WO2022170878A1 - 一种无人机测量输电线路影像距离的系统及方法 - Google Patents

一种无人机测量输电线路影像距离的系统及方法 Download PDF

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Publication number
WO2022170878A1
WO2022170878A1 PCT/CN2021/143374 CN2021143374W WO2022170878A1 WO 2022170878 A1 WO2022170878 A1 WO 2022170878A1 CN 2021143374 W CN2021143374 W CN 2021143374W WO 2022170878 A1 WO2022170878 A1 WO 2022170878A1
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Prior art keywords
dimensional
transmission line
distance
dimensional point
image data
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PCT/CN2021/143374
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English (en)
French (fr)
Inventor
戴永东
姚建光
毛锋
王茂飞
余万金
翁蓓蓓
鞠玲
蒋中军
卜鑫链
范炜豪
张泽
徐兴春
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国网江苏省电力有限公司泰州供电分公司
众芯汉创（北京）科技有限公司
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Application filed by 国网江苏省电力有限公司泰州供电分公司, 众芯汉创（北京）科技有限公司 filed Critical 国网江苏省电力有限公司泰州供电分公司
Priority to US17/765,849 priority Critical patent/US20240053477A1/en
Publication of WO2022170878A1 publication Critical patent/WO2022170878A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/176—Urban or other man-made structures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
    • G01C11/04—Interpretation of pictures
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/08—Systems determining position data of a target for measuring distance only
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
    • G01S17/06—Systems determining position data of a target
    • G01S17/42—Simultaneous measurement of distance and other co-ordinates
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/87—Combinations of systems using electromagnetic waves other than radio waves
    • G01S17/875—Combinations of systems using electromagnetic waves other than radio waves for determining attitude
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • G01S17/894—3D imaging with simultaneous measurement of time-of-flight at a 2D array of receiver pixels, e.g. time-of-flight cameras or flash lidar
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/933—Lidar systems specially adapted for specific applications for anti-collision purposes of aircraft or spacecraft
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/003—Transmission of data between radar, sonar or lidar systems and remote stations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes
    • G06V20/17—Terrestrial scenes taken from planes or by drones
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U10/00—Type of UAV
    • B64U10/10—Rotorcrafts
    • B64U10/13—Flying platforms
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B64—AIRCRAFT; AVIATION; COSMONAUTICS
    • B64U—UNMANNED AERIAL VEHICLES [UAV]; EQUIPMENT THEREFOR
    • B64U2101/00—UAVs specially adapted for particular uses or applications
    • B64U2101/30—UAVs specially adapted for particular uses or applications for imaging, photography or videography
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10028—Range image; Depth image; 3D point clouds
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/60—Type of objects
    • G06V20/64—Three-dimensional objects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Definitions

  • the present application relates to the technical field of unmanned aerial vehicles, and in particular, to a system and method for measuring the distance of an image of a transmission line by an unmanned aerial vehicle.
  • the traditional method is to measure the distance of the transmission line by using artificial ground laser ranging.
  • the inspector uses a handheld laser rangefinder to measure the distance between the target and the transmission line.
  • the basic principle of this method is to use the flight of light. Time, distance is calculated from the speed of light and the coefficient of refraction of the atmosphere.
  • the commonly used transmission line measurement tool is the laser scanner.
  • the laser scanner can realize the three-dimensional restoration of a large-scale transmission line corridor scene, and can realize the distance measurement between any observation targets within the scanning range. Its working principle is similar to that of a handheld laser rangefinder. It also uses the time of flight of light to obtain the spatial coordinate information of the target, and then calculates the Euclidean space distance between the targets.
  • the measurement method of traditional hand-held laser rangefinders is easily interfered and influenced by human and environmental factors. For example, in areas with more sunny days, the infrared rays contained in the strong sunlight will cause a large measurement error for the handheld laser rangefinder used outdoors; in rainy and snowy weather conditions, rain will also affect the reflection of the laser beam, resulting in The measurement equipment cannot work normally; at the same time, the inaccurate target positioning caused by humans will also bring errors to the measurement.
  • the transmission line measurement method based on laser scanner has high accuracy and little influence of human factors, but it is also affected by rain and snow weather, and the operation cost of this method is high and the amount of data is large.
  • the invention provides a system and method for measuring the image distance of a transmission line by an unmanned aerial vehicle, which can implement all-weather and all-day monitoring of the transmission line, and the obtained distance measurement value is more accurate.
  • a system for measuring the image distance of a transmission line by a drone comprising a plurality of power towers and a transmission line corridor between adjacent power towers, the system comprising a drone, a master console and a plurality of cameras ;
  • the camera is fixed on the power tower, and is used for collecting two-dimensional image data of the transmission line corridor;
  • the UAV includes a body, a lidar device, a rotor assembly, a power device, a flight control processor, a state detection device, and a wireless communication module;
  • the state detection device is used to obtain its own positioning information and to collect the distance information between the drone and the ground and send it to the flight control processor, and the flight control processor is used to generate a control signal according to the distance information and the positioning information.
  • the lidar device is used to collect the three-dimensional point cloud data of the transmission line, and the three-dimensional point cloud data is communicated through the wireless communication.
  • the module is sent to the master console;
  • the master console is used to receive the two-dimensional image data and the three-dimensional point cloud data, and establish a relationship between the two-dimensional image data and the three-dimensional point cloud data according to the inner orientation elements of the camera and the outer orientation elements of the two-dimensional image data in the three-dimensional space.
