Drone-based inspection system and method for mesh docks

Abstract

A system and method for patrol inspection of a drone (33) on a meshed dock (3, 34) including a plurality of docks (3, 34) arranged in a mesh and each used to accommodate at least one drone (33), wherein the dock (3, 34) includes a dock controller communicating with a control terminal, the dock controller communicating with a drone remote control, the drone remote control communicating with the drone (33), and the control terminal is used to generate an optimal patrol inspection route for the drone (33) based on the current flight range of the drone (33) and the distance from the patrol inspection target to each dock (3, 34) with the optimization goal of minimizing the patrol inspection time, and send it to the dock controller, with beneficial effects being to realize efficient cooperative patrol inspection of the drone (33) based on the drone docks (3, 34) arranged in a mesh, reduce labor costs, and meet the needs of regular or emergency patrol inspection of a plurality of patrol inspection targets across a plurality of different fields.

Description

Technical Field

[0001] The present invention relates to the technical field of power patrol inspection, and particularly to a patrol inspection system and method for drones of a meshed dock.

Background Art

[0002] The description in this part only provides the background art related to the present invention, and does not necessarily constitute the prior art.

[0003] As a relay station for ensuring drones, the function of the drone dock is self-evident. The location of the drone dock is extremely important for the drone, which directly affects the radius of the flight patrol inspection of the drone, the working efficiency and the results.

[0004] The inventor has discovered that the existing power patrol inspection has the following problems.

[0005] (1) The setting of the position of the drone dock is free, or only a few drone docks are sparsely arranged. Often, full coverage of the patrol inspection waiting targets cannot be achieved. Moreover, in the process of patrol inspection, often, a single flight patrol inspection is sequentially carried out for each patrol inspection waiting target, and there is no concern about the coverage of the nearby waypoints around, creating a situation where the flight distance and power in the patrol inspection are wasted.

[0006] (2) Since the existing drone dock adopts a large number of robotic arms to perform centering control and battery replacement control of the drone, the battery replacement of the drone becomes complicated. Moreover, the cooperation between the multi-degree-of-freedom robotic arm or battery replacement mechanism and the drone is also likely to cause failures of the robotic arm or the drone, thereby causing damage to the equipment and reducing the stability of the entire system.

[0007] (3) While intelligent drone docks can communicate with background monitoring centers, after monitoring the flight environment on-site, operators at the background monitoring center often make subjective judgments about the on-site flight conditions. This is due to a low level of intelligence, high subjectivity, and a certain possibility of misjudgment. Alternatively, the judgments regarding flight conditions are merely a collection of readily available data, lacking comprehensive analysis of multi-source data, which raises certain safety concerns for flight tasks.

[0008] (4) When a drone identifies the coordinates of the landing waiting position, it requires highly precise real-time positioning, which not only makes the cost of positioning components high, but also requires real-time acquisition of coordinate data of pre-set points on the drone's airfield, making landing control complicated. Conventional technologies have been used to achieve landing by identifying specific images of the landing point, but this often only involves identifying a single data source, and landing accuracy cannot be guaranteed.

[0009] (5) In the prior art, a method has been disclosed that uses binocular vision to hover and perform positioning and distance measurement. However, the drone is still controlled to reach the inspection targets in order, brake and hover, take a photograph at a predetermined point, and then accelerate to the next inspection target. The braking, hovering, and acceleration of the drone consume a large amount of battery power, making it impossible to perform autonomous inspections without hovering. [Overview of the project] [Problems that the invention aims to solve]

[0010] To address the shortcomings of conventional technology, the present invention provides a drone patrol inspection system and method for a mesh dock, enabling efficient collaborative drone patrol inspections based on a mesh-configured drone dock, reducing labor costs, and meeting the needs for routine or emergency patrol inspections for multiple inspection targets spanning multiple different fields. [Means for solving the problem]

[0011] To achieve the above objective, the present invention employs the following technical embodiments.

[0012] The first aspect of the present invention is, It includes multiple docks arranged in a mesh pattern, each used to accommodate at least one drone, The dock includes a dock controller that communicates with a control terminal, the dock controller communicates with a drone remote control, and the drone remote control communicates with the drone. The control terminal is used to optimize the patrol inspection time to the shortest possible, based on the drone's current flight range and the distance from the patrol inspection target to each dock. It obtains the patrol inspection target corresponding to each dock, generates the optimal patrol inspection route for each drone based on the determined patrol inspection target, and transmits it to the dock controller. We provide a drone-based patrol inspection system for mesh-type docks.

[0013] Furthermore, the dock is The dock body includes a mounting mechanism, a vertical fixing mechanism, and a horizontal fixing mechanism provided within the dock body, the mounting mechanism includes an extendable landing platform and a first motor, and the landing platform is driven by the first motor. The longitudinal fixing mechanism includes a first centering rod, one end of which is provided on the side wall of the dock body via a pivot shaft and equipped with a gear, and the landing platform is provided with a rack that meshes with the gear, and the meshing of the gear and the rack drives the first centering rod to rotate around the pivot shaft. The lateral fixing mechanism includes a rotating rod with both ends provided on the side walls of the dock body, a second centering rod provided on the rotating rod, and a second motor. The rotating rod is driven by the second motor and rotates along the direction opposite to the direction of movement of the landing platform relative to the dock body, and drives the second centering rod to move along the direction perpendicular to the direction of movement of the landing platform.

[0014] Furthermore, the meshing of the gear and the rack causes the first centering rods, which are provided on both side walls, to rotate around their axes, thereby moving the other ends of both first centering rods to an intermediate position or spreading them apart in the lateral direction.

[0015] Furthermore, a second centering rod is provided at each end of the rotating rod, and when the landing platform is driven and reset, the rotating rod rotates in the forward direction, and the second centering rods at both ends move along the rotating rod to an intermediate position, restraining the drone laterally. The meshing of the rack and gears allows the first centering rods on both side walls to be moved to an intermediate position, thereby restraining the drone in the vertical direction.

[0016] Furthermore, a second centering rod is provided at each end of the rotating rod, and when the landing platform is pushed out from the dock body, the rotating rod rotates in the opposite direction, and the second centering rods at both ends move along the rotating rod to the sides, releasing the lateral constraint on the drone. The meshing of the rack and gears allows the first centering rods on both side walls to spread out to the sides, releasing the vertical constraint on the drone.

[0017] Furthermore, the dock is The dock body includes a drone parking space, charging module and energy storage module inside. The dock body is equipped with a mounting module that secures the dock body with a screw-type automatic locking structure, the drone parking space is equipped with a drone fixing device that autonomously dampens vibrations in the horizontal and vertical directions, and the dock controller communicates with the charging module and the mounting module, respectively.

[0018] Furthermore, the drone is equipped with a three-axis pan / tilt head, an RTK positioning module, and a front-end AI processing module. A camera and a video camera are attached to the three-axis pan-tilt. The camera is a monocular zoomable camera, and the video camera is used to obtain video information of towers and columns. Among them, the camera and the video camera are integrated into one lens.

[0019] The RTK positioning module is used to measure the three-dimensional coordinate information of the drone. The front-end AI processing module fits the flight control data of the drone, the data of the RTK positioning module, and the images collected by the zoom camera, issues a flight control command to control the flight of the drone, controls the pan-tilt to adjust the angle and zoom of the camera, locks on the inspection target point for taking pictures. Takes pictures during the flight process of approaching the hovering point using the visual zoom wide-angle camera, calculates the coordinate values (GPS values) of the taken pictures and the attitude of the pan-tilt, and identifies the inspection target point in the pictures according to the camera imaging principle. According to the current GPS position and three-dimensional speed of the drone, and the roll angle, pitch angle and yaw angle of the attitude of the pan-tilt, the position of the drone's pan-tilt is adjusted by the Kalman filter algorithm, and the target inspection point of the tower and column is locked on the zoom camera by zooming. By taking pictures to complete the information collection for the target inspection point of the tower and column, it is configured to improve the accuracy of information collection for the inspection target and the quality of the collected images.

[0020] The second aspect of the present invention is to obtain the distance from each inspection target to each dock, select the dock closest to the inspection target as the optimal dock, and sequentially judge each inspection target to obtain the inspection target corresponding to each dock. Among them, each dock executes the planned task of the inspection task, and the task numbers the inspection targets based on the distance from the inspection targets within the dock range to the dock, and the farther the distance, the larger the number. For each inspection target within the dock range, determine whether the value of the difference between the total flight duration of the drone and the time required to perform a single inspection of the inspection target alone is less than the minimum value of the time required to perform a single inspection of other inspection targets within the dock range. If YES, set this inspection target as a single tower task, and if NO, set this inspection target as the current inspection target, and determine whether the sum of the time from the dock to the current inspection target, the inspection time of the current inspection target, the inspection time from the current inspection target to the nearest secondary inspection target with a number smaller than the current inspection target, the time from the current inspection target to the secondary inspection target, and the time from the secondary inspection target to the dock is greater than the total flight duration of the drone. If YES, set the current inspection target as a single tower task; if NO, execute the route tasks of two towers and columns, and sequentially perform the inspections of the current inspection target and the secondary inspection target. Provide a method for inspecting drones in a meshed dock.

