Unmanned aerial vehicle inspection route planning method and planning system

Abstract

The invention discloses an unmanned aerial vehicle inspection route planning method and system, and relates to the technical field of unmanned aerial vehicle inspection, and the method comprises the steps: S1, carrying out the analysis and processing of a to-be-cruised region distribution diagram of an unmanned aerial vehicle based on a route planning terminal, and obtaining the related information of a to-be-cruised point of the unmanned aerial vehicle; and S2, based on the route planning terminal, analyzing and processing the distance information between the to-be-cruised points, and determining the to-be-cruised path of the unmanned aerial vehicle. The method comprises the following steps: firstly, analyzing a to-be-cruised area distribution map of the unmanned aerial vehicle to determine related information of a to-be-cruised point of the unmanned aerial vehicle, then, performing path analysis on the related information of the to-be-cruised point of the unmanned aerial vehicle to determine a to-be-cruised path of the unmanned aerial vehicle, and finally, determining a to energy consumption calculation is carried out on the energy consumption parameter of the unmanned aerial vehicle, the cruising area information of the to-be-cruised point and the first navigation distance of the unmanned aerial vehicle, whether the unmanned aerial vehicle needs to be supplemented with energy or not is determined, the situation that energy is insufficient in the inspection process of the unmanned aerial vehicle is avoided, and the unmanned aerial vehicle can complete the inspection task within the set time.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle inspection, and in particular to a method and system for planning an unmanned aerial vehicle inspection route. Background Art

[0002] Unmanned aerial vehicles (UAVs), also known as drones, are unmanned aircraft controlled by radio remote control and self-contained programmable controls. Drones are a general term for unmanned aerial vehicles (UAVs), which can be technically categorized into: unmanned helicopters, unmanned fixed-wing aircraft, unmanned multi-rotor aircraft, unmanned airships, and unmanned paragliders.

[0003] When existing drones perform inspection tasks, they do not analyze the real-time energy of the drones, which may cause the drones to run out of energy during the inspection process, thereby extending the inspection time of the drones. Summary of the Invention

[0004] The present invention provides a method and system for planning a drone inspection route, which solves the problem raised in the above background technology that the existing drones do not analyze the real-time energy of the drones when performing inspection tasks, resulting in the drones being short of energy during the inspection process, thereby extending the inspection time of the drones.

[0005] In order to achieve the above objects, the technical solution adopted by the present invention is:

[0006] A method for planning a UAV inspection route, comprising:

[0007] S1. Obtain a distribution map of the area to be cruised by the drone, and analyze and process the distribution map of the area to be cruised by the drone based on the route planning terminal to obtain relevant information of the drone's cruise points, wherein the relevant information of the drone's cruise points includes location information of the cruise points, cruise area information of the cruise points, and distance information between the cruise points;

[0008] S2. Based on the route planning terminal, the distance information between the cruise points is analyzed and processed to determine the cruise path of the UAV;

[0009] S3. Obtain the energy consumption parameters of the drone, and based on the route planning terminal, analyze and process the energy consumption parameters of the drone, the drone's to-be-cruised path, and the cruising area information of the to-be-cruised point to determine the drone inspection plan, wherein the drone's energy consumption parameters include the drone's navigation energy consumption and the drone's inspection energy consumption.

[0010] Preferably, the step S1, obtaining a distribution map of the area to be cruised by the drone, analyzing and processing the distribution map of the area to be cruised by the drone based on the route planning terminal, and obtaining relevant information of the points to be cruised by the drone specifically includes the following steps:

[0011] S11. Based on the route planning terminal, retrieve and process information from the database to obtain a distribution map of the area to be cruised by the UAV;

[0012] S12. Analyze and process the distribution map of the area to be cruised by the UAV based on the route planning terminal to determine the location information of the cruise point to be cruised;

[0013] S13. Based on the route planning terminal, the position information of the cruise points and the distribution map of the area to be cruised by the UAV are analyzed and processed to determine the distance information between the cruise points;

[0014] S14. Based on the route planning terminal, the distribution map of the area to be cruised by the UAV is analyzed and processed to determine the cruise area information of the cruise point to be cruised.

[0015] Preferably, the step S12, analyzing and processing the distribution map of the area to be cruised by the drone based on the route planning terminal to determine the location information of the point to be cruised, specifically comprises the following steps:

[0016] S121. Based on the route planning terminal, data is read and processed on the distribution map of the drone's waiting cruise area to obtain the drone's waiting cruise area;

[0017] S122. Based on the route planning terminal, perform equivalent substitution processing on the waiting cruise area of the UAV to obtain the waiting cruise point of the UAV;

[0018] S123. The route planning terminal performs position analysis on the distribution map of the drone's waiting cruise area based on the waiting cruise point of the drone as a feature to determine the position information of the waiting cruise point.

