Unmanned aerial vehicle autonomous charging system and method suitable for water surface photovoltaic cleaning

Abstract

The invention relates to the technical field of unmanned aerial vehicle charging, in particular to an unmanned aerial vehicle autonomous charging system and method suitable for water surface photovoltaic cleaning, and the method comprises the steps: judging whether the unmanned aerial vehicle autonomous charging system is in butt joint with a water charging platform or not; the overwater charging platform adjusts the driving device to move in the driving direction based on the obtained approaching direction of the unmanned aerial vehicle, and judges whether to stop moving or adjust the inclination angle of the unmanned aerial vehicle; adjusting the hovering state of the unmanned aerial vehicle or shortening the launching distance, and generating a vibration characteristic value; determining a vibration reason of the overwater charging platform based on the vibration characteristic value; and determining the landing position of the unmanned aerial vehicle, calculating and generating a deviation distance in combination with the charging position of the water charging platform so as to determine the landing condition of the unmanned aerial vehicle, and determining the next docking processing method of the unmanned aerial vehicle and the water charging platform. According to the invention, the stability and accuracy of autonomous docking charging of the unmanned aerial vehicle suitable for water surface photovoltaic cleaning and the water charging platform can be improved.

Description

Technical Field

[0001] This invention relates to the field of drone charging technology, and in particular to an autonomous charging system and method for drones suitable for water surface photovoltaic cleaning. Background Technology

[0002] As one of the mainstays of clean energy, photovoltaics has expanded its application scenarios from land to water. Floating photovoltaics have become an important growth pole in the global photovoltaic industry due to their advantages such as not occupying arable land resources, improving module efficiency through natural cooling of water bodies, and reducing water evaporation. They provide key support for the transformation of the energy structure. However, the special water environment makes them face more complex panel pollution problems. Drone cleaning has solved the flexibility problem, but the core bottleneck is the endurance. To address the above pain points, drone cleaning needs to be upgraded from manual charging to autonomous endurance. It needs to adapt to the dynamic interference of waves in the water environment and the interference of the drone propeller blowing causing the charging platform to shake, so as to achieve precise docking between the drone and the charging platform.

[0003] Chinese Patent Publication No. CN111152678A discloses a drone charging device based on water-surface photovoltaics. This device includes a landslide, a baffle at the lower end of the landslide, a photovoltaic panel on the upper surface of the landslide, a supporting pontoon at the bottom, and a support frame between the photovoltaic panel and the pontoon. The landslide is cleverly designed with multiple sliding tracks and multiple landslide units divided by these tracks. It also features arc-shaped grooves and sloping grooves, with elastic charging contacts within the sloping grooves. Furthermore, a drone charging system located on a water-surface photovoltaic panel is disclosed, achieving on-site charging on the water surface and enabling drones to inspect and clean the photovoltaic panels. This system offers advantages such as wide coverage and significantly reduced manual labor intensity.

[0004] However, the following problems still exist in the existing technology. When the charging platform shakes significantly due to strong water flow, the drone is prone to landing deviations and falling into the water. Also, when the charging platform shakes significantly, the accuracy of the drone landing is not improved by using flexible connection methods such as adhesive joints. Summary of the Invention

[0005] To address these issues, the present invention provides an autonomous charging system and method for drones suitable for water surface photovoltaic cleaning, which overcomes the problems in the prior art where drones are prone to landing deviations and falling into the water when the charging platform shakes significantly due to large water flow impacts, and where the accuracy of drone landing cannot be improved by using flexible connection methods such as adhesive joints when the charging platform shakes significantly.

[0006] To achieve the above objectives, in one aspect, the present invention provides an autonomous charging method for unmanned aerial vehicles (UAVs) suitable for surface photovoltaic cleaning, comprising: A target area is set at the lower part of the drone, and a launchable adhesive connector and drive device are set on the water charging platform. A charging characterization value is generated based on the drone's remaining power, total power, and weight to determine whether to dock with the water charging platform. The floating charging platform adjusts the drive device to move along the drive direction based on the approach direction of the drone, and determines whether to stop moving or adjust the tilt angle of the drone based on the comparison result of the exposed area ratio of the target area obtained by the floating platform with several preset area ratios. Based on the determination result of the water charging platform launching the adhesive joint to the target area, the hovering state of the UAV is adjusted or the launch distance is shortened, and the water wave height and water wave frequency are generated based on the collected water wave image of the edge of the water charging platform to generate vibration characteristic values. Based on the vibration characteristic values, the cause of vibration of the water charging platform is determined, and measures are taken based on different causes of vibration, such as reducing the rotation speed of the UAV propeller or driving the adhesive joint to pull the UAV. Based on the collected images of the drone landing on the water-based charging platform, the landing position of the drone is determined. Combined with the charging position of the water-based charging platform, the deviation distance is calculated to determine the landing situation of the drone and to determine the processing method for the next docking of the drone and the water-based charging platform.

