Urban high-rise glass curtain wall cleaning method based on unmanned aerial vehicle group

Abstract

The invention relates to the technical field of unmanned aerial vehicles, and particularly discloses an urban high-rise glass curtain wall cleaning method based on an unmanned aerial vehicle group, and the method comprises the steps: calculating the respective density of three cleaning modes in each region based on the respective cleaning mode of each glass plate in each preset region; and according to the density proportion of each cleaning mode, providing three unmanned aerial vehicle configuration modes to clean each preset area. And after cleaning is completed, area scanning is carried out, the target to be cleaned for the second time is obtained, and secondary cleaning is carried out. The unmanned aerial vehicle of the corresponding type can be configured for cleaning according to the dirt type of the glass plate. Through the configuration mode of the unmanned aerial vehicle, the cleaning efficiency can be greatly improved, and the loss of the unmanned aerial vehicle on the way is reduced.

Description

Technical Field

[0001] The invention belongs to the technical field of unmanned aerial vehicles, and in particular relates to a method for cleaning glass curtain walls of urban high-rise buildings based on a group of unmanned aerial vehicles. Background Art

[0002] Currently, when cleaning the exterior walls of tall buildings, most of them require "Spider-Man" to climb on the exterior walls to clean manually. This work is not only risky, but the staff also need to constantly lift, replenish and replace cleaning equipment, which is time-consuming and laborious.

[0003] Prior art Chinese patent application CN201610865457.8 discloses a glass exterior wall cleaning drone, including a drone unit and a ground unit, wherein a signal line, a power line and a water pipe are bundled together to form a working cable, and the drone unit and the ground unit are connected via the working cable.

[0004] The above prior art has realized the cleaning of glass curtain walls by drones. However, the prior art can only perform point-to-point cleaning, and in practice, manual control is still required.

[0005] Another prior art Chinese patent application CN202310330164.X discloses a solar glass panel cleaning operation monitoring and control system, which includes a glass panel basic information acquisition module, a glass panel dust monitoring module, a glass panel contamination monitoring module, a glass panel cleaning mode analysis module, a glass panel cleaning rule analysis module, a glass panel cleaning control scheme generation module and a cleaning operation information library; The above-mentioned prior art monitors the dust concentration and dirt information of each solar glass panel laid in a designated area, thereby analyzing the cleaning needs, cleaning mode and cleaning rules, and then performing cleaning control. The prior art is applied to the cleaning of glass curtain walls, which can realize automatic cleaning by drones.

[0006] However, even if the above two existing technologies are combined, it is still impossible to make a comprehensive plan for drones to achieve efficient cleaning operations of high-rise glass curtain walls. Summary of the invention

[0007] The purpose of the present invention is to provide a method for cleaning the glass curtain walls of urban high-rise buildings based on a drone swarm, which partially solves or alleviates the above-mentioned deficiencies in the prior art and can configure corresponding types of drones for cleaning according to the type of dirt on the glass plate.

[0008] In order to solve the above-mentioned technical problems, the present invention specifically adopts the following technical solutions: A method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm, comprising the following steps: S101 calculates the density Pi of the three cleaning modes in each preset area based on the cleaning mode of each glass plate, and executes step S103, S105 or S107; the three cleaning modes include: normal cleaning mode, strong cleaning mode and mixed cleaning mode; the density is the number of glass plates corresponding to each cleaning mode in the current area; i=1, 2, 3; S103: If the density of the first cleaning mode in any area is greater than the first preset density threshold value P0, and the sum of the densities of the other two cleaning modes is less than the second preset density threshold value P0', multiple drones with the first cleaning mode are configured for the any area, and step S109 is executed; the first cleaning mode is any one of the ordinary cleaning mode, the strong cleaning mode and the mixed cleaning mode; S105: If the density of the first cleaning mode in any area is greater than the third preset density threshold value P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold value P0''', multiple drones with the first cleaning mode and multiple second drones with the second cleaning mode are configured for the any area; the first cleaning mode is any one of the ordinary cleaning mode, the strong cleaning mode and the mixed cleaning mode, and the second cleaning mode is any one of the remaining two cleaning modes other than the first cleaning mode; the third preset density threshold is less than the first preset density threshold, and the fourth preset density threshold is greater than the second preset density threshold, and step S109 is executed; S107: If the difference between the densities of the three cleaning modes in any area is less than the preset difference threshold, multiple drones with a normal cleaning mode, multiple drones with a strong cleaning mode, and multiple drones with a mixed cleaning mode are respectively configured for the any area, and step S109 is executed; S109 After the cleaning is completed, a regional scan is performed to obtain the target to be cleaned a second time, and a second cleaning is performed.