  • Mapping relationship the target object is identified according to the two-dimensional image data, the three-dimensional point coordinates of the target object are determined according to the mapping relationship, and the distance from the target object to the transmission line is calculated according to the three-dimensional point coordinates of the target object.
  • the state detection device includes a GPS positioning device and a laser ranging radar
  • the GPS positioning device is used to obtain the positioning information of the drone
  • the laser ranging radar is used to detect the height of the drone to the ground.
  • the width of the transmission line corridor is greater than or equal to 50 meters.
  • the flight control processor is also used to receive the ground control signal sent by the master console through the wireless communication module, and control the power unit to adjust the flight trajectory and flight height of the drone according to the ground control signal.
  • the priority of the ground control signal is higher than that of the control signal.
  • a method for measuring the image distance of a transmission line using the above system comprising the following steps:
  • the main console receives the two-dimensional image data and the three-dimensional point cloud data
  • mapping relationship between the two-dimensional image data and the three-dimensional point cloud data is established according to the internal orientation elements of the camera and the external orientation elements of the two-dimensional image data in the three-dimensional space, including:
  • the transformation relationship between the coordinates is established with the inner orientation element of the camera, the two-dimensional pixel coordinates of the feature in the background image, and the three-dimensional space coordinates of the feature in the three-dimensional point cloud data;
  • each pixel coordinate in the background image corresponds to the three-dimensional coordinate in the three-dimensional point cloud data, and the mapping relationship between the two-dimensional image data and the three-dimensional point cloud data is obtained.
  • d x and dy represent the physical size of each pixel on the horizontal axis x and vertical axis y of the two-dimensional image data, respectively, (u 0 , v 0 ) is the intersection of the optical axis of the camera and the two-dimensional image data plane.
  • Pixel coordinates, f represents the focal length of the camera, (u, v) are two-dimensional pixel coordinates, (X w , Y W , Z W ) are three-dimensional space coordinates; R represents the distance between the two-dimensional pixel coordinate system and the three-dimensional space coordinate system Rotation matrix, T represents the translation vector from the two-dimensional pixel coordinate system to the three-dimensional space coordinate system;
  • the inner orientation element of the camera includes the pixel coordinates of the intersection of the optical axis of the camera and the two-dimensional image data plane and the focal length of the camera.
  • determine the three-dimensional point coordinates of the target including:
  • the method further includes:
  • the target object after identifying the target object according to the two-dimensional image data, it also includes:
  • the spatial distance value is respectively increased on the Z axis to obtain the three-dimensional point coordinates of the two top corners of the box;
  • the Euclidean distances from the two vertex angles to the nearest three-dimensional point of the transmission line are calculated respectively, and the smaller distance value is used as the distance from the target to the transmission line.
  • the system and method for measuring the image distance of a transmission line by an unmanned aerial vehicle establishes a mapping relationship between two-dimensional image data and three-dimensional point cloud data, and through the mapping relationship, realizes that the target object in the two-dimensional image data is three-dimensional in three-dimensional space.
  • the point coordinates are determined to calculate the distance between the target and the transmission line. The calculation accuracy is high.
  • the camera can monitor the distance of the target in the entire transmission line corridor, and realize all-weather and all-day monitoring of the transmission line.
  • FIG. 1 is a schematic structural diagram of an embodiment of a transmission line corridor in the system for measuring the distance of a transmission line image by an unmanned aerial vehicle provided by the present invention.
  • FIG. 2 is a schematic structural diagram of an embodiment of a system for measuring the distance of an image of a transmission line provided by an unmanned aerial vehicle.
  • FIG. 3 is a flow chart of an embodiment of a method for measuring the distance of an image of a transmission line provided by an unmanned aerial vehicle.
  • FIG. 4 is a schematic structural diagram of an embodiment of an apparatus for measuring the distance of an image of a transmission line provided by a UAV.
  • a system for measuring the distance of an image of a transmission line by an unmanned aerial vehicle is provided, and the transmission line includes a plurality of power towers 1 and a transmission line corridor 2 between adjacent power towers.
  • the system includes an unmanned aerial vehicle 3, a master console 4 and a plurality of cameras 5;
  • the camera 5 is fixed on the power tower 1, and is used to collect two-dimensional image data of the transmission line corridor;
  • the drone 3 includes a body 31 , a lidar device 32 , a rotor assembly 33 , a power device 34 , a flight control processor 35 , a state detection device 36 and a wireless communication module 37 ;
  • the state detection device 36 is used to obtain its own positioning information and collect the distance information between the drone and the ground and send it to the flight control processor 35, and the flight control processor 35 is used to generate a control signal according to the distance information and the positioning information, and The power device 34 is controlled to adjust the flight trajectory and flight height of the UAV according to the control signal, and the lidar device 32 is used to collect the three-dimensional point cloud data of the transmission line, and the three-dimensional point cloud data is sent to the general controller through the wireless communication module 37 table 4;
  • the main console 4 is used to receive the two-dimensional image data and the three-dimensional point cloud data, and establish a mapping between the two-dimensional image data and the three-dimensional point cloud data according to the internal orientation elements of the camera and the external orientation elements of the two-dimensional image data in the three-dimensional space.
  • the target object is identified according to the two-dimensional image data, the three-dimensional point coordinates of the target object are determined according to the mapping relationship, and the distance from the target object to the transmission line is calculated according to the three-dimensional point coordinates of the target object.
