CN109459437A - Multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning - Google Patents
Multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning Download PDFInfo
- Publication number
- CN109459437A CN109459437A CN201811318451.4A CN201811318451A CN109459437A CN 109459437 A CN109459437 A CN 109459437A CN 201811318451 A CN201811318451 A CN 201811318451A CN 109459437 A CN109459437 A CN 109459437A
- Authority
- CN
- China
- Prior art keywords
- aerial vehicle
- unmanned aerial
- rotor unmanned
- transmission tower
- tower
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000005540 biological transmission Effects 0.000 title claims abstract description 32
- 230000007547 defect Effects 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 title claims abstract description 16
- 238000007689 inspection Methods 0.000 claims abstract description 25
- 238000005507 spraying Methods 0.000 claims description 5
- 230000002708 enhancing effect Effects 0.000 claims description 4
- 229910000831 Steel Inorganic materials 0.000 claims description 3
- 239000010959 steel Substances 0.000 claims description 3
- 230000005945 translocation Effects 0.000 claims description 3
- 230000000007 visual effect Effects 0.000 claims description 3
- 230000005611 electricity Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000012937 correction Methods 0.000 description 3
- 238000012423 maintenance Methods 0.000 description 2
- 238000012512 characterization method Methods 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000003379 elimination reaction Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008092 positive effect Effects 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/84—Systems specially adapted for particular applications
- G01N21/88—Investigating the presence of flaws or contamination
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Automation & Control Theory (AREA)
- Health & Medical Sciences (AREA)
- Aviation & Aerospace Engineering (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
A kind of multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning includes the following steps: 1. to make an inspection tour that anchor point is sprayed at the tower body of region in transmission tower；2. demarcating control point in earth's surface stability region and measuring control point coordinates；3. setting up ground at control point enhances positioning reference station；4. configuration multi-rotor unmanned aerial vehicle hovering three-dimensional coordinate and lens direction simultaneously start；5. unmanned plane hovers in fixed position and calibrates shooting direction by anchor point, N photos of shooting are simultaneously numbered；6. inspection work is carried out, 3~5 operation of repetition carries out multiple image of clapping and obtains；7. the N of multiple take photos are corrected with standard photographs by anchor point respectively；8. traversing the pixel of corresponding photo-overlap phase width part using image recognition program；9. pixel difference is demarcated beyond the region of threshold value；10. whether judge calibration part is shaft tower defect or defect early warning.The present invention can shift to an earlier date discovering device defect, promote fining, the standardization level of inspection work.
Description
Technical field
The invention belongs to electric device maintenance technical fields, more particularly to the transmission tower based on unmanned plane and image recognition
Inspection field.
Background technique
Inspection to transmission tower is the important component of the daily maintenance work of transmission line of electricity, in recent years, more rotors without
It is man-machine that the important means that the high advantage of fineness has become transmission line of electricity fining inspection is maked an inspection tour with it.But it still relies primarily at present
Personnel are manually operated unmanned plane and carry out inspection, are affected, are deposited by factors such as personnel's operating experience, level of skill, environmental catastrophes
The problems such as routing inspection efficiency is low, stability is poor, simultaneously because the differences such as polling path, camera site, the shadow for causing inspection to shoot
As differing greatly.Although existing unmanned plane device has the function of fixed point flight, shooting at present, it is limited by hovering precision, shadow
The shooting angle and quality of picture cannot be guaranteed, and can not obtain the consistent image of phase panel height degree for automatic processing.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of more rotors based on high accuracy positioning nobody
Machine transmission tower defect identification method, this method enhances positioning reference station using ground and target stem tower beacon note anchor point greatly mentions
High the hovering precision of multi-rotor unmanned aerial vehicle and the map sheet precision of shooting image, ensure that the height of multiple bat image is consistent.It utilizes
Map sheet anchor point accurately corrects bat image again and makes the accuracy for automating defect recognition that can realize stable promotion, fundamentally mentions
Transmission tower unmanned plane routing inspection efficiency, benefit and quality are risen, transmission of electricity fortune inspection personnel labor intensity is mitigated.