[0009] As an improvement, in step S103, when the first cleaning mode is the normal cleaning mode or the strong cleaning mode, a drone with the corresponding cleaning mode is configured to perform cleaning, and the remaining part is to be cleaned a second time; When the first cleaning mode is the mixed cleaning mode, the drone with the mixed cleaning mode is configured to clean the entire area.

[0010] As an improvement, in step S105, when the first cleaning mode and the second cleaning mode are both one of the ordinary cleaning mode and the strong cleaning mode, a drone with the corresponding cleaning mode is configured to perform cleaning; and the remaining part is cleaned by a drone with the ordinary cleaning mode and a drone with the strong cleaning mode respectively; When the first cleaning mode or the second cleaning mode is a mixed cleaning mode, a drone with a corresponding cleaning mode is configured to perform cleaning; and the remaining part is to be cleaned a second time.

[0011] As an improvement, the entire area to be cleaned is divided into a number of preset areas according to a division rule; the division rule is to divide according to the type of dirt.

[0012] As an improvement, before the second cleaning, the remaining part after the first cleaning is divided according to the division rule.

[0013] As an improvement, the steps are also included: S111: When the remaining power of any UAV reaches a preset power threshold, obtain the pending task list of any UAV, and determine whether the pending task list is empty. If it is not empty, execute step S113; if it is empty, execute step S115; the preset power threshold can only support the UAV to return from the current position to the starting point; S113 obtains the remaining power and pending task lists of multiple other drones near the any drone, and executes step S117; wherein, with the current location of the any drone as the center, the other drones within the preset radius are other drones adjacent to the any drone; S115 controls any one of the drones to return from the current position to the starting point; S117 determines whether the other drones nearby can add new cleaning tasks according to the remaining power of the other drones and the number of pending tasks in the pending task list; if they can be added, execute step S119; if they cannot be added, execute step S201; S119: selecting at least one other drone from all other drones whose number of cleaning tasks that can be added is greater than a preset threshold, and evenly distributing the to-be-processed tasks in the to-be-processed task list of any of the drones to the selected at least one other drone.

[0014] As an improvement, when at least one other drone is screened out, the recommendation index of each other drone is calculated: P=K1*D i，j +K2*T i，j ; Among them, D i，j is the distance between the other UAV and any UAV, T i，j The waiting time for the other drones to execute the newly added task; K1 and K2 are empirical constants; Among the tasks to be processed, the tasks that are ranked higher in the queue are preferentially assigned to other drones with smaller recommendation indexes.

[0015] As an improvement, before executing step S113, the following steps are further included: S201 determines whether the number of tasks to be processed in the to-be-processed task list of any UAV is greater than or equal to a preset to-be-processed number threshold, if it is greater than or equal to the preset to-be-processed number threshold, executes step S203; if it is less than the preset to-be-processed number threshold, executes step S113; S203 dispatches a new drone to the area.

[0016] As an improvement, any one of the drones is in the same area as multiple other nearby drones.

[0017] As an improvement, step S115 specifically includes the following steps: S114 determines whether the current task is completed. If it is completed, control any one of the drones to return to the starting point; if it is not completed, assign the current task to the nearest other drone.

[0018] As an improvement, the steps are also included: S401 calculates the number of secondary cleaning targets in each area, and determines whether the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to be processed by all drones that can work again in the area. If so, execute step S403; otherwise, execute step S405; S403 deploys idle and reusable drones in adjacent areas; S405 evenly distributes the secondary cleaning targets in the area to all drones in the area that can work again.

[0019] The present invention is beneficial in that: The present invention divides the entire area to be cleaned into several preset areas according to a predetermined division rule, and calculates the cleaning density of the three cleaning modes in each area. After obtaining the density ratio of the three cleaning modes, different forms of drone configuration are performed in three situations.

