15 中国能源建设集团江苏省电力设计院有限公司 分布式共享机巢及其电力线路无人机巡检方法
CN113552900A (zh) * 2021-07-23 2021-10-26 中国科学院地理科学与资源研究所 一种无人机智能机库
CN114253300A (zh) * 2021-12-03 2022-03-29 国网智能科技股份有限公司 一种网格化机巢的无人机巡检系统及方法

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116614377A (zh) * 2023-07-20 2023-08-18 北京邮电大学 无人机集群服务功能链动态配置方法和装置
CN116614377B (zh) * 2023-07-20 2023-09-19 北京邮电大学 无人机集群服务功能链动态配置方法和装置
CN117082214A (zh) * 2023-09-18 2023-11-17 国网山东省电力公司高唐县供电公司 变电站巡检作业系统及通讯方法
CN117311381A (zh) * 2023-09-20 2023-12-29 中国农业大学 一种基于车载移动机巢的多无人机智能巡检系统及方法
CN117311381B (zh) * 2023-09-20 2024-03-26 中国农业大学 一种基于车载移动机巢的多无人机智能巡检系统及方法
CN117148871A (zh) * 2023-11-01 2023-12-01 中国民航管理干部学院 一种多无人机协同电力巡检方法及系统
CN117148871B (zh) * 2023-11-01 2024-02-27 中国民航管理干部学院 一种多无人机协同电力巡检方法及系统
CN117615304A (zh) * 2023-11-30 2024-02-27 北京中科医信科技有限公司 一种应用于医院安保的巡更管理方法、装置及电子设备
CN117615304B (zh) * 2023-11-30 2024-05-24 北京中科医信科技有限公司 一种应用于医院安保的巡更管理方法、装置及电子设备

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