[0019] Preferably, the step S13, analyzing and processing the position information of the to-be-cruised points and the distribution map of the to-be-cruised areas of the drone based on the route planning terminal, and determining the distance information between the to-be-cruised points specifically includes the following steps:

[0020] S131. The route planning terminal connects the waiting-for-cruise points of every two drones in the distribution map of the waiting-for-cruise area with a straight line to obtain a zoomed-in waiting-for-cruise path;

[0021] S132. Based on the route planning terminal, perform parameter extraction processing on the distribution map of the area to be cruised by the UAV to obtain a scaling ratio of the distribution map;

[0022] S133: Based on the route planning terminal, the distribution map scaling ratio and the to-be-cruised scaling path are calculated and processed to determine the distance information between the to-be-cruised points;

[0023] The specific calculation formula for determining the distance information between the waiting cruise points is:

[0024]

[0025] Where D j D is the distance information between the waiting cruise points; i is the zoom path to be cruised; α is the distribution map zoom ratio; n is the specific number of zoom paths to be cruised and the specific number of distance information between the points to be cruised.

[0026] Preferably, the step S14, analyzing and processing the distribution map of the area to be cruised by the drone based on the route planning terminal to determine the cruise area information of the point to be cruised, specifically comprises the following steps:

[0027] S141. Analyze and process the area to be cruised by the UAV based on the route planning terminal to determine the shape of the area to be cruised by the UAV;

[0028] S142, the route planning terminal constructs a function based on the shape of the area to be cruised by the UAV and determines a similarity function;

[0029] S143. Based on the route planning terminal, the similarity function and the distribution map scaling ratio are calculated and processed to determine the cruising area information of the waiting cruising point;

[0030] The specific calculation formula for determining the cruising area information of the waiting cruising point is:

[0031]

[0032] Where A k is the cruising area information of the point to be cruised; f k (x, y) is the similarity function; Ω is the shape of the area where the UAV is waiting to cruise; α is the scaling ratio of the distribution map; and k is the specific number of the area where the UAV is waiting to cruise.

[0033] Preferably, the step S2, analyzing and processing the distance information between the cruise points based on the route planning terminal to determine the cruise path of the drone, specifically comprises the following steps:

[0034] S21. Based on the route planning terminal, filter the distance information between the cruise points to be cruised and determine a shortest distance set, where the shortest distance set is specifically the shortest distance between every two cruise points;

[0035] S22. The route planning terminal performs route planning on the distribution map of the UAV's waiting cruise area based on the shortest distance between every two waiting cruise points, and determines the UAV's waiting cruise path.

[0036] Preferably, the step S21, screening the distance information between the cruise points based on the route planning terminal to determine the shortest distance set, specifically comprises the following steps:

[0037] S211. Based on the route planning terminal, randomly select the waiting cruise point of the UAV to determine the first waiting cruise point;

[0038] S212: The route planning terminal filters the distance information between the waiting cruise points based on the first waiting cruise point as a feature, and obtains the distance information corresponding to the first waiting cruise point;

[0039] S213: Based on the route planning terminal, sort the distance information corresponding to the first waiting cruise points to obtain the shortest distance to the first waiting cruise points, where the shortest distance to the first waiting cruise points is specifically the shortest distance between every two waiting cruise points;

[0040] S214: Analyze and process the shortest distance to the first waiting cruise point based on the route planning terminal to determine a second waiting cruise point, where the second waiting cruise point is specifically an end point of the shortest distance to the first waiting cruise point;

[0041] S215. Based on the route planning terminal, repeat steps S222-S224 to determine the shortest distance between each two waiting cruise points in a plurality of groups;

[0042] S216: Based on the route planning terminal, a shortest distance set is determined by combining the shortest distances between each two cruise points in a plurality of groups.

[0043] Preferably, the S3, obtaining the energy consumption parameters of the drone, analyzing and processing the energy consumption parameters of the drone, the drone's to-be-cruised path, and the cruising area information of the to-be-cruised point based on the route planning terminal, and determining the drone inspection plan specifically includes the following steps:

[0044] S31. Based on the route planning terminal, retrieve and process information from the database to obtain the navigation energy consumption and inspection energy consumption of the UAV;

[0045] S32. Analyze and process the drone's pending cruise path based on the route planning terminal to determine the drone inspection starting point, where the drone inspection starting point is any one of the two end points of the drone's pending cruise path;

[0046] S33. The route planning terminal filters and processes the cruising area information of the cruising point based on the drone inspection starting point, and determines the cruising area corresponding to the drone inspection starting point;

[0047] S34. Based on the route planning terminal, the cruising area corresponding to the inspection starting point of the drone and the inspection energy consumption of the drone are calculated and processed to determine the remaining energy of the drone;

[0048] S35. Based on the route planning terminal, the remaining energy of the UAV and the navigation energy consumption of the UAV are compared and judged to determine the UAV inspection plan;

[0049] The specific calculation formula for determining the remaining energy of the drone is:

[0050]

[0051] Where E1 is the remaining energy of the UAV; E2 is the energy of the UAV before inspection; A1 is the cruising area corresponding to the starting point of the UAV inspection; and B is the energy consumption of the UAV inspection.