[0007] Furthermore, the process of generating a charging characteristic value based on the drone's remaining battery power, total battery power, and weight includes, The ratio of the drone's total battery power to its weight is denoted as the drone's energy density. The remaining battery power of the drone is collected and combined with the drone's energy density to generate the charging characterization value.

[0008] Furthermore, based on the charging characteristic value, it is determined whether the drone has docked with the water-based charging platform, wherein... If the charging characteristic value is less than or equal to the preset characteristic value, it is determined that the drone and the water charging platform are docking. The preset characterization value is positively correlated with the usage time of the drone.

[0009] Furthermore, the process by which the floating charging platform adjusts the movement of the drive unit along the drive direction based on the approach direction of the drone includes: The floating charging platform uses visual detection to obtain the approach direction of the drone in order to adjust the drive device to move along the drive direction; The water-based charging platform obtains the exposed area ratio of the target area through visual detection, and stops moving when the exposed area ratio is greater than or equal to a first preset area ratio. Adjust the tilt angle of the drone so that the exposed area percentage is greater than or equal to the second preset area percentage; The approach direction is the projection of the line connecting the drone and the water charging platform onto the water charging platform on a horizontal plane, and the driving direction is the opposite direction in the same vertical plane as the approach direction.

[0010] Furthermore, based on the determination result of the water-based charging platform launching the adhesive connector to the target area, the hovering state of the drone is adjusted or the launch distance is shortened, wherein... If the adhesive joint is successfully attached to the target area, it is determined that the drone should be adjusted to hover directly above the water charging platform. If the adhesive joint fails to adhere successfully to the target area, the launch distance is determined to be shortened.

[0011] Furthermore, the process of generating wave height and frequency based on the acquired water wave images of the edge of the floating charging platform to generate vibration feature values ​​includes, The ratio of water wave height to general wave height is determined as the wave height influence factor; The ratio of the water wave frequency to the general frequency is determined as the frequency influence factor; The weighted sum of the wave height influence factor and the frequency influence factor is determined to be the vibration characteristic value.

[0012] Furthermore, the determination of the vibration cause of the floating charging platform based on the vibration characteristic values, wherein, If the vibration characteristic is less than the preset characteristic value, the cause of the vibration is determined to be the blowing of the drone propeller, and the corresponding treatment method is to reduce the rotation speed of the drone propeller. If the vibration characteristic value is greater than or equal to the preset characteristic value, the cause of the vibration is determined to be natural water fluctuation, and the corresponding treatment method is to drive the adhesive joint to pull the drone.

[0013] Furthermore, the process of calculating the deviation distance to determine the drone landing situation and determining the corresponding processing method includes, The landing position of the drone is determined based on the collected images of the drone landing on the water charging platform, and the distance between the landing position and the charging position of the water charging platform is calculated as the deviation distance. The deviation distance is compared and analyzed with several preset deviation distances. Based on the analysis results, the landing situation of the UAV is determined and the corresponding processing method is determined.

[0014] Furthermore, the process of determining the drone's landing situation based on the analysis results and determining the handling method for the next docking between the drone and the water-based charging platform includes, If the deviation distance is greater than the first preset deviation distance and less than or equal to the second preset deviation distance, it is determined that the drone landing position has deviated, and the drone tilt angle is adjusted. If the deviation distance is greater than the second preset deviation distance, the landing position of the UAV is determined to be unqualified, and the method of adjusting the tilt angle of the UAV and shortening the launch distance of the water platform is adopted. Both the first preset deviation distance and the second preset deviation distance are positively correlated with the projected area of ​​the UAV on the horizontal plane, and the first preset deviation distance is less than the second preset deviation distance.