[0020] When the density of the first cleaning mode is greater than the first preset density threshold value P0, and the sum of the densities of the other two cleaning modes is less than the second preset density threshold value P0', only multiple drones with the first cleaning mode are configured. If the first cleaning mode is the normal cleaning mode or the strong cleaning mode, the corresponding drone is configured for cleaning, and the remaining part is to be cleaned a second time. If the first cleaning mode is a mixed cleaning mode, a drone with a mixed cleaning mode is configured to clean the entire area. A drone with a mixed cleaning mode can clean all types of dirt. Since the total amount of normal + strong dirt in the area is small, it is more economical and efficient to directly configure a drone with a mixed cleaning mode for cleaning.

[0021] When the density of the first cleaning mode is greater than the third preset density threshold value P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold value P0''', configure the drone of the corresponding cleaning mode for cleaning. If the first cleaning mode and the second cleaning mode are both one of the ordinary cleaning mode and the strong cleaning mode, configure the corresponding drone for cleaning. The remaining part can be cleaned separately by a drone with an ordinary cleaning mode and a drone with a strong cleaning mode, without the need to separately configure a drone with a mixed cleaning mode for cleaning. If the first cleaning mode or the second cleaning mode is a mixed cleaning mode, configure the corresponding drone for cleaning, and the remaining part is subject to secondary cleaning.

[0022] When the difference between the densities of the three cleaning modes is less than the preset difference threshold, the drone corresponding to the cleaning mode can be configured to perform cleaning.

[0023] Through the above-mentioned drone configuration method, the cleaning efficiency can be greatly improved and the loss of the drone during the journey can be reduced.

[0024] In addition, the present invention can also adjust the drones according to their power. When the remaining power of a drone reaches a power threshold, the drone is allowed to return, thereby avoiding the problem that the drone cannot return due to low remaining power during work due to the large distance between photovoltaic base stations.

[0025] At the same time, the present invention also searches for a successor for the returning drone to take over its unfinished task and ensure the execution of the cleaning task. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, each element or part is not necessarily drawn according to the actual scale. Obviously, the drawings described below are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without paying creative labor.

[0027] Figure 1 This is a flow chart of Embodiment 1 of the present invention; Figure 2 This is a flow chart of Embodiment 2 of the present invention; Figure 3 This is a flowchart of Embodiment 3 of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0029] Herein, suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of the present invention, and have no specific meanings by themselves. Therefore, "module", "component" or "unit" can be used mixedly.

[0030] In this document, the terms "upper", "lower", "inner", "outer", "front", "back", "one end", "the other end" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0031] In this document, unless otherwise clearly specified and limited, the terms "installed", "provided with", "connected", etc. should be understood in a broad sense. For example, "connected" can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, a direct connection, or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0032] Herein "and / or" includes any and all combinations of one or more of the associated listed items.

[0033] Herein, "plurality" means two or more than two, ie, it includes two, three, four, five, etc.

[0034] Embodiment 1: like Figure 1 As shown, the present invention provides a method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm, which is used to clean the glass panels on the glass curtain wall with relatively concentrated distribution, such as a group of high-rise buildings in the city. The specific steps include: S101 calculates the density Pi of the three cleaning modes in each preset area based on the cleaning mode of each glass plate, and executes step S103, or S105 or S107; the three cleaning modes include: normal cleaning mode, strong cleaning mode and mixed cleaning mode; the density is the number of glass plates corresponding to each cleaning mode in the current area; i=1, 2, 3.

[0035] The dirt on the glass plates on the glass curtain walls of urban high-rise buildings mainly includes dust, scale, oil, bird droppings, etc. Among them, the cleaning of dust and scale is relatively simple, so in the present invention, the cleaning mode of the drone for cleaning dust and scale is summarized as the normal mode. The cleaning of oil and bird droppings is more complicated, so in the present invention, the cleaning mode of the drone for cleaning oil and bird droppings is summarized as the strong mode. The cleaning agents and cleaning tools carried by the drone in the two modes are different, resulting in that both cleaning modes can only target their own types of dirt and cannot cover other dirt. In practice, the dirt on some glass plates is not just one type, so the cleaning mode of the drone in the present invention also includes a mixed cleaning mode, which can perform both ordinary cleaning and strong cleaning. Of course, it is foreseeable that the drone carries more types of cleaning agents and cleaning tools in the mixed cleaning mode, which will greatly reduce the drone's flight time, so it cannot be used as a regular mode.