  • the state detection device 36 includes a GPS positioning device and a laser ranging radar, the GPS positioning device is used to obtain the positioning information of the drone, and the laser ranging radar is used to detect the height of the drone to the ground.
  • the rotor assembly 33 includes at least one rotor
  • the power unit 34 includes motors equivalent to the number of rotors
  • the flight control processor 35 is used to control the rotational speed and direction of the relevant motors, thereby controlling the flying attitude of the drone and adjusting the drone. flight path and flight altitude.
  • the width of the transmission line corridor is greater than or equal to 50 meters.
  • the flight control processor 35 is also used to receive the ground control signal sent by the master console 4 through the wireless communication module 37, and control the power unit 34 to adjust the flight trajectory and flight height of the drone according to the ground control signal, so The ground control signal has a higher priority than the control signal.
  • the main console 4 sends a ground control signal through the wireless communication module 37, and after receiving the ground control signal, the flight control processor 35 controls the rotation speed and direction of the relevant motor in the power unit 34 according to the ground control signal, so that no one is unmanned.
  • the drone flies according to the preset flight trajectory, and the flight attitude can be adjusted according to the distance from the ground and the position information of the drone during the flight.
  • the system for measuring the image distance of a transmission line provided by an unmanned aerial vehicle in this embodiment collects the three-dimensional point cloud data of the transmission line corridor through the unmanned aerial vehicle, and then establishes a mapping relationship between the two-dimensional image data and the three-dimensional point cloud data. The determination of the three-dimensional point coordinates of the target in the two-dimensional image data in the three-dimensional space, so as to calculate the distance from the target to the transmission line. Transmission line monitoring.
  • this embodiment provides a method for measuring the image distance of a transmission line using the system described in Embodiment 1, including the following steps:
  • the main console receives the two-dimensional image data and the three-dimensional point cloud data
  • the main console receives the two-dimensional image data sent by the camera connected to it, receives the three-dimensional point cloud data collected by the wireless communication module of the drone, and then drives away after the drone collects the three-dimensional point cloud. Power line corridor.
  • mapping relationship between the two-dimensional image data and the three-dimensional point cloud data is established according to the inner orientation elements of the camera and the outer orientation elements of the two-dimensional image data in the three-dimensional space, including:
  • the selection of features must exist in both the two-dimensional image data returned by the camera and the three-dimensional point cloud data scanned by the UAV lidar, and the features have not changed in position and shape in the scene; the selected features Objects should be unique and evenly distributed in the entire scene; optional, at least 3 sets of features should be obtained. Understandably, in order to ensure the accuracy of the mapping relationship, as many features as possible should be selected evenly distributed in the scene thing.
  • d x and dy represent the physical size of each pixel on the horizontal axis x and vertical axis y of the two-dimensional image data, respectively, (u 0 , v 0 ) is the intersection of the optical axis of the camera and the two-dimensional image data plane.
  • Pixel coordinates, f represents the focal length of the camera, (u, v) are two-dimensional pixel coordinates, (X w , Y W , Z W ) are three-dimensional space coordinates; R represents the distance between the two-dimensional pixel coordinate system and the three-dimensional space coordinate system Rotation matrix, T represents the translation vector from the two-dimensional pixel coordinate system to the three-dimensional space coordinate system;
  • the inner orientation element of the camera includes the pixel coordinates of the intersection of the optical axis of the camera and the two-dimensional image data plane and the focal length of the camera.
  • the two-dimensional image data collected in real time by the camera can be used to calculate the three-dimensional coordinates of the target object, and then calculate the Euclidean distance between the target object and the transmission line.
  • the three-dimensional point coordinates of the target object are determined according to the mapping relationship, including:
  • the Euclidean distance between two pixels in the two-dimensional image data can be calculated: arbitrarily select two pixels, and according to the mapping relationship, find the coordinates of the three-dimensional point corresponding to the two pixels, and according to the two
  • the Euclidean space distance is calculated from the coordinate values of the three-dimensional point, and the distance between the two objects can be measured from the image.
  • the Euclidean distance calculation formula is as follows:
  • (X w1 , Y W1 , Z W1 ) and (X w2 , Y W2 , Z W2 ) are the coordinates of two three-dimensional points, respectively, and d is the Euclidean distance.
  • the method further includes:
  • the target object after identifying the target object according to the two-dimensional image data, it also includes:
  • the spatial distance value is respectively increased on the Z axis to obtain the three-dimensional point coordinates of the two top corners of the box;
  • the Euclidean distances from the two vertex angles to the nearest three-dimensional point of the transmission line are calculated respectively, and the smaller distance value is used as the distance from the target to the transmission line.
  • the method for measuring the distance of a transmission line image establishes a mapping relationship between the two-dimensional image data and the three-dimensional point cloud data, and through the mapping relationship, the determination of the three-dimensional point coordinates in the three-dimensional space of the target object in the two-dimensional image data is realized. , so as to calculate the distance from the target to the transmission line, and the calculation accuracy is high.
  • the camera can monitor the distance of the target in the entire transmission line corridor, and realize all-weather and all-day monitoring of the transmission line.
  • the present embodiment provides a device for measuring the distance of an image of a transmission line by a drone, including:
  • a receiving module 301 configured to receive the two-dimensional image data and the three-dimensional point cloud data
  • the relationship determination module 302 is configured to establish a mapping relationship between the two-dimensional image data and the three-dimensional point cloud data according to the inner orientation elements of the camera and the outer orientation elements of the two-dimensional image data in the three-dimensional space;
  • the coordinate determination module 303 is used to identify the target object according to the two-dimensional image data, and determine the three-dimensional point coordinates of the target object according to the mapping relationship;
  • the distance calculation module 304 is configured to calculate the distance from the target to the transmission line according to the three-dimensional point coordinates of the target.