[0052] Preferably, the step S35, comparing and judging the remaining energy of the drone and the navigation energy consumption of the drone based on the route planning terminal, and determining the drone inspection plan specifically includes the following steps:

[0053] S351. The route planning terminal locates the drone's patrol path based on the drone's patrol starting point and determines the drone's second patrol point.

[0054] S352, the route planning terminal reads and processes the data of the shortest distance set based on the UAV inspection starting point and the UAV second inspection point as features to determine the UAV's first navigation distance;

[0055] S353. Calculate and process the first flight distance of the UAV and the flight energy consumption of the UAV based on the route planning terminal to obtain energy information required for the first flight distance of the UAV;

[0056] S354: Based on the route planning terminal, determine and process the remaining energy of the UAV and the energy required for the first navigation distance of the UAV;

[0057] S355: If the remaining energy of the drone is greater than the energy required for the first navigation distance of the drone, the drone does not need to recharge energy at the starting point of the drone inspection;

[0058] S356. If the remaining energy of the drone is less than or equal to the energy information required for the first navigation distance of the drone, the drone cannot complete the second inspection mission, and the drone needs to replenish energy at the starting point of the drone inspection.

[0059] Furthermore, a drone inspection route planning system is proposed, which is used to implement the above-mentioned drone inspection route planning method, including:

[0060] A route planning terminal is used to control each module to analyze the distribution map of the drone's cruise area and the drone's energy consumption parameters, determine the drone's inspection plan, and control information exchange and data transmission between each module;

[0061] A drone, wherein the drone performs inspections according to an inspection area in a distribution map of areas to be patrolled by drones;

[0062] A database for storing a distribution map of the area to be cruised by the drone and energy consumption parameters of the drone;

[0063] A distribution map analysis module is used to analyze the distribution map of the area to be cruised by the UAV, and determine the location information of the cruise points to be cruised, the cruise area information of the cruise points to be cruised, and the distance information between the cruise points to be cruised;

[0064] A path determination module, which is used to analyze and process distance information between the cruise points to be cruised and determine the cruise path of the UAV;

[0065] The inspection starting point selection module is used to randomly select the endpoints of the drone's patrol path to determine the drone's inspection starting point;

[0066] An energy calculation module, which calculates and processes the remaining energy of the drone based on the cruising area corresponding to the drone's inspection starting point and the drone's inspection energy consumption, and obtains energy information required for the drone's first navigation distance based on the drone's first navigation distance and the drone's navigation energy consumption;

[0067] The comparison and judgment module determines the inspection plan of the drone based on the remaining energy of the drone and the energy required for the first navigation distance of the drone.

[0068] Compared with the existing technology, the present invention provides a UAV inspection route planning method and planning system, which has the following beneficial effects:

[0069] The present invention first analyzes the distribution map of the drone's waiting cruise area to determine the relevant information of the drone's waiting cruise point, then performs path analysis on the relevant information of the drone's waiting cruise point to determine the drone's waiting cruise path, and finally calculates the energy consumption parameters of the drone, the cruising area information of the waiting cruise point and the drone's first navigation distance to determine whether the drone needs to replenish energy, thereby avoiding the situation where the drone is short of energy during the inspection process and enabling the drone to complete the inspection task within the specified time. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 This is a flow chart of steps S1-S3 in a method for planning a UAV inspection route proposed by the present invention;

[0071] Figure 2 This is a flow chart of steps S11-S14 in a method for planning a UAV inspection route proposed by the present invention;

[0072] Figure 3This is a flow chart of steps S121-S123 in a method for planning a UAV inspection route proposed by the present invention;

[0073] Figure 4 This is a flow chart of steps S131-S133 in a method for planning a UAV inspection route proposed by the present invention;

[0074] Figure 5 This is a flow chart of steps S141-S143 of a UAV inspection route planning method proposed in the present invention;

[0075] Figure 6 This is a flow chart of steps S21-S22 in a method for planning a UAV inspection route proposed by the present invention;

[0076] Figure 7 This is a flow chart of steps S211-S216 in a UAV inspection route planning method proposed by the present invention;

[0077] Figure 8 This is a flow chart of steps S31-S35 in a method for planning a UAV inspection route proposed by the present invention;

[0078] Figure 9 This is a flow chart of steps S351-S356 in a method for planning a UAV inspection route proposed by the present invention;

[0079] Figure 10 This is a structural block diagram of the UAV inspection route planning system proposed by the present invention. DETAILED DESCRIPTION

[0080] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are described below in conjunction with the accompanying drawings. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0081] The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The following description is intended to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are for illustrative purposes only, and those skilled in the art will readily appreciate other obvious variations.