[0036] In this step, the cleaning mode of each glass plate in the entire area to be cleaned (which may include several high-rise buildings) can be obtained in advance, that is, the corresponding cleaning mode is matched according to the dirt type on each glass plate. The specific method of obtaining the dirt type can be referred to the prior art CN202310330164.X in the background technology, which will not be repeated here.

[0037] Since the area to be cleaned may be relatively large, which is not conducive to the deployment of drones, in this embodiment, the area to be cleaned may be divided into several preset areas before the drones are coordinated for cleaning.

[0038] The rule for dividing the preset areas can be to directly divide the area to be cleaned into equal areas, or to divide it according to the type of dirt. In this embodiment, the second division method is more preferred.

[0039] In this embodiment, the types of dirt include ordinary type (dust + scale), strong type (oil + bird droppings) and mixed type (dust + scale + oil + bird droppings), which correspond to the cleaning modes of the drone: ordinary cleaning mode, strong cleaning mode and mixed cleaning mode.

[0040] Of course, it is understandable that even if the division is based on the type of filth, for the sake of simplicity, the regional division is also a rough division, and try to have only one type of filth in one area, but in reality there will still be multiple types of filth in some areas.

[0041] After the preset areas are divided, the density of various cleaning modes can be calculated according to the density of the glass plates with various types of dirt. In simple terms, if it is analyzed that there are 80% ordinary dirt, 15% strong dirt and 10% mixed dirt in a preset area, the density of the corresponding cleaning mode is P1=80%, P2=15%, P3=5%, and so on.

[0042] S103: If the density of the first cleaning mode in any area is greater than the first preset density threshold value P0, and the sum of the densities of the other two cleaning modes is less than the second preset density threshold value P0', multiple drones with the first cleaning mode are configured for the any area, and step S109 is executed; the first cleaning mode is any one of the normal cleaning mode, the strong cleaning mode and the mixed cleaning mode.

[0043] In the previous step, the density of each cleaning mode in a preset area was calculated. However, it is unreasonable to match drones completely according to density in some cases. For example, when the density of a cleaning mode is as high as 90% or more, and the density of other modes combined does not exceed 5% (the remaining 5% does not need to be cleaned), for a drone with a cleaning mode density of only 5%, the round-trip time and the time to jump within the area may be longer than the cleaning time, which is considered uneconomical.

[0044] Therefore, in this step, when the density of a certain cleaning mode (such as the normal cleaning mode) is greater than the first preset density threshold P0 (such as 90%), and the sum of the densities of the other two cleaning modes is less than the second preset density threshold P0' (5%), then only the drone with the normal cleaning mode is configured to go there.

[0045] The mode with a density greater than the preset density threshold P0 may be one of the normal cleaning mode, the strong cleaning mode and the mixed cleaning mode.

[0046] When the first cleaning mode is the normal cleaning mode or the strong cleaning mode, a drone with the normal cleaning mode or the strong cleaning mode is configured to clean 90% of the corresponding area, and the remaining 5% will be cleaned by a drone in the subsequent secondary cleaning.

[0047] When the first cleaning mode is the mixed cleaning mode, a drone with the mixed cleaning mode is configured to clean the entire area. The drone with the mixed cleaning mode can clean all types of dirt. Since the total amount of ordinary + strong dirt in the area is also less than 5%, it is more economical and efficient to directly configure the drone with the mixed cleaning mode for cleaning.

[0048] S105 If the density of the first cleaning mode in any area is greater than the third preset density threshold P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold P0'', configure multiple drones with the first cleaning mode and multiple second drones with the second cleaning mode for any area; the first cleaning mode is any one of the normal cleaning mode, the strong cleaning mode and the mixed cleaning mode, and the second cleaning mode is any one of the other two cleaning modes other than the first cleaning mode; the third preset density threshold is less than the first preset density threshold, and the fourth preset density threshold is greater than the second preset density threshold, and execute step S109.

[0049] Based on the analysis in the previous step, if the density of a certain cleaning mode in a preset area is too small, it is not economical to deploy a drone alone. However, when the density of a certain type of dirt reaches a certain threshold, it is necessary to deploy a drone of the corresponding type for cleaning.