  • the relationship determination module 302 establishes the mapping relationship between the two-dimensional image data and the three-dimensional point cloud data according to the internal orientation elements of the camera and the external orientation elements of the two-dimensional image data in the three-dimensional space, including:
  • the transformation relationship between the coordinates is established with the inner orientation element of the camera, the two-dimensional pixel coordinates of the feature in the background image, and the three-dimensional space coordinates of the feature in the three-dimensional point cloud data;
  • each pixel coordinate in the background image corresponds to the three-dimensional coordinate in the three-dimensional point cloud data, and the mapping relationship between the two-dimensional image data and the three-dimensional point cloud data is obtained.
  • the coordinate determination module 303 determines the three-dimensional point coordinates of the target object according to the mapping relationship, including:
  • the distance calculation module 304 is further configured to search the three-dimensional point coordinates of the power transmission line closest to the target from the three-dimensional point cloud data of the power transmission line, according to the three-dimensional point coordinates of the target object and the three-dimensional point coordinates of the nearest power transmission line. , calculate the Euclidean distance from the target to the nearest transmission line.
  • the Euclidean distance calculation formula is shown in formula (2).
  • the distance calculation module 304 is also used to:
  • the spatial distance value is respectively increased on the Z-axis to obtain the three-dimensional point coordinates of the two top corners of the box;
  • the Euclidean distances from the two vertex angles to the nearest three-dimensional point of the transmission line are calculated respectively, and the smaller distance value is used as the distance from the target to the transmission line.
  • the apparatus for measuring the image distance of a power transmission line by an unmanned aerial vehicle includes: a processor, wherein the processor is configured to execute the above program modules stored in the memory, including: a receiving module 301 , a relationship determining module 302 , and a coordinate determining module 303 and distance calculation module 304.
  • the device for measuring the image distance of a transmission line establishes a mapping relationship between the two-dimensional image data and the three-dimensional point cloud data, and through the mapping relationship, the determination of the three-dimensional point coordinates in the three-dimensional space of the target object in the two-dimensional image data is realized. , so as to calculate the distance from the target to the transmission line, and the calculation accuracy is high.