[0082] Reference Figure 1 As shown, a method for planning a UAV inspection route includes:

[0083] S1. Obtain a distribution map of the area to be cruised by the drone, and analyze and process the distribution map of the area to be cruised by the drone based on the route planning terminal to obtain relevant information of the drone's cruise points, wherein the relevant information of the drone's cruise points includes location information of the cruise points, cruise area information of the cruise points, and distance information between the cruise points;

[0084] It is understandable that the drone's waiting area for patrol is not just one area, but is composed of multiple areas, which may be adjacent or non-adjacent. The waiting area distribution map records the locations of all waiting areas for patrol;

[0085] When planning the drone's cruise route later, since the waiting cruise area is an area in the drone's waiting cruise area distribution map, in order to display the inspection route more intuitively, the waiting cruise area is equivalent to the drone's waiting cruise point. For example, when traveling, the route map does not display each area, and each area is equivalently replaced by a point. This solution uses the above idea to enable the drone's inspection route to be displayed intuitively.

[0086] S2. Based on the route planning terminal, the distance information between the cruise points is analyzed and processed to determine the cruise path of the UAV;

[0087] S3. Obtain energy consumption parameters of the drone, and analyze and process the drone's energy consumption parameters, the drone's pending cruise path, and the cruise area information of the pending cruise point based on the route planning terminal to determine a drone inspection plan, wherein the drone's energy consumption parameters include the drone's navigation energy consumption and the drone's inspection energy consumption;

[0088] It can be understood that the route planning terminal is used to control various modules to plan and design the inspection route of the drone and determine the drone inspection plan;

[0089] Those skilled in the art will understand that when a drone performs an inspection task, it needs to capture images or data of the inspection location, and both image capture and data capture consume the drone's energy. Therefore, when a drone performs an inspection task, it is necessary to monitor the drone's energy to avoid energy shortages during the inspection task, which may cause the drone to crash due to energy shortages, thereby extending the inspection cycle. Therefore, by analyzing the distribution map of the drone's patrol area and the drone's energy consumption parameters, the drone can be prevented from crashing due to energy shortages, thereby reducing the inspection cost. For example, in a wind farm, wind power generation equipment is set up in multiple areas, and in order to monitor the status of wind power generation equipment in real time, it is necessary to inspect it through a drone. However, the drone's energy is limited. In order to avoid energy shortages when the drone inspects wind farms, etc., the location of the wind power generation equipment is analyzed to determine the best inspection route, thereby avoiding energy shortages for the drone.

[0090] Reference Figure 2 As shown, S1, obtaining a distribution map of the drone's waiting cruise area, analyzing and processing the distribution map of the drone's waiting cruise area based on the route planning terminal, and obtaining relevant information of the drone's waiting cruise point specifically includes the following steps:

[0091] S11. Based on the route planning terminal, retrieve and process information from the database to obtain a distribution map of the area to be cruised by the UAV;

[0092] S12. Analyze and process the distribution map of the area to be cruised by the UAV based on the route planning terminal to determine the location information of the cruise point to be cruised;

[0093] S13. Based on the route planning terminal, the position information of the cruise points and the distribution map of the area to be cruised by the UAV are analyzed and processed to determine the distance information between the cruise points;

[0094] S14. Based on the route planning terminal, the distribution map of the area to be cruised by the UAV is analyzed and processed to determine the cruise area information of the cruise point to be cruised;

[0095] In this embodiment, when a drone performs an inspection mission, it may need to inspect multiple areas, but these areas may be in different locations. Therefore, the areas of these areas and the routes between these areas are calculated to provide data reference for subsequent analysis of the drone's energy, making the drone's energy analysis more accurate and reducing the risk of the drone crashing due to insufficient energy.

[0096] Reference Figure 3 As shown, S12, based on the route planning terminal, analyzes and processes the distribution map of the area to be cruised by the UAV, and determines the location information of the cruise point to be cruised, which specifically includes the following steps:

[0097] S121. Based on the route planning terminal, data is read and processed on the distribution map of the drone's waiting cruise area to obtain the drone's waiting cruise area;

[0098] S122. Based on the route planning terminal, perform equivalent substitution processing on the waiting cruise area of the UAV to obtain the waiting cruise point of the UAV;

[0099] S123. The route planning terminal performs position analysis on the distribution map of the drone's waiting cruise area based on the drone's waiting cruise point as a feature to determine the location information of the waiting cruise point.

[0100] In this embodiment, in order to make the analysis of the drone's waiting cruise area more convenient and quick, it is approximately regarded as a point, so that the subsequent drone's waiting cruise path is simpler. At the same time, processing a point is more convenient than processing an area.

