A UAV resource management system and method based on urban CIM

Abstract

The present invention proposes a UAV resource management system and method based on urban CIM, which belongs to the technical field of UAV task scheduling; it includes a task publishing unit, which is used to receive the first and second tasks published by system users; a task matching unit, which is connected to the task publishing unit in communication, and combines the first and second tasks to obtain a task package; a path planning unit, which is connected to the task matching unit in communication, calculates the content of the task package, judges the rationality of the task package division, maintains or adjusts the number of the first or second tasks in the task package, and generates a preset path for the UAV and sends it to the UAV; a display output unit, which is connected to the UAV in communication, and is used to display the real-time position of the UAV executing the task, environmental information and the execution status of each task in the task package on the urban CIM model, and update feedback to the system user. Through reasonable planning, real-time tracking of tasks can be achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle task scheduling, and in particular to an unmanned aerial vehicle resource management system and method based on urban CIM. Background Art

[0002] Urban CIM (City Information Modeling) refers to the digital description and simulation of various physical and social elements of a city through digital technology and information technology to achieve optimization and intelligence in urban planning, construction, management and operation. The core of urban CIM is to integrate various types of urban data to form a comprehensive, dynamic and visual urban model to support decision-making and management.

[0003] Drones can complete different types of tasks through onboard space or equipment, such as hovering or landing during flight or at a fixed height for the purpose of video / image acquisition, facility monitoring, or logistics delivery. In order to integrate the city's drone resources, meet the needs of personalized task execution, and reduce the repeated investment in equipment construction, system users only need to rent drones on a time-sharing basis to obtain exclusive data or inspection results for designated tasks. However, the existing drone path planning mainly relies on personal experience, and the management lacks visual means to monitor the status of drones in real time, resulting in untimely maintenance of drones, which affects the smooth execution of tasks and customer experience.

[0004] Therefore, in view of the above situation, it is very necessary to provide a UAV resource management system and method based on urban CIM, which can integrate the tasks of the appointment person, reasonably plan the flight path, and provide real-time feedback on the status of the UAV to achieve visual management. Summary of the invention

[0005] In view of this, the present invention proposes an urban CIM drone resource management system and method based on a temporary path between the starting point and the end point of the task, which integrates one or more adjacent tasks, rationally plans the flight path, and realizes the continuous execution of multiple tasks.

[0006] On the one hand, the present invention provides a UAV resource management system based on urban CIM, comprising:

[0007] A task issuing unit, used for receiving first-category tasks issued regularly by system users, and receiving second-category tasks issued temporarily by system users;

[0008] The task matching unit is connected to the task issuing unit for communication, and combines the first-category tasks and the second-category tasks having a time-limited inclusion relationship according to the first-category tasks and the second-category tasks acquired by the task issuing unit to form a task package including a plurality of the first-category tasks and / or the second-category tasks;

[0009] The path planning unit is connected to the task matching unit in communication, calculates the content of the task package, determines the rationality of the task package division, maintains or adjusts the number of the first or second type of tasks in the task package, and generates a preset path for the UAV and sends it to the UAV;

[0010] The display output unit is connected to the UAV for communication and is used to display the real-time position, environmental information and execution status of each task in the mission package of the UAV in the mission execution on the city CIM model, and provide update feedback to the system users.

[0011] On the basis of the above technical solution, preferably, the first category of tasks are inspection tasks of fixed facilities that require periodic maintenance, and the first category of tasks has an independent preset path; the second category of tasks are temporary tasks with timeliness requirements; the execution priority of the second category of tasks is higher than that of the first category of tasks; temporary tasks with timeliness requirements include shooting, monitoring and delivery types, and the priorities of shooting tasks, monitoring tasks and delivery tasks increase in sequence.

[0012] Preferably, the task matching unit classifies the first-category tasks and the second-category tasks having a time-limited inclusion relationship to form a task package containing a plurality of first-category tasks and / or second-category tasks, specifically:

[0013] 1-1) Sort the second-category tasks by their end time. The second-category tasks with earlier end time have higher priority. Establish temporary paths between the starting point and end point of each second-category task. Exclude the second-category tasks whose end point is within the no-fly zone.

[0014] 1-2) If the temporary path between the start and end point of the current second-type task overlaps or is adjacent to the temporary path determined by another second-type task, first confirm whether the start time of the two different second-type tasks is on the same day. If the start time is on the same day, further compare whether the start-end time of the two different second-type tasks overlap; if the start time is not on the same day, the two different second-type tasks will not be combined; if the start-end time of the two different second-type tasks does not overlap on the same day and the interval does not exceed 20% of the flight endurance of the drone, or the overlap of the start-end time of the two different second-type tasks does not exceed the set time threshold, and the end time is different, then the two different second-type tasks will be combined, otherwise the two different second-type tasks will not be combined; after the different second-type tasks are combined, the combined first-task time period is obtained, and the first-task time period meets the requirements of continuous execution of different second-type tasks;

[0015] 1-3) After completing the combination of different second-category tasks, if the temporary path between the starting point and the end point of the current second-category task coincides with or is adjacent to the preset path for at least one first-category task, confirm whether the start time of the first time period is on the same day as the start time of at least the first-category task; if it is on the same day, further compare whether the start-end time of the first time period overlaps with the start-end time of the first-category task; if the start times are not on the same day, the combined second-category task is not further combined with at least the first-category task; if the start-end time of the first time period overlaps with the start-end time of at least one first-category task, then the combined second-category task is not combined with the first-category task; If the end times do not overlap within the same day and the interval does not exceed 20% of the UAV flight duration, or the overlap between the start-end time of the first time period and the start-end time of at least one first-category task does not exceed the set duration threshold, and the end times are different, then the combined second-category task is further combined with at least one first-category task, otherwise no combination is performed; after the combined second-category task completes the combination process with at least one first-category task, a task package and a corresponding second task time period are obtained; the first time period is not completely equal to the second time period, and the second time period meets the requirement of continuous execution of each task in the task package;

[0016] 1-4) If the temporary path of the second type of task does not overlap or is not adjacent to the temporary path of another second type of task or the preset path of the first type of task, the second type of task is executed alone.