[0050] For example, if the density of the first cleaning mode in a certain area is greater than the third preset density threshold value P0'' (50%), and the density of the second cleaning mode is greater than the fourth preset density threshold value P0''' (for example, 40%), then a drone with the above two cleaning modes should be configured for targeted cleaning.

[0051] In the case where the first cleaning mode and the second cleaning mode are both one of the normal cleaning mode and the strong cleaning mode, the corresponding drone is configured for cleaning. The remaining 10% (of course, it may be less than 10% because some glass plates do not need to be cleaned) can be cleaned by the drone with the normal cleaning mode and the drone with the strong cleaning mode respectively, without the need to configure a drone with the mixed cleaning mode for cleaning.

[0052] When the first cleaning mode or the second cleaning mode is a mixed cleaning mode, the corresponding drone is configured for cleaning. The remaining 10% (which may be a normal cleaning mode or a strong cleaning mode) can be cleaned by configuring the corresponding drone in the subsequent secondary cleaning.

[0053] S107: If the difference between the densities of the three cleaning modes in any area is less than the preset difference threshold, multiple drones with ordinary cleaning mode, multiple drones with strong cleaning mode and multiple drones with mixed cleaning mode are respectively configured for the said any area, and step S109 is executed.

[0054] It is foreseeable that if the density difference between the three modes is too small, it will be uneconomical to use alternative cleaning methods (i.e., using a drone with a normal cleaning mode and a drone with a strong cleaning mode to clean mixed dirt, or using a drone with a compound cleaning mode to clean normal dirt or strong dirt).

[0055] Therefore, in this step, when the difference between the densities of the three cleaning modes is less than a preset difference threshold (for example, 10%), the corresponding drone is directly configured for cleaning.

[0056] S109 After the cleaning is completed, a regional scan is performed to obtain the target to be cleaned a second time, and a second cleaning is performed.

[0057] In step S103 and step S105, for the sake of economy, some areas may not be cleaned. After the entire area to be cleaned has been cleaned once, the areas that have not been cleaned are re-divided and steps S101 to S109 are repeated until all glass plates are cleaned. Of course, the second cleaning can also be performed in accordance with the method of embodiment 3, see embodiment 3 for details.

[0058] Embodiment 2: Based on the first embodiment, this embodiment allocates the drone according to the power of the drone, and the specific steps include: S111 When the remaining power of any UAV reaches the preset power threshold, obtain the pending task list of any UAV, and determine whether the pending task list is empty. If it is not empty, execute step S113; if it is empty, execute step S115; the preset power threshold can only support the UAV to return from the current position to the starting point.

[0059] Generally speaking, photovoltaic base stations are relatively large, and cleaning work consumes a lot of power from drones, so it is necessary to always pay attention to the power of the drone to avoid being unable to return.

[0060] In this step, the remaining power of the drone is monitored in real time. Once the remaining power reaches the power threshold, the drone should be returned.

[0061] When the drone reaches the preset power level, it may still be performing a mission or have another mission to perform. In the above case, it is necessary to find a successor for the mission.

[0062] S113 obtains the remaining power and pending task lists of multiple other drones near any one of the drones, and executes step S117; wherein, with the current location of any one of the drones as the center of the circle, other drones within a preset radius area are other drones adjacent to any one of the drones.

[0063] When a drone that is still performing a task or has tasks to perform reaches the preset power level, it needs to find a successor. Therefore, it searches for neighboring drones with the current location of the drone as the center and a preset radius, and obtains the remaining power and pending task list of the neighboring drones.

[0064] S115 controls any one of the drones to return from the current position to the starting point.

[0065] Of course, it is foreseeable that in this step, it is necessary to determine whether the current task is completed before returning. If it is completed, the drone is controlled to return to the starting point; if it is not completed, the current task is assigned to the nearest other drone.

[0066] S117 determines whether the other drones nearby can add new cleaning tasks based on the remaining power of the other drones and the number of pending tasks in the pending task list; if they can be added, execute step S119; if they cannot be added, execute step S201.

[0067] When looking for a task successor, it is necessary to determine whether the drone has enough power to support subsequent tasks and new tasks, so as to determine whether the drone is suitable for adding new tasks. It is easy to understand that drones with sufficient power and fewer tasks are preferred.