[0101] Reference Figure 4 As shown, S13, based on the route planning terminal, analyzes and processes the location information of the to-be-cruised points and the distribution map of the to-be-cruised areas of the drone, and determines the distance information between the to-be-cruised points, specifically including the following steps:

[0102] S131. The route planning terminal connects the waiting-for-cruise points of every two drones in the distribution map of the waiting-for-cruise area with a straight line to obtain a zoomed-in waiting-for-cruise path;

[0103] S132. Based on the route planning terminal, perform parameter extraction processing on the distribution map of the area to be cruised by the UAV to obtain a scaling ratio of the distribution map;

[0104] S133: Based on the route planning terminal, the distribution map scaling ratio and the to-be-cruised scaling path are calculated and processed to determine the distance information between the to-be-cruised points;

[0105] The specific calculation formula for determining the distance information between the waiting cruise points is:

[0106]

[0107] Where D j D is the distance information between the waiting cruise points; i is the zoom path to be cruised; α is the distribution map zoom ratio; n is the specific number of zoom paths to be cruised and the specific number of distance information between the points to be cruised;

[0108] In this embodiment, when the drone performs an inspection task, it needs to inspect multiple areas, and different areas are distributed in different locations. Therefore, it is necessary to calculate the distance between different areas so that the drone can have a shortest inspection path when performing the inspection task, which can reduce the energy loss of the drone and indirectly reduce the inspection cost. It can be understood that the straight-line distance between two points is the shortest, so a straight line is connected between each two patrol points. Finally, the actual distance between the two areas to be inspected is determined by the distribution map scaling ratio.

[0109] Reference Figure 5 As shown, S14, based on the route planning terminal, analyzes and processes the distribution map of the area to be cruised by the UAV to determine the cruise area information of the cruise point to be cruised, which specifically includes the following steps:

[0110] S141. Analyze and process the area to be cruised by the UAV based on the route planning terminal to determine the shape of the area to be cruised by the UAV;

[0111] S142, the route planning terminal constructs a function based on the shape of the area to be cruised by the UAV and determines a similarity function;

[0112] S143. Based on the route planning terminal, the similarity function and the distribution map scaling ratio are calculated and processed to determine the cruising area information of the waiting cruising point;

[0113] The specific calculation formula for determining the cruising area information of the waiting cruising point is:

[0114]

[0115] Where A k is the cruising area information of the point to be cruised; f k (x, y) is a similarity function; Ω is the shape of the area where the UAV is waiting to cruise; α is the scaling ratio of the distribution map; k is the specific number of the area where the UAV is waiting to cruise;

[0116] In this embodiment, when the drone performs an inspection task, it needs to collect images or data of the inspection area. Therefore, by calculating the area of the inspection area, the energy consumed by the drone in inspecting a certain area can be determined, and accurate monitoring of the drone's energy can be achieved, thereby avoiding the drone crashing due to insufficient energy, reducing the inspection cost, and shortening the inspection time.

[0117] Reference Figure 6 As shown, S2, based on the route planning terminal, analyzes and processes the distance information between the cruise points to determine the drone's cruise path, which specifically includes the following steps:

[0118] S21. Based on the route planning terminal, filter the distance information between the cruise points to be cruised and determine a shortest distance set, where the shortest distance set is specifically the shortest distance between every two cruise points;

[0119] S22. The route planning terminal performs route planning on the distribution map of the UAV's waiting cruise area based on the shortest distance between every two waiting cruise points, and determines the UAV's waiting cruise path.

[0120] Reference Figure 7 As shown, S21, based on the route planning terminal, screening the distance information between the cruise points to determine the shortest distance set specifically includes the following steps:

[0121] S211. Based on the route planning terminal, randomly select the waiting cruise point of the UAV to determine the first waiting cruise point;

[0122] S212: The route planning terminal filters the distance information between the waiting cruise points based on the first waiting cruise point as a feature, and obtains the distance information corresponding to the first waiting cruise point;

[0123] S213: Based on the route planning terminal, sort the distance information corresponding to the first waiting cruise points to obtain the shortest distance to the first waiting cruise points, where the shortest distance to the first waiting cruise points is specifically the shortest distance between every two waiting cruise points;

[0124] S214: Analyze and process the shortest distance to the first waiting cruise point based on the route planning terminal to determine a second waiting cruise point, where the second waiting cruise point is specifically an end point of the shortest distance to the first waiting cruise point;

[0125] S215. Based on the route planning terminal, repeat steps S222-S224 to determine the shortest distance between each two waiting cruise points in a plurality of groups;

[0126] S216. Based on the route planning terminal, aggregating the shortest distances between each pair of the cruise points in a plurality of groups to determine a shortest distance set;

[0127] In this embodiment, the distance between two points is the shortest. Therefore, in the previous step, the drone's waiting cruise area is equivalent to the drone's waiting cruise point. By analyzing the distance between each two drone's waiting cruise points, the shortest distance between each two waiting cruise points is obtained by screening, and the rest of the distance data is all eliminated. Only the shortest distance is retained, that is, the shortest inspection path when the drone performs the inspection task, which can effectively reduce the drone's energy loss and reduce the inspection cost.