[0015] On the other hand, the present invention also provides an autonomous charging system for drones suitable for water surface photovoltaic cleaning, comprising: The data acquisition module is used to acquire the drone's remaining battery power, total battery power, and weight, as well as the drone's approach direction and the percentage of the target area exposed, and to acquire water wave images of the edge of the water charging platform and landing images of the drone landing on the water charging platform. An adjustment module, connected to the acquisition module, is used to adjust the driving direction of the driving device of the water platform based on the approach direction, and to determine whether to stop moving the water platform or adjust the tilt angle of the UAV based on the comparison analysis results of the exposed area ratio of the target area and several preset area ratios, and to adjust the hovering state of the UAV or shorten the launch distance based on the determination result of the water charging platform launching the adhesive joint to the target area. The analysis module, which is connected to the acquisition module, is used to generate charging characterization values ​​based on the remaining battery power of the drone, the total battery power of the drone, and the weight of the drone to determine whether the drone is docking with the water charging platform; to generate water wave height and water wave frequency based on the water wave image to generate vibration characteristic values; and to determine the landing position of the drone based on the landing image and calculate the deviation distance by combining it with the charging position of the water charging platform. The processing module, which is connected to the acquisition module and the analysis module respectively, is used to determine the cause of vibration of the water-based charging platform based on the vibration characteristic value, take corresponding processing methods based on different vibration causes, and determine the landing situation of the UAV based on the deviation distance and determine the processing method for the next docking of the UAV and the water-based charging platform.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: By setting a target area at the bottom of the drone and setting a launchable adhesive joint and driving device on the water-based charging platform, the water-based charging platform adjusts the distance between the water-based charging platform and the drone, as well as the tilt angle of the drone, to expose more of the target area based on the observable exposure area ratio of the target area set at the bottom of the drone. The water-based charging platform captures the target area at the bottom of the drone in real time through a camera, such as geometric shapes with high-contrast markings, and uses image processing technology to calculate the exposure area ratio of the target area. This solves the stability problem of traditional charging platforms under complex water surface conditions, and is suitable for diverse scenarios such as lakes, rivers, and near seas. It improves the stability and accuracy of the autonomous docking and charging of drones suitable for water surface photovoltaic cleaning with the water-based charging platform.

[0017] Furthermore, this invention effectively determines whether a drone needs charging based on its remaining battery power, total battery power, and weight. It also adjusts the driving direction of the charging platform based on the drone's approach direction, reducing power loss as the drone approaches the platform. Additionally, the charging platform scans the exposed area of ​​the target region beneath the drone, and by adjusting the drone's tilt angle to increase the exposed area percentage, the success rate of the adhesive connector hitting the target region is improved, extending the single cleaning operation time. This invention proposes a multi-sensor fusion-based attitude collaborative control strategy, providing an efficient and reliable solution for autonomous charging of drones in complex environments. This further improves the stability and accuracy of autonomous docking and charging between drones suitable for water surface photovoltaic cleaning and water-based charging platforms.

[0018] Furthermore, this invention analyzes the water waves at the edge of the floating charging platform to determine the cause of the platform's swaying, and then adopts corresponding processing methods to improve the accuracy of drone landing. If the main cause is water wave vibration caused by the drone's propeller fan, the propeller speed is reduced; if the main cause is water wave pushing the floating charging platform, the adhesive joint is tightened to guide the drone to the accurate position. Through the collaborative design of multi-source disturbance identification, propeller disturbance suppression, and dynamic response to natural water waves, this system significantly improves the stability and accuracy of autonomous charging of floating photovoltaic cleaning drones. It proposes an adhesive joint traction strategy based on force control-vision closed loop, providing an efficient and reliable solution for autonomous charging of drones in complex water surface environments, and further improving the stability and accuracy of autonomous docking and charging between drones suitable for floating photovoltaic cleaning and floating charging platforms.

[0019] Furthermore, this invention analyzes the location of the drone landing on the water-based charging platform and further corrects the process of launching the adhesive connector on the water-based platform in the next operation. This improves the accuracy of the adhesive connector hitting the target area, enhances the practicality of the adhesive connector tightening the drone during landing, and achieves dynamic correction of the adhesive connector launch angle based on historical landing data. This further improves the stability and accuracy of the drone, which is suitable for water surface photovoltaic cleaning, autonomously docking and charging with the water-based charging platform. Attached Figure Description