[0068] S119: selecting at least one other drone from all other drones whose number of cleaning tasks that can be added is greater than a preset threshold, and evenly distributing the to-be-processed tasks in the to-be-processed task list of any of the drones to the selected at least one other drone.

[0069] In addition to determining whether a drone can add a new task, the distance between the two and the waiting time must also be considered. Therefore, in this embodiment, when at least one other drone is screened out, the recommendation index of each other drone is calculated: P = K1*D i，j +K2*T i，j ; Among them, D i，j is the distance between the other UAV and any UAV, T i，j The waiting time for the other UAVs to execute the newly added task; K1 and K2 are empirical constants.

[0070] Among the tasks to be processed, the tasks that are ranked higher in the queue are preferentially assigned to other drones with smaller recommendation indexes.

[0071] S201 determines whether the number of tasks to be processed in the to-be-processed task list of any UAV is greater than or equal to a preset to-be-processed number threshold, if it is greater than or equal to the preset to-be-processed number threshold, executes step S203; if it is less than the preset to-be-processed number threshold, executes step S113; The number of pending tasks in a drone's task list is set to a threshold, indicating that the drone's tasks are saturated and no new tasks can be accepted. When all drones are saturated, new drones need to be added.

[0072] S203 dispatches a new drone to the area.

[0073] Embodiment three: This embodiment is based on the drone deployment method of the first and second embodiments, and selects an appropriate drone for cleaning during secondary cleaning, thereby improving efficiency. The specific steps include: S401 calculates the number of secondary cleaning targets in each area, and determines whether the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to be processed for all drones that can work again in the area. If so, execute step S403; otherwise, execute step S405.

[0074] During the second cleaning, the remaining uncleaned areas after the first cleaning are integrated and re-divided. The division rules are still divided according to the type of dirt.

[0075] After the second area division, there may be drones in the area that are still performing the previous cleaning task. Therefore, it is possible to first determine whether the drones in the area can meet the current cleaning requirements.

[0076] S403 deploys drones that are idle and can work again in adjacent areas.

[0077] If the drones in an area are unable to meet the secondary cleaning needs of the area, drones that can still perform tasks will be deployed from adjacent areas for cleaning. It is foreseeable that if the task lists of drones in adjacent areas are saturated, drones will need to be reconfigured.

[0078] The adjacent area may be an area bordering the target area, or an area whose distance from the target area is less than a distance threshold.

[0079] S405 evenly distributes the secondary cleaning targets in the area to all drones in the area that can work again.

[0080] If the drones in the area are already able to meet the demand, the secondary cleaning tasks can be evenly distributed.

[0081] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0082] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a computer terminal (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0083] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

Claims

1. A method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm, characterized in that: Includes steps: S101: Based on the cleaning modes of each glass plate in each preset area, the density Pi of each of the three cleaning modes in each area is calculated, and step S103, or S105 or S107 is executed; The three cleaning modes include: normal cleaning mode, strong cleaning mode and mixed cleaning mode; the density is the number of glass plates corresponding to each cleaning mode in the current area; i=1, 2, 3; S103: If the density of the first cleaning mode in any area is greater than the first preset density threshold value P0, and the sum of the densities of the other two cleaning modes is less than the second preset density threshold value P0', multiple drones with the first cleaning mode are configured for the any area, and step S109 is executed; the first cleaning mode is any one of the ordinary cleaning mode, the strong cleaning mode and the mixed cleaning mode; S105: If the density of the first cleaning mode in any area is greater than the third preset density threshold value P0'', and the density of the second cleaning mode is greater than the fourth preset density threshold value P0''', multiple drones with the first cleaning mode and multiple second drones with the second cleaning mode are configured for the any area; the first cleaning mode is any one of the ordinary cleaning mode, the strong cleaning mode and the mixed cleaning mode, and the second cleaning mode is any one of the remaining two cleaning modes other than the first cleaning mode; the third preset density threshold is less than the first preset density threshold, and the fourth preset density threshold is greater than the second preset density threshold, and step S109 is executed; S107: If the difference between the densities of the three cleaning modes in any area is less than the preset difference threshold, multiple drones with a normal cleaning mode, multiple drones with a strong cleaning mode, and multiple drones with a mixed cleaning mode are respectively configured for the any area, and step S109 is executed; After the cleaning is completed, S109 performs a regional scan to obtain a second cleaning target and performs a second cleaning.