  • the camera can monitor the distance of the target in the entire transmission line corridor, and realize all-weather and all-day monitoring of the transmission line.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Remote Sensing (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Electromagnetism (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

一种无人机测量输电线路影像距离的系统及方法，系统包括无人机（3）、总控台（4）以及多个摄像头（5），摄像头（5）固定于电力杆塔（1）上，用于采集输电线路走廊的二维影像数据，无人机（3）包括机体（31）、激光雷达装置（32）、旋翼组件（33）、动力装置（34）、飞控处理器（35）、状态检测装置（36）以及无线通信模块（37），激光雷达装置（32）用于采集输电线路的三维点云数据，总控台（4）用于接收二维影像数据以及三维点云数据，建立二维影像数据与三维点云数据的映射关系；根据二维影像数据识别目标物，根据映射关系，确定目标物的三维点坐标，根据目标物的三维点坐标计算目标物到输电线路的距离；通过摄像头（5）即可监控整个输电线路走廊的目标物距离情况，实现全天候、全天时的输电线路监测。

Description

一种无人机测量输电线路影像距离的系统及方法 技术领域
本申请涉及无人机技术领域，尤其涉及一种无人机测量输电线路影像距离的系统及方法。
背景技术
传统方法对输电线路的测距是采用人工地面激光测距的方式，检测人员利用手持式激光测距仪对目标物与输电线路之间的距离进行测量，该方式的基本原理是利用光的飞行时间，通过光速和大气折射系数计算出距离。随着激光雷达技术的发展，目前常用的输电线路测量工具为激光扫描仪，通过激光扫描仪可以实现大范围的输电线路走廊场景三维恢复，可实现扫描范围内任意观测目标间的距离量测，其工作原理与手持式激光测距仪相似，同样借助光的飞行时间来获取目标的空间坐标信息，进而计算出目标间的欧式空间距离。
传统手持式激光测距仪的测量方式易受到人为以及环境因素的干扰和影响。例如晴天较多地区，强烈的阳光里所含有的红外射线会使户外使用的手持式激光测距仪产生较大的测量误差；在雨雪天气条件下，雨水也会影响激光束的反射，导致测量设备无法正常工作；同时，人为导致的目标定位不准确也会给测量带来误差。基于激光扫描仪的输电线路测量方式精度高，人为因素影响小，但同样受雨雪天气的影响，且该方式的作业成本较高，数据量较大。对于以上两种测量方式，还存在一个相同的不足之处，即由于人力和实际野外作业成本的原因，无法实施全天候、全天时的输电线路监测，当实际作业场景与原始数据获取场景保持一致时，以上两种方式获取的原始数据具有一定的参考价值和有效性，但当实际测量场景与数据采集时的场景存在差异时，比如场景中出现新的目标物，则难以基于原始数据来实现新目标物与输电线路间的距离量测。
发明内容
本发明提供了一种无人机测量输电线路影像距离的系统及方法，能够实施全天候、全天时的输电线路监测，获得的距离测量值更加准确。
一种无人机测量输电线路影像距离的系统，所述输电线路包括多个电力杆塔以及位于相邻电力杆塔之间的输电线路走廊，所述系统包括无人机、总控台以及多个摄像头；
所述摄像头固定于所述电力杆塔上，用于采集所述输电线路走廊的二维影像数据；
所述无人机包括机体、激光雷达装置、旋翼组件、动力装置、飞控处理器、状态检测装置以及无线通信模块；
所述状态检测装置用于获取自身的定位信息和采集无人机与地面的距离信息并发送至所述飞控处理器，所述飞控处理器用于根据所述距离信息和定位信息生成控制信号，并根据所述控制信号控制所述动力装置调整无人机的飞行轨迹和飞行高度，所述激光雷达装置用于采集输电线路的三维点云数据，所述三维点云数据通过所述无线通信模块发送至所述总控台；
所述总控台用于接收所述二维影像数据以及三维点云数据，根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系；根据所述二维影像数据识别目标物，根据所述映射关系，确定目标物的三维点坐标，根据目标物的三维点坐标计算目标物到输电线路的距离。
进一步地，所述状态检测装置包括GPS定位装置和激光测距雷达，所述GPS定位装置用于获取无人机的定位信息，所述激光测距雷达用于检测无人机到地面的高度。
进一步地，所述输电线路走廊宽度大于或等于50米。
进一步地，所述飞控处理器还用于通过所述无线通信模块接收总控台发送的地面控制信号，并根据所述地面控制信号控制所述动力装 置调整无人机的飞行轨迹和飞行高度，所述地面控制信号的优先级高于所述控制信号。
一种采用上述系统的测量输电线路影像距离的方法，包括以下步骤：
总控台接收所述二维影像数据以及三维点云数据；
根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系；
根据所述二维影像数据识别目标物，根据所述映射关系，确定目标物的三维点坐标；
根据目标物的三维点坐标计算目标物到输电线路的距离。
进一步地，根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系，包括：
从所述二维影像数据中选择第一帧画面作为背景图像；
从所述背景图像中和所述三维点云数据中选取特征物；
以摄像头的内方位元素、所述特征物在所述背景图像中的二维像素坐标以及特征物在三维点云数据中的三维空间坐标，建立坐标间的变换关系；
计算所述变换关系中的旋转矩阵和平移向量；
