Automatic planning system for inspection task of unmanned aerial vehicle in limited space

Abstract

The invention relates to the technical field of unmanned aerial vehicle inspection, and discloses an automatic planning system for an unmanned aerial vehicle inspection task in a limited space. Comprising a task planning and scheduling module, an environment modeling and sensing module, a flight control module, a data acquisition and processing module, a communication and data transmission module, an intelligent analysis and decision module and a user interface and interaction module. According to the unmanned aerial vehicle inspection task automatic planning system in the limited space, through mutual cooperation of multiple modules and acquisition and analysis of use environment data, the automatic planning system can enable an unmanned aerial vehicle to automatically take off, execute an inspection task and safely land according to a preset task, and manual real-time control is not needed, so that the manpower demand is greatly reduced; and the inspection efficiency and frequency are improved.

Description

Technical Field

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

[0002] Drone inspection is a service that uses high-resolution cameras and other sensors on drones to conduct aerial inspections and tests on specific areas. This technology can collect data remotely and efficiently, providing real-time information for decision-making. Drone inspection uses sensors on drones, such as high-definition cameras and infrared thermal imagers, to conduct all-round, no-dead-angle inspections of target areas. The collected image data is transmitted to the command center through data links for intelligent analysis, so as to conduct precise analysis in accordance with the specific inspection scenarios and improve inspection efficiency and accuracy.

[0003] As people's lives continue to change, the use of drones has become more and more common, and the use of drone inspections has also become more and more common. However, traditional inspections require manual intervention, which makes them time-consuming and laborious to use. Therefore, a new system is now proposed to solve this technical problem. Summary of the invention

[0004] 1. Technical issues to be solved

[0005] In view of the shortcomings of the prior art, the present invention provides an automatic planning system for drone inspection tasks in a limited space, which has the advantages of improving inspection efficiency and solves the problem of low inspection efficiency of traditional methods mentioned in the above background technology.

[0006] (II) Technical solution

[0007] In order to achieve the purpose of improving inspection efficiency mentioned in the above background technology, the present invention provides the following technical solutions: an automatic planning system for inspection tasks of unmanned aerial vehicles in a limited space, including a task planning and scheduling module, an environment modeling and perception module, a flight control module, a data acquisition and processing module, a communication and data transmission module, an intelligent analysis and decision-making module, and a user interface and interaction module;

[0008] Task planning and scheduling module: responsible for automatically planning the specific content, sequence and schedule of inspection tasks based on inspection objectives, space restrictions and drone performance;

[0009] Environmental modeling and perception module: Use 3D modeling technology to build a digital model of a limited space, including terrain, buildings, and obstacles;

[0010] Flight control module: adjusts the flight attitude and trajectory of the drone in real time according to mission planning and environmental perception information, and is responsible for controlling the drone's takeoff, flight, hovering, landing and other flight actions;

[0011] Data collection and processing module: controls the sensors and equipment carried by the drone to collect data and pre-processes the collected data;

[0012] Communication and data transmission module: responsible for the communication and data transmission between the UAV and the ground control center, and ensuring the real-time, integrity and security of the data;

[0013] Intelligent analysis and decision-making module: conducts in-depth analysis and mining of collected data, identifies potential problems and anomalies, and automatically adjusts inspection strategies or issues early warning signals based on the analysis results;

[0014] User interface and interaction module: Provides an intuitive and easy-to-use user interface to facilitate users to view the status, progress and results of inspection tasks, and supports users to plan tasks, set parameters and view data through the interface.

[0015] Preferably, the mission planning and scheduling module includes target positioning and environment analysis, route planning, mission parameter setting and task allocation, resource scheduling, and mission monitoring and adjustment, wherein:

[0016] Target positioning and environmental analysis: Use airborne sensors to scan the inspection area, quickly locate the mission target, and analyze the surrounding environment characteristics, such as terrain and obstacle distribution;

[0017] Route planning: Based on the results of target positioning and environmental analysis, combined with the flight characteristics of the drone, advanced algorithms are used to plan one or more optimal routes for the drone;

[0018] Mission parameter setting: according to inspection requirements, set corresponding mission parameters for the drone to ensure the accuracy and completeness of inspection data;

[0019] Task allocation: According to the current status of the drone and the priority and difficulty of the task, the inspection task is reasonably allocated to the appropriate drone;

[0020] Resource scheduling: monitor the status and resource usage of drones in real time, and schedule resources as needed;

[0021] Task monitoring and adjustment: By real-time monitoring of the drone's flight status and task execution, the scheduling module can promptly detect and handle abnormal situations and adjust tasks as needed to ensure the smooth completion of inspection tasks;

[0022] According to the formula f(n) = g(n) + h(n), where g(n) represents the actual cost from the starting point to node n, and h(n) represents the estimated cost from node n to the end point;

[0023] And where g(n) = d × steps, where d is the constant cost of each step, and steps is the number of steps from the starting point to node n;

[0024] Where h(n) = [nx - gx] + [ny - gy], where (nx, ny) are the coordinates of node n and (gx, gy) are the coordinates of the end point;

[0025] Finally, the route is obtained according to f(h)=d×steps+[nx-gx]+[ny-gy].