2. A method for cleaning the glass curtain wall of a high-rise building in a city based on a drone swarm according to claim 1, characterized in that: In step S103, when the first cleaning mode is the normal cleaning mode or the strong cleaning mode, a drone with the corresponding cleaning mode is configured to perform cleaning, and the remaining part is to be cleaned twice; When the first cleaning mode is the mixed cleaning mode, the drone with the mixed cleaning mode is configured to clean the entire area.

3. A method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm according to claim 1, characterized in that: In step S105, when the first cleaning mode and the second cleaning mode are both one of the normal cleaning mode and the strong cleaning mode, a drone having the corresponding cleaning mode is configured to perform cleaning; And the remaining parts are cleaned by drones with normal cleaning mode and drones with strong cleaning mode respectively; When the first cleaning mode or the second cleaning mode is a mixed cleaning mode, a drone with a corresponding cleaning mode is configured to perform cleaning; and the remaining part is to be cleaned a second time.

4. A method for cleaning glass curtain walls of urban high-rise buildings based on drone swarms according to claim 1, characterized in that: The entire area to be cleaned is divided into a number of preset areas according to a division rule; the division rule is to divide according to the type of dirt.

5. A method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm according to claim 4, characterized in that: Before the second cleaning, the remaining parts after the first cleaning are divided according to the division rules.

6. A method for cleaning the glass curtain wall of a high-rise building in a city based on a drone swarm according to claim 1, characterized in that: Also includes the steps: S111: When the remaining power of any UAV reaches a preset power threshold, obtain the pending task list of any UAV, and determine whether the pending task list is empty. If not, execute step S113; if empty, execute step S115; The preset power threshold is only capable of supporting the drone to return from the current position to the starting point; S113 obtains the remaining power and pending task lists of multiple other drones near the any drone, and executes step S117; wherein, with the current location of the any drone as the center, the other drones within the preset radius are other drones adjacent to the any drone; S115 controls any one of the drones to return from the current position to the starting point; S117 determines whether the other drones nearby can add new cleaning tasks according to the remaining power of the other drones and the number of pending tasks in the pending task list; if they can be added, execute step S119; if they cannot be added, execute step S201; S119: selecting at least one other drone from all other drones whose number of cleaning tasks that can be added is greater than a preset threshold, and evenly distributing the to-be-processed tasks in the to-be-processed task list of any of the drones to the selected at least one other drone.

7. A method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm according to claim 6, characterized in that: When at least one other drone is screened out, the recommendation index of each other drone is calculated: P=K1*D i，j +K2*T i，j Among them, D i，j is the distance between the other UAV and any UAV, T i，j The waiting time for the other drones to perform the newly added tasks; K1 and K2 are empirical constants; Among the tasks to be processed, the tasks that are ranked higher in the queue are preferentially assigned to other drones with smaller recommendation indexes.

8. A method for cleaning the glass curtain wall of a high-rise building in a city based on a drone swarm according to claim 6, characterized in that: Before executing step S113, the method further includes the following steps: S201 determines whether the number of tasks to be processed in the to-be-processed task list of any UAV is greater than or equal to a preset to-be-processed number threshold, if it is greater than or equal to the preset to-be-processed number threshold, executes step S203; if it is less than the preset to-be-processed number threshold, executes step S113; S203 dispatches a new drone to the area.

9. A method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm according to claim 6, characterized in that: Step S115 specifically includes the following steps: S114 determines whether the current task is completed. If it is completed, control any one of the drones to return to the starting point; if it is not completed, assign the current task to the nearest other drone.

10. The method for cleaning the glass curtain wall of a city high-rise building based on a drone swarm according to claim 1, characterized in that: Also includes the steps: S401 calculates the number of secondary cleaning targets in each area, and determines whether the number of secondary cleaning targets is greater than or equal to the amount of tasks that can be added to be processed by all drones that can work again in the area. If so, execute step S403; otherwise, execute step S405; S403 deploys idle and reusable drones in adjacent areas; S405 evenly distributes the secondary cleaning targets in the area to all drones in the area that can work again.

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