As above design, the present invention solve its technical problem and adopt the following technical solutions to achieve: one kind is based on high-precision
The multi-rotor unmanned aerial vehicle transmission tower defect identification method of positioning, characterized by the following steps:
1. being maked an inspection tour in transmission tower and spraying anchor point at the tower body of region；
2. demarcating control point in earth's surface stability region and measuring control point coordinates；
3. setting up ground at control point enhances positioning reference station；
4. configuration multi-rotor unmanned aerial vehicle hovering three-dimensional coordinate and lens direction simultaneously start；
5. unmanned plane hovers in fixed position and calibrates shooting direction by anchor point, N photos of shooting are simultaneously numbered；
6. inspection work is carried out, 3~5 operation of repetition carries out multiple image of clapping and obtains；
7. the N of multiple take photos are corrected with standard photographs by anchor point respectively；
8. traversing the pixel of corresponding photo-overlap phase width part using image recognition program；
9. pixel difference is demarcated beyond the region of threshold value；
10. whether judge calibration part is shaft tower defect or defect early warning.
1. transmission tower tour region includes transmission tower base foundation position, nameplate position and tower head portion to above-mentioned steps
Position, and three anchor points of spraying are enclosed at the tour visual angle of the shaft tower tower body at them.
2. above-mentioned steps demarcate control point with steel nail and determine control point coordinates by translocation.
Above-mentioned steps 3. at the control point pair in and set up ground enhancing positioning reference station.
4. above-mentioned steps select the multi-rotor unmanned aerial vehicle with RTK, connect positioning reference station and configure the three of N number of hovering point
Coordinate is tieed up, rotating lens direction alignment shaft tower simultaneously starts.
Map sheet shape determined by above three anchor point is square, and what anchor point was surrounded rectangular should cover tour portion
The 80% of part.
The advantages and positive effects of the present invention are:
1, the present invention is aided with bar by carrying the multi-rotor unmanned aerial vehicle connection ground enhancing base station of high-precision positioner
Anchor point on tower realizes that high-precision shaft tower is maked an inspection tour area image and obtained, improve inspection data acquisition standardization level and
The degree of automation improves working efficiency.
2, the present invention realizes the investigation and transmission tower wind of Pixel-level defect by the fining comparison of High-precision image
The prediction of danger effectively raises the fining degree of transmission tower inspection, excludes human factor and does caused by work quality
It disturbs.
3, it is aided with high accuracy positioning base station the present invention is based on airborne RTK device and realizes that unmanned plane hovering position high-precision is controlled
System, while realizing the shooting direction calibration of camera based on three anchor points and focusing.
Three anchor points realize the essence of image as interior industry image correcting error control point while realizing data acquisition positioning
Quasi- correction.
4, the method for the invention only compares the image pixel information being overlapped in anchor point region, avoids subtracting while erroneous judgement
Lack calculation amount, improves recognition efficiency.
5, the method for the invention can not only find shaft tower defect characteristic, also recordable shaft tower changing features, such as nut
It loosens, the deformation of tower material, is prevented and handled before defect characterization.
Detailed description of the invention
Fig. 1 is flow diagram of the invention.
Specific embodiment
Technical solution of the present invention is described in further detail below with reference to drawings and examples, but should
Know, these attached drawings are designed for task of explanation, therefore not as the restriction of the scope of the invention.In addition, except non-specifically
It points out, these attached drawings are meant only to conceptually illustrate structure construction described herein, without to be drawn to scale.
The present invention just is illustrated in conjunction with Fig. 1 below.
A kind of multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning, includes the following steps:
1, spraying three is enclosed at the shaft tower tower body tour visual angle at transmission tower base foundation position, nameplate position, tower head position
A anchor point；
Three white anchor points are sprayed in shaft tower tower body, map sheet shape determined by three anchor points is square, and is positioned
Rectangular should cover that point is surrounded makes an inspection tour 80% or so of component.
2, the earth's surfaces such as rock or hard surfacing stability region is with steel nail calibration control point and true by translocation near shaft tower
Determine control point coordinates；
Determine that the absolute position of base station is intended to multi-rotor unmanned aerial vehicle energy when unification is repeatedly clapped again with unified coordinate system
It is enough to keep consistent with the positional relationship of shaft tower.
3, at the control point pair in and set up ground enhancing positioning reference station；
By ground enhance positioning reference station pair in be intended to fix each flight when base station position with the more rotors of fixation without
The fixed erection of base station can also be set up base station stablizing geological province to reduce artificial repetition, realized by man-machine hovering position
Inspection working automation is carried out.