[0020] Figure 1 This is a schematic flowchart of an embodiment of the present invention for an autonomous charging method for drones used in water surface photovoltaic cleaning; Figure 2 This is a schematic diagram illustrating the process of the water-based charging platform moving along the driving direction according to an embodiment of the present invention. Figure 3 This is a logic diagram for determining the cause of vibration of a floating charging platform based on vibration characteristic values, according to an embodiment of the present invention. Figure 4 This is a structural block diagram of an autonomous charging system for drones applicable to water surface photovoltaic cleaning, according to an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0022] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0023] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0024] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0025] Please see Figure 1 As shown, this is a flowchart illustrating an autonomous charging method for drones used in water surface photovoltaic cleaning according to an embodiment of the present invention. The embodiment of the present invention provides an autonomous charging method for drones used in water surface photovoltaic cleaning, comprising: Step S1: Set a target area at the bottom of the drone, set an adhesive connector and drive device that can be launched on the water charging platform, and generate a charging characterization value based on the drone's remaining power, total power and weight to determine whether to dock with the water charging platform. Step S2: The water-based charging platform adjusts the drive device to move along the drive direction based on the approach direction of the drone. Based on the comparison between the exposed area ratio of the target area obtained by the water-based platform and several preset area ratios, it determines whether to stop moving or adjust the tilt angle of the drone. Step S3: Based on the determination result of the launch adhesive joint of the water charging platform to the target area, adjust the hovering state of the UAV or shorten the launch distance, and generate water wave height and water wave frequency based on the collected water wave image of the edge of the water charging platform to generate vibration characteristic values. Step S4: Determine the cause of vibration of the water charging platform based on vibration characteristic values, and take measures such as reducing the rotation speed of the drone propeller or driving the adhesive joint to pull the drone based on different vibration causes. Step S5: Based on the collected images of the drone landing on the water charging platform, determine the drone's landing position, and combine this with the charging position of the water charging platform to calculate and generate the deviation distance to determine the processing method for the next docking between the drone and the water charging platform.

[0026] Understandably, the adhesive joint can be set as a magnetic structure with a traction rope. The target area of ​​the drone is also a magnetic structure. The type of magnet needs to be selected based on the weight of the drone, the force requirements during docking, the resistance to water surface swaying, and the support of the drone's own weight. For small water surface cleaning drones (usually 5-15kg), it is recommended to use neodymium iron boron strong magnets, but the weight of the magnets needs to be controlled, usually not exceeding 5% of the total load of the drone, to avoid significantly reducing the battery life. The magnetic structure should be staggered from sensitive components, such as GPS antennas and compasses, and a safe distance of at least 15cm should be maintained. For example, the magnetic structure can be placed in the center of the abdomen, and the compass can be placed on the arm or top.

[0027] It is understandable that for those skilled in the art, the drive device is located underwater on the water-based charging platform to adjust the launch device of the water-based charging platform to align with the target area of ​​the drone, and to drive the water-based charging platform to approach the drone. This is existing technology and will not be described in detail here.

[0028] Specifically, this invention sets a target area at the bottom of a drone and sets up a launchable adhesive connector and drive device on a floating charging platform. The floating charging platform adjusts the distance between itself and the drone, as well as the drone's tilt angle, to expose more of the target area based on the observable percentage of the exposed area of ​​the target area set at the bottom of the drone. The floating charging platform captures the target area at the bottom of the drone in real time using a camera, such as geometric shapes with high-contrast markings, and uses image processing technology to calculate the percentage of the exposed area of ​​the target area. This solves the stability problem of traditional charging platforms under complex water surface conditions and is suitable for diverse scenarios such as lakes, rivers, and nearshore areas. It improves the stability and accuracy of drones suitable for water surface photovoltaic cleaning and autonomous docking and charging with the floating charging platform.

[0029] Specifically, in step S1, the process of generating a charging characterization value based on the drone's remaining battery power, total battery power, and weight includes: The ratio of the drone's total battery power to its weight is denoted as the drone's energy density. The remaining battery power of the drone is collected and combined with the drone's energy density to generate a charging characterization value.

[0030] Specifically, the charging performance value = ax_remaining drone battery power + bx_drone energy density / 10, where the drone battery power is in Wh, the drone energy density is in Wh / kg, and a and b are weighting coefficients, a + b = 1. Since the drone battery power has a significant impact on whether the drone needs to be charged on water, a is generally taken as 0.7 and b as 0.3. In the above formula, only the numerical values ​​are used in the calculation.

[0031] Specifically, in step S1, it is determined whether the drone has docked with the water-based charging platform based on the charging characteristic value. If the charging indicator value is less than or equal to the preset indicator value, it is determined that the drone and the water charging platform are docking. If the charging performance value is greater than the preset performance value, it is determined that the drone and the water charging platform will not dock. The preset characterization value is positively correlated with the usage time of the drone.

[0032] In one specific embodiment, a preset characterization value is set to 20. If the charging characterization value is 17.75, which is less than the preset characterization value, it is determined that the drone and the water charging platform will dock. If the charging performance value is 45.75, which is greater than the preset performance value, it is determined that the drone and the water charging platform will not dock. It is understandable that the longer a drone is used, the lower its total battery capacity and the lower its battery life. When the drone displays a higher remaining battery level, it needs to be charged to ensure normal operation. Therefore, the preset characterization value is positively correlated with the drone's usage time. Preferably, for a drone with a battery capacity of 200Wh and a weight of 10kg, the drone's usage time is 0.5 years, and the preset characterization value is 13. The drone will be used for one year, with a preset performance value of 16. The drone will be used for 2 years, with a preset performance value of 20.