[0021] The third aspect of the present invention is Utilize the above-mentioned drone inspection system for the meshed dock, acquire the environmental information inside the dock and the environmental information outside the dock within the sensing range, select a target dock based on the drone's position, determine the corresponding flight impact factors based on the flight command, obtain the corresponding flight environment data from the external environmental information of the selected target dock, and if the flight environment data does not meet the flight conditions, control the drone to return. Determine the corresponding landing impact factors based on the return command, obtain the corresponding landing environment data and return environment data from the external environmental information and internal environmental information of the target dock based on the landing impact factors, control the landing method of the drone based on the landing environment data until the drone returns to the target dock, and adjust the internal environment of the target dock based on the return environment data. Provide a method for judging the task execution environment of a drone.

[0022] The selection of a target dock based on the drone's position specifically includes determining the detection range of the dock where the drone is located based on the drone's position, designating the dock within the detection range as the target dock, and, if two or more docks are all within the detection range, determining the dock closest to the drone as the target dock.

[0023] The fourth aspect of the present invention is, Using the drone patrol inspection system for the mesh dock described above, To acquire positioning data from the drone, Based on the acquired positioning data, the system determines whether the drone is within the preset landing range, and if not, controls the drone to move until the position requirement is met. After it is confirmed that the drone is within the preset landing range, if the drone is located at a position a first preset distance from the landing point, image data or video data is acquired from below the drone. If the precise landing range code cannot be identified based on the acquired image data or video data, the drone is controlled to descend to a position a third preset distance from the landing point and attempt to identify the precise landing range code again until the precise landing range code is identified. If a precise landing range code is identified based on the acquired image data or video data, the drone is controlled to descend to a position a second preset distance away from the landing point and to acquire image data or video data below the drone again; if a precise landing position code is identified based on the acquired image data or video data again, the drone is controlled to descend to a position a fourth preset distance away from the landing point and to land the drone; This provides a control method for precise drone landings.

[0024] The fifth aspect of the present invention is, Using the drone patrol inspection system for the mesh dock described above, In response to a patrol inspection request, S1 acquires real-time wide-angle images of the patrol inspection target by employing an image acquisition module on the pan / tilt head before the drone enters the detection point at a constant speed. The system determines whether the inspection target is located in the real-time image captured. If the answer is YES, it proceeds to step S3. If the answer is NO, it controls the movement of the pan / tilt head and changes its orientation until the inspection target is found in the real-time image (step S2). The processing module, based on the real-time image information of the patrol inspection target position, the drone's shooting position, and the pan / tilt head attitude, employs a Kalman filter algorithm to fit the drone's shooting position and pan / tilt head attitude position, and determines the focal length mode of the image acquisition module in S3. The drone is controlled to fly to the targeting position obtained by fitting at a constant speed, and during the flight process, the processing module adjusts the attitude of the pan / tilt head in real time in reverse according to the three-dimensional direction in which the drone is flying at a constant speed, and also adjusts the focal length mode of the image acquisition module, S4, so that the patrol inspection target is locked onto the set area of ​​the real-time image of the image acquisition module. The drone reaches the shooting position, confirms that the patrol inspection target location is within the real-time image setting area of ​​the image acquisition module, locks onto the inspection point, and acquires an image (S5). The processing module processes the captured pictures and controls the drone to perform the task for the next detection point until the image acquisition task for all detection points is completed, including S6 which re-executes S1. This provides a drone patrol inspection method based on visual movement tracking. [Effects of the Invention]

[0025] Compared to conventional technology, the beneficial effects of the present invention are as follows:

[0026] 1. The present invention innovatively designs a drone patrol inspection system for a mesh dock and proposes a drone patrol inspection method for a mesh dock. Based on the current flight range of the drone and the distance from the patrol inspection target to each dock, the invention aims to optimize the patrol inspection time to the shortest possible duration. Multiple types of patrol inspection targets are obtained corresponding to each dock, and the optimal patrol inspection route for each drone is generated based on the determined patrol inspection targets. This solves the optimization problem of collaborative patrol inspections for single-tower and multi-tower tasks, achieves optimization of the patrol inspection route with the goal of the shortest possible patrol inspection time, realizes efficient collaborative drone patrol inspections based on a mesh drone dock for patrol inspection targets in each field, reduces labor costs, and meets the normalized or emergency patrol inspection needs for multiple patrol inspection targets in each field.

[0027] 2. The present invention innovatively proposes a drone dock, designing a dual constraint technology that provides both lateral and longitudinal constraints on the drone, and proposing a method of centering the drone by combining a centering rod set fixing mechanism and a gear rack mechanism. This solves the single-scene limitations of the drone dock and the stability of the drone's parking, improving the stability of the drone's landing in different patrol inspection environments. Furthermore, as a general-purpose dock, the drone dock supports remote control operations, significantly improving the efficiency of patrol inspection work, diversifying application scenes, and enabling wider coverage for the drone.

[0028] 3. The present invention innovatively provides a method for determining the task execution environment of a drone, linking different task environment conditions to different flight tasks or return tasks, and determining whether they are suitable for task execution, thereby meeting the needs of the dock's flight condition determination logic, achieving redundancy in the determination conclusion through a dock self-determination method in complex flight situations, increasing the accuracy of the determination, solving the limitations of existing flight environment monitoring technologies, which have a single determination condition, are subjectively interfered with, and have a low degree of intelligence, eliminating the need for manual intervention, achieving autonomous prediction of flight conditions for different tasks, and significantly improving the efficiency of drone patrol inspections and the safety of the dock system.

[0029] 4. The present invention innovatively proposes a control method for precise drone landing, achieving preliminary positioning of the drone and landing waiting area based on drone positioning data, integrating real-time differential positioning data, precise landing range codes, and precise landing position codes, and solving the problem of difficulty in controlling precise drone landings through continuous image recognition and proximity detection, thereby achieving precise and stepwise control of drone landings and improving the control accuracy of drone landings.

[0030] 5. The present invention innovatively proposes a drone patrol inspection method based on visual motion tracking. During the flight process from when the drone enters the patrol inspection target until when it leaves the target, the drone always flies according to a set path, and the current position and velocity data are fitted using a Kalman filter algorithm to adjust the pan / tilt attitude and camera zoom in real time, enabling camera motion tracking and lock-on shooting relative to the patrol inspection target. The present invention enables the automatic acquisition of images of the patrol inspection target while the drone is conducting the inspection without hovering, significantly reducing the workload of the patrol inspection worker. Furthermore, the present invention adopts a reverse motion tracking method and dynamically adjusts the attitude of the drone and the pan / tilt camera to achieve relative stationarity with respect to the patrol inspection target, significantly saving the drone's power consumption and the workload per flight. The acquisition of patrol inspection targets in the present invention is completed based on a monocular camera, resulting in a simple structure and low cost.

[0031] The advantages of additional aspects of the present invention are, in part, shown in the following description, in part, evident from the following description, or understood through the practice of the present invention.

[0032] The accompanying drawings of the specification, which constitute a part of the present invention, are intended to provide a further understanding of the present invention, and the schematic embodiments and descriptions thereof are for interpretation purposes only and do not unduly limit the present invention. [Brief explanation of the drawing]

[0033] [Figure 1]This is a schematic diagram of a drone patrol inspection system for a mesh dock according to Embodiment 1 of the present invention. [Figure 2] This is a schematic diagram of a drone dock according to Embodiment 1 of the present invention. [Figure 3] This is a schematic diagram of the drone dock body according to Embodiment 1 of the present invention. [Figure 4] This is a schematic diagram of the drive mechanism of the gear at the bottom of the first centering rod according to Embodiment 1 of the present invention. [Figure 5] This is a schematic diagram illustrating the resetting of the first centering rod and the second centering rod according to Embodiment 1 of the present invention. [Figure 6(a)] This is a schematic diagram showing a drone according to Embodiment 1 of the present invention in a centered position. [Figure 6(b)] This is a schematic diagram showing a drone according to Embodiment 1 of the present invention in a centered position. [Figure 7(a)] This is a schematic diagram showing a drone landing according to Embodiment 1 of the present invention. [Figure 7(b)] This is a schematic diagram showing a drone landing according to Embodiment 1 of the present invention. [Figure 8] This is a schematic diagram illustrating the installation of a drone dock according to Embodiment 1 of the present invention. [Figure 9(a)] This is a schematic diagram of the internal structure of a mobile drone dock according to Embodiment 2 of the present invention. [Figure 9(b)] This is a schematic diagram of the structure of the door of a mobile drone dock according to Embodiment 2 of the present invention. [Figure 10] This is a schematic diagram of the structure of a charging module according to Embodiment 2 of the present invention. [Figure 11] This is a schematic diagram of the structure of a drone parking space fixing device according to Embodiment 2 of the present invention. [Figure 12] This is a schematic diagram of the local structure of a drone parking space fixing device according to Embodiment 2 of the present invention. [Figure 13(a)] This is a schematic diagram of the structure of a mounting module according to Embodiment 2 of the present invention. [Figure 13(b)] This is a schematic diagram of the local structure of a mounting module according to Embodiment 2 of the present invention. [Figure 13(c)]This is a schematic diagram of the local structure of a mounting module according to Embodiment 2 of the present invention. [Figure 14] This is a workflow flowchart of a drone system according to Embodiment 2 of the present invention. [Figure 15] This is a schematic diagram of the route planning flow according to Embodiment 3 of the present invention. [Figure 16] This is a schematic diagram 1 of the task plan according to Embodiment 3 of the present invention. [Figure 17] This is a schematic diagram 2 of the task plan according to Embodiment 3 of the present invention. [Figure 18] This is a schematic diagram illustrating the task command and corresponding environmental factors according to Embodiment 4 of the present invention. [Figure 19] This is a schematic diagram illustrating the determination of the execution environment for the drone storage task according to Embodiment 4 of the present invention. [Figure 20] This is a schematic flowchart of the control method for precise drone landing according to Embodiment 5 of the present invention. [Figure 21] This is a schematic diagram of the flow chart for the autonomous patrol inspection method of a drone according to Embodiment 6 of the present invention. [Modes for carrying out the invention]