[0026] The system is also highly efficient: through intelligent route planning and task scheduling, drones can efficiently cover the inspection area, reducing unnecessary flight time and waste of resources;

[0027] Safety: The system has automatic obstacle avoidance and environmental perception functions, which can ensure the safe flight of the drone in complex environments;

[0028] Flexibility: The system supports a variety of mission types and drone models to meet the needs of different inspection scenarios;

[0029] Intelligence: Using artificial intelligence and machine learning algorithms to analyze and process inspection data can automatically identify abnormal situations and issue early warnings, thereby improving the efficiency and accuracy of inspections.

[0030] Preferably, the environment modeling and perception module, wherein environment modeling is the basis for automatic planning of drone inspection tasks, and through laser radar scanning and visual sensor fusion, and in conjunction with three-dimensional space modeling software, a three-dimensional environment model that can be used for drone navigation and mission planning is finally generated;

[0031] The perception module is used by the drone to obtain real-time information about the surrounding environment and dynamically adjust the flight path and posture during inspection missions, including obstacle detection, visual perception analysis, and autonomous obstacle avoidance.

[0032] Obstacle detection: By using millimeter-wave radar and TOF ranging method, the distance between the drone and the obstacle is accurately measured by continuously sending light pulses to the target and receiving the returned light. The relative position of the drone relative to cables or other obstacles is measured in real time by using radar on multi-rotor drones, and is passed as feedback to the flight control system to achieve high-precision distance measurement or obstacle avoidance.

[0033] Visual perception analysis: The drone will carry a visual perception information module. Using binocular vision for stereo matching is a key step in environmental modeling. When two cameras are shooting, the image information is wirelessly transmitted to the ground station. After the ground station receives the image data, it is measured through a high-precision measurement system.

[0034] Autonomous obstacle avoidance: Based on the results of the above obstacle detection and visual perception analysis, the drone can judge the complexity and potential risks of the surrounding environment in real time, and automatically adjust the flight path and posture to avoid obstacles, so as to ensure that the drone can maintain a stable flight state and mission execution efficiency while avoiding obstacles.

[0035] Preferably, the flight control module is a core component that ensures that the UAV can fly autonomously according to a preset path or mission plan, and adjusts the flight status in real time to adapt to environmental changes, including autonomous flight control, real-time status monitoring, dynamic path planning, high-precision positioning and navigation;

[0036] Autonomous flight control: Automatically control the takeoff, flight and landing of the drone according to the preset route or mission plan, and use advanced flight control algorithms to ensure that the drone can fly accurately along the predetermined path;

[0037] Real-time status monitoring: monitors the flight status of the drone, including position, speed, and attitude. Once an abnormality or deviation from the predetermined path is found, the module will immediately take corrective measures;

[0038] Dynamic path planning: In a limited space, the flight path is dynamically adjusted based on real-time perception data to avoid obstacles or respond to other emergencies;

[0039] High-precision positioning and navigation: Combined with GPS and inertial measurement unit sensor data, the flight control module can achieve high-precision positioning and navigation, ensuring the precise flight of the drone in a limited space.

[0040] It also includes flight control algorithms: The core of the flight control module is the flight control algorithm, which can calculate and output control instructions according to the dynamic characteristics and environmental constraints of the UAV to adjust the flight state of the UAV;

[0041] Sensor fusion: To improve flight accuracy and reliability, the flight control module will fuse data from multiple sensors, such as GPS, IMU, lidar, and visual sensors. These sensors provide multi-dimensional information such as the drone's position, speed, attitude, and surrounding environment.

[0042] Actuator: The flight control module adjusts the flight state of the drone by controlling the actuator, controls the rise and fall, forward and backward movement of the drone by changing the speed of the motor, and changes the flight direction of the drone by adjusting the angle of the servo.