[0017] Further preferably, when two different second-type tasks are combined, the start and end times of one second-type task are A1 and A2 respectively, and the start and end times of the other second-type task are A3 and A4 respectively;

[0018] When A1 < A2 ≤ A3 < A4, the starting time A1 is used as the starting time of the first combined task period, and the ending time A4 is used as the ending time of the first combined task period; the interval between time A2 and time A3 does not exceed 20% of the flight endurance time of the unmanned aerial vehicle.

[0019] When A1 < A3 ≤ A2 < A4, the starting time A1 is advanced by (A2 - A3) × (1 + a%) as the starting time of the first task period, and the ending time A4 is used as the ending time of the first combined task period, or the starting time A1 is used as the starting time of the first combined task period, and the ending time A4 is postponed by (A2 - A3) × (1 + a%) as the ending time of the first combined task period; a is a real number.

[0020] When A1 < A3 < A4 < A2, the starting time A1 is advanced by (A4 - A3) × (1 + b%) as the starting time of the first task period, and the ending time A2 is used as the ending time of the first combined task period; b is a real number, and A4 - A3 ≤ 50% × (A2 - A1); the first type of task is arranged after the first task period.

[0021] Preferably, the specific working content of the path planning unit is as follows:

[0022] 2-1) Obtain the operating environment information and construct an energy demand model for each task based on the execution task package.

[0023] 2-2) Construct a UAV battery capacity degradation model.

[0024] 2-3) Select a suitable UAV to execute the current task package.

[0025] 2-4) If no UAV can execute all the tasks in the task package, then eliminate one or more tasks with the lowest priority in the task package, and re-execute step 2-3) until the current UAV can execute all the tasks in the task package. The eliminated tasks are executed separately or are recombined with other tasks by the task matching unit to form a task package.

[0026] Further preferably, for the construction of the energy demand model for each task based on the execution task package, the energy demand of the task E is divided into the sum of flight energy consumption, shooting energy consumption, storage and compression energy consumption, and data transmission energy consumption and satisfies the following formula: , where is the corrected flight power demand, is the flight time of the UAV, is the power demand for the UAV to take pictures using the on-board camera, The time taken by the drone to shoot using the onboard camera, is the shooting frequency, The power required to compress and store each megabyte of data captured by the drone’s camera. The total amount of data compressed and stored by the drone. The power required per megabyte of data for long-distance real-time transmission of data by drones, is the total amount of data transmitted by the UAV wirelessly, is the transmission power coefficient of the UAV antenna; the corrected flight power requirement The expression is: ,in is the horizontal flight power, is the cumulative time of horizontal flight during the execution of the mission package, is the hovering flight power, The cumulative hovering time when executing the task package. is the ascending flight power, is the cumulative duration of the drone's ascent process when executing the mission package. To reduce the power of the flight sub- is the cumulative duration of the drone’s descent process when executing the mission package, and ; First wind speed correction factor , is the wind speed correction factor, is the ambient wind speed, is the horizontal flight speed of the drone; the second wind speed correction factor ; Altitude correction factor , is the altitude correction factor, is the altitude of the drone relative to sea level, is the unloaded mass of the UAV, is the mass of the object being delivered when the drone is performing a delivery mission; the temperature correction factor , is the height of the drone relative to sea level The ambient temperature at The best temperature for drone batteries to work.

[0027] Further preferably, the construction of the drone battery capacity decay model is to set the initial capacity of the drone battery to C 0 , in watt-hours, the current maximum capacity of the drone battery is C ; Then the expression of the UAV battery capacity degradation model is as follows: , is the rated capacity attenuation factor, ;make To accumulate the number of complete discharge cycles, The number of times the drone starts charging after completing a mission or mission package. The number of times the drone starts charging after completing a mission or mission package. It is the number of times the drone has completed the mission or mission package after the third starting charging capacity. The calculation formula for the cumulative number of discharge cycles is: ,and Round up, where , and They correspond to the cumulative initial charge capacity relative to the discharge depth of the rated capacity; according to the cumulative number of complete discharge cycles Get the rated capacity attenuation factor .

[0028] Further preferably, the selection of a suitable drone to perform the current mission or mission package is the current maximum capacity of the drone battery. C Energy requirements of the task E Match, if satisfied , is the discharge efficiency of the drone battery, , then arrange the current UAV to perform the current task or task package; if , it indicates that the current drone is not suitable for the current mission or mission package, and the number of complete discharge cycles is replaced Less another drone, re-performing the above energy requirements E The current maximum capacity of the drone battery C The matching process, if after several replacements, different drones cannot match the energy demand E If the drone is executing a single task, it will report to the path planning unit that it cannot complete the task; if the drone is executing a task package containing multiple tasks, it will try to remove at least one task with lower priority or high energy consumption in the task package to reduce energy demand. E , re-energizing demand E The current maximum capacity of the drone battery C The matching process continues until the task requirements are met.