[0128] Reference Figure 8As shown, S3, obtaining the energy consumption parameters of the UAV, analyzing and processing the energy consumption parameters of the UAV, the UAV's waiting cruise path and the cruising area information of the waiting cruise point based on the route planning terminal, and determining the UAV inspection plan specifically includes the following steps:

[0129] S31. Based on the route planning terminal, retrieve and process information from the database to obtain the navigation energy consumption and inspection energy consumption of the UAV;

[0130] S32. Analyze and process the drone's pending cruise path based on the route planning terminal to determine the drone inspection starting point, where the drone inspection starting point is any one of the two end points of the drone's pending cruise path;

[0131] S33. The route planning terminal filters and processes the cruising area information of the cruising point based on the drone inspection starting point, and determines the cruising area corresponding to the drone inspection starting point;

[0132] S34. Based on the route planning terminal, the cruising area corresponding to the inspection starting point of the drone and the inspection energy consumption of the drone are calculated and processed to determine the remaining energy of the drone;

[0133] S35. Based on the route planning terminal, the remaining energy of the UAV and the navigation energy consumption of the UAV are compared and judged to determine the UAV inspection plan;

[0134] The specific calculation formula for determining the remaining energy of the drone is:

[0135]

[0136] Where E1 is the remaining energy of the UAV; E2 is the energy of the UAV before inspection; A1 is the cruising area corresponding to the starting point of the UAV inspection; and B is the energy consumption of the UAV inspection.

[0137] Reference Figure 9 As shown, S35, based on the route planning terminal, the remaining energy of the drone and the navigation energy consumption of the drone are compared and judged, and the drone inspection plan is determined, which specifically includes the following steps:

[0138] S351. The route planning terminal locates the drone's patrol path based on the drone's patrol starting point and determines the drone's second patrol point.

[0139] S352, the route planning terminal reads and processes the data of the shortest distance set based on the UAV inspection starting point and the UAV second inspection point as features to determine the UAV's first navigation distance;

[0140] S353. Calculate and process the first flight distance of the UAV and the flight energy consumption of the UAV based on the route planning terminal to obtain energy information required for the first flight distance of the UAV;

[0141] S354: Based on the route planning terminal, determine and process the remaining energy of the UAV and the energy required for the first navigation distance of the UAV;

[0142] S355: If the remaining energy of the drone is greater than the energy required for the first navigation distance of the drone, the drone does not need to recharge energy at the starting point of the drone inspection;

[0143] S356: If the remaining energy of the drone is less than or equal to the energy required for the first navigation distance of the drone, the drone cannot complete the second inspection mission and the drone needs to recharge energy at the starting point of the drone inspection.

[0144] In this embodiment, after the drone completes the inspection of a certain inspection area, it needs to go to the next inspection area to collect data, but the drone's energy may not be able to reach the next area. Therefore, the energy required for the drone to reach the next area is compared with the drone's remaining energy to determine whether the drone's energy can reach the next inspection area. If it cannot reach it, the drone is replenished with energy, avoiding the phenomenon of the drone crashing due to insufficient energy and reducing the inspection cost. If the drone can reach the next inspection area, there is no need to replenish the drone's energy.

[0145] Reference Figure 10 As shown, a drone inspection route planning system is used to implement the drone inspection route planning method as described above, including:

[0146] A route planning terminal is used to control each module to analyze the distribution map of the drone's cruise area and the drone's energy consumption parameters, determine the drone's inspection plan, and control information exchange and data transmission between each module;

[0147] A drone, wherein the drone performs inspections according to an inspection area in a distribution map of areas to be patrolled by drones;

[0148] A database for storing a distribution map of the area to be cruised by the drone and energy consumption parameters of the drone;

[0149] A distribution map analysis module is used to analyze the distribution map of the area to be cruised by the UAV, and determine the location information of the cruise points to be cruised, the cruise area information of the cruise points to be cruised, and the distance information between the cruise points to be cruised;

[0150] A path determination module, which is used to analyze and process distance information between the cruise points to be cruised and determine the cruise path of the UAV;

[0151] The inspection starting point selection module is used to randomly select the endpoints of the drone's patrol path to determine the drone's inspection starting point;

[0152] An energy calculation module, which calculates and processes the remaining energy of the drone based on the cruising area corresponding to the drone's inspection starting point and the drone's inspection energy consumption, and obtains energy information required for the drone's first navigation distance based on the drone's first navigation distance and the drone's navigation energy consumption;

[0153] The comparison and judgment module determines the inspection plan of the drone based on the remaining energy of the drone and the energy required for the first navigation distance of the drone.

[0154] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structures or equivalent process changes made using the contents of the present invention's description and drawings, or directly or indirectly applied to other related technical fields, are also included in the patent protection scope of the present invention.