根据所述变换关系，计算所述背景图像中每一像素坐标对应于所述三维点云数据中的三维坐标，获得二维影像数据与三维点云数据的映射关系。
进一步地，所述变换关系为：
Figure PCTCN2021143374-appb-000001
式中，d x与d y分别表示每个像素在二维影像数据的横轴x和纵轴y上的物理尺寸，(u 0,v 0)为摄像头光轴与二维影像数据平面的交点像 素坐标，f表示摄像头的焦距，(u,v)为二维像素坐标，(X w,Y W,Z W)为三维空间坐标；R表示二维像素坐标系与三维空间坐标系之间的旋转矩阵，T表示二维像素坐标系到三维空间坐标系的平移向量；
所述摄像头的内方位元素包括摄像头光轴与二维影像数据平面的交点像素坐标以及摄像头的焦距。
进一步地，根据所述映射关系，确定目标物的三维点坐标，包括：
选取所述目标物的任意一个像素，根据所述映射关系，查找所述像素对应的三维点坐标。
进一步地，根据所述映射关系，确定目标物的三维点坐标之后，还包括：
从输电线路的三维点云数据中搜索与所述目标物最近的输电线路的三维点坐标，根据目标物的三维点坐标和最近的输电线路的三维点坐标，计算所述目标物到最近输电线路的欧式距离。
进一步地，根据所述二维影像数据识别目标物之后，还包括：
框选所述目标物，并得到方框任意两个斜对角的像素坐标值；
根据两个斜对角的像素坐标值计算出方框底端另一个角的像素坐标值，并根据所述映射关系获得方框底端两个底角对应的三维点坐标，并依此计算两个底角的欧式距离；
将两个底角的欧式距离除以两个底角的像素距离，获得方框每个像素对应的空间大小，计算方框顶角到同侧底角的空间距离值；
在两个底角三维点坐标的基础上，分别在Z轴上增加所述空间距离值，以得到方框两个顶角的三维点坐标；
根据两个顶角的三维点坐标，分别计算两个顶角到最近的输电线路的三维点的欧式距离，并以其中较小的一个距离值作为所述目标物到输电线路的距离。
本发明提供的无人机测量输电线路影像距离的系统及方法，建立二维影像数据与三维点云数据的映射关系，通过该映射关系，实现二维影像数据中的目标物在三维空间中三维点坐标的确定，从而计算目标物到输电线路的距离，计算的准确性高，通过摄像头即可监控整个 输电线路走廊的目标物距离情况，实现全天候、全天时的输电线路监测。
附图说明
图1为本发明提供的无人机测量输电线路影像距离的系统中的输电线路走廊一种实施例的结构示意图。
图2为本发明提供的无人机测量输电线路影像距离的系统一种实施例的结构示意图。
图3为本发明提供的无人机测量输电线路影像距离的方法一种实施例的流程图。
图4为本发明提供的无人机测量输电线路影像距离的装置一种实施例的结构示意图。
具体实施方式
为了更好的理解上述技术方案，下面将结合说明书附图以及具体的实施方式对上述技术方案做详细的说明。
实施例一
参考图1和图2，在一些实施例中，提供一种无人机测量输电线路影像距离的系统，所述输电线路包括多个电力杆塔1以及位于相邻电力杆塔之间的输电线路走廊2，所述系统包括无人机3、总控台4以及多个摄像头5；
摄像头5固定于电力杆塔1上，用于采集输电线路走廊的二维影像数据；
无人机3包括机体31、激光雷达装置32、旋翼组件33、动力装置34、飞控处理器35、状态检测装置36以及无线通信模块37；
状态检测装置36用于获取自身的定位信息和采集无人机与地面的距离信息并发送至飞控处理器35，飞控处理器35用于根据所述距离信息和定位信息生成控制信号，并根据所述控制信号控制动力装置34调整无人机的飞行轨迹和飞行高度，激光雷达装置32用于采集输 电线路的三维点云数据，所述三维点云数据通过无线通信模块37发送至总控台4；
总控台4用于接收所述二维影像数据以及三维点云数据，根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系；根据所述二维影像数据识别目标物，根据所述映射关系，确定目标物的三维点坐标，根据目标物的三维点坐标计算目标物到输电线路的距离。
进一步地，状态检测装置36包括GPS定位装置和激光测距雷达，GPS定位装置用于获取无人机的定位信息，激光测距雷达用于检测无人机到地面的高度。
进一步地，旋翼组件33包括至少一个旋翼，动力装置34包括与旋翼数量相当的电机，飞控处理器35用于控制相关电机的转速和方向，从而控制无人机的飞行姿态，调整无人机的飞行轨迹和飞行高度。
进一步地，所述输电线路走廊宽度大于或等于50米。
进一步地，飞控处理器35还用于通过无线通信模块37接收总控台4发送的地面控制信号，并根据所述地面控制信号控制动力装置34调整无人机的飞行轨迹和飞行高度，所述地面控制信号的优先级高于所述控制信号。
具体地，总控台4通过无线通信模块37发送地面控制信号，飞控处理器35接收到地面控制信号后，根据该地面控制信号，控制动力装置34中相关电机的转速和方向，使得无人机按照预设的飞行轨迹飞行，飞行过程中还可根据与地面的距离和无人机的位置信息调整其飞行姿态。
本实施例提供的无人机测量输电线路影像距离的系统，通过无人机采集输电线路走廊三维点云数据，进而建立二维影像数据与三维点云数据的映射关系，通过该映射关系，实现二维影像数据中的目标物在三维空间中三维点坐标的确定，从而计算目标物到输电线路的距离，通过摄像头即可监控整个输电线路走廊的目标物距离情况，实现全天候、全天时的输电线路监测。
实施例二
参考图3，本实施例提供一种采用实施例一所述系统的测量输电线路影像距离的方法，包括以下步骤：
S1、总控台接收所述二维影像数据以及三维点云数据；
S2、根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系；
S3、根据所述二维影像数据识别目标物，根据所述映射关系，确定目标物的三维点坐标；
S4、根据目标物的三维点坐标计算目标物到输电线路的距离。
具体地，S1中，总控台接收与之连接的摄像头发送的二维影像数据，通过无人机的无线通信模块接收其采集的三维点云数据，无人机采集该三维点云之后驶离输电线路走廊。
S2中，根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系，包括：
S21、从所述二维影像数据中选择第一帧画面作为背景图像；
S22、从所述背景图像中和所述三维点云数据中选取特征物；
具体地，特征物的选取，须同时存在于摄像头所返回二维影像数据以及无人机激光雷达扫描的三维点云数据中，且特征物在场景中未发生位置及形态的变化；选取的特征物应保证独特性，且均匀分布于整个场景中；可选的，至少获取3组特征物，可以理解的，为了保证映射关系的准确性，应尽可能多的选取均匀分布在场景中的特征物。