[0034] The present invention will be further described below with reference to the drawings and embodiments.

[0035] It should be noted that the following detailed descriptions are illustrative and intended to provide further explanation for the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art.

[0036] Furthermore, the terminology used herein is solely for the purpose of describing specific embodiments and is not intended to limit the exemplary embodiments of the present invention. Unless otherwise explicitly indicated in the context, the singular and plural forms are intended to be used as used herein, and it should be further understood that when the terms “include” and / or “contain” are used herein, they indicate the presence of features, steps, operations, devices, parts and / or combinations thereof.

[0037] As long as they do not conflict, the embodiments and features of the present invention can be combined with each other.

[0038] Example 1 Embodiment 1 of the present invention, as shown in Figure 1, includes a plurality of docks 34 arranged in a mesh and each used to accommodate at least one drone 33, The dock includes a dock controller that communicates with a control terminal, the dock controller communicates with a drone remote control, and the drone remote control communicates with the drone. The control terminal provides a drone patrol inspection system for a mesh dock network, which is used to optimize the system to minimize patrol inspection time based on the drone's current flight range and the distance from the patrol inspection target to each dock, obtain the patrol inspection target corresponding to each dock, and generate the optimal patrol inspection route for each drone based on the determined patrol inspection target and transmit it to the dock controller.

[0039] In this embodiment, a substation is selected as the main location for the drone dock. The drone can first conduct patrol inspections of the substation's equipment nearby. The area around the substation is a major confluence point for power lines and is an area that requires focused inspection. By conducting patrol inspections around the substation, the drone can conduct maximum inspections of the power lines. The drone dock can be located within the substation and may be considered part of the substation's inspection and repair work, making it easy to operate and maintain.

[0040] In some other embodiments, the drone dock may be appropriately positioned on a site such as a 5G base station or a solar power plant on a mountaintop, and may also be used as a patrol inspection target for targets in other fields, such as the communications field or the firefighting field, and it can be understood that the drone dock can be deployed as long as there is electricity.

[0041] As shown in Figures 2 and 3, the drone dock described in this embodiment is a miniaturized drone dock including a dock body and a mounting mechanism, a vertical fixing mechanism, and a horizontal fixing mechanism provided within the dock body, wherein the mounting mechanism includes an extendable landing platform and a first motor, and the landing platform is driven by the first motor. The longitudinal fixing mechanism includes a first centering rod, one end of which is provided on the side wall of the dock body via a pivot shaft and equipped with a gear, and the landing platform is provided with a rack that meshes with the gear, and the meshing of the gear and the rack drives the first centering rod to rotate around the pivot shaft. The lateral fixing mechanism includes a rotating rod with both ends provided on the side walls of the dock body, a second centering rod provided on the rotating rod, and a second motor. The rotating rod is driven by the second motor and rotates along the direction opposite to the direction of movement of the landing platform relative to the dock body, and drives the second centering rod to move along the direction perpendicular to the direction of movement of the landing platform.

[0042] In this embodiment, the dock body 6 has a rectangular frame structure, a top cover 5 is provided at the top end of the dock body 6, and a solar power generation panel is provided on the top cover 5. The solar power generation panel absorbs light energy, converts the light energy into electrical energy and stores it, and supports the power supply of the dock.

[0043] Preferably, the top cover 5 is designed in a sloping manner to prevent water from accumulating at the top of the dock.

[0044] In this embodiment, an extendable landing platform 4 is provided inside the dock body 6. When the drone lands, the landing platform 4 is pushed out from inside the dock body 6 to place the drone on it. After the drone lands, the landing platform 4 is retrieved back into the dock body 6. When the drone performs a patrol inspection task, the landing platform 4 is pushed out from inside the dock body 6, the drone takes off, and then the landing platform 4 is retrieved back into the dock body 6.

[0045] In this embodiment, the three sides of the dock body 6 are closed, and the forward-facing side and the landing platform 4 form a closed surface, ensuring the overall protective performance of the dock.

[0046] In this embodiment, the first motor 9 is connected to the landing platform 4 via a rod and drives the landing platform 4 to be pushed out of the dock body 6 or retrieved into the dock body 6.

[0047] Preferably, two first motors 9 are provided.

[0048] In this embodiment, as shown in Figure 3, slide rails are provided at both ends of the dock body 6, and the rotating rod 7 is attached to the slide rails of the dock body 6 at both ends by rolling pulleys, and its rotation is controlled by the second motor 8, and the direction of rotation of the rotating rod 7 is opposite to the direction of movement of the landing platform 4.

[0049] A slide groove is provided at the end of the second centering rod 10, and one second centering rod 10 is provided at each end of the rotating rod 7. The second centering rod 10 is attached to the rotating rod 7 via the slide groove and moves in one direction along the direction of the rotating rod 7 as the rotating rod 7 rotates, that is, it moves laterally along the direction perpendicular to the direction of rotation of the rotating rod 7.

[0050] The rotating rod 7 is provided with screw threads, and the second centering rod 10 moves in one direction along the screw threads as the rotating rod 7 rotates via a slide groove.

[0051] Preferably, the rotating rod 7 employs a screw.

[0052] The rotating rod 7 rotates on the slide rail driven by the second motor 8, and controls the direction of motion of the second centering rod 10 based on the rotation direction of the rotating rod 7. Preferably, when the rotating rod 7 rotates in the forward direction, the second centering rods 10 on both sides perform a centering motion, i.e., move to an intermediate position, and when the rotating rod 7 rotates in the reverse direction, the second centering rods 10 on both sides move in opposite directions, i.e., spread out to both sides, and the coordination between the rotation of the rotating rod 7 on the slide rail and the movement of the second centering rods 10 on the slide groove balances the force acting on the second centering rods 10 to reciprocate along with the rotating rod 7, ensuring that the second centering rods 10 are displaced with a degree of freedom in one direction.

[0053] Preferably, when the landing platform 4 is pushed out, the pivot rod 7 rotates in the opposite direction, causing the second centering rods 10 on both sides to move in the opposite direction, i.e., to spread out to both sides. In this case as well, the second centering rods 10 are used so that the drone can take off from the landing platform 4 after they have spread out. When the landing platform is retrieved and reset, the pivot rod 7 rotates in the forward direction, causing the second centering rods 10 on both sides to perform a centering motion, i.e., move to an intermediate position. In this case as well, the drone is used to reset laterally on the landing platform and to restrain and fix the drone laterally.

[0054] In this embodiment, first centering rods 13 are provided on both of the two opposing side walls of the dock body 6, and the meshing of the gear and the rack causes the first centering rods 13 on both sides to rotate around their axis, thereby moving the other ends of the first centering rods 13 to an intermediate position or spreading them out to both sides.

[0055] In this embodiment, as shown in Figure 4, a gear is provided on the first centering rod 13, and a rack 14 is connected to the landing platform 4 via a screw. The rack 14 meshes with the gear, and when the landing platform is pushed out and returned, the gear rotates. The meshing of the gear and the rack causes the first centering rod 13 to rotate around its axis. When the first centering rod 13 rotates around its axis, the power transmitted between the gear and the rack is converted into a rotational power moment.

[0056] Preferably, the first centering rod 13 is used for longitudinal resetting of the drone, and the first centering rod 13 rotates circumferentially around the axis via a pivot shaft, and the rotation causes the other end to rotate to an intermediate position around the axis, fixing the drone in place.

[0057] In this embodiment, the reset of the drone is completed by the joint pushing motion of the second centering rod 10 and the first centering rod 13. As shown in Figure 5, the reset of the drone is divided into two parts: one part is reset laterally by the pushing motion of the second centering rod 10, and the other part is completed vertically by the rotation of the first centering rod 13.