[0033] Please see Figure 2 As shown, this is a schematic diagram of the process of the water-based charging platform moving along the driving direction according to an embodiment of the present invention. In step S2, the process of adjusting the driving device to move along the driving direction based on the approach direction of the drone includes: In step S201, the water-based charging platform obtains the approach direction of the drone through visual detection to adjust the drive device to move along the drive direction. In step S202, the water-based charging platform obtains the exposed area ratio of the target area through visual detection, and stops moving when the exposed area ratio is greater than or equal to the first preset area ratio. Step S203: Adjust the tilt angle of the drone so that the exposed area percentage is greater than or equal to the second preset area percentage; The approach direction is the projection of the line connecting the drone and the floating charging platform onto the floating charging platform on the horizontal plane, and the driving direction is the opposite direction in the same vertical plane as the approach direction.

[0034] Specifically, the floating charging platform uses visual detection to obtain the distance the drone travels over a period of time to determine the drone's approach direction, adjusts the drive device to move along the drive direction, and detects the ratio of the area of ​​the target area that can be scanned to the total designed area of ​​the target area as the exposure area percentage.

[0035] In one specific embodiment, the first preset area ratio is set to 80%, and the second preset area ratio is set to 90%. If the exposed area ratio is 73%, which is less than the first preset area ratio, it is determined that the water charging platform will continue to move toward the drone. If the exposed area percentage is 87%, which is greater than the first preset area percentage but less than the second preset area percentage, then the water charging platform is determined to stop moving, and the tilt angle of the drone is adjusted to increase the exposed area percentage. If the exposed area percentage is 94%, which is greater than the second preset area percentage, then the adjustment of the drone's tilt angle will be stopped.

[0036] It is understandable that the larger the exposed area percentage, the greater the probability that the adhesive will hit the target area. Therefore, the first preset area percentage range is 80% to 85%, and the second preset area percentage range is 90% to 95%.

[0037] Specifically, in step S3, based on the determination result of the launch adhesive connector of the water-based charging platform reaching the target area, the hovering state of the drone is adjusted or the launch distance is shortened. If the adhesive connector is successfully attached to the target area, then the drone is adjusted to hover directly above the water charging platform. If the adhesive joint fails to adhere successfully to the target area, the launch distance will be shortened.

[0038] Specifically, if the adhesive joint fails to adhere successfully to the target area, the launch distance is shortened based on the closest distance between the adhesive joint and the edge of the target area, which will not be elaborated further here.

[0039] Specifically, this invention effectively determines whether a drone needs charging based on its remaining battery power, total battery power, and weight. It also adjusts the driving direction of the charging platform based on the drone's approach direction, reducing power loss as the drone approaches. Furthermore, the charging platform scans the exposed area of ​​the target region beneath the drone, and by adjusting the drone's tilt angle to further increase the exposed area percentage, the success rate of the adhesive connector hitting the target region is improved, extending the single cleaning operation time. This invention proposes a multi-sensor fusion-based attitude collaborative control strategy, providing an efficient and reliable solution for autonomous charging of drones in complex environments. It further improves the stability and accuracy of autonomous docking and charging between drones suitable for water surface photovoltaic cleaning and water-based charging platforms.

[0040] Specifically, in step S3, the process of generating water wave height and frequency based on the acquired water wave image of the edge of the floating charging platform to generate vibration feature values ​​includes, The ratio of water wave height to general wave height is determined as the wave height influence factor; The ratio of the water wave frequency to the general frequency is determined as the frequency influence factor; The weighted sum of the wave height influence factor and the frequency influence factor is determined to be the vibration characteristic value.

[0041] Specifically, in practice, the wave height is generally the average wave height in the water wave images of the edge of the floating charging platform collected within a predetermined time period, and the frequency is generally the average frequency in the water wave images of the edge of the floating charging platform collected within a predetermined time period.

[0042] Specifically, the sum of the weighting coefficients of the wave height influence factor and the frequency influence factor is 1. Since the wave height influence factor and the frequency influence factor have similar characteristics in representing the vibration of the water charging platform, the weighting coefficient of the wave height influence factor is generally taken as 0.5, and the weighting coefficient of the frequency influence factor is also 0.5.