[0029] More preferably, the path planning unit generates a preset path for the drone and sends it to the drone, and the path generation is performed according to the following rules:

[0030] 1) The preset path of the drone needs to take into account the round-trip path. The outbound path to the farthest point of the preset path is not exactly the same as the return path to the starting point; the ambient wind speed must not be greater than 10m / s;

[0031] 2) The delivery task in the second category has the highest priority, and the delivery task is performed first to reduce the flight quality of the drone; a shortest straight temporary path is set for the delivery task, without considering the impact of increased flight energy consumption caused by wind speed; if the end point of the delivery task is at the farthest point of the preset path, other tasks other than the delivery task are planned on the return path; if the end point of the delivery task is not at the farthest point of the preset path, after completing the delivery task, the drone will arrive at the nearest adjacent task area to perform the subsequent task with the highest timeliness priority;

[0032] 3) After the delivery task is completed, when moving to the location of the shooting task or monitoring task, the drone will lower its flight altitude and choose the moving path with the lowest energy consumption according to the average wind speed for a period of time before the current moment to move to the location of the shooting task or monitoring task until it reaches the shooting task or monitoring task area;

[0033] 4) For shooting or monitoring missions, the drone will fly back and forth over the designated area to minimize the headwind during flight and reduce energy consumption during flight or hovering. The drone will shoot or monitor the designated area from at least two different directions and compress and temporarily store the acquired images in the drone's internal storage space until the set flight time is reached. If the drone is performing shooting or monitoring missions, the current maximum capacity of the drone battery is C No more than the initial capacity of the drone battery C 0 If the shooting frequency of the designated area is reduced by 30%, ; After completing all the tasks in the mission package, the remaining capacity of the drone battery is not less than the initial capacity C 0 15%;

[0034] 5) If the shooting task or monitoring task requires real-time data transmission, the temporarily stored compressed image is further transmitted to the cloud through the drone antenna, so that the preset path of the drone passes through the nearest communication base station. After the cloud data transmission is completed, the compressed image temporarily stored in the internal storage space of the drone is deleted. The overall requirements are: ensure that the delivery task path is the shortest, the shooting task or monitoring task has the lowest energy consumption, and the inspection task of fixed facilities has the lowest priority but does not reduce power consumption.

[0035] On the other hand, a method for managing drone resources based on urban CIM includes the following steps:

[0036] S1: Configure the above-mentioned urban CIM-based drone resource management system;

[0037] S2: using the task publishing unit to receive the first-category tasks regularly published by system users, and to receive the second-category tasks temporarily published by system users; combining different tasks that are time-related on the same day into task packages containing several first-category tasks and / or second-category tasks; forming tasks that cannot be combined into separate tasks;

[0038] S3: Current capacity of currently available drones C , the energy requirements of a task or task package E Conduct evaluation and select suitable drones to perform corresponding tasks or task packages; if they meet the requirements , is the discharge efficiency of the drone battery, , then arrange the current UAV to perform the current task or task package; if , it indicates that the current drone is not suitable for the current mission or mission package, and the number of complete discharge cycles is replaced Less another drone, re-performing the above energy requirements E The current maximum capacity of the drone battery C The matching process, or eliminating tasks with lower priority or higher energy consumption;

[0039] S4: The path planning unit generates a preset path for the UAV and sends it to the UAV, executes each task according to priority, and displays the real-time status of the UAV executing the task on the CIM mode.

[0040] The present invention provides a UAV resource management system and method based on urban CIM, which has the following beneficial effects compared with the prior art:

[0041] The present invention combines several tasks with similar endpoints into a task package, and realizes the continuous execution of tasks of different priorities by integrating the task packages, thereby improving the efficiency of task execution; then, the estimated energy consumption demand of the task package, the power of the currently assigned drone, and the aging degree of the battery are used to judge whether the drone is competent for the current task package, and the drone that is not competent will be replaced; if the power of all drones does not support the completion of the task package, it indicates that the combination of the task package content is unreasonable and the content of the task package needs to be adjusted; if a single task cannot be executed by the drone, it means that the drone is not suitable for completing the single task and needs to be transported by other means of transportation;

[0042] After selecting the corresponding drones and mission packages based on the matching degree of energy consumption and drone battery capacity, further rationally plan the energy use strategy of each task in the corresponding real-time path, select the shortest path for delivery tasks, select the strategy with the lowest energy consumption for shooting tasks or monitoring tasks, and ensure that the drone can return smoothly after completing the mission. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a structural block diagram of a UAV resource management system and method based on urban CIM of the present invention;

[0045] Figure 2 This is a flowchart of the steps of a UAV resource management system and method based on urban CIM of the present invention. DETAILED DESCRIPTION

[0046] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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 creative work are within the scope of protection of the present invention.

[0047] like Figure 1 As shown, on the one hand, the present invention provides a UAV resource management system based on urban CIM, comprising:

[0048] The task publishing unit is used to receive the first-class tasks regularly published by system users, and the second-class tasks temporarily published by system users; the task publishing platform is a public service platform for the Internet. System users registered on the platform can publish, modify or cancel the first-class tasks or the second-class tasks at any time after logging in. The second-class tasks are time-sensitive, that is, they have corresponding significance only in a specific time period of a specific date, so they have a higher priority. The task publishing unit can be imported in different types, such as mobile APP, web page or PC application, etc.

[0049] The task matching unit is communicated with the task issuing unit, and combines the first-category tasks and the second-category tasks having a time-limited inclusion relationship according to the first-category tasks and the second-category tasks obtained by the task issuing unit to form a task package containing several first-category tasks and / or second-category tasks; the task matching unit attempts to combine one or more tasks adjacent to each other in the task area so that different tasks can be executed continuously, thereby shortening the waiting time and the inefficiency caused by frequent returns to the starting point.

[0050] The path planning unit communicates with the task matching unit, calculates the content of the task package, determines the rationality of the task package division, maintains or adjusts the number of first-category tasks or second-category tasks in the task package, generates a preset path for the UAV and sends it to the UAV; whether the task package combined by the task matching unit is reasonable requires building an energy demand model for the tasks in the task package to determine whether the existing UAVs can complete all the tasks in the task package and return smoothly. If the energy consumption requirements of the UAV and the task package do not match, the UAV is replaced or the task composition in the task package is adjusted to select a suitable execution method.