[0155] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for planning a drone inspection route, characterized in that: include: S1. Obtain a distribution map of the area to be cruised by the drone, and analyze and process the distribution map of the area to be cruised by the drone based on the route planning terminal to obtain relevant information of the drone's cruise points, wherein the relevant information of the drone's cruise points includes location information of the cruise points, cruise area information of the cruise points, and distance information between the cruise points; S2. Based on the route planning terminal, the distance information between the cruise points is analyzed and processed to determine the cruise path of the UAV; S3. Obtain the energy consumption parameters of the drone, and based on the route planning terminal, analyze and process the energy consumption parameters of the drone, the drone's to-be-cruised path, and the cruising area information of the to-be-cruised point to determine the drone inspection plan, wherein the drone's energy consumption parameters include the drone's navigation energy consumption and the drone's inspection energy consumption.

2. The method for planning a drone inspection route according to claim 1, characterized in that: The step S1, obtaining a distribution map of the area to be cruised by the drone, analyzing and processing the distribution map of the area to be cruised by the drone based on the route planning terminal, and obtaining relevant information of the points to be cruised by the drone specifically includes the following steps: S11. Based on the route planning terminal, retrieve and process information from the database to obtain a distribution map of the area to be cruised by the UAV; S12. Analyze and process the distribution map of the area to be cruised by the UAV based on the route planning terminal to determine the location information of the cruise point to be cruised; S13. Based on the route planning terminal, the position information of the cruise points and the distribution map of the area to be cruised by the UAV are analyzed and processed to determine the distance information between the cruise points; S14. Based on the route planning terminal, the distribution map of the area to be cruised by the UAV is analyzed and processed to determine the cruise area information of the cruise point to be cruised.

3. The method for planning a UAV inspection route according to claim 2, characterized in that: The step S12, analyzing and processing the distribution map of the area to be cruised by the UAV based on the route planning terminal to determine the location information of the point to be cruised, specifically includes the following steps: S121. Based on the route planning terminal, data is read and processed on the distribution map of the drone's waiting cruise area to obtain the drone's waiting cruise area; S122. Based on the route planning terminal, perform equivalent substitution processing on the waiting cruise area of the UAV to obtain the waiting cruise point of the UAV; S123. The route planning terminal performs position analysis on the distribution map of the drone's waiting cruise area based on the waiting cruise point of the drone as a feature to determine the position information of the waiting cruise point.

4. The method for planning a UAV inspection route according to claim 3, characterized in that: The step S13, analyzing and processing the position information of the to-be-cruised points and the distribution map of the to-be-cruised areas of the drone based on the route planning terminal, and determining the distance information between the to-be-cruised points, specifically includes the following steps: S131. The route planning terminal connects the waiting-for-cruise points of every two drones in the distribution map of the waiting-for-cruise area with a straight line to obtain a zoomed-in waiting-for-cruise path; S132. Based on the route planning terminal, perform parameter extraction processing on the distribution map of the area to be cruised by the UAV to obtain a scaling ratio of the distribution map; S133: Based on the route planning terminal, the distribution map scaling ratio and the to-be-cruised scaling path are calculated and processed to determine the distance information between the to-be-cruised points; The specific calculation formula for determining the distance information between the waiting cruise points is: Where D j D is the distance information between the waiting cruise points; i is the zoom path to be cruised; α is the distribution map zoom ratio; n is the specific number of zoom paths to be cruised and the specific number of distance information between the points to be cruised.

5. The method for planning a drone inspection route according to claim 2, wherein: The step S14, analyzing and processing the distribution map of the area to be cruised by the UAV based on the route planning terminal to determine the cruise area information of the cruise point specifically includes the following steps: S141. Analyze and process the area to be cruised by the UAV based on the route planning terminal to determine the shape of the area to be cruised by the UAV; S142, the route planning terminal constructs a function based on the shape of the area to be cruised by the UAV and determines a similarity function; S143. Based on the route planning terminal, the similarity function and the distribution map scaling ratio are calculated and processed to determine the cruising area information of the waiting cruising point; The specific calculation formula for determining the cruising area information of the waiting cruising point is: Where A k is the cruising area information of the point to be cruised; f k (x, y) is the similarity function; Ω is the shape of the area where the UAV is waiting to cruise; α is the scaling ratio of the distribution map; and k is the specific number of the area where the UAV is waiting to cruise.

6. The method for planning a UAV inspection route according to claim 1, characterized in that: S2, based on the route planning terminal, analyzes and processes the distance information between the cruise points to determine the cruise path of the drone, specifically including the following steps: S21. Based on the route planning terminal, filter the distance information between the cruise points to be cruised and determine a shortest distance set, where the shortest distance set is specifically the shortest distance between every two cruise points; S22. The route planning terminal performs route planning on the distribution map of the UAV's waiting cruise area based on the shortest distance between every two waiting cruise points, and determines the UAV's waiting cruise path.