[0043] Specifically, the wave height and frequency obtained from the water wave images of the edge of the floating charging platform acquired within a predetermined time period are due to natural water undulations.

[0044] Please see Figure 3 As shown, this is a logic diagram for determining the vibration cause of a water-based charging platform based on vibration characteristic values ​​according to an embodiment of the present invention. In step S4, the vibration cause of the water-based charging platform is determined based on vibration characteristic values, wherein... If the vibration characteristic value is less than the preset characteristic value, the cause of the vibration is determined to be the blowing of the drone propeller, and the corresponding treatment method is to reduce the rotation speed of the drone propeller. If the vibration characteristic value is greater than or equal to the preset characteristic value, the cause of the vibration is determined to be natural water fluctuation, and the corresponding treatment method is to drive the adhesive joint to pull the drone.

[0045] In one specific embodiment, a preset characteristic value is set to 80%. If the vibration characteristic value is 94%, which is greater than the preset characteristic value, the vibration is determined to be caused by the drone propeller blowing. The corresponding treatment method is to reduce the rotation speed of the drone propeller. If the vibration characteristic value is 63%, which is less than the preset characteristic value, the vibration is determined to be caused by natural water fluctuations, and the corresponding treatment method is to drive the adhesive joint to pull the drone.

[0046] Specifically, to ensure the accuracy of determining the vibration of the water-based charging platform caused by the drone propeller, the preset characteristic value range is 70% to 90%.

[0047] Specifically, this invention analyzes the water waves at the edge of the floating charging platform to determine the cause of the platform's swaying, and then takes corresponding measures to improve the accuracy of drone landing. If the main cause is water wave vibration caused by the drone's propeller, the propeller speed is reduced; if the main cause is water wave pushing the floating charging platform, the adhesive joint is tightened to guide the drone to the accurate position. Through the collaborative design of multi-source disturbance identification, propeller disturbance suppression, and dynamic response to natural water waves, this system significantly improves the stability and accuracy of autonomous charging of drones used for photovoltaic cleaning on water surfaces. It proposes an adhesive joint traction strategy based on force control-vision closed loop, providing an efficient and reliable solution for autonomous charging of drones in complex water surface environments, and further improving the stability and accuracy of autonomous docking and charging between drones suitable for photovoltaic cleaning on water surfaces and floating charging platforms.

[0048] Specifically, in step S5, the process of calculating the generated deviation distance to determine the drone landing situation and determining the corresponding processing method includes, The landing position of the drone is determined by the collected images of the drone landing on the water charging platform, and the distance between the landing position and the charging position of the water charging platform is calculated as the deviation distance. The deviation distance is compared and analyzed with several preset deviation distances. Based on the analysis results, the landing situation of the UAV is determined and the corresponding handling method is determined.

[0049] Specifically, the landing position is the center of the drone when it lands on the water charging platform, the charging position is the area where the drone can connect with the magnetic charging port of the water charging platform through the magnetic charging port, and the deviation distance is the minimum distance between the landing position and the edge of the charging position.

[0050] Specifically, in step S5, the landing situation of the drone is determined based on the analysis results, and the processing method for the next docking of the drone and the water-based charging platform is determined. If the deviation distance is less than or equal to the first preset deviation distance, the drone landing position is determined to be normal. If the deviation distance is greater than the first preset deviation distance and less than or equal to the second preset deviation distance, it is determined that the drone landing position has deviated, and the drone tilt angle is adjusted. If the deviation distance is greater than the second preset deviation distance, the landing position of the UAV is deemed unqualified, and the following measures are taken: adjust the tilt angle of the UAV and shorten the launch distance of the water platform. Both the first preset deviation distance and the second preset deviation distance are positively correlated with the projected area of ​​the UAV on the horizontal plane, and the first preset deviation distance is smaller than the second preset deviation distance.

[0051] In one specific embodiment, the first preset deviation distance is set to 20cm and the second preset deviation distance is set to 40cm. If the deviation distance is 15cm, which is less than the first preset deviation distance, the landing position of the drone is determined to be normal. If the deviation distance is 28cm, which is greater than the first preset deviation distance but less than the second preset deviation distance, it is determined that the drone landing position has deviated, and the drone tilt angle is adjusted. If the deviation distance is 49cm, which is greater than the second preset deviation distance, the landing position of the drone is deemed unqualified, and the drone's tilt angle is adjusted while the launch distance of the water platform is shortened. Specifically, in order to ensure accurate docking between the magnetic charging port of the drone and the magnetic charging port of the water charging platform, preferably, the first preset deviation distance is in the range of 15cm to 30cm, and the second preset deviation distance is in the range of 30cm to 50cm.