[0051] The display output unit is connected to the UAV communication system and is used to display the real-time location of the UAV executing the mission, environmental information, and the execution status of each task in the mission package on the city CIM model, and to provide updated feedback to the system users. The city information model CIM is based on the basic components of high-precision urban modeling. It has extremely high accuracy for roads, buildings and their structures, and public facilities. Combined with the city information model, it is conducive to planning more sophisticated UAV flight paths and improving the obstacle avoidance capabilities and mission execution efficiency of UAV flights. Visual output can be achieved through the display output unit. System users can log in to the public service platform to query and observe in real time the status of the user's published tasks currently being executed, and obtain real-time information such as the speed, altitude, and returned video data of the UAV to meet the customized needs of system users.

[0052] like Figure 1As shown in the figure, the first type of tasks mentioned in the task release unit are inspection tasks for fixed facilities that require periodic maintenance. The first type of tasks has an independent preset path; the second type of tasks are temporary tasks with timeliness requirements; the execution priority of the second type of tasks is higher than that of the first type of tasks; temporary tasks with timeliness requirements include shooting, monitoring and delivery task types, and the priorities of shooting tasks, monitoring tasks and delivery tasks increase in sequence. Delivery tasks have the highest priority because of the timeliness requirements for cargo delivery, and the weight of the drone increases when carrying cargo. The longer the flight time, the greater the energy consumption, which will affect the execution of other tasks of the same drone. The energy consumption of the remaining second type of tasks is mainly related to the flight distance or altitude, and also involves the energy consumption of temporary storage or real-time transmission of data, such as news reports or traffic guidance with strong timeliness, which have higher requirements for data processing. Regular inspection tasks usually only need to be completed during the daytime period before and after the corresponding date, so they have the lowest priority. If the second type of tasks that the drone needs to perform have the same priority, such as carrying goods for more than two different delivery tasks, the delivery task with the shortest distance from the starting point will be performed first, that is, the drone's load will be reduced as quickly as possible.

[0053] like Figure 1 As shown, the task matching unit classifies the first-category tasks and the second-category tasks having a time-limited inclusion relationship to form a task package containing several first-category tasks and / or second-category tasks, specifically:

[0054] 1-1) Sort different second-category tasks by their end time, and the second-category tasks with earlier end time have higher priority; establish temporary paths between the starting point and end point of each second-category task; exclude second-category tasks whose end point is in the no-fly zone, and even if the end point is not in the no-fly zone, the temporary path cannot pass through or be adjacent to the no-fly zone; the no-fly zone involves confidential or military content, and no matter what the priority of the task is, its preset path or temporary path cannot pass through or pass through the area adjacent to the no-fly zone. The priority order here is: fixed facility inspection task < shooting task = monitoring task < delivery task.

[0055] 1-2) If the temporary path between the start point and the end point of the current second type of task coincides with or is adjacent to the temporary path defined by another second type of task, first confirm whether the start times of the two different second type of tasks are on the same day. If the start times are on the same day, further compare whether there is an overlap between the start-end times of the two different second type of tasks; if the start times are not on the same day, do not combine the two different second type of tasks; if the start-end times of the two different second type of tasks do not overlap within the same day and the interval does not exceed 20% of the drone's flight endurance time, or the overlapping part of the start-end times of the two different second type of tasks does not exceed the set time threshold and the end times are different, then combine the two different second type of tasks, otherwise do not combine the two different second type of tasks; after combining different second type of tasks, the combined first task time period is obtained, and the combined first task time period meets the requirement of continuous execution of different second type of tasks.

[0056] This content first determines whether the second type of tasks are on the same day. Only those on the same day can be tried to be combined, and those not on the same day cannot be combined. When on the same day, it is necessary to ensure that different second type of tasks have different end times. If the end times are very close, the drone cannot handle two different tasks simultaneously, which may lead to poor timeliness. Therefore, it is preferred to select two second type of tasks with different priorities and completely separated start time periods, two second type of tasks with different priorities where the end time period of one task partially overlaps with the start time period of the other task, or two second type of tasks with different priorities where the time period of one task is completely contained in the non-end part of the time period of the other task.

[0057] The specific rules are as follows: When combining two different second type of tasks, let the start-end times of one second type of task be A1 and A2 respectively, and the start-end times of the other second type of task be A3 and A4 respectively;

[0058] When A1 < A2 ≤ A3 < A4, use the start time A1 as the start time of the combined first task time period, and use the end time A4 as the end time of the combined first task time period; the interval between time A2 and time A3 does not exceed 20% of the drone's flight endurance time;

[0059] When A1 < A3 ≤ A2 < A4, move the start time A1 forward by (A2 - A3) × (1 + a%) as the start time of the first task time period, and use the end time A4 as the end time of the combined first task time period, or use the start time A1 as the start time of the combined first task time period, and move the end time A4 backward by (A2 - A3) × (1 + a%) as the end time of the combined first task time period; a is a real number;

[0060] When A1 < A3 < A4 < A2, move the start time A1 forward by (A4 - A3) × (1 + b%) as the start time of the first task period, and the end time A2 as the end time of the combined first task period; b is a real number, and A4 - A3 ≤ 50% × (A2 - A1); the first type of task is arranged after the first task period. The above content of adjusting the start time is to take into account the end times of two different tasks, avoid the end times being too close, and leave enough completion time for each task and the necessary moving time between the corresponding areas of the two tasks.