S23、以摄像头的内方位元素、所述特征物在所述背景图像中的二维像素坐标以及特征物在三维点云数据中的三维空间坐标，建立坐标间的变换关系；
所述变换关系为：
Figure PCTCN2021143374-appb-000002
式中，d x与d y分别表示每个像素在二维影像数据的横轴x和纵轴y上的物理尺寸，(u 0,v 0)为摄像头光轴与二维影像数据平面的交点像素坐标，f表示摄像头的焦距，(u,v)为二维像素坐标，(X w,Y W,Z W)为三维空间坐标；R表示二维像素坐标系与三维空间坐标系之间的旋转矩阵，T表示二维像素坐标系到三维空间坐标系的平移向量；
所述摄像头的内方位元素包括摄像头光轴与二维影像数据平面的交点像素坐标以及摄像头的焦距。
S24、计算所述变换关系中的旋转矩阵和平移向量；
S25、根据所述变换关系，计算所述背景图像中每一像素坐标对应于所述三维点云数据中的三维坐标，获得二维影像数据与三维点云数据的映射关系。
至此，获得二维影像数据与三维点云数据的映射关系之后，通过摄像头实时采集的二维影像数据，即可实现目标物三维坐标的计算，进而计算目标物与输电线路的欧式距离。
进一步地，S3中，根据所述映射关系，确定目标物的三维点坐标，包括：
选取所述目标物的任意一个像素，根据所述映射关系，查找所述像素对应的三维点坐标。
在一些实施例中，可以计算二维影像数据中两个像素点之间的欧式距离：任意选取两个像素点，根据所述映射关系，查找这两个像素点对应的三维点坐标，根据两个三维点坐标值计算欧式空间距离，即可实现从影像上测量两个目标间的距离。
欧式距离计算公式如下所示：
Figure PCTCN2021143374-appb-000003
其中，(X w1,Y W1,Z W1)和(X w2,Y W2,Z W2)分别为两个三维点坐标，d为欧式距离。
在一些实施例中，根据所述映射关系，确定目标物的三维点坐标之后，还包括：
从输电线路的三维点云数据中搜索与所述目标物最近的输电线路的三维点坐标，根据目标物的三维点坐标和最近的输电线路的三维点坐标，计算所述目标物到最近输电线路的欧式距离。
进一步地，根据所述二维影像数据识别目标物之后，还包括：
框选所述目标物，并得到方框任意两个斜对角的像素坐标值；
根据两个斜对角的像素坐标值计算出方框底端另一个角的像素坐标值，并根据所述映射关系获得方框底端两个底角对应的三维点坐标，并依此计算两个底角的欧式距离；
将两个底角的欧式距离除以两个底角的像素距离，获得方框每个像素对应的空间大小，计算方框顶角到同侧底角的空间距离值；
在两个底角三维点坐标的基础上，分别在Z轴上增加所述空间距离值，以得到方框两个顶角的三维点坐标；
根据两个顶角的三维点坐标，分别计算两个顶角到最近的输电线路的三维点的欧式距离，并以其中较小的一个距离值作为所述目标物到输电线路的距离。
本实施例提供的测量输电线路影像距离的方法，建立二维影像数据与三维点云数据的映射关系，通过该映射关系，实现二维影像数据中的目标物在三维空间中三维点坐标的确定，从而计算目标物到输电线路的距离，计算的准确性高，通过摄像头即可监控整个输电线路走廊的目标物距离情况，实现全天候、全天时的输电线路监测。
实施例三
参考图4，本实施例提供一种无人机测量输电线路影像距离的装置，包括：
接收模块301，用于接收所述二维影像数据以及三维点云数据；
关系确定模块302，用于根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系；
坐标确定模块303，用于根据所述二维影像数据识别目标物，根 据所述映射关系，确定目标物的三维点坐标；
距离计算模块304，用于根据目标物的三维点坐标计算目标物到输电线路的距离。
其中，关系确定模块302根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系，包括：
从所述二维影像数据中选择第一帧画面作为背景图像；
从所述背景图像中和所述三维点云数据中选取特征物；
以摄像头的内方位元素、所述特征物在所述背景图像中的二维像素坐标以及特征物在三维点云数据中的三维空间坐标，建立坐标间的变换关系；
计算所述变换关系中的旋转矩阵和平移向量；
根据所述变换关系，计算所述背景图像中每一像素坐标对应于所述三维点云数据中的三维坐标，获得二维影像数据与三维点云数据的映射关系。
其中，变换关系如式(1)所示。
坐标确定模块303根据所述映射关系，确定目标物的三维点坐标，包括：
选取所述目标物的任意一个像素，根据所述映射关系，查找所述像素对应的三维点坐标。
进一步地，距离计算模块304还用于从输电线路的三维点云数据中搜索与所述目标物最近的输电线路的三维点坐标，根据目标物的三维点坐标和最近的输电线路的三维点坐标，计算所述目标物到最近输电线路的欧式距离。
欧式距离计算公式如式(2)所示。
距离计算模块304还用于：
框选所述目标物，并得到方框任意两个斜对角的像素坐标值；
根据两个斜对角的像素坐标值计算出方框底端另一个角的像素坐标值，并根据所述映射关系获得方框底端两个底角对应的三维点坐 标，并依此计算两个底角的欧式距离；
将两个底角的欧式距离除以两个底角的像素距离，获得方框每个像素对应的空间大小，计算方框顶角到同侧底角的空间距离值；
在两个底角三维坐标的基础上，分别在Z轴上增加所述空间距离值，以得到方框两个顶角的三维点坐标；
根据两个顶角的三维点坐标，分别计算两个顶角到最近的输电线路的三维点的欧式距离，并以其中较小的一个距离值作为所述目标物到输电线路的距离。
在另一个实施示例中，无人机测量输电线路影像距离的装置包括：处理器，其中所述处理器用于执行存在存储器的上述程序模块，包括：接收模块301、关系确定模块302、坐标确定模块303和距离计算模块304。
本实施例提供的测量输电线路影像距离的装置，建立二维影像数据与三维点云数据的映射关系，通过该映射关系，实现二维影像数据中的目标物在三维空间中三维点坐标的确定，从而计算目标物到输电线路的距离，计算的准确性高，通过摄像头即可监控整个输电线路走廊的目标物距离情况，实现全天候、全天时的输电线路监测。