[0058] Preferably, before the drone takes off, the first motor 9 pushes the landing platform 4, opening the front of the dock body 6. In the process of opening, the second centering rod 10 spreads out, and the rotation of the pivot rod 7 in the opposite direction causes both second centering rods 10 to move in opposite directions, i.e., spread out to the sides, releasing the lateral fixation to the drone. At the same time, the rack connected to the landing platform 4 is pushed forward in sync with the landing platform 4, and the engagement of the rack 14 on the landing platform 4 with the gears on the first centering rod 13 causes the first centering rod 13 to rotate, and both first centering rods 13 also spread out to the sides by rotating around their axis, releasing the longitudinal fixation to the drone. As a result, the drone can take off autonomously based on the planned flight path and perform patrol inspection work.

[0059] After completing its inspection task, the drone precisely lands on the landing platform 4 with visual assistance. Subsequently, the first motor 9 moves the landing platform 4 to perform the cabin closing operation. In the process of closing the cabin door, the forward rotation of the pivot rod 7 causes the second centering rods 10 on both sides to perform a centering motion, i.e., move to an intermediate position, completing the lateral reset of the drone. Simultaneously, the meshing of the rack 14 and gears causes the first centering rod 13 to rotate, and the first centering rods 13 on both sides rotate around their axis, moving to an intermediate position to fix the drone in place, completing the longitudinal reset of the drone. Schematic diagrams of the drone's centering and landing are shown in Figures 6(a)-6(b) and 7(a)-7(b).

[0060] In this embodiment, charging rods 11 are further provided at both ends of the dock body 6, and several charging ports 12 are provided on the charging rods. After the drone is reset, the charging contact plate on the bottom of the drone contacts the charging ports 12, and charging is performed by the control command of the dock.

[0061] When the drone performs a patrol inspection task, it first detects the remaining power level of the battery. If the power level is insufficient, it charges the drone's power battery via the charging port 12. When the drone has sufficient power, it pushes out the landing platform 4 and takes off.

[0062] In many embodiments, the drone dock described above can be applied to towers and columns as a general-purpose drone dock. As shown in Figure 8, the dock 3 is attached to the tower / column 1 by the dock bottom support 2, the dock 3 is connected to the dock bottom support by screws, and the dock bottom support 2 is fixed to the tower / column 1 by bolts. It can be installed on towers and columns in various terrains, enabling diversification of scenes.

[0063] In more embodiments, the drone dock can be used in conjunction with a vehicle-mounted drone, and the drone dock is attached to the roof by a support at the bottom of the dock.

[0064] Example 2 Embodiment 2 of the present invention includes a plurality of docks arranged in a mesh, each used to accommodate at least one drone, The dock includes a dock controller that communicates with a control terminal, the dock controller communicates with a drone remote control, and the drone remote control communicates with the drone. The control terminal provides a drone patrol inspection system for a mesh dock network, which is used to optimize the system to minimize patrol inspection time based on the drone's current flight range and the distance from the patrol inspection target to each dock, obtain the patrol inspection target corresponding to each dock, and generate the optimal patrol inspection route for each drone based on the determined patrol inspection target and transmit it to the dock controller.

[0065] As shown in Figures 9(a) and 9(b), the dock described in this embodiment is a mobile drone dock including a master controller and a dock body. Inside the dock body are a charging module 16, a drone parking space 17, an energy storage module 18, and a display module 19. A mounting module is provided on the dock body, and the mounting module secures the dock body with a screw-type automatic locking structure. The drone parking space is provided with a drone fixing device that autonomously dampens vibrations in the horizontal and vertical directions. The master controller is connected to the charging module and the mounting module, respectively.

[0066] in particular, As shown in Figure 10, the charging module includes several charging ports 20, a BMS (BATTERY MANAGEMENT SYSTEM) control board 21, a charging heat dissipation fan 22, a communication interface 23, and a charging indicator light 24. The dock body's drone parking space can accommodate commercially available mainstream RTK (Real-time kinematic) drones. To accommodate mobile drone docks that frequently move with vehicles in environments with different terrains, the drone parking space is provided with a fixing device for securing the drone. As shown in Figure 11, the fixing device includes a first clamping member 25 and a second clamping member 28, which are connected by an elastic material 27 to form a clamping structure (similar to a clip structure).

[0067] Of these, the first clamping member 25 is fixed to the surface of the drone parking space, and as shown in Figure 12, the second clamping member includes a handle 27-1, a first sleeve 27-2, a first spring 27-5, two telescopic rods 27-3 located at both ends of the sleeve, and a fixed end. The first spring is located in the middle of the sleeve, and both ends of the first spring are fixedly connected to one end of each of the two telescopic rods. The first spring applies a tensile force to the two telescopic rods toward the center of the sleeve, and the fixed end provides horizontal fixation to the drone. At the same time, the fixed end provides vertical fixation to the drone based on the clamping structure formed in the fixing device. Based on the spring in the horizontal direction and the elastic material in the vertical direction of the fixing device, the fixing device can be fixed well, and after being subjected to shaking or other conditions, the spring and elastic material act as dampers to absorb the horizontal and vertical forces of the drone, providing vibration damping protection and further guaranteeing the safety of the drone.

[0068] The dock body is provided with an attachment module for attaching the drone dock, the attachment module penetrates the dock body and is fixedly connected to the dock body, and as shown in Figures 13(a) to 13(c), the attachment module fixes the dock body with a screw-type automatic locking structure, the screw-type automatic locking structure includes a second sleeve 28 and a double-output shaft motor 29 fixed at the center of the sleeve, both ends of the rotor of the double-output shaft motor are fixedly connected to a part of the screw 32, the other end of the screw 32 is connected to one end of a spring slider 31 via a screw hole, the spring slider 31 moves horizontally and linearly as the screw rotates, and moves the second telescopic rod 30 fixedly connected to the other end of the spring slider to extend and retract. 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 screw hole that matches the screw 32, and the second slider 31-3 is provided with a circular hole at a position corresponding to the first slider 31-1, the diameter of which is larger than the outer diameter of the screw, and at the same time, a hole of a predetermined length is provided at one end of a fixing rod fixed to the second slider, the diameter of which is also larger than the outer diameter of the screw.

[0069] This is intended to allow the spring slider 31 and the second telescopic rod 30 to easily extend and retract horizontally within the sleeve.

[0070] To ensure the automation of the installation process, a pressure sensor is provided on the first slider 31-1, the pressure sensor is connected to the master controller, and at the same time, the master controller is connected to the two output shaft motors, and the operation of the two output shaft motors is controlled based on the comparison result of the pressure value obtained from the pressure sensor with a preset threshold.

[0071] Specifically, the operating mechanism of the mounting module is as follows: The two output shaft motors move to rotate a screw as a power core, and the rotation of the screw displaces the power block horizontally. The power block transmits thrust force via springs, gradually bringing its fixed end into contact with the cargo box (in this embodiment, the passenger compartment of a pickup truck). A pressure sensor is attached to the power block, and after the sensor receives that the reaction force from the passenger compartment has reached a predetermined value, it forms a feedback loop, stopping the rotation of both output shaft motors and automatically locking them. When the vehicle shakes, the springs act as dampers to absorb vibrations and maintain the self-stable state of the mobile dock.

[0072] The drone performs tasks according to the patrol inspection schedule. Autonomous patrol inspection software for the drone is deployed in the dock, and the patrol inspection work is refined based on a pre-prepared flight path plan. The worker determines the drone's current status and specific work mode based on the instructions displayed on the dock screen. After the drone's work is completed, the worker manually replaces the drone's battery, fully utilizing the worker's subjective initiative.

[0073] The master controller is further connected to a display module that displays the battery status in the charging port of the charging module and issues commands. Among these commands, the issuing of commands includes issuing an installation command (i.e., to install the drone dock inside the vehicle) and issuing a work task to the drone.

[0074] The energy storage module 18, as a mobile work energy supply module for the dock, is equipped with a dedicated charging gun for charging it, and during the process in which the mobile drone dock goes to the site with the vehicle and performs patrol inspection work, the energy storage module supports the power supply to each component in the dock, including the charging module, display module, and master module.

[0075] As shown in Figure 14, after integrating the mobile drone dock described in the present invention into a pickup truck, the worker operates the mounting module using the display module to automatically lock it to the pickup truck. When the drone is performing inspection work, the vehicle carries the mobile dock to the vicinity of the work site, opens the dock, turns on the drone securing device and removes the drone, selects and installs the recommended battery from the charging module, the autonomous flight software in the dock selects an appropriate inspection route, the drone autonomously completes the inspection work, and after the task is completed, the worker replaces the battery and returns the drone to the dock.

[0076] Example 3 As shown in Figure 15, Embodiment 3 of the present invention provides a drone patrol inspection method for a mesh dock, which specifically includes the following: Assuming the drone's flight speed is V and the dock's position is at three-dimensional coordinate (0,0,0), this embodiment uses towers and columns as examples of inspection targets.