[0043] Preferably, the data acquisition and processing module is further divided into data acquisition and data processing, wherein data acquisition includes real-time monitoring of equipment or environment in a limited space by carrying various sensors, such as temperature sensors, vibration sensors, and current sensors;

[0044] Use high-definition cameras, infrared thermal imagers and other image acquisition devices to shoot inspection targets and obtain high-definition image data;

[0045] Data processing involves preliminary processing of the collected data, including deletion of useless data, data noise reduction, and data standardization, and then classification, clustering, and predictive analysis of massive data to mine valuable information. Cloud computing technology is used to provide convenient, efficient, and stable computing resources, and artificial intelligence algorithms are used to conduct in-depth analysis of the processed data, identify abnormal situations, and provide decision support.

[0046] Preferably, the communication and data transmission module is usually composed of a transmitter, a receiver and an antenna feed line, and includes two main parts: data transmission and image transmission;

[0047] The data transmission system is responsible for the uplink and downlink transmission of information such as the UAV's flight status and control instructions, ensuring that the UAV can perform inspection tasks according to the instructions of the ground control center;

[0048] The image transmission system is mainly used to transmit visible light video, infrared video and other image data collected by the drone in real time for real-time monitoring and analysis by ground control center personnel.

[0049] It also includes good real-time performance: ensuring that the communication delay between the drone and the ground control center is as low as possible so that problems encountered during the inspection process can be discovered and handled in a timely manner;

[0050] High reliability: In a limited space, the communication environment may be affected by various factors, such as obstacles and electromagnetic interference. The communication system needs to have high reliability to ensure stable operation in various environments.

[0051] Strong anti-interference ability: In view of the electromagnetic interference generated by high-voltage lines and high-voltage equipment, the communication system needs to have strong anti-interference ability to ensure the accuracy and integrity of data transmission.

[0052] Preferably, the communication and data transmission module also includes a data transmission method, and commonly used data transmission methods include digital transmission module communication and GPRS data transmission, wherein the digital transmission module communication: the digital transmission radio uses an ultra-short wave wireless communication channel to achieve remote data transmission, and in a space environment within line of sight and without obstructions, the digital transmission module can achieve a transmission distance of tens of kilometers;

[0053] GPRS data transmission: GPRS is a data transmission method based on mobile communication network, with wide coverage and fast transmission speed. In a limited space, if the mobile communication network coverage is good.

[0054] In order to ensure the accuracy and reliability of data transmission, the automatic planning system for drone inspection tasks usually uses standard communication protocols for data transmission. In drone inspection tasks, each independent module can be connected through the CAN communication protocol to achieve fast and accurate data transmission;

[0055] When conducting drone inspections in confined spaces, special attention must be paid to the security of communications and data transmission, including data encryption and access control measures to prevent unauthorized access and data leakage. A comprehensive emergency response mechanism must also be established to deal with possible communication failures or data loss.

[0056] Preferably, the intelligent analysis and decision-making module can capture detailed images and videos of the inspection area through the high-definition camera it is equipped with, and is equipped with multiple sensors such as infrared and lidar. By using machine learning or deep learning algorithms, the system can automatically identify key equipment or structures in the inspection area. By comparing the image differences between the normal state and the current state, the system can detect potential anomalies or faults, and can analyze historical data and perform predictive maintenance.

[0057] Preferably, the intelligent analysis and decision-making module is responsible for processing and analyzing the data collected by the drone and making corresponding decisions accordingly, including image recognition and analysis: using advanced image recognition algorithms to perform real-time analysis on high-definition images taken by the drone;

[0058] Data fusion and mining: Collect various other types of data, such as temperature, humidity, and vibration, and fuse them to obtain more comprehensive equipment status information;

[0059] Fault prediction and diagnosis: Based on the analysis of historical data and real-time data, predict possible equipment failures and perform preliminary diagnosis.

[0060] The module can also plan and adjust tasks: based on the analysis results, the intelligent analysis and decision-making module can automatically generate or adjust the inspection task plan of the drone. When an abnormality is found in a certain area, the inspection frequency of the area can be automatically increased or the inspection route can be changed.

[0061] Abnormal handling suggestions: For detected abnormalities or potential problems, the module will provide corresponding handling suggestions. For minor surface defects, it is recommended to mark and arrange subsequent repairs. For serious faults, it is recommended to shut down immediately and start the emergency response mechanism.

[0062] Human-computer interaction interface: In order to facilitate operators to understand and implement decision recommendations, the intelligent analysis and decision-making module is usually also equipped with an intuitive human-computer interaction interface, which can display analysis results, decision recommendations, and the current status of the drone in real time.

[0063] Preferably, the user interface and interaction module provide users with an intuitive, easy-to-use and efficient interactive experience to support the planning, execution and monitoring of drone inspection tasks, including modular design: the interface layout adopts modular design, dividing the main functions into different modules;

[0064] Map display: The main interface displays a map in a prominent position to intuitively display the drone's real-time location, inspection path, target area and other key information;

[0065] Status bar: displays the key status information and system status of the drone in real time, allowing users to understand the overall situation of the inspection task at any time;

[0066] Chart display: Data analysis results are displayed in chart form so that users can intuitively understand data trends and abnormal situations;

[0067] Images and videos: Supports real-time playback and playback of high-definition images and videos taken by drones, providing users with intuitive inspection site conditions.