4, selection has the multi-rotor unmanned aerial vehicle of RTK, connects positioning reference station and configures the three-dimensional coordinate of N number of hovering point,
Rotating lens direction alignment shaft tower simultaneously starts；
RTK need to fly control with unmanned plane and be integrated to realize that the location information of positioning can instruct the target of unmanned plane during flying
Position.
5, unmanned plane hovers in fixed position and calibrates shooting direction by anchor point, and N photos of shooting are simultaneously numbered (first
Photo is completed standard picture and is obtained as standard photographs)；
Normal data acquisition is carried out when shaft tower state is normal, is provided with the inspection work automated in for a long time for the later period
Reference frame.
6, when inspection work is carried out, 3~5 operation of repetition carries out multiple image of clapping and obtains；
3~5 image-acquisition phases to work for Daily Round Check, 1,2 two o'clocks are basic preparation, are worked in Daily Round Check
Shi Wuxu carries out.
7, the N of multiple take photos are corrected with standard photographs by anchor point respectively, it is ensured that corresponding equipment region picture
Vegetarian refreshments is substantially overlapping；
Due to anchor point in the position of object be it is absolutely fixed, can carry out repeatedly multiple clapping figure with this anchor point
The correction of picture, so that the shaft tower equipment image overlap for repeatedly clapping same position again reaches to realize the diversity ratio pair of Pixel-level
To the purpose of discovery tiny defect.
8, the pixel of corresponding photo-overlap phase width part is traversed using image recognition program；
9, pixel difference is demarcated beyond the region of threshold value；
10, shaft tower defect or defect early warning are judged whether it is according to the equipment image variation of calibration part.
The present invention using ground enhance positioning reference station and target stem tower beacon note anchor point greatly improve more rotors nobody
The hovering precision of machine and the map sheet precision of shooting image, ensure that the multiple height for clapping image is consistent.It is accurate using map sheet anchor point
Correction claps image again and makes the accuracy for automating defect recognition that can realize stable promotion.The present invention helps polling transmission line people
Member promotion transmission tower inspection work fining degree, thus be effectively promoted polling transmission line efficiency, alleviate it is defeated
The labor intensity of electricity fortune inspection personnel effectively prevents the generation of transmission tower defect, and important early warning is provided for active defect elimination.
Above embodiments describe the invention in detail, but content is only the preferred embodiment of the present invention, no
It can be believed to be used to limit the scope of the invention.Any changes and modifications in accordance with the scope of the present application,
It should still fall within the scope of the patent of the present invention.
Claims (6)
1. a kind of multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning, it is characterised in that: including such as
Lower step:
1. being maked an inspection tour in transmission tower and spraying anchor point at the tower body of region；
2. demarcating control point in earth's surface stability region and measuring control point coordinates；
3. setting up ground at control point enhances positioning reference station；
4. configuration multi-rotor unmanned aerial vehicle hovering three-dimensional coordinate and lens direction simultaneously start；
5. unmanned plane hovers in fixed position and calibrates shooting direction by anchor point, N photos of shooting are simultaneously numbered；
6. inspection work is carried out, 3~5 operation of repetition carries out multiple image of clapping and obtains；
7. the N of multiple take photos are corrected with standard photographs by anchor point respectively；
8. traversing the pixel of corresponding photo-overlap phase width part using image recognition program；
9. pixel difference is demarcated beyond the region of threshold value；
10. whether judge calibration part is shaft tower defect or defect early warning.
2. the multi-rotor unmanned aerial vehicle transmission tower defect identification method according to claim 1 based on high accuracy positioning,
Be characterized in that: 1. transmission tower tour region includes transmission tower base foundation position, nameplate position and tower head portion to above-mentioned steps
Position, and three anchor points of spraying are enclosed at the tour visual angle of the shaft tower tower body at them.
3. the multi-rotor unmanned aerial vehicle transmission tower defect identification method according to claim 1 based on high accuracy positioning,
Be characterized in that: 2. above-mentioned steps demarcate control point with steel nail and determine control point coordinates by translocation.
4. the multi-rotor unmanned aerial vehicle transmission tower defect identification method according to claim 1 based on high accuracy positioning,
Be characterized in that: above-mentioned steps 3. at the control point pair in and set up ground enhancing positioning reference station.