[0061] 1 - 3) After completing the combination of different second - type tasks, if the temporary path between the start point and the end point of the current second - type task coincides or is adjacent to the preset path defined by at least one first - type task pair, confirm whether the start time of the first period is on the same day as the start time of at least one first - type task. If it is on the same day, further compare whether there is an overlap between the start - end time of the first period and the start - end time of the first - type task; if the start times are not on the same day, do not further combine the combined second - type task with at least one first - type task; if there is no overlap between the start - end time of the first period and the start - end time of at least one first - type task on the same day and the interval does not exceed 20% of the UAV flight endurance time, or the overlapping part between the start - end time of the first period and the start - end time of at least one first - type task does not exceed the set duration threshold and the end times are different, then further combine the combined second - type task with at least one first - type task, otherwise do not combine; after the combined second - type task completes the combination process with at least one first - type task, obtain the task package and the corresponding second task period; the first period and the second period are not exactly equal, and the second period meets the requirement of continuous execution of each task in the task package.

[0062] After completing the combination of the second - type tasks, then consider combining with the first - type tasks. The combination rule of the first - type tasks is similar to the combination of two second - type tasks, and it is recommended to execute the first - type tasks after the second - type tasks are completed. Since the timeliness of the first - type tasks is relatively weak, delaying them appropriately will not affect the smooth execution of the first - type tasks. The start time of the first - type tasks is preferably set as the latest end time of all second - type tasks.

[0063] 1 - 4) If the temporary path of the second - type task does not coincide or is not adjacent to the temporary path of another second - type task or the preset path of the first - type task, execute the second - type task separately.

[0064] For isolated first-category tasks or second-category tasks, since they are too far away from the starting point or the area where other tasks are performed, such as more than 20 km, it is recommended to execute the first-category tasks or second-category tasks separately instead of combining them with non-adjacent tasks into a task package.

[0065] like Figure 1 As shown in the figure, the specific work content of the path planning unit is:

[0066] 2-1) Obtain operating environment information and build an energy demand model for each task based on the execution task package.

[0067] Specifically, the energy demand of the task E Divided into flight energy consumption, shooting energy consumption, storage compression energy consumption and data transmission energy consumption The accumulation satisfies the following formula: ,in is the corrected flight power requirement, is the flight time of the drone, The power requirement for drones to shoot with onboard cameras. The time taken by the drone to shoot using the onboard camera, is the shooting frequency, The power required to compress and store each megabyte of data captured by the drone’s camera. The total amount of data compressed and stored by the drone, in megabytes; The power required per megabyte of data for long-distance real-time transmission of data by drones, is the total amount of data transmitted by the UAV wirelessly, in megabytes; is the transmission power coefficient of the UAV antenna, It is a real number not less than 1. When the delay of data transmission exceeds the set transmission threshold.

[0068] Corrected flight power requirements The expression is: ,in is the horizontal flight power, is the cumulative time of horizontal flight during the execution of the mission package, is the hovering flight power, The cumulative hovering time when executing the task package. is the ascending flight power, is the cumulative duration of the drone's ascent process when executing the mission package. To reduce the power of the flight sub- is the cumulative duration of the drone’s descent process when executing the mission package, and ; First wind speed correction factor , is the wind speed correction factor, is the ambient wind speed, is the horizontal flight speed of the drone; the second wind speed correction factor ; Altitude correction factor , is the altitude correction factor, is the altitude of the drone relative to sea level, is the unloaded mass of the UAV, It is the mass of the object being delivered when the drone performs a delivery mission. The greater the mass, the greater the impact on energy consumption as the flight time or altitude changes. Temperature correction factor , is the height of the drone relative to sea level The ambient temperature at The optimal operating temperature for drone batteries, in degrees Celsius or Fahrenheit.

[0069] The reason for correcting the flight power demand is that the external environment is changing repeatedly. Weather such as wind, rain, fog or snow, ambient temperature, altitude and the mass of the cargo carried will have a great impact on the flight power demand and hovering power demand. The flight sub-power demand and hovering sub-power demand are also the main energy consumption functions of the UAV to perform tasks or mission packages, so they must be considered. The rise sub-power or the descent sub-power does not take into account the impact of the environment because of the short cumulative time. The higher the altitude, the higher the flight energy consumption; the stronger the wind, the greater the power consumption to overcome wind resistance when against the wind; the closer the ambient temperature is to the maximum operating temperature, the better the battery output is. On the contrary, the lower the ambient temperature, the charging and discharging of the battery will be adversely affected.

[0070] 2-2) Construct a drone battery capacity degradation model.

[0071] Specifically, the initial capacity of the drone battery is C 0 , in watt-hours, the current maximum capacity of the drone battery is C ; Then the expression of the UAV battery capacity degradation model is as follows: , is the rated capacity attenuation factor, ;make To accumulate the number of complete discharge cycles, The number of times the drone starts charging after completing a mission or mission package. The number of times the drone starts charging after completing a mission or mission package. It is the number of times the drone has completed the mission or mission package after the third starting charging capacity. The calculation formula for the cumulative number of discharge cycles is: ,and Round up, where , and They correspond to the cumulative initial charge capacity relative to the discharge depth of the rated capacity; according to the cumulative number of complete discharge cycles Get the rated capacity attenuation factor . , and The initial value of can be obtained according to the characteristic curve of the drone battery, such as the initial capacity of the drone battery C 0 The voltage in the 20%-80% range is linearly related to the current capacity.

[0072] The above calculation of rated capacity attenuation factor is a quick estimation method. k It is an interval value with low accuracy. In actual use, a more sophisticated model can also be used to calculate the rated capacity attenuation factor. k , increasing the current maximum capacity of drone batteries C Energy requirements of the task E The accuracy of the match: ,in The initial capacity of the drone battery C 0 The corresponding discharge voltage can be used to estimate the rated capacity attenuation factor using interval values ​​when the number of cumulative discharge cycles of the drone is small. k In the case of a large number of cumulative discharge cycles of the UAV, a sophisticated model is used to calculate the rated capacity attenuation factor. k .

[0073] 2-3) Select the appropriate drone to execute the current mission package.