[0052] Specifically, this invention analyzes the location of the drone landing on the water-based charging platform and further corrects the process of launching the adhesive connector on the water-based platform in the next operation. This improves the accuracy of the adhesive connector hitting the target area, enhances the practicality of the adhesive connector tightening the drone during landing, and achieves dynamic correction of the adhesive connector launch angle based on historical landing data. This further improves the stability and accuracy of the drone, which is suitable for water surface photovoltaic cleaning, autonomously docking and charging with the water-based charging platform.

[0053] Please see Figure 4 The diagram shown is a structural block diagram of an autonomous charging system for drones used in water surface photovoltaic cleaning, according to an embodiment of the present invention. The present invention also provides an autonomous charging system for drones used in water surface photovoltaic cleaning, comprising: The data acquisition module is used to acquire the drone's remaining battery power, total battery power, and weight, as well as the drone's approach direction and the percentage of the target area exposed, and to acquire water wave images of the edge of the water charging platform and landing images of the drone landing on the water charging platform. The adjustment module, which is connected to the acquisition module, is used to adjust the driving direction of the driving device of the water platform based on the approach direction, and to determine whether to stop moving the water platform or adjust the tilt angle of the drone based on the comparative analysis results of the exposure area ratio of the target area and several preset area ratios, and to adjust the hovering state of the drone or shorten the launch distance based on the determination result of the water charging platform launching adhesive joint to the target area. The analysis module, which is connected to the acquisition module, is used to generate charging characterization values ​​based on the drone's remaining battery power, total battery power, and weight to determine whether the drone is docking with the water charging platform; to generate water wave height and frequency based on water wave images to generate vibration characteristic values; and to determine the drone's landing position based on landing images and calculate the deviation distance by combining the landing position of the water charging platform. The processing module, which is connected to the acquisition module and the analysis module respectively, is used to determine the cause of vibration of the water charging platform based on vibration characteristic values, take corresponding processing methods based on different vibration causes, and determine the landing situation of the UAV based on the deviation distance and determine the processing method for the next docking of the UAV and the water charging platform.

[0054] Specifically, the drone autonomous charging system for water surface photovoltaic cleaning provided in this embodiment of the invention can achieve the same technical effect by adopting the above-mentioned drone autonomous charging method for water surface photovoltaic cleaning, which will not be repeated here.

[0055] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for autonomous charging of unmanned aerial vehicles (UAVs) suitable for surface photovoltaic cleaning, characterized in that, include: A target area is set at the lower part of the drone, and a launchable adhesive connector and drive device are set on the water charging platform. A charging characterization value is generated based on the drone's remaining power, total power, and weight to determine whether to dock with the water charging platform. The floating charging platform adjusts the drive device to move along the drive direction based on the approach direction of the drone, and determines whether to stop moving or adjust the tilt angle of the drone based on the comparison result of the exposed area ratio of the target area obtained by the floating platform with several preset area ratios. Based on the determination result of the water charging platform launching the adhesive joint to the target area, the hovering state of the UAV is adjusted or the launch distance is shortened, and the water wave height and water wave frequency are generated based on the collected water wave image of the edge of the water charging platform to generate vibration characteristic values. Based on the vibration characteristic values, the cause of vibration of the water charging platform is determined, and measures are taken based on different causes of vibration, such as reducing the rotation speed of the UAV propeller or driving the adhesive joint to pull the UAV. Based on the collected images of the drone landing on the water-based charging platform, the landing position of the drone is determined. Combined with the charging position of the water-based charging platform, the deviation distance is calculated to determine the landing situation of the drone and to determine the processing method for the next docking of the drone and the water-based charging platform.

2. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 1, characterized in that, The process of generating a charging characterization value based on the drone's remaining battery power, total battery power, and weight includes... The ratio of the total battery power of the drone to its weight is denoted as the drone's energy density. The remaining battery power of the drone is collected and combined with the drone's energy density to generate the charging characterization value.

3. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 2, characterized in that, The determination of whether the drone has docked with the water-based charging platform is based on the charging performance value. If the charging characteristic value is less than or equal to the preset characteristic value, it is determined that the drone and the water charging platform are docking. The preset characterization value is positively correlated with the usage time of the drone.

4. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 3, characterized in that, The process by which the floating charging platform adjusts the movement of the drive unit along the drive direction based on the approach direction of the drone includes: The floating charging platform obtains the approach direction of the drone through visual detection to adjust the drive device to move along the drive direction; The water-based charging platform obtains the exposed area ratio of the target area through visual detection, and stops moving when the exposed area ratio is greater than or equal to a first preset area ratio. Adjust the tilt angle of the drone so that the exposed area percentage is greater than or equal to the second preset area percentage; The approach direction is the projection of the line connecting the drone and the water charging platform onto the water charging platform on a horizontal plane, and the driving direction is the opposite direction in the same vertical plane as the approach direction.

5. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 4, characterized in that, Based on the determination result of the water-based charging platform launching the adhesive connector to the target area, the hovering state of the drone is adjusted or the launch distance is shortened, wherein... If the adhesive joint is successfully attached to the target area, it is determined that the drone should be adjusted to hover directly above the water charging platform. If the adhesive joint fails to adhere successfully to the target area, the launch distance is determined to be shortened.

6. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 5, characterized in that, The process of generating wave height and frequency based on acquired water wave images of the edge of the floating charging platform to generate vibration feature values ​​includes, The ratio of water wave height to general wave height is determined as the wave height influence factor; The ratio of the water wave frequency to the general frequency is determined as the frequency influence factor; The weighted sum of the wave height influence factor and the frequency influence factor is determined to be the vibration characteristic value.

7. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 6, characterized in that, The determination of the vibration cause of the water-based charging platform based on the vibration characteristic values, wherein, If the vibration characteristic value is less than the preset characteristic value, the cause of the vibration is determined to be the blowing of the drone propeller, and the corresponding treatment method is to reduce the rotation speed of the drone propeller. If the vibration characteristic value is greater than or equal to the preset characteristic value, the cause of the vibration is determined to be natural water fluctuation, and the corresponding treatment method is to drive the adhesive joint to pull the drone.

8. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 7, characterized in that, The process of calculating and generating the deviation distance to determine the drone landing situation and determining the corresponding processing method includes: The landing position of the drone is determined based on the collected images of the drone landing on the water charging platform, and the distance between the landing position and the charging position of the water charging platform is calculated as the deviation distance. The deviation distance is compared and analyzed with several preset deviation distances. Based on the analysis results, the landing situation of the UAV is determined and the corresponding processing method is determined.

9. The autonomous charging method for unmanned aerial vehicles (UAVs) suitable for water surface photovoltaic cleaning according to claim 8, characterized in that, The process involves determining the drone's landing situation based on the analysis results and determining the handling method for the next docking between the drone and the water-based charging platform. If the deviation distance is greater than the first preset deviation distance and less than or equal to the second preset deviation distance, it is determined that the drone landing position has deviated, and the drone tilt angle is adjusted. If the deviation distance is greater than the second preset deviation distance, the landing position of the UAV is determined to be unqualified, and the method of adjusting the tilt angle of the UAV and shortening the launch distance of the water platform is adopted. Both the first preset deviation distance and the second preset deviation distance are positively correlated with the projected area of ​​the UAV on the horizontal plane, and the first preset deviation distance is less than the second preset deviation distance.

10. An autonomous charging system for unmanned aerial vehicles (UAVs) suitable for surface photovoltaic cleaning, comprising the autonomous charging method for UAVs suitable for surface photovoltaic cleaning as described in any one of claims 1-9, characterized in that, include: The data acquisition module is used to acquire the drone's remaining battery power, total battery power, and weight, as well as the drone's approach direction and the percentage of the target area exposed, and to acquire water wave images of the edge of the water charging platform and landing images of the drone landing on the water charging platform. An adjustment module, connected to the acquisition module, is used to adjust the driving direction of the driving device of the water platform based on the approach direction, and to determine whether to stop moving the water platform or adjust the tilt angle of the UAV based on the comparison analysis results of the exposed area ratio of the target area and several preset area ratios, and to adjust the hovering state of the UAV or shorten the launch distance based on the determination result of the water charging platform launching the adhesive joint to the target area. The analysis module, which is connected to the acquisition module, is used to generate charging characterization values ​​based on the remaining battery power of the drone, the total battery power of the drone, and the weight of the drone to determine whether the drone is docking with the water charging platform; to generate water wave height and water wave frequency based on the water wave image to generate vibration characteristic values; and to determine the landing position of the drone based on the landing image and calculate the deviation distance by combining it with the charging position of the water charging platform. The processing module, which is connected to the acquisition module and the analysis module respectively, is used to determine the cause of vibration of the water charging platform based on the vibration characteristic value, take corresponding processing methods based on different vibration causes, and determine the landing situation of the UAV based on the deviation distance and determine the next docking processing method between the UAV and the water charging platform.

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