5. the multi-rotor unmanned aerial vehicle transmission tower defect identification method according to claim 1 based on high accuracy positioning,
Be characterized in that: 4. above-mentioned steps select the multi-rotor unmanned aerial vehicle with RTK, connect positioning reference station and configure N number of hovering point
Three-dimensional coordinate, rotating lens direction alignment shaft tower simultaneously start.
6. the multi-rotor unmanned aerial vehicle transmission tower defect identification method according to claim 2 based on high accuracy positioning,
Be characterized in that: map sheet shape determined by above three anchor point is square, and what anchor point was surrounded rectangular should cover tour
The 80% of component.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811318451.4A CN109459437A (en) | 2018-11-07 | 2018-11-07 | Multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811318451.4A CN109459437A (en) | 2018-11-07 | 2018-11-07 | Multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109459437A true CN109459437A (en) | 2019-03-12 |
Family
ID=65609558
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811318451.4A Pending CN109459437A (en) | 2018-11-07 | 2018-11-07 | Multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109459437A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110850872A (en) * | 2019-10-31 | 2020-02-28 | 深圳市优必选科技股份有限公司 | Robot inspection method and device, computer readable storage medium and robot |
| CN111256702A (en) * | 2020-04-27 | 2020-06-09 | 天津市普迅电力信息技术有限公司 | Unmanned aerial vehicle autonomous inspection method for inspection of power tower |
| CN112269398A (en) * | 2020-11-04 | 2021-01-26 | 国网福建省电力有限公司漳州供电公司 | Unmanned aerial vehicle of transformer substation independently patrols and examines system |
| CN113064438A (en) * | 2021-03-31 | 2021-07-02 | 中国计量大学 | Inspection robot and control device and inspection method thereof |
| CN114047779A (en) * | 2021-10-22 | 2022-02-15 | 贵州电网有限责任公司 | Defect tracking method and system based on unmanned aerial vehicle inspection |
| CN114489102A (en) * | 2022-01-19 | 2022-05-13 | 上海复亚智能科技有限公司 | Self-inspection method and device for electric power tower, unmanned aerial vehicle and storage medium |
| CN115565118A (en) * | 2022-12-07 | 2023-01-03 | 南方电网数字电网研究院有限公司 | Method for identifying single hanging point and single string of cross crossing point of power transmission line |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101346623A (en) * | 2005-12-26 | 2009-01-14 | 株式会社尼康 | Defect inspection device for inspecting defect by image analysis |
| CN102510011A (en) * | 2011-10-24 | 2012-06-20 | 华北电力大学 | Method for realizing the intelligent tour-inspection of power tower based on miniature multi-rotor unmanned helicopter |
| KR101309098B1 (en) * | 2013-04-09 | 2013-09-25 | (주)엠투랩 | Apparatus for inspecting power transmission system based on unmanned aerial vehicle and system for inspecting power transmission system using the same |
| CN103454556A (en) * | 2013-08-09 | 2013-12-18 | 国家电网公司 | Tour inspection device with 3D scanning function and detection method thereof |
| CN104298248A (en) * | 2014-10-08 | 2015-01-21 | 南京航空航天大学 | Accurate visual positioning and orienting method for rotor wing unmanned aerial vehicle |
| US9439092B1 (en) * | 2015-07-27 | 2016-09-06 | Sprint Communications Company L.P. | Detection of component fault at cell towers |
| CN107729808A (en) * | 2017-09-08 | 2018-02-23 | 国网山东省电力公司电力科学研究院 | A kind of image intelligent acquisition system and method for power transmission line unmanned machine inspection |
-
2018
- 2018-11-07 CN CN201811318451.4A patent/CN109459437A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101346623A (en) * | 2005-12-26 | 2009-01-14 | 株式会社尼康 | Defect inspection device for inspecting defect by image analysis |
| CN102510011A (en) * | 2011-10-24 | 2012-06-20 | 华北电力大学 | Method for realizing the intelligent tour-inspection of power tower based on miniature multi-rotor unmanned helicopter |
| KR101309098B1 (en) * | 2013-04-09 | 2013-09-25 | (주)엠투랩 | Apparatus for inspecting power transmission system based on unmanned aerial vehicle and system for inspecting power transmission system using the same |