[0074] Specifically, the current maximum capacity of the drone battery C Energy requirements of the task E Match, if satisfied , is the discharge efficiency of the drone battery, , then arrange the current UAV to perform the current task or task package; if , it indicates that the current drone is not suitable for the current mission or mission package, and the number of complete discharge cycles is replaced Less another drone, re-performing the above energy requirements E The current maximum capacity of the drone battery CThe matching process, if after several replacements, different drones cannot match the energy demand E If the drone is executing a single task, it will report to the path planning unit that it cannot complete the task; if the drone is executing a task package containing multiple tasks, it will try to remove at least one task with lower priority or high energy consumption in the task package to reduce energy demand. E , re-energizing demand E The current maximum capacity of the drone battery C The matching process continues until the task requirements are met.

[0075] 2-4) If no drone can perform all the tasks in the task package, then remove one or more tasks with the lowest priority in the task package and re-execute step 2-3) until the current drone can perform all the tasks in the task package. The removed tasks are executed individually or recombined with other tasks by the task matching unit to form a task package. If a task is too far from the starting point or the execution area of ​​other tasks, or the energy required for the execution of a single task exceeds the current maximum capacity of the drone battery C If the task is less than 75%, it is not recommended to combine it with other tasks but to perform it separately.

[0076] like Figure 1 Combination Figure 2 As shown, the path planning unit generates a preset path for the drone and sends it to the drone. The path generation is performed according to the following rules:

[0077] 1) The preset path of the drone needs to take into account the round-trip path. The outbound path to the farthest point of the preset path is not exactly the same as the return path to the starting point. The ambient wind speed must not be greater than 10m / s. Excessive ambient wind speed will greatly interfere with the execution of each task and bring safety issues. Therefore, it is not recommended to perform any task under high wind speed. The system user can be notified through the public service platform to change the start-end time of the task.

[0078] 2) The delivery task in the second category has the highest priority, and the delivery task is performed first to reduce the flight quality of the drone; a shortest straight temporary path is set for the delivery task, without considering the impact of increased flight energy consumption caused by wind speed; if the end point of the delivery task is at the farthest point of the preset path, other tasks other than the delivery task are planned on the return path; if the end point of the delivery task is not at the farthest point of the preset path, after completing the delivery task, it will reach the nearest adjacent task area to perform the subsequent task with the highest timeliness priority; at this time, the drone's flight altitude is selected to be 80-100m above the ground, which can avoid most obstacles, shorten the obstacle avoidance time, and better improve the timeliness of the delivery task.

[0079] 3) After the delivery task is completed, when moving to the location of the shooting task or monitoring task, the UAV's flight altitude is lowered, and according to the average wind speed for a period of time before the current moment, the moving path with the lowest energy consumption is selected to move to the location of the shooting task or monitoring task until the shooting task or monitoring task area is reached; the average wind speed for a period of time before the current moment can be the average wind speed and wind direction in the last 10 minutes. When moving between locations corresponding to different tasks, it is best to fly with the wind as much as possible, which is conducive to reducing energy consumption.

[0080] 4) For shooting or monitoring missions, the drone will fly back and forth over the designated area to minimize the headwind during flight and reduce energy consumption during flight or hovering. The drone will shoot or monitor the designated area from at least two different directions and compress and temporarily store the acquired images in the drone's internal storage space until the set flight time is reached. If the drone is performing shooting or monitoring missions, the current maximum capacity of the drone battery is C No more than the initial capacity of the drone battery C 0 If the shooting frequency of the designated area is reduced by 30%, ; After completing all the tasks in the mission package, the remaining capacity of the drone battery is not less than the initial capacity C 0 15% of the total.

[0081] The frequency of shooting or monitoring tasks The default setting is 100%. When you need to reduce the shooting frequency, reduce the shooting frequency by 10% each time during flight to reduce the amount of data compression, data transmission, and corresponding energy consumption until the shooting or monitoring task is completed.

[0082] 5) If the shooting task or monitoring task requires real-time data transmission, the temporarily stored compressed image is further transmitted to the cloud through the drone antenna, so that the preset path of the drone passes through the nearest communication base station. After the cloud data transmission is completed, the compressed image temporarily stored in the internal storage space of the drone is deleted. The overall requirements are: ensure that the delivery task path is the shortest, the shooting task or monitoring task has the lowest energy consumption, and the inspection task of fixed facilities has the lowest priority but does not reduce power consumption.

[0083] On the other hand, a method for managing drone resources based on urban CIM includes the following steps:

[0084] S1: Configure the above-mentioned urban CIM-based drone resource management system;

[0085] S2: using the task publishing unit to receive the first-category tasks regularly published by system users, and to receive the second-category tasks temporarily published by system users; combining different tasks that are time-related on the same day into task packages containing several first-category tasks and / or second-category tasks; forming tasks that cannot be combined into separate tasks;

[0086] S3: Current capacity of currently available drones C , the energy requirements of a task or task package E Conduct evaluation and select suitable drones to perform corresponding tasks or task packages; if they meet the requirements , is the discharge efficiency of the drone battery, , then arrange the current UAV to perform the current task or task package; if , it indicates that the current drone is not suitable for the current mission or mission package, and the number of complete discharge cycles is replaced Less another drone, re-performing the above energy requirements E The current maximum capacity of the drone battery C The matching process, or eliminating tasks with lower priority or higher energy consumption;

[0087] S4: The path planning unit generates a preset path for the UAV and sends it to the UAV, executes each task according to priority, and displays the real-time status of the UAV executing the task on the CIM mode.