尽管已描述了本发明的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例作出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明范围的所有变更和修改。显然，本领域的技术人员可以对本发明进行各种改动和变型而不脱离本发明的精神和范围。这样，倘若本发明的这些修改和变型属于本发明权利要求及其等同技术的范围之内，则本发明也意图包含这些改动和变型在内。

Claims (9)

  1. 一种无人机测量输电线路影像距离的系统，所述输电线路包括多个电力杆塔以及位于相邻电力杆塔之间的输电线路走廊，其特征在于，所述系统包括无人机、总控台以及多个摄像头；
    所述摄像头固定于所述电力杆塔上，用于采集所述输电线路走廊的二维影像数据；
    所述无人机包括机体、激光雷达装置、旋翼组件、动力装置、飞控处理器、状态检测装置以及无线通信模块；
    所述状态检测装置用于获取自身的定位信息和采集无人机与地面的距离信息并发送至所述飞控处理器，所述飞控处理器用于根据所述距离信息和定位信息生成控制信号，并根据所述控制信号控制所述动力装置调整无人机的飞行轨迹和飞行高度，所述激光雷达装置用于采集输电线路的三维点云数据，所述三维点云数据通过所述无线通信模块发送至所述总控台；
    所述总控台用于接收所述二维影像数据以及三维点云数据，根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系；根据所述二维影像数据识别目标物，根据所述映射关系，确定目标物的三维点坐标，根据目标物的三维点坐标计算目标物到输电线路的距离；
    其中，根据所述二维影像数据识别目标物之后，还包括：
    框选所述目标物，并得到方框任意两个斜对角的像素坐标值；
    根据两个斜对角的像素坐标值计算出方框底端另一个角的像素坐标值，并根据所述映射关系获得方框底端两个底角对应的三维点坐标，并依此计算两个底角的欧式距离；
    将两个底角的欧式距离除以两个底角的像素距离，获得方框每个像素对应的空间大小，计算方框顶角到同侧底角的空间距离值；
    在两个底角三维点坐标的基础上，分别在Z轴上增加所述空间距离值，以得到方框两个顶角的三维点坐标；
    根据两个顶角的三维点坐标，分别计算两个顶角到最近的输电线 路的三维点的欧式距离，并以其中较小的一个距离值作为所述目标物到输电线路的距离。
  2. 根据权利要求1所述的无人机测量输电线路影像距离的系统，其特征在于，所述状态检测装置包括GPS定位装置和激光测距雷达，所述GPS定位装置用于获取无人机的定位信息，所述激光测距雷达用于检测无人机到地面的高度。
  3. 根据权利要求1所述的无人机测量输电线路影像距离的系统，其特征在于，所述输电线路走廊宽度大于或等于50米。
  4. 根据权利要求1所述的无人机测量输电线路影像距离的系统，其特征在于，所述飞控处理器还用于通过所述无线通信模块接收总控台发送的地面控制信号，并根据所述地面控制信号控制所述动力装置调整无人机的飞行轨迹和飞行高度，所述地面控制信号的优先级高于所述控制信号。
  5. 一种测量输电线路影像距离的方法，其特征在于，应用于如权利要求1至4任意一项所述的系统；
    所述方法包括以下步骤：
    总控台接收所述二维影像数据以及三维点云数据；
    根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系；
    根据所述二维影像数据识别目标物，根据所述映射关系，确定目标物的三维点坐标；
    根据目标物的三维点坐标计算目标物到输电线路的距离；
    根据所述二维影像数据识别目标物之后，还包括：
    框选所述目标物，并得到方框任意两个斜对角的像素坐标值；
    根据两个斜对角的像素坐标值计算出方框底端另一个角的像素坐标值，并根据所述映射关系获得方框底端两个底角对应的三维点坐标，并依此计算两个底角的欧式距离；
    将两个底角的欧式距离除以两个底角的像素距离，获得方框每个像素对应的空间大小，计算方框顶角到同侧底角的空间距离值；
    在两个底角三维点坐标的基础上，分别在Z轴上增加所述空间距离值，以得到方框两个顶角的三维点坐标；
    根据两个顶角的三维点坐标，分别计算两个顶角到最近的输电线路的三维点的欧式距离，并以其中较小的一个距离值作为所述目标物到输电线路的距离。
  6. 根据权利要求5所述的测量输电线路影像距离的方法，其特征在于，根据摄像头的内方位元素以及二维影像数据在三维空间中的外方位元素建立二维影像数据与三维点云数据的映射关系，包括：
    从所述二维影像数据中选择第一帧画面作为背景图像；
    从所述背景图像中和所述三维点云数据中选取特征物；
    以摄像头的内方位元素、所述特征物在所述背景图像中的二维像素坐标以及特征物在三维点云数据中的三维空间坐标，建立坐标间的变换关系；
    计算所述变换关系中的旋转矩阵和平移向量；
    根据所述变换关系，计算所述背景图像中每一像素坐标对应于所述三维点云数据中的三维坐标，获得二维影像数据与三维点云数据的映射关系。
  7. 根据权利要求6所述的测量输电线路影像距离的方法，其特征在于，所述变换关系为：
    Figure PCTCN2021143374-appb-100001
    式中，d x与d y分别表示每个像素在二维影像数据的横轴x和纵轴y上的物理尺寸，(u 0,v 0)为摄像头光轴与二维影像数据平面的交点像素坐标，f表示摄像头的焦距，(u,v)为二维像素坐标，(X W,Y W,Z W)为三维空间坐标；R表示二维像素坐标系与三维空间坐标系之间的旋转矩阵，T表示二维像素坐标系到三维空间坐标系的平移向量；
    所述摄像头的内方位元素包括摄像头光轴与二维影像数据平面 的交点像素坐标以及摄像头的焦距。
  8. 根据权利要求5所述的测量输电线路影像距离的方法，其特征在于，根据所述映射关系，确定目标物的三维点坐标，包括：
    选取所述目标物的任意一个像素，根据所述映射关系，查找所述像素对应的三维点坐标。
  9. 根据权利要求8所述的测量输电线路影像距离的方法，其特征在于，根据所述映射关系，确定目标物的三维点坐标之后，还包括：
    从输电线路的三维点云数据中搜索与所述目标物最近的输电线路的三维点坐标，根据目标物的三维点坐标和最近的输电线路的三维点坐标，计算所述目标物到最近输电线路的欧式距离。
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