[0068] It also includes real-time data updates: ensuring that the data collected by the drone can be updated on the interface in real time for users to analyze and make decisions;

[0069] Data export and import: Supports the export and import functions of inspection data, which is convenient for users to back up, share and further analyze data;

[0070] Autonomous path planning: The system can autonomously plan the flight path of the drone based on inspection targets and environmental conditions, and allow users to manually adjust and optimize it;

[0071] Dynamic task adjustment: During the inspection process, users are allowed to dynamically adjust the inspection task or the flight parameters of the drone, such as altitude, speed, and direction, based on real-time data and environmental changes;

[0072] User rights management: The system should set different user roles and rights, such as administrator, operator, etc., to ensure that only authorized users can access and operate key functions;

[0073] Data security: Encryption technology is used to protect the secure transmission and storage of inspection data to prevent data leakage or tampering.

[0074] Compared with the prior art, the present invention provides an automatic planning system for drone inspection tasks in a limited space, which has the following beneficial effects:

[0075] 1. The present invention, through the cooperation between multiple modules, the collection and analysis of the use environment data and the automatic planning system, can make the drone automatically take off, perform inspection tasks and land safely according to the preset tasks, without the need for manual real-time control, which greatly reduces the manpower demand and improves the efficiency and frequency of inspections.

[0076] 2. The automatic planning system of the present invention reduces the reliance on manual labor during the inspection process, especially in confined spaces or dangerous environments, thereby avoiding the safety risks faced by inspection personnel.

[0077] 3. The present invention, through the automatic planning system, the UAV can complete more inspection tasks in a shorter time, thereby improving the utilization rate of the UAV. BRIEF DESCRIPTION OF THE DRAWINGS

[0078] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0079] The following will be combined with the drawings in 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.

[0080] See also Figure 1 ,An automatic planning system for UAV inspection tasks in a limited space, characterized by: including a task planning and scheduling module, an environment modeling and perception module, a flight control module, a data acquisition and processing module, a communication and data transmission module, an intelligent analysis and decision-making module, and a user interface and interaction module;

[0081] Task planning and scheduling module: responsible for automatically planning the specific content, sequence and schedule of inspection tasks based on inspection objectives, space restrictions and drone performance;

[0082] Environmental modeling and perception module: Use 3D modeling technology to build a digital model of a limited space, including terrain, buildings, and obstacles;

[0083] Flight control module: adjusts the flight attitude and trajectory of the drone in real time according to mission planning and environmental perception information, and is responsible for controlling the drone's takeoff, flight, hovering, landing and other flight actions;

[0084] Data collection and processing module: controls the sensors and equipment carried by the drone to collect data and pre-processes the collected data;

[0085] Communication and data transmission module: responsible for the communication and data transmission between the UAV and the ground control center, and ensuring the real-time, integrity and security of the data;

[0086] Intelligent analysis and decision-making module: conducts in-depth analysis and mining of collected data, identifies potential problems and anomalies, and automatically adjusts inspection strategies or issues early warning signals based on the analysis results;

[0087] User interface and interaction module: Provides an intuitive and easy-to-use user interface to facilitate users to view the status, progress and results of inspection tasks, and supports users to plan tasks, set parameters and view data through the interface.

[0088] Specifically, Figure 1 As shown, the mission planning and scheduling module includes target positioning and environment analysis, route planning, mission parameter setting and task allocation, resource scheduling, and mission monitoring and adjustment, among which:

[0089] Target positioning and environmental analysis: Use airborne sensors to scan the inspection area, quickly locate the mission target, and analyze the surrounding environment characteristics, such as terrain and obstacle distribution;

[0090] Route planning: Based on the results of target positioning and environmental analysis, combined with the flight characteristics of the drone, advanced algorithms are used to plan one or more optimal routes for the drone;

[0091] Mission parameter setting: according to inspection requirements, set corresponding mission parameters for the drone to ensure the accuracy and completeness of inspection data;

[0092] Task allocation: According to the current status of the drone and the priority and difficulty of the task, the inspection task is reasonably allocated to the appropriate drone;

[0093] Resource scheduling: monitor the status and resource usage of drones in real time, and schedule resources as needed;

[0094] Task monitoring and adjustment: By real-time monitoring of the drone's flight status and task execution, the scheduling module can promptly detect and handle abnormal situations and adjust tasks as needed to ensure the smooth completion of inspection tasks;

[0095] According to the formula f(n) = g(n) + h(n), where g(n) represents the actual cost from the starting point to node n, and h(n) represents the estimated cost from node n to the end point;

[0096] And where g(n) = d × steps, where d is the constant cost of each step, and steps is the number of steps from the starting point to node n;

[0097] Where h(n) = [nx - gx] + [ny - gy], where (nx, ny) are the coordinates of node n and (gx, gy) are the coordinates of the end point;

[0098] Finally, the route is obtained according to f(h)=d×steps+[nx-gx]+[ny-gy].