[0088] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A UAV resource management system based on urban CIM, characterized in that: include: A task issuing unit, used for receiving first-category tasks issued regularly by system users, and receiving second-category tasks issued temporarily by system users; The task matching unit is connected to the task issuing unit for communication, and combines the first-category tasks and the second-category tasks having a time-limited inclusion relationship according to the first-category tasks and the second-category tasks acquired by the task issuing unit to form a task package including a plurality of the first-category tasks and / or the second-category tasks; The path planning unit is connected to the task matching unit in communication, calculates the content of the task package, determines the rationality of the task package division, maintains or adjusts the number of the first or second type of tasks in the task package, and generates a preset path for the UAV and sends it to the UAV; The display output unit is connected to the UAV for displaying the real-time position, environmental information and execution status of each task in the task package of the UAV in the task execution on the city CIM model, and providing update feedback to the system user; The first type of tasks are inspection tasks for fixed facilities that require periodic maintenance, and the first type of tasks have independent preset paths; the second type of tasks are temporary tasks with timeliness requirements; the execution priority of the second type of tasks is higher than that of the first type of tasks; temporary tasks with timeliness requirements include shooting, monitoring and delivery types, and the priorities of shooting tasks, monitoring tasks and delivery tasks increase in sequence; The task matching unit classifies the first-category tasks and the second-category tasks having a time-limited inclusion relationship to form a task package containing a plurality of first-category tasks and / or second-category tasks, specifically: 1-1) Sort the second-category tasks by their end time. The second-category tasks with earlier end time have higher priority. Establish temporary paths between the starting point and the end point of each second-category task. Excluding the second type of missions whose destination is within the no-fly zone; 1-2) If the temporary path between the start and end point of the current second-type task overlaps or is adjacent to the temporary path determined by another second-type task, first confirm whether the start time of the two different second-type tasks is on the same day. If the start time is on the same day, further compare whether the start-end time of the two different second-type tasks overlap; if the start time is not on the same day, the two different second-type tasks will not be combined; if the start-end time of the two different second-type tasks does not overlap on the same day and the interval does not exceed 20% of the flight endurance of the drone, or the overlap of the start-end time of the two different second-type tasks does not exceed the set time threshold, and the end time is different, then the two different second-type tasks will be combined, otherwise the two different second-type tasks will not be combined; after the different second-type tasks are combined, the combined first-task time period is obtained, and the first-task time period meets the requirements of continuous execution of different second-type tasks; 1-3) After completing the combination of different second-type tasks, if the temporary path between the starting point and the ending point of the current second-type task coincides with or is adjacent to the preset path defined by at least one first-type task pair, it is necessary to confirm whether the starting time of the first time period is on the same day as the starting time of at least the first-type task. If it is on the same day, further compare whether there is an overlap between the starting and ending times of the first time period and the starting and ending times of the first-type task. If the starting times are not on the same day, the combined second-type task and at least the first-type task are not further combined. If there is no overlap between the starting and ending times of the first time period and the starting and ending times of at least one first-type task on the same day and the interval does not exceed 20% of the drone's flight endurance time, or the overlapping part between the starting and ending times of the first time period and the starting and ending times of at least one first-type task does not exceed the set duration threshold and the ending times are different, then further combine the combined second-type task with at least one first-type task, otherwise do not combine. After the combined second-type task completes the combination process with at least one first-type task, a task package and the corresponding second task time period are obtained. The first time period and the second time period are not exactly equal, and the second time period meets the requirement of continuous execution of each task in the task package. 1-4) If the temporary path of the second-type task does not coincide with or is adjacent to the temporary path of another second-type task or the preset path of the first-type task, the second-type task is executed separately.

2. The UAV resource management system based on urban CIM according to claim 1 is characterized in that: When combining two different second-type tasks, let the starting and ending times of one second-type task be A1 and A2 respectively, and the starting and ending times of the other second-type task be A3 and A4 respectively. When A1 < A2 ≤ A3 < A4, the starting time A1 is used as the starting time of the combined first task time period, and the ending time A4 is used as the ending time of the combined first task time period. The interval between time A2 and time A3 does not exceed 20% of the drone's flight endurance time. When A1 < A3 ≤ A2 < A4, the starting time A1 is shifted forward by (A2 - A3) × (1 + a%) as the starting time of the first task time period, and the ending time A4 is used as the ending time of the combined first task time period, or the starting time A1 is used as the starting time of the combined first task time period, and the ending time A4 is shifted backward by (A2 - A3) × (1 + a%) as the ending time of the combined first task time period. a is a real number. When A1 < A3 < A4 < A2, the starting time A1 is shifted forward by (A4 - A3) × (1 + b%) as the starting time of the first task time period, and the ending time A2 is used as the ending time of the combined first task time period. b is a real number, and A4 - A3 ≤ 50% × (A2 - A1). The first-type task is arranged after the first task time period.

3. The UAV resource management system based on urban CIM according to claim 2 is characterized in that: The specific working content of the path planning unit is as follows: 2-1) Obtain the operating environment information and construct an energy demand model based on the energy requirements of each task in the task package to be executed. 2-2) Construct a drone battery capacity degradation model. 2-3) Select the appropriate drone to execute the current mission package; 2-4) If no drone can perform all the tasks in the task package, then remove one or more tasks with the lowest priority in the task package and re-execute step 2-3) until the current drone can perform all the tasks in the task package. The removed tasks are executed individually or recombined with other tasks by the task matching unit into a task package.