7. The method for planning a UAV inspection route according to claim 6, characterized in that: S21, based on the route planning terminal, screening the distance information between the cruise points to determine the shortest distance set, specifically includes the following steps: S211. Based on the route planning terminal, randomly select the waiting cruise point of the UAV to determine the first waiting cruise point; S212: The route planning terminal filters the distance information between the waiting cruise points based on the first waiting cruise point as a feature, and obtains the distance information corresponding to the first waiting cruise point; S213: Based on the route planning terminal, sort the distance information corresponding to the first waiting cruise points to obtain the shortest distance to the first waiting cruise points, where the shortest distance to the first waiting cruise points is specifically the shortest distance between every two waiting cruise points; S214: Analyze and process the shortest distance to the first waiting cruise point based on the route planning terminal to determine a second waiting cruise point, where the second waiting cruise point is specifically an end point of the shortest distance to the first waiting cruise point; S215. Based on the route planning terminal, repeat steps S222-S224 to determine the shortest distance between each two waiting cruise points in a plurality of groups; S216: Based on the route planning terminal, a shortest distance set is determined by combining the shortest distances between each two cruise points in a plurality of groups.

8. The method for planning a UAV inspection route according to claim 1, characterized in that: The above S3, obtaining the energy consumption parameters of the UAV, analyzing and processing the energy consumption parameters of the UAV, the UAV's to-be-cruised path, and the cruising area information of the to-be-cruised point based on the route planning terminal, and determining the UAV inspection plan specifically includes the following steps: S31. Based on the route planning terminal, retrieve and process information from the database to obtain the navigation energy consumption and inspection energy consumption of the UAV; S32. Analyze and process the drone's pending cruise path based on the route planning terminal to determine the drone inspection starting point, where the drone inspection starting point is any one of the two end points of the drone's pending cruise path; S33. The route planning terminal filters and processes the cruising area information of the cruising point based on the drone inspection starting point, and determines the cruising area corresponding to the drone inspection starting point; S34. Based on the route planning terminal, the cruising area corresponding to the inspection starting point of the drone and the inspection energy consumption of the drone are calculated and processed to determine the remaining energy of the drone; S35. Based on the route planning terminal, the remaining energy of the UAV and the navigation energy consumption of the UAV are compared and judged to determine the UAV inspection plan; The specific calculation formula for determining the remaining energy of the drone is: Where E1 is the remaining energy of the UAV; E2 is the energy of the UAV before inspection; A1 is the cruising area corresponding to the starting point of the UAV inspection; and B is the energy consumption of the UAV inspection.

9. The method for planning a UAV inspection route according to claim 8, characterized in that: The above S35, based on the route planning terminal, compares and determines the remaining energy of the drone and the navigation energy consumption of the drone to determine the drone inspection plan, specifically includes the following steps: S351. The route planning terminal performs positioning processing on the drone's patrol path based on the drone's patrol starting point, and determines the drone's second patrol point. S352, the route planning terminal reads and processes the data of the shortest distance set based on the drone inspection starting point and the drone second inspection point, and determines the first navigation distance of the drone; S353. Calculate and process the first flight distance of the UAV and the flight energy consumption of the UAV based on the route planning terminal to obtain energy information required for the first flight distance of the UAV; S354: Based on the route planning terminal, determine and process the remaining energy of the UAV and the energy required for the first navigation distance of the UAV; S355: If the remaining energy of the drone is greater than the energy required for the first navigation distance of the drone, the drone does not need to recharge energy at the starting point of the drone inspection; S356. If the remaining energy of the drone is less than or equal to the energy information required for the first navigation distance of the drone, the drone cannot complete the second inspection mission, and the drone needs to replenish energy at the starting point of the drone inspection.

10. A drone inspection route planning system, used to implement a drone inspection route planning method according to any one of claims 1 to 9, characterized in that: include: A route planning terminal is used to control each module to analyze the distribution map of the drone's cruise area and the drone's energy consumption parameters, determine the drone inspection plan, and control information exchange and data transmission between each module; A database for storing a distribution map of the area to be cruised by the drone and energy consumption parameters of the drone; A distribution map analysis module is used to analyze the distribution map of the area to be cruised by the UAV, and determine the location information of the cruise points to be cruised, the cruise area information of the cruise points to be cruised, and the distance information between the cruise points to be cruised; A path determination module, which is used to analyze and process distance information between the cruise points to be cruised and determine the cruise path of the UAV; The inspection starting point selection module is used to randomly select the endpoints of the drone's patrol path to determine the drone's inspection starting point; An energy calculation module, which calculates and processes the remaining energy of the drone based on the cruising area corresponding to the drone's inspection starting point and the drone's inspection energy consumption, and obtains energy information required for the drone's first navigation distance based on the drone's first navigation distance and the drone's navigation energy consumption; The comparison and judgment module determines the inspection plan of the drone based on the remaining energy of the drone and the energy required for the first navigation distance of the drone.

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