[0099] Through the above technical solutions, the system is also highly efficient: through intelligent route planning and task scheduling, the drone can efficiently cover the inspection area, reducing unnecessary flight time and resource waste;

[0100] Safety: The system has automatic obstacle avoidance and environmental perception functions, which can ensure the safe flight of the drone in complex environments;

[0101] Flexibility: The system supports a variety of mission types and drone models to meet the needs of different inspection scenarios;

[0102] Intelligence: Using artificial intelligence and machine learning algorithms to analyze and process inspection data can automatically identify abnormal situations and issue early warnings, thereby improving the efficiency and accuracy of inspections.

[0103] Specifically, Figure 1 As shown, the environment modeling and perception module, wherein environment modeling is the basis for automatic planning of UAV inspection tasks, and through laser radar scanning and visual sensor fusion, as well as three-dimensional space modeling software, a three-dimensional environment model that can be used for UAV navigation and mission planning is finally generated;

[0104] The perception module is used by the drone to obtain real-time information about the surrounding environment and dynamically adjust the flight path and posture during inspection missions, including obstacle detection, visual perception analysis, and autonomous obstacle avoidance.

[0105] Through the above technical solutions, obstacle detection: by using millimeter wave radar and TOF ranging method, the distance between the drone and the obstacle is accurately measured by continuously sending light pulses to the target and receiving the returned light, and the relative position of the drone relative to the cable or other obstacles is measured in real time through the multi-rotor drone equipped with radar, and is transmitted to the flight control system as a feedback value to achieve high-precision distance measurement or obstacle avoidance;

[0106] Visual perception analysis: The drone will carry a visual perception information module. Using binocular vision for stereo matching is a key step in environmental modeling. When two cameras are shooting, the image information is wirelessly transmitted to the ground station. After the ground station receives the image data, it is measured through a high-precision measurement system.

[0107] Autonomous obstacle avoidance: Based on the results of the above obstacle detection and visual perception analysis, the drone can judge the complexity and potential risks of the surrounding environment in real time, and automatically adjust the flight path and posture to avoid obstacles, so as to ensure that the drone can maintain a stable flight state and mission execution efficiency while avoiding obstacles.

[0108] Specifically, Figure 1 As shown, the flight control module is a core component that ensures that the UAV can fly autonomously according to the preset path or mission plan, and adjust the flight status in real time to adapt to environmental changes, including autonomous flight control, real-time status monitoring, dynamic path planning, high-precision positioning and navigation;

[0109] Autonomous flight control: Automatically control the takeoff, flight and landing of the drone according to the preset route or mission plan, and use advanced flight control algorithms to ensure that the drone can fly accurately along the predetermined path;

[0110] Real-time status monitoring: monitors the flight status of the drone, including position, speed, and attitude. Once an abnormality or deviation from the predetermined path is found, the module will immediately take corrective measures;

[0111] Dynamic path planning: In a limited space, the flight path is dynamically adjusted based on real-time perception data to avoid obstacles or respond to other emergencies;

[0112] High-precision positioning and navigation: Combined with GPS and inertial measurement unit sensor data, the flight control module can achieve high-precision positioning and navigation, ensuring the precise flight of the drone in a limited space.

[0113] The above technical solution also includes a flight control algorithm: the core of the flight control module is that the flight control algorithm can calculate and output control instructions according to the dynamic characteristics and environmental constraints of the UAV to adjust the flight state of the UAV;

[0114] Sensor fusion: To improve flight accuracy and reliability, the flight control module will fuse data from multiple sensors, such as GPS, IMU, lidar, and visual sensors. These sensors provide multi-dimensional information such as the drone's position, speed, attitude, and surrounding environment.

[0115] Actuator: The flight control module adjusts the flight state of the drone by controlling the actuator, controls the rise and fall, forward and backward movement of the drone by changing the speed of the motor, and changes the flight direction of the drone by adjusting the angle of the servo.

[0116] Specifically, Figure 1As shown, the data acquisition and processing module is further divided into data acquisition and data processing, wherein data acquisition includes real-time monitoring of equipment or environment in a limited space by carrying various sensors, such as temperature sensors, vibration sensors, and current sensors;

[0117] Use high-definition cameras, infrared thermal imagers and other image acquisition devices to shoot inspection targets and obtain high-definition image data;

[0118] Data processing involves preliminary processing of the collected data, including deletion of useless data, data noise reduction, and data standardization, and then classification, clustering, and predictive analysis of massive data to mine valuable information. Cloud computing technology is used to provide convenient, efficient, and stable computing resources, and artificial intelligence algorithms are used to conduct in-depth analysis of the processed data, identify abnormal situations, and provide decision support.

[0119] Specifically, Figure 1 As shown, the communication and data transmission module is usually composed of a transmitter, a receiver and an antenna feed line, and includes two main parts: data transmission and image transmission;

[0120] The data transmission system is responsible for the uplink and downlink transmission of information such as the UAV's flight status and control instructions, ensuring that the UAV can perform inspection tasks according to the instructions of the ground control center;

[0121] The image transmission system is mainly used to transmit visible light video, infrared video and other image data collected by the drone in real time for real-time monitoring and analysis by ground control center personnel.

[0122] The above technical solution also includes good real-time performance: ensuring that the communication delay between the drone and the ground control center is as low as possible, so that problems encountered during the inspection process can be discovered and handled in a timely manner;

[0123] High reliability: In a limited space, the communication environment may be affected by various factors, such as obstacles and electromagnetic interference. The communication system needs to have high reliability to ensure stable operation in various environments.

[0124] Strong anti-interference ability: In view of the electromagnetic interference generated by high-voltage lines and high-voltage equipment, the communication system needs to have strong anti-interference ability to ensure the accuracy and integrity of data transmission.

[0125] Specifically, Figure 1 As shown, the communication and data transmission module also includes a data transmission method, and the commonly used data transmission methods include digital transmission module communication and GPRS data transmission. Among them, digital transmission module communication: the digital transmission radio uses an ultra-short wave wireless communication channel to realize remote transmission of data. In a space environment within line of sight and without obstructions, the digital transmission module can achieve a transmission distance of tens of kilometers;

[0126] GPRS data transmission: GPRS is a data transmission method based on mobile communication network, with wide coverage and fast transmission speed. In a limited space, if the mobile communication network coverage is good.

[0127] Through the above technical solution, in order to ensure the accuracy and reliability of data transmission, the automatic planning system of the UAV inspection task usually adopts a standard communication protocol for data transmission. In the UAV inspection task, each independent module can be connected through the CAN communication protocol to achieve fast and accurate data transmission;

[0128] When conducting drone inspections in confined spaces, special attention must be paid to the security of communications and data transmission, including data encryption and access control measures to prevent unauthorized access and data leakage. A comprehensive emergency response mechanism must also be established to deal with possible communication failures or data loss.

[0129] Specifically, Figure 1 As shown, the intelligent analysis and decision-making module can capture detailed images and videos of the inspection area through the high-definition camera it is equipped with. It is equipped with multiple sensors such as infrared and lidar. By using machine learning or deep learning algorithms, the system can automatically identify key equipment or structures in the inspection area. By comparing the image differences between the normal state and the current state, the system can detect potential anomalies or faults, and can analyze historical data and perform predictive maintenance.

[0130] Specifically, Figure 1 As shown, the intelligent analysis and decision-making module is responsible for processing and analyzing the data collected by the drone and making corresponding decisions based on it, including image recognition and analysis: using advanced image recognition algorithms to perform real-time analysis on high-definition images taken by the drone;

[0131] Data fusion and mining: Collect various other types of data, such as temperature, humidity, and vibration, and fuse them to obtain more comprehensive equipment status information;

[0132] Fault prediction and diagnosis: Based on the analysis of historical data and real-time data, predict possible equipment failures and perform preliminary diagnosis.

[0133] Through the above technical solution, the module can also plan and adjust tasks: according to the analysis results, the intelligent analysis and decision-making module can automatically generate or adjust the inspection task plan of the drone. When an abnormality is found in a certain area, the inspection frequency of the area can be automatically increased or the inspection route can be changed;

[0134] Abnormal handling suggestions: For detected abnormalities or potential problems, the module will provide corresponding handling suggestions. For minor surface defects, it is recommended to mark and arrange subsequent repairs. For serious faults, it is recommended to shut down immediately and start the emergency response mechanism.

[0135] Human-computer interaction interface: In order to facilitate operators to understand and implement decision recommendations, the intelligent analysis and decision-making module is usually also equipped with an intuitive human-computer interaction interface, which can display analysis results, decision recommendations, and the current status of the drone in real time.

[0136] Specifically, Figure 1 As shown, the user interface and interaction module provide users with an intuitive, easy-to-use and efficient interactive experience to support the planning, execution and monitoring of drone inspection tasks, including modular design: the interface layout adopts a modular design, dividing the main functions into different modules;

[0137] Map display: The main interface displays a map in a prominent position to intuitively display the drone's real-time location, inspection path, target area and other key information;

[0138] Status bar: displays the key status information and system status of the drone in real time, allowing users to understand the overall situation of the inspection task at any time;

[0139] Chart display: Data analysis results are displayed in chart form so that users can intuitively understand data trends and abnormal situations;

[0140] Images and videos: Supports real-time playback and playback of high-definition images and videos taken by drones, providing users with intuitive inspection site conditions.

[0141] The above technical solution also includes real-time data update: ensuring that the data collected by the drone can be updated to the interface in real time for users to analyze and make decisions;

[0142] Data export and import: Supports the export and import functions of inspection data, which is convenient for users to back up, share and further analyze data;

[0143] Autonomous path planning: The system can autonomously plan the flight path of the drone based on inspection targets and environmental conditions, and allow users to manually adjust and optimize it;

[0144] Dynamic task adjustment: During the inspection process, users are allowed to dynamically adjust the inspection task or the flight parameters of the drone, such as altitude, speed, and direction, based on real-time data and environmental changes;

[0145] User rights management: The system should set different user roles and rights, such as administrator, operator, etc., to ensure that only authorized users can access and operate key functions;

[0146] Data security: Encryption technology is used to protect the secure transmission and storage of inspection data to prevent data leakage or tampering.

[0147] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An automatic planning system for drone inspection tasks in limited space, characterized by: It includes mission planning and scheduling module, environment modeling and perception module, flight control module, data acquisition and processing module, communication and data transmission module, intelligent analysis and decision-making module, user interface and interaction module; Task planning and scheduling module: responsible for automatically planning the specific content, sequence and schedule of inspection tasks based on inspection objectives, space restrictions and drone performance; Environmental modeling and perception module: Use 3D modeling technology to build a digital model of a limited space, including terrain, buildings, and obstacles; Flight control module: adjusts the flight attitude and trajectory of the drone in real time according to mission planning and environmental perception information, and is responsible for controlling the drone's takeoff, flight, hovering, landing and other flight actions; Data collection and processing module: controls the sensors and equipment carried by the drone to collect data and pre-processes the collected data; Communication and data transmission module: responsible for the communication and data transmission between the UAV and the ground control center, and ensuring the real-time, integrity and security of the data; Intelligent analysis and decision-making module: conducts in-depth analysis and mining of collected data, identifies potential problems and anomalies, and automatically adjusts inspection strategies or issues early warning signals based on the analysis results; User interface and interaction module: Provides an intuitive and easy-to-use user interface to facilitate users to view the status, progress and results of inspection tasks, and supports users to plan tasks, set parameters and view data through the interface.

2. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The mission planning and scheduling module includes target positioning and environment analysis, route planning, mission parameter setting and task allocation, resource scheduling, and mission monitoring and adjustment, among which: Target positioning and environmental analysis: Use airborne sensors to scan the inspection area, quickly locate the mission target, and analyze the surrounding environment characteristics, such as terrain and obstacle distribution; Route planning: Based on the results of target positioning and environmental analysis, combined with the flight characteristics of the drone, advanced algorithms are used to plan one or more optimal routes for the drone; Mission parameter setting: according to inspection requirements, set corresponding mission parameters for the drone to ensure the accuracy and completeness of inspection data; Task allocation: According to the current status of the drone and the priority and difficulty of the task, the inspection task is reasonably allocated to the appropriate drone; Resource scheduling: monitor the status and resource usage of drones in real time, and schedule resources as needed; Task monitoring and adjustment: By real-time monitoring of the drone's flight status and task execution, the scheduling module can promptly detect and handle abnormal situations and adjust tasks as needed to ensure the smooth completion of inspection tasks; According to the formula f(n) = g(n) + h(n), where g(n) represents the actual cost from the starting point to node n, and h(n) represents the estimated cost from node n to the end point; And where g(n) = d × steps, where d is the constant cost of each step, and steps is the number of steps from the starting point to node n; Where h(n) = [nx - gx] + [ny - gy], where (nx, ny) are the coordinates of node n and (gx, gy) are the coordinates of the end point; Finally, the route is obtained according to f(h)=d×steps+[nx-gx]+[ny-gy].

3. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized in that: The environmental modeling and perception module, in which environmental modeling is the basis for automatic planning of UAV inspection tasks, and through laser radar scanning and visual sensor fusion, and in conjunction with three-dimensional space modeling software, a three-dimensional environmental model that can be used for UAV navigation and mission planning is finally generated; The perception module is used by the drone to obtain real-time information about the surrounding environment and dynamically adjust the flight path and posture during inspection missions, including obstacle detection, visual perception analysis, and autonomous obstacle avoidance.

4. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The flight control module is a core component that ensures that the drone can fly autonomously according to the preset path or mission plan, and adjust the flight status in real time to adapt to environmental changes. It includes autonomous flight control, real-time status monitoring, dynamic path planning, high-precision positioning and navigation; Autonomous flight control: Automatically control the takeoff, flight and landing of the drone according to the preset route or mission plan, and use advanced flight control algorithms to ensure that the drone can fly accurately along the predetermined path; Real-time status monitoring: monitors the flight status of the drone, including position, speed, and attitude. Once an abnormality or deviation from the predetermined path is found, the module will immediately take corrective measures; Dynamic path planning: In a limited space, the flight path is dynamically adjusted based on real-time perception data to avoid obstacles or respond to other emergencies; High-precision positioning and navigation: Combined with GPS and inertial measurement unit sensor data, the flight control module can achieve high-precision positioning and navigation, ensuring the precise flight of the drone in a limited space.

5. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The data acquisition and processing module is further divided into data acquisition and data processing, wherein data acquisition includes real-time monitoring of equipment or environment in a limited space by carrying various sensors, such as temperature sensors, vibration sensors, and current sensors; Use high-definition cameras, infrared thermal imagers and other image acquisition devices to shoot inspection targets and obtain high-definition image data; Data processing involves preliminary processing of the collected data, including deletion of useless data, data noise reduction, and data standardization, and then classification, clustering, and predictive analysis of massive data to mine valuable information. Cloud computing technology is used to provide convenient, efficient, and stable computing resources, and artificial intelligence algorithms are used to conduct in-depth analysis of the processed data, identify abnormal situations, and provide decision support.

6. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The communication and data transmission module is usually composed of a transmitter, a receiver and an antenna feed line, and includes two main parts: data transmission and image transmission; The data transmission system is responsible for the uplink and downlink transmission of information such as the UAV's flight status and control instructions, ensuring that the UAV can perform inspection tasks according to the instructions of the ground control center; The image transmission system is mainly used to transmit visible light video, infrared video and other image data collected by the drone in real time for real-time monitoring and analysis by ground control center personnel.

7. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The intelligent analysis and decision-making module is responsible for processing and analyzing the data collected by the drone and making corresponding decisions based on it, including image recognition and analysis: using advanced image recognition algorithms to perform real-time analysis of high-definition images taken by the drone; Data fusion and mining: Collect various other types of data, such as temperature, humidity, and vibration, and fuse them to obtain more comprehensive equipment status information; Fault prediction and diagnosis: Based on the analysis of historical data and real-time data, predict possible equipment failures and perform preliminary diagnosis.

8. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The communication and data transmission module also includes a data transmission method, and commonly used data transmission methods include data transmission module communication and GPRS data transmission, wherein: Digital transmission module communication: The digital transmission radio uses ultra-short wave wireless communication channels to achieve long-distance data transmission. In a line-of-sight and unobstructed space environment, the digital transmission module can achieve a transmission distance of tens of kilometers; GPRS data transmission: GPRS is a data transmission method based on mobile communication network, with wide coverage and fast transmission speed. In a limited space, if the mobile communication network coverage is good.

9. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The intelligent analysis and decision-making module can capture detailed images and videos of the inspection area through the high-definition camera it is equipped with. It is equipped with multiple sensors such as infrared and lidar. By using machine learning or deep learning algorithms, the system can automatically identify key equipment or structures in the inspection area. By comparing the image differences between the normal state and the current state, the system can detect potential anomalies or faults, and can analyze historical data and perform predictive maintenance.

10. The automatic planning system for UAV inspection tasks in a limited space according to claim 1 is characterized by: The user interface and interaction module provide users with an intuitive, easy-to-use and efficient interactive experience to support the planning, execution and monitoring of drone inspection tasks, including modular design: the interface layout adopts modular design, dividing the main functions into different modules; Map display: The main interface displays a map in a prominent position to intuitively display the drone’s real-time location, inspection path, target area and other key information; Status bar: displays the key status information and system status of the drone in real time, allowing users to understand the overall situation of the inspection task at any time; Chart display: Data analysis results are displayed in chart form so that users can intuitively understand data trends and abnormal situations; Images and videos: Supports real-time playback and playback of high-definition images and videos taken by drones, providing users with intuitive inspection site conditions.

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