| CN103454556A (en) * | 2013-08-09 | 2013-12-18 | 国家电网公司 | Tour inspection device with 3D scanning function and detection method thereof |
| CN104298248A (en) * | 2014-10-08 | 2015-01-21 | 南京航空航天大学 | Accurate visual positioning and orienting method for rotor wing unmanned aerial vehicle |
| US9439092B1 (en) * | 2015-07-27 | 2016-09-06 | Sprint Communications Company L.P. | Detection of component fault at cell towers |
| CN107729808A (en) * | 2017-09-08 | 2018-02-23 | 国网山东省电力公司电力科学研究院 | A kind of image intelligent acquisition system and method for power transmission line unmanned machine inspection |
Non-Patent Citations (2)
| Title |
|---|
| 彭向阳: "无人机激光扫描作业杆塔位置提取算法", 《电网技术》 * |
| 焦明连: "《测绘技术在城市建设中的应用》", 31 December 2016, 中国矿业大学出版社 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110850872A (en) * | 2019-10-31 | 2020-02-28 | 深圳市优必选科技股份有限公司 | Robot inspection method and device, computer readable storage medium and robot |
| CN111256702A (en) * | 2020-04-27 | 2020-06-09 | 天津市普迅电力信息技术有限公司 | Unmanned aerial vehicle autonomous inspection method for inspection of power tower |
| CN112269398A (en) * | 2020-11-04 | 2021-01-26 | 国网福建省电力有限公司漳州供电公司 | Unmanned aerial vehicle of transformer substation independently patrols and examines system |
| CN112269398B (en) * | 2020-11-04 | 2024-03-15 | 国网福建省电力有限公司漳州供电公司 | Unmanned aerial vehicle of transformer substation independently patrols and examines system |
| CN113064438A (en) * | 2021-03-31 | 2021-07-02 | 中国计量大学 | Inspection robot and control device and inspection method thereof |
| CN114047779A (en) * | 2021-10-22 | 2022-02-15 | 贵州电网有限责任公司 | Defect tracking method and system based on unmanned aerial vehicle inspection |
| CN114489102A (en) * | 2022-01-19 | 2022-05-13 | 上海复亚智能科技有限公司 | Self-inspection method and device for electric power tower, unmanned aerial vehicle and storage medium |
| CN115565118A (en) * | 2022-12-07 | 2023-01-03 | 南方电网数字电网研究院有限公司 | Method for identifying single hanging point and single string of cross crossing point of power transmission line |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109459437A (en) | Multi-rotor unmanned aerial vehicle transmission tower defect identification method based on high accuracy positioning | |
| US10089529B2 (en) | Systems and methods for adaptive scanning based on calculated shadows | |
| CN106124517B (en) | The multi-rotor unmanned aerial vehicle detection platform system of detection structure part surface crack and its method for detection structure part surface crack | |
| JP6597603B2 (en) | Control device, imaging device, control method, imaging method, and computer program | |
| US9898821B2 (en) | Determination of object data by template-based UAV control | |
| CN103941748B (en) | Autonomous navigation method and system and Map building method and system | |
| JP6555255B2 (en) | Information processing apparatus, information processing method, and computer program | |
| CN106932784B (en) | Wagon box based on two-dimensional laser radar describes device 3 D scanning system measurement method | |
| Thomson et al. | Mobile laser scanning for indoor modelling | |
| CN112484704B (en) | Rapid mapping method and device | |
| JP2016082441A (en) | Controller, control method and computer program | |
| EP3474109A1 (en) | Measuring device, control device for unmanned aerial vehicle and method for controlling unmanned aerial vehicle | |
| CN109911188A (en) | The bridge machinery UAV system of non-satellite navigator fix environment | |
| CN104298248A (en) | Accurate visual positioning and orienting method for rotor wing unmanned aerial vehicle | |
| CN109945874B (en) | Bridge inspection route planning method | |
| CN111006646B (en) | Method for monitoring construction progress based on unmanned aerial vehicle oblique photography measurement technology | |
| CN109885097B (en) | Method for planning inspection route of outer edge surface of bridge | |
| CN106705962B (en) | A kind of method and system obtaining navigation data | |
| CN109885098B (en) | Method for planning inspection route of bridge side fence | |
| CN112200863B (en) | Unmanned aerial vehicle monitoring telegraph pole inclination system based on synchronous positioning and mapping | |
| CN