4. The UAV resource management system based on urban CIM according to claim 3 is characterized in that: The energy demand model of each task based on the execution of the task package is constructed by converting the energy demand of the task into E Divided into flight energy consumption, shooting energy consumption, storage compression energy consumption and data transmission energy consumption The accumulation satisfies the following formula: ,in is the corrected flight power requirement, is the flight time of the drone, The power requirement for drones to shoot with onboard cameras. The time taken by the drone to shoot using the onboard camera, is the shooting frequency, The power required to compress and store each megabyte of data captured by the drone’s camera. The total amount of data compressed and stored by the drone. The power required per megabyte of data for long-distance real-time transmission of data by drones, is the total amount of data transmitted by the UAV wirelessly, is the transmission power coefficient of the UAV antenna; the corrected flight power requirement The expression is: ,in is the horizontal flight power, is the cumulative time of horizontal flight during the execution of the mission package, is the hovering flight power, The cumulative hovering time when executing the task package. is the ascending flight power, is the cumulative duration of the drone's ascent process when executing the mission package. To reduce the power of the flight sub- is the cumulative duration of the drone’s descent process when executing the mission package, and ; First wind speed correction factor , is the wind speed correction factor, is the ambient wind speed, is the horizontal flight speed of the drone; the second wind speed correction factor ; Altitude correction factor , is the altitude correction factor, is the altitude of the drone relative to sea level, is the unloaded mass of the UAV, is the mass of the object being delivered when the drone is performing a delivery mission; the temperature correction factor , is the height of the drone relative to sea level The ambient temperature at The best operating temperature for drone batteries.

5. The UAV resource management system based on urban CIM according to claim 4 is characterized in that: The construction of the UAV battery capacity degradation model is to set the initial capacity of the UAV battery to C 0, in watt-hours, the current maximum capacity of the drone battery is C ; Then the expression of the UAV battery capacity degradation model is as follows: , is the rated capacity attenuation factor, ;make To accumulate the number of complete discharge cycles, The number of times the drone starts charging after completing a mission or mission package. The number of times the drone starts charging after completing a mission or mission package. It is the number of times the drone has completed the mission or mission package after the third starting charging capacity. The calculation formula for the cumulative number of discharge cycles is: ,and Round up, where , and They correspond to the cumulative initial charge capacity relative to the discharge depth of the rated capacity; according to the cumulative number of complete discharge cycles Get the rated capacity attenuation factor .

6. The UAV resource management system based on urban CIM according to claim 5 is characterized in that: Select the appropriate drone to perform the current mission or mission package, which is the current maximum capacity of the drone battery. C Energy requirements of the task E Match, if satisfied , is the discharge efficiency of the drone battery, , then arrange the current UAV to perform the current task or task package; if , it indicates that the current drone is not suitable for the current mission or mission package, and the number of complete discharge cycles is replaced Less another drone, re-performing the above energy requirements E The current maximum capacity of the drone battery C The matching process, if after several replacements, different drones cannot match the energy demand E If the drone is executing a single task, it will report to the path planning unit that it cannot complete the task; if the drone is executing a task package containing multiple tasks, it will try to remove at least one task with lower priority or high energy consumption in the task package to reduce energy demand. E , re-energizing demand E The current maximum capacity of the drone battery C The matching process continues until the task requirements are met.

7. The UAV resource management system based on urban CIM according to claim 6 is characterized in that: The path planning unit generates a preset path for the drone and sends it to the drone. The path is generated according to the following rules: 1) The preset path of the drone needs to take into account the round-trip path. The outbound path to the farthest point of the preset path is not exactly the same as the return path to the starting point; the ambient wind speed must not be greater than 10m / s; 2) The delivery task in the second category has the highest priority, and the delivery task is performed first to reduce the flight quality of the drone; a shortest straight temporary path is set for the delivery task, without considering the impact of increased flight energy consumption caused by wind speed; if the end point of the delivery task is at the farthest point of the preset path, other tasks other than the delivery task are planned on the return path; if the end point of the delivery task is not at the farthest point of the preset path, after completing the delivery task, the drone will arrive at the nearest adjacent task area to perform the subsequent task with the highest timeliness priority; 3) After the delivery task is completed, when moving to the location of the shooting task or monitoring task, the drone will lower its flight altitude and choose the moving path with the lowest energy consumption according to the average wind speed for a period of time before the current moment to move to the location of the shooting task or monitoring task until it reaches the shooting task or monitoring task area; 4) For shooting or monitoring missions, the drone will fly back and forth over the designated area to minimize the headwind during flight and reduce energy consumption during flight or hovering. The drone will shoot or monitor the designated area from at least two different directions and compress and temporarily store the acquired images in the drone's internal storage space until the set flight time is reached. If the drone is performing shooting or monitoring missions, the current maximum capacity of the drone battery is C No more than the initial capacity of the drone battery C 0, the frequency of shooting or monitoring the specified area is reduced. ; After completing all the tasks in the mission package, the remaining capacity of the drone battery is not less than the initial capacity C 15% of 0; 5) If the shooting task or monitoring task requires real-time data transmission, the temporarily stored compressed image is further transmitted to the cloud through the drone antenna, so that the preset path of the drone passes through the nearest communication base station. After the cloud data transmission is completed, the compressed image temporarily stored in the internal storage space of the drone is deleted. The overall requirements are: ensure that the delivery task path is the shortest, the shooting task or monitoring task has the lowest energy consumption, and the inspection task of fixed facilities has the lowest priority but does not reduce power consumption.

8. A method for managing drone resources based on urban CIM, characterized in that: The steps include: S1: configuring a drone resource management system based on urban CIM as described in any one of claims 1 to 7; S2: using the task publishing unit to receive the first-category tasks regularly published by system users, and to receive the second-category tasks temporarily published by system users; combining different tasks that are time-related on the same day into task packages containing several first-category tasks and / or second-category tasks; forming tasks that cannot be combined into separate tasks; S3: Current capacity of currently available drones C , the energy requirements of a task or task package E Conduct an evaluation and select suitable drones to perform the corresponding tasks or task packages; if the , is the discharge efficiency of the drone battery, , then arrange the current UAV to perform the current task or task package; if , it indicates that the current drone is not suitable for the current mission or mission package, and the number of complete discharge cycles is replaced Less another drone, re-performing the above energy requirements E The current maximum capacity of the drone battery C The matching process, or eliminating tasks with lower priority or higher energy consumption; S4: The path planning unit generates a preset path for the UAV and sends it to the UAV, executes each task according to priority, and displays the real-time status of the UAV executing the task on the CIM mode.

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