[0077] The position coordinates of several towers and columns are sequentially (X1, Y1, Z1), (X2, Y2, Z2), ..., (Xn, Yn, Zn). Assuming the dock's position is the center of a sphere or plane, extending in three directions along the X, Y, and Z axes, and assuming the coordinates of tower / column N are (Xn, Yn, Zn), and since the shortest straight line is between the two points, the straight-line distance the drone travels from the dock to tower / column N is: The filename is JPEG0007829691000001.jpg747.

[0078] The inspection complexity of a single tower or column is determined by the type of tower or column (tension tower, straight tower, angle tower, etc.). Based on a three-dimensional point cloud model of the tower or column, its inspection complexity can be determined, where time Tn represents the complexity of the tower or column N, and its physical significance is the time spent by the drone to inspect the power tower or column.

[0079] To illustrate with an example, the time required to complete one inspection of a single power tower / pole N is T = Sn / V + Tn + Sn / V, which includes three parts: Sn / V, the time it takes for the drone to get from the dock to the tower / pole N; Tn, the time it takes to inspect the target object, the tower / pole N; and Sn / V, the time it takes for the drone to return to the dock after the inspection is completed.

[0080] One consideration here is that, if the drone's flight time is still sufficient after inspecting towers / pillars N, it may be possible to inspect two or more towers / pillars in a single flight task. This is done to reduce the number of times the drone has to return to the dock, i.e., to reduce the number of times the drone inspects within the dock's coverage area, thereby achieving the goal of the optimal route and shortest time.

[0081] In this embodiment, the complexity T of towers and columns 1, 2, 3, ..., n and their three-dimensional coordinates (Xn, Yn, Zn) are known. Towers and columns are numbered 1, 2, 3, ..., n from those closest to the dock origin to those furthest away, providing a basis for subsequent planning methods. The drone's cruising capability is T, the drone's patrol inspection speed is V, and the dock position coordinates are (0,0,0).

[0082] The method and steps for autonomously planning the shipping route are as follows: The basic principle of shipping route planning is to first plan the towers and pillars that are farther from the dock origin, that is, The process starts with JPEG0007829691000002.jpg747, which has the largest size, and then proceeds to determine the best option by decreasing the size sequentially.

[0083] First, we plan and confirm a task that allows for the inspection of only one tower at a time. The conditions for satisfying this task are to screen for towers / columns that are far from the dock origin, within the dock's coverage area, and have a high degree of complexity, and to execute this as a single-tower task. In mathematical terms, Represented in JPEG0007829691000003.jpg1184, Eventually, The image is JPEG0007829691000004.jpg841, where the complexity of tower / column N is denoted as Tn in seconds, the three-dimensional coordinates of tower / column N are denoted as (Xn,Yn,Zn) in meters, the cruising capability of the drone is denoted as T in seconds, the patrol inspection speed of the drone is V in meters per second, and the dock's position is (0,0,0) in meters.

[0084] The criterion for the above formula is as follows: After the drone has completed its inspection of a single tower or column, its remaining range becomes smaller than the complexity T of all other towers or columns within the dock's coverage area. In other words, this tower or column can be completed in a single inspection task, and these towers or columns are considered to be the furthest route tasks within the dock's coverage area.

[0085] Next, some tower / pillar tasks JPEG0007829691000005.jpg876, but the surrounding towers and pillars T n-1 In contrast, the remaining range after inspecting the towers and columns Tn is insufficient to complete one inspection cycle, and mathematically, JPEG0007829691000006.jpg769, and, Represented in JPEG0007829691000007.jpg9146, Eventually, T n-1 These are the surrounding towers and pillars that are close in a straight line to Tn, and since their number is n-1, they are even closer to the dock origin, and at this point, the planning of the routes for all single-tower tasks is already complete.

[0086] The next task involves a flight path involving two towers / pillars, and the decision-making principle is as follows: If, after the drone has completed patrolling a single tower / pillar, its remaining range is only enough to continue patrolling one nearby tower / pillar, it will fly in a straight line to the nearby tower / pillar to continue patrolling, and then return in a straight line to the dock, with its flight path forming a triangle.

[0087] Furthermore, the order of the route plan is from farthest to nearest, that is, from largest to smallest number. After the inspection of one tower or pillar is completed, if there is still cruising range, when searching for nearby towers or pillars, only towers or pillars with numbers smaller than the current tower or pillar number can be searched, ensuring clarity of the method.

[0088] The formula is expressed as follows: JPEG0007829691000008.jpg10156

[0089] Next is a navigation task involving three towers / pillars. This navigation task forms a rectangle, and in this case, it is necessary to search in one direction for nearby towers / pillars. For example, the tower / pillar 3-2-1 on the left side of Figure 16 is searched in a clockwise direction. In this way, overlapping navigation routes can be avoided and the navigation route can be optimized. Since the distance of tower / pillar 3 to the dock origin is greater than that of tower / pillar 1, the navigation plan is calculated starting from tower / pillar 3. In practice, after the navigation task is determined, it is possible to inspect in reverse order. For example, the inspection order of towers / pillars 3-2-1 or 1-2-3 is both possible because the distances of the inspection routes are equal. The reason why the planned navigation route here is 3-2-1 is that it follows the principle of planning from farther to nearer towers / pillars, and this principle results in a shorter calculated route compared to the reverse planning method from nearer to farer.

[0090] By sequential analogy, route tasks involving four or five towers or pillars can be planned and generated one after another. For example, a route with four towers or pillars would be planned as an irregular pentagon, and the sum of the lengths of the five sides would give the total length of the route. As the number of route plans increases, it means that towers or pillars farther from the dock origin have already been planned in the route, and the closer a tower or pillar is to the dock origin, the larger the search area for that nearby tower or pillar becomes, because the closer a tower or pillar is to the dock origin, the greater its remaining range.

[0091] As shown in Figure 16, the difference between the two diagrams lies in the route planning for towers 6, 1, 2, and 3. In the left diagram, tower 6 is planned first, and towers in the nearby range are searched based on the range capability. If tower 1 is not included in the search range, tower 6 can only be planned as a single tower route task, as shown in the left diagram. On the other hand, as shown in the right diagram, if tower 1 is included within the planning range of tower 6, and calculations show that the triangular route consisting of tower 6, tower 1, and the dock origin satisfies the drone's range capability, then towers 6 and tower 1 are planned as a double tower route.

[0092] In this embodiment, as shown in Figure 17, meshing is implemented by arranging multiple docks based on substations within an area where power towers and poles are evenly distributed, and arranging them intersectingly within the area like a mesh. If there are power towers or poles that need to be inspected within the coverage area of ​​two docks, the method for generating the optimal route is as follows: First, determine which drone dock is closest to the power tower / pole in question, as this is because the closer tower / pole has a shorter inspection route. Each tower / pole only needs to be included once in the inspection task of one drone dock. Next, following the single-dock route planning method described above, power towers and poles within the dock's coverage area are first numbered in ascending order of distance, from closest to furthest. The starting tower or pole for route planning is the one with the highest number, i.e., the one furthest from the drone dock. Then, it is determined whether the tower or pole is a single-tower or multi-tower route task, starting from the furthest to the nearest.

[0093] If a single power tower or pole is covered by two or more drone docks, it is sufficient to determine which drone dock's route task the tower or pole belongs to.

[0094] The number of docks located in a substation is not limited to one. For example, to improve the efficiency of routine inspections, multiple docks can be located in a single substation, each completing routine inspections of lines with different requirements, such as different directions or different voltage levels. It can be understood that such a mesh-like arrangement within a substation further enhances the significance and feasibility of meshing the docks.

[0095] After all drone docks and their corresponding towers / pillars are bound together and the route task plan is completed, each tower / pillar is ensured to exist only for one route task for one drone dock, and there are no overlapping inspection routes. The background control terminal will then determine the route that only that dock has, based on the drone dock's SN number, ensuring a one-to-one correspondence between each route and drone dock.

[0096] Example 4 Embodiment 4 of the present invention provides a method for determining the task execution environment of a drone that utilizes the drone patrol inspection system for a mesh dock described in Embodiment 1 or Embodiment 2, wherein the method is To acquire information about the environment inside the dock and information about the environment outside the dock within the detection range, The system selects a target dock based on the drone's position, determines the corresponding flight influencing factors based on the flight command, retrieves corresponding flight environment data from the external environment information of the selected target dock, determines the flight conditions based on the flight environment data, and controls the drone to return if the flight environment data does not meet the flight conditions. This includes determining the corresponding landing impact factors based on the return command, obtaining corresponding landing environment data and return environment data from the target dock's out-of-dock environment information and in-dock environment information based on the landing impact factors, controlling the drone's landing method based on the landing environment data and adjusting the in-dock environment based on the return environment data until the drone returns to the target dock.

[0097] In this embodiment, the dock environment information includes dock temperature, dock humidity, and dock fumes concentration. The above-mentioned dock environment information is collected by a temperature sensor, a humidity sensor, and a haze sensor. The temperature sensor is used to measure the temperature of the dock's internal environment. If the temperature is below the lower limit of the set temperature range, the air conditioner's heating function is controlled to bring the dock's internal temperature to the normal operating range. If the temperature is above the upper limit of the set temperature range, the air conditioner's cooling function is turned on to bring the dock's internal temperature to the normal operating range. The humidity sensor is used to detect the humidity of the dock's internal environment. If the humidity inside the dock is above the set threshold, the air conditioner's dehumidification function is turned on. The haze sensor is used to detect the haze concentration inside the dock.

[0098] In this embodiment, the external dock environment information includes wind speed, wind direction, external dock temperature, external dock humidity, rainfall, atmospheric pressure, solar radiation intensity, and visibility. The aforementioned external dock environment information is collected by wind speed sensors, wind direction sensors, temperature sensors, humidity sensors, rain gauges, barometers, light sensors, and visibility sensors. Among these, the wind speed sensor is used to measure the wind speed at the dock's location; 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 rain gauge is used to measure the amount of rain during rainfall and can be used to distinguish between light rain, moderate rain, heavy rain, etc.; the barometer is used to measure the local atmospheric pressure; the light sensor is used to measure the current solar radiation intensity; and the visibility sensor can continuously output the atmospheric visibility.

[0099] In this embodiment, the sensors transmit the collected data wirelessly.

[0100] As an optional embodiment, wireless communication can employ UWB wireless communication technology, which has features such as low power consumption, high data transmission speed, strong interference resistance, and strong penetration capability.

[0101] While employing UWB wireless communication is only one feasible embodiment as shown in this example, it is understood that the wireless communication method is not limited to this one, and in many more embodiments, other wireless communication methods, such as 4G or 5G, may be adopted depending on the actual situation on site.

[0102] This embodiment merely lists and summarizes the types of data and sensors commonly used in the field, and it should be understood that in more embodiments, sensor types may be added or removed depending on the actual situation.

[0103] In this embodiment, various sensors are used to collect data on the dock's internal and external environment, and the collected sensor data is preprocessed. This preprocessing includes using a moving average low-pass filter to filter out hopping or abnormal environmental information, thereby obtaining relatively calm environmental information after preprocessing. As a selectable embodiment, the model of the moving average low-pass filter takes the output of an N-point moving average filter, The file is JPEG0007829691000009.jpg563.

[0104] In this embodiment, influencing factors are categorized by task command, and flight conditions are determined by associating them with the necessary influencing factors for different task commands. As shown in Figure 18, specifically, task commands include drone storage, drone charging, drone inspection, dock self-check, dock opening and closing operations, dock open status, drone flight tasks, drone precision landing, drone alternative landing, etc. Specifically, the main influencing factors for drone storage, drone charging, and dock self-checks are dock environment information, including dock temperature, dock humidity, and dock fumes concentration. The main influencing factors for drone inspection patrols include wind speed, wind direction, outside dock temperature, rainfall, barometer readings, solar radiation intensity, and visibility. The main factors influencing the opening and closing of the dock are rainfall conditions and the concentration of smog inside the dock. The main influencing factors in drone flight tasks are wind speed, wind direction, barometer readings, and visibility. The main factors influencing the precision landing of a drone are wind speed, wind direction, solar radiation intensity, and visibility. The main factors influencing alternative landings for drones are wind speed and wind direction.

[0105] As an example of a selectable embodiment, taking the drone storage task as an example, the environmental impact factors under the conditions of the task are linked, and the conditions suitable for the task are determined by a threshold determination method, as shown in Figure 19, We will obtain the dock temperature, dock humidity, and dock fumes concentration. Temperature threshold, humidity threshold, and haze threshold are set in advance. The system determines whether the dock temperature meets the temperature threshold condition. If the dock temperature does not meet the temperature threshold condition, the dock temperature is considered abnormal. If the dock temperature meets the temperature threshold condition, it is determined whether the dock humidity meets the humidity threshold condition. If the dock humidity does not meet the humidity threshold condition, the dock humidity is considered abnormal. If the humidity inside the dock meets the humidity threshold condition, the system uses a haze threshold to determine whether or not there is haze inside the dock. If haze is present, the haze inside the dock is abnormal; if there is no haze, the internal environment of the dock is normal, and the drone can return to normal operation.

[0106] In one selectable embodiment, the current judgment result and abnormality factor are packed into message information and pushed. The output of the corresponding task represents the current judgment result and abnormality factor as U8 type data, where 01 is the task number, and the following 8 bits of data are used to represent the judgment result. The judgment conclusion is the overall environmental judgment result, where 0 is abnormal and 1 is appropriate. The subsequent bits are sequentially the sensor judgment conclusions, where 0 means the current environmental item is abnormal, otherwise the environment is appropriate. If the environmental judgment result is 1, all sensor judgment results are 1. Otherwise, the data in the register of the sensor's location allows for interpretation of which current environmental element does not meet the needs of the current task. By sequentially inferring, message information for different tasks is formed, and the judgment result can be directly retrieved based on the current task state to decide whether or not to execute the task.

[0107] In one selectable embodiment, message information is transmitted outward at a speed greater than or equal to the set speed.

[0108] As an optional embodiment, the above method can be applied to a single dock and a drone performing flight tasks within the sensing range of a single dock, specifically, To acquire environmental information within a single dock and environmental information outside the dock within the sensing range of a single dock, Based on the flight command, the system determines the corresponding flight influencing factors, retrieves corresponding flight environment data from external environmental information of a single dock, determines the flight conditions based on the flight environment data, and controls the drone to return if the flight environment data does not meet the flight conditions. This includes determining the corresponding landing impact factors based on the return command, obtaining corresponding landing environment data and return environment data from external and internal environment information of a single dock, controlling the drone's landing method based on the landing environment data and adjusting the internal dock environment based on the return environment data until the drone returns to the dock.

[0109] In this embodiment, a one-dock, one-drone system is adopted, and since all drone flight tasks are within the dock's sensing range, the dock can collect environmental information in real time during the drone's flight tasks and return journey, and make conditional judgments.

[0110] As an optional embodiment, if the drone flies out of the dock's sensing range, a method is employed in which the drone performs flight tasks within the sensing range of multiple docks arranged in a mesh, and the specific method is as follows: To acquire information about the environment inside the dock and information about the environment outside the dock within the detection range, The system selects a target dock based on the drone's position, determines the corresponding flight influencing factors based on the flight command, retrieves corresponding flight environment data from the external environment information of that dock, determines the flight conditions based on the flight environment data, and controls the drone to return if the flight environment data does not meet the flight conditions. This includes determining the corresponding landing impact factors based on the return command, obtaining corresponding landing environment data and return environment data from the target dock's out-of-dock and in-dock environment information, controlling the drone's landing method based on the landing environment data, and adjusting the in-dock environment based on the return environment data until the drone returns to the target dock.

[0111] In this embodiment, the distance between docks does not exceed the sensing distance; that is, if the drone flies out of the sensing range of one dock, it enters the sensing range of the other dock. Therefore, based on the drone's position, it is determined whether or not the drone is within the sensing range of a dock, the dock within the sensing range is designated as the target dock, and environmental information during the drone's flight task and return is collected from the target dock. If the detection ranges of the two docks overlap, the dock closest to the drone will be designated as the target dock based on the distance between the drone and the dock.

[0112] In this embodiment, the flow for determining the flight conditions of the drone using the above method is, specifically, Receiving sensor information and task commands, Based on the task instructions, determine the task category and break down the task, If it's a routine inspection order, you must determine whether the current external environment of the dock is suitable for the routine inspection task, and if not, terminate the task and upload the reason for the task termination. If suitable for performing the task, perform a self-check of the dock, After passing the dock's self-check, the drone will take off and perform its inspection patrol task. During the execution of the patrol inspection task, it is necessary to determine whether or not unfavorable conditions for the patrol inspection have appeared in the external environment, If the external environment is unsuitable for flight or if a return command is received by the drone, the drone will return and determine whether the current environment meets the conditions for precision landing. If precision landing conditions are met, the system will perform a precision landing of the drone, determine whether the dock is suitable for storing and charging the drone, and if the dock's internal environment is abnormal, adjust the dock's internal environment until the drone can be charged and stored. If precision landing is not achieved, an alternative landing procedure for the drone will be performed. If alternative landing conditions for the drone are not met, the drone will forcibly land, and the forced landing condition and adverse factors will be uploaded.

[0113] In this embodiment, the process of adjusting the internal environment of the dock is as follows: If the temperature inside the dock is lower than the lower limit of the set temperature range, the dock temperature will be brought up to the normal operating range by controlling the heating function of the air conditioner. If the temperature inside the dock is higher than the upper limit of the set temperature range, the air conditioner's cooling function will be turned on to bring the internal temperature of the dock back to the normal operating range. If the humidity inside the dock is higher than the set threshold, the air conditioner's dehumidification function will be turned on. This includes performing an alternative landing for the drone if the smog inside the dock is abnormal.

[0114] Example 5 As shown in Figure 20, Embodiment 5 of the present invention utilizes the drone patrol inspection system for a mesh dock described in Embodiment 1 or Embodiment 2. To acquire positioning data from the drone, Based on the acquired positioning data, the system determines whether the drone is within the preset landing range, and if not, controls the drone to move until the position requirement is met. After it is confirmed that the drone is within the preset landing range, if the drone is located at a position a first preset distance from the landing point, image data or video data is acquired from below the drone. If the precise landing range code cannot be identified based on the acquired image data or video data, the drone is controlled to descend to a position a third preset distance from the landing point and attempt to identify the precise landing range code again until the precise landing range code is identified. The present invention provides a method for controlling the precise landing of a drone, which includes: if a precise landing range code is identified based on acquired image data or video data, controlling the drone to descend to a position a second preset distance away from the landing point and to acquire image data or video data below the drone again; and if a precise landing position code is identified based on the acquired image data or video data, controlling the drone to descend to a position a fourth preset distance away from the landing point and to land the drone.

[0115] In this embodiment, the precision landing range code and the precision landing position code are adjacent to each other, one large and one small. The large one is called the precision landing range code and is used at high altitudes, primarily to determine the approximate landing position of the drone, and is used to constantly land and adjust its position and attitude. The small one is called the precision landing position code and, at low altitudes, the drone begins to identify it, constantly adjusts its position and attitude, and finally lands at this small drone precision landing position code.

[0116] The method described in this embodiment first utilizes RTK technology for the drone, enabling it to quickly and accurately return to the landing point after completing a task. RTK technology can reduce the drone's flight error to centimeter-level. In this way, the drone does not need to update its coordinates multiple times, can quickly return to the landing point, reach the landing area, begin imaging, search for the landing area code, complete image reception, complete identification within 0.7 seconds, return to adjust the drone's position, descend to a height of 20 cm to perform an instrument landing, and achieve complete automation of the drone's patrol inspection task.

[0117] Example 6 Embodiment 6 of the present invention provides a drone patrol inspection method based on visual movement tracking, which utilizes the drone patrol inspection system for a meshed dock described in Embodiment 1 or Embodiment 2, among which, The drone is equipped with a tri-axis pan / tilt head, an RTK positioning module, and a front-end AI processing module. A camera and a video camera are mounted on the tri-axis pan / tilt head. The camera is a monocular, zoomable camera, and the video camera is used to acquire video information of towers and columns. The camera and video camera are integrated into a single lens.

[0118] The RTK positioning module is used to determine the three-dimensional coordinate information of the drone. The front-end AI processing module is used to improve the accuracy of information gathering on patrol targets and the quality of the collected images by fitting the drone's flight control data, RTK positioning module data, and images taken by the zoom camera, issuing flight control commands to control the drone's flight, controlling the pan / tilt head to adjust the camera angle and zoom, locking onto inspection targets and taking pictures, taking pictures during the flight process approaching the hovering point using the visual zoom wide-angle camera, calculating the coordinate values ​​(GPS values) of the pictures taken and the attitude of the pan / tilt head, identifying the inspection targets in the pictures using the camera imaging principle, adjusting the position of the drone's pan / tilt head using a Kalman filter algorithm according to the current GPS position and three-dimensional velocity of the drone, as well as the roll angle, pitch angle, and yaw angle of the pan / tilt head attitude, locking onto the target inspection point of the tower / pillar with the zoom camera by zooming, and finally taking a picture to complete the information gathering on the target inspection point of the tower / pillar.

[0119] During the flight process from when the drone enters its inspection target until it leaves it, the drone always flies according to a set path, and the Kalman filter algorithm fits the current position and velocity data to adjust the pan / tilt attitude and camera zoom in real time, enabling camera movement tracking and lock-on shooting relative to the inspection target.

[0120] When controlling the rotation of the pan / tilt head using a method based on visual motion tracking, the pan / tilt head has m degrees of freedom, and the angular velocity of the pan / tilt head's rotation is The file is JPEG0007829691000010.jpg629, and the terminal linear velocity is The file is JPEG0007829691000011.jpg630, and the two have the following relationship: JPEG0007829691000012.jpg622 Eventually, The file is JPEG0007829691000013.jpg3643.

[0121] Rotation matrix used to transform from geodetic coordinates to camera coordinates. Calculate JPEG0007829691000014.jpg77, JPEG0007829691000015.jpg31144 Among these, the subscript cw represents an abbreviation for conversion from geodetic coordinate system to camera coordinate system. JPEG0007829691000016.jpg639 represents a matrix that needs to be rotated around the x, y, and z axes to move from the camera coordinate system to the geodetic coordinate system. JPEG0007829691000017.jpg1135 shows the roll angle, pitch angle, and yaw angle of the camera's tripod head orientation, starting from the first initial rotation from left to right, based on the camera's initial orientation. It is necessary to multiply JPEG0007829691000018.jpg69, and at this time, The filename becomes JPEG0007829691000019.jpg880. During the ceremony, The filename is JPEG0007829691000020.jpg1931.

[0122] As shown in Figure 21, the specific steps include the following:

[0123] In S1, in response to a patrol inspection request, before the drone enters the hovering point at a constant speed, the monocular zoom (telephoto mode) camera on the pan / tilt head is used to acquire a real-time wide-angle image of the patrol inspection target, and then the system proceeds to the next step.

[0124] In S2, it is determined whether the inspection target is located in the real-time image captured. If it is YES, proceed to S4. If it is NO, the pan / tilt head orientation is controlled in an "O" shape to search for the inspection target in the real-time image. After the inspection target is found, proceed to the next step.

[0125] In S3, the front-end AI processing module uses a Kalman filter algorithm based on information such as the patrol inspection target position, drone shooting position, and triaxial head attitude in real-time images to fit and output the drone position, head attitude position, and camera focal length mode that need to be adjusted, and then proceeds to execution in S2.

[0126] In S4, before the drone reaches the hovering point at a constant speed, the monocular zoom (close-focus mode) camera on the pan / tilt head is adjusted, and the front-end AI processing module reverses the attitude of the triaxial pan / tilt head in real time according to the three-dimensional direction in which the drone is flying at a constant speed, so that the patrol inspection target is locked onto in the center of the real-time image of the monocular zoom camera, and then proceeds to the next step.

[0127] In S5, the drone reaches the hovering point, that is, it reaches the front, directly in front of the inspection target, confirms that the inspection target is locked onto in the center of the real-time image of the monocular zoom camera, takes a photograph, and proceeds to the next step.

[0128] In S6, once the camera capture is complete, the front-end AI processing module processes the photos and controls the drone to perform the next hovering point task until all hovering point captures are complete and the drone has safely returned to the airport, and S1 is repeated.

[0129] Furthermore, the specific process of S2 is as follows: The Faster-RCNN algorithm is used to input the picture into the CNN, perform feature extraction, and then determine whether or not the picture contains a target for patrol inspection.

[0130] Furthermore, the specific process of S3 is as follows: The step assumes that the presence of a patrol inspection target object has already been identified in the image by S2, In S3.1, based on the position of the target object of the detection point in the image, the rotation direction of the pan / tilt head is determined, which is the direction in which the tower / pillar is offset to the center of the image. First, the pan / tilt head is rotated by the smallest unit to obtain an image of the tower / pillar at the current position, and its features are extracted. In S3.2, the features of the two preceding and succeeding pictures are matched, and the offset amount of the matching point at the pixel point is calculated. In S3.3, the rotation amount of the pan / tilt head is obtained based on the linear mapping relationship between the feature offset amount and the rotation amount of the pan / tilt head. In S3.4, adjust the pan / tilt head position according to the amount of rotation, and re-execute S2.

[0131] Furthermore, the specific process of S4 is as follows: Assuming the initial state is as described in Step 3, and the inspection target is already positioned in the center of the camera image, In S4.1, the current drone position and the intended three-dimensional vector direction P are calculated using RTK and an accelerometer on the drone. In S4.2, the camera's motion vector on the pan / tilt head is adjusted so that it is equal in magnitude to the drone's motion vector and opposite in direction. In S4.3, the offset amount at the pixel of the camera's central target at the current time is calculated according to the method described in S4.2. If there is no offset amount, it is considered that the camera's movement tracking relative to the inspection target object is stationary. Otherwise, proceed to the next step. In S4.4, the rotation amount of the pan / tilt head is obtained based on the linear mapping relationship between the feature offset amount of the central pixel of the image and the rotation amount of the pan / tilt head. Then, the camera on the pan / tilt head is finely adjusted to re-lock onto the target object of the inspection view relative to the center of the camera on the pan / tilt head.

[0132] The above are merely preferred embodiments of the present invention and do not limit it; various modifications and changes are possible for those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should all be within the scope of protection of the present invention. [Explanation of symbols]

[0133] 1...Tower / Column, 2...Dock bottom support, 3...Dock, 4...Landing platform, 5...Top cover, 6...Dock body, 7...Rotating rod, 8...Second motor, 9...First motor, 10...Second centering rod, 11...Charging rod, 12...Charging port, 13...First centering rod, 14...Rack, 15...Fixed seat, 16...Charging module, 17...Drone parking space, 18...Energy storage module, 19...Display module, 20...Charging port, 21...BMS control board, 22... 23. Cooling fan, 24. Communication interface, 25. 1st clamping member, 26. Elastic member, 27. 2nd clamping member, 27-1. Handle, 27-2. 1st sleeve, 27-3. 1st telescopic rod, 27-4. Fixed end, 27-5. 1st spring, 28. 2nd sleeve, 29. Dual output shaft motor, 30. 2nd telescopic rod, 31. Spring slider, 31-1. 1st slider, 31-2. 2nd spring, 31-3. 2nd slider, 32. Screw, 33. Drone, 34. Dock.

Claims

1. It includes multiple docks arranged in a mesh pattern, each used to accommodate at least one drone, The dock includes a dock controller that communicates with a control terminal, the dock controller communicates with a drone remote control, and the drone remote control communicates with the drone. The control terminal is used to optimize the patrol inspection time to the shortest possible, based on the drone's current flight range and the distance from the patrol inspection target to each dock. It obtains the patrol inspection target corresponding to each dock, generates the optimal patrol inspection route for each drone based on the determined patrol inspection target, and transmits it to the dock controller. The dock includes a dock body and a mounting mechanism, a vertical fixing mechanism, and a horizontal fixing mechanism provided within the dock body, the mounting mechanism includes an extendable landing platform and a first motor, and the landing platform is driven by the first motor. The longitudinal fixing mechanism includes a first centering rod, one end of which is provided on the side wall of the dock body via a pivot shaft and equipped with a gear, and the landing platform is provided with a rack that meshes with the gear, and the meshing of the gear and the rack drives the first centering rod to rotate around the pivot shaft. The lateral fixing mechanism includes a rotating rod with both ends provided on the side walls of the dock body, a second centering rod provided on the rotating rod, and a second motor. The rotating rod is driven by the second motor and rotates relative to the dock body in a direction opposite to the direction of movement of the landing platform, and drives the second centering rod to move in a direction perpendicular to the direction of movement of the landing platform. A drone-based patrol inspection system for mesh-type docks, characterized by the following features.

2. The meshing of the gear and rack causes the first centering rods, provided on both side walls, to rotate around their axes, thereby moving the other ends of both first centering rods to an intermediate position or spreading them apart in the lateral direction. The drone patrol inspection system for a mesh dock as described in feature 1.

3. A second centering rod is provided at each end of the rotating rod. When the landing platform is driven and reset, the rotating rod rotates in the forward direction, and the second centering rods at both ends move along the rotating rod to an intermediate position, restraining the drone laterally. The meshing of the rack and gears allows the first centering rods on both side walls to be moved to an intermediate position, thereby restraining the drone in the vertical direction. and / or, A second centering rod is provided at each end of the rotating rod. When the landing platform is pushed out from the dock body, the rotating rod rotates in the opposite direction, and the second centering rods at both ends move along the rotating rod to the sides, releasing the lateral constraint on the drone. The meshing of the rack and gears allows the first centering rods on both side walls to spread out to the sides, releasing the vertical constraint on the drone. The drone patrol inspection system for a mesh dock according to feature 2.

4. The drone is equipped with a three-axis pan / tilt head, an RTK positioning module, and a front-end AI processing module. A camera and a video camera are mounted on a three-axis pan / tilt head; the camera is a monocular, zoomable camera, and the video camera is used to acquire video information of the tower and pillars; the camera and video camera are integrated into a single lens. The RTK positioning module is used to determine the three-dimensional coordinate information of the drone. The front-end AI processing module is used to fit the drone's flight control data, RTK positioning module data, and images taken by the zoom camera, issue flight control commands to control the drone's flight, control the pan / tilt head to adjust the camera angle and zoom, lock onto inspection targets and take pictures, and, if the inspection target is not in the center of the camera image, to control the rotation of the pan / tilt head using a visual motion tracking method, and to determine the direction of rotation of the pan / tilt head based on the position of the inspection target in the image. The drone patrol inspection system for a mesh dock as described in feature 1.

5. Applied to the drone patrol inspection system for mesh docks according to any one of claims 1 to 4, To obtain the distance from the patrol inspection target to each dock, The dock closest to the inspection target is selected as the optimal dock, This includes sequentially determining the inspection targets for each dock and obtaining the inspection targets corresponding to each dock, Each dock performs a routine inspection task, and the routine inspection task is: The inspection targets within the dock area are numbered based on the distance from the target to the dock. The numbering rule is that the greater the distance from the inspection target to the dock, the higher the number. For each inspection target within the dock area, determine whether the difference between the drone's total flight time and the time required for a single inspection of that target is smaller than the minimum time required for a single inspection of any other inspection target within the dock area. If the answer is YES, then this inspection target will be treated as a single-tower task. If the answer is NO, the current inspection target is designated as the current inspection target, and it is determined whether the sum of the time from the dock to the current inspection target, the inspection time of the current inspection target, the inspection time from the current inspection target to the nearest secondary inspection target with a smaller number than the current inspection target, the time from the current inspection target to the secondary inspection target, and the time from the secondary inspection target to the dock is greater than the drone's total flight time. If the answer is YES, the current inspection target is designated as a single-tower task, and if the answer is NO, a two-tower / pillar route task is performed, including sequentially inspecting the current inspection target and the secondary inspection target. A method for drone-based patrol inspection of a mesh-type dock, characterized by the following features.

6. This includes determining the overall inspection time for the next node, and if the overall inspection time is greater than the drone's total flight time, performing only the current inspection task; otherwise, continuing to determine the overall inspection time for the next node. The method for patrolling and inspecting a mesh-type dock with a drone, as described in feature 5.

7. Applied to the drone patrol inspection system for mesh docks according to any one of claims 1 to 4, In response to a patrol inspection request, S1 acquires a real-time wide-angle image of the patrol inspection target by using an image acquisition module on the pan / tilt head before the drone enters the detection point at a constant speed. The system determines whether the inspection target is located in the real-time image captured. If the answer is YES, it proceeds to step S3. If the answer is NO, it controls the movement of the pan / tilt head to change its orientation until the inspection target is found in the real-time image (step S2). The processing module, based on the information of the patrol inspection target position, drone shooting position, and pan / tilt head attitude in the real-time image, employs a Kalman filter algorithm to fit the drone's shooting position and pan / tilt head attitude position, and determines the focal length mode of the image acquisition module in S3. The drone is controlled to fly to the shooting position obtained by fitting at a constant speed, and during the flight process, the processing module adjusts the attitude of the pan / tilt head in real time in reverse according to the three-dimensional direction in which the drone is flying at a constant speed, and also adjusts the focal length mode of the image acquisition module, in order to achieve that the patrol inspection target is locked onto the set area of ​​the real-time image of the image acquisition module, S4. The drone reaches the shooting position, confirms that the patrol inspection target location is within the real-time image setting area of ​​the image acquisition module, locks onto the inspection point, and acquires an image in S5. The processing module processes the captured pictures and controls the drone to perform the image acquisition task for the next detection point until the image acquisition task for all detection points is completed, and includes S6, which repeats S1. A drone patrol inspection method based on visual movement tracking, characterized by the following features.

8. In S2, The specific process for determining whether a patrol inspection target is located in a real-time image captured by a photograph includes employing a Faster-RCNN algorithm to input the picture into a CNN, performing feature extraction, and then determining whether or not a patrol inspection target exists in the picture. S3 specifically means, S3.1 involves determining the rotation direction of the pan / tilt head, which is the direction in which the tower / pillar is offset to the center of the image based on the position of the target object of the inspection point in the image, first rotating the pan / tilt head by the smallest unit, acquiring an image of the tower / pillar at the current position, and extracting its features. S3.2 involves matching the features of two tower / pillar images (front and back) and calculating the offset amount at the pixel point of the matching point in the image. S3.3 obtains the rotation amount of the tripod head based on the linear mapping relationship between the feature offset amount and the rotation amount of the tripod head, S3.4 includes adjusting the pan / tilt head position according to the amount of rotation, S4 specifically means, S4.1 calculates the current drone position and the three-dimensional vector direction P of the drone's intended movement based on the drone's position information and acceleration information. S4.2 adjusts the motion vector of the image acquisition module on the pan / tilt head so that it is equal in magnitude to the motion vector of the drone and opposite in direction. S4.3 calculates the offset amount at the pixel of the central target object of the image acquisition module at the current time. If there is no offset amount, it is determined that the movement tracking of the pan / tilt head's image acquisition module relative to the patrol inspection target object is in a stationary state. If there is an offset amount, the process proceeds to step S4.

4. S4.4 includes obtaining the rotation amount of the pan / tilt head based on a linear mapping relationship between the feature offset amount of the central pixel of the image and the rotation amount of the pan / tilt head, and then fine-tuning the position of the image acquisition module of the pan / tilt head to re-lock onto the target object of the detection point with respect to the center of the image acquisition module of the pan / tilt head, The method for patrolling and inspecting a drone based on visual movement tracking as described in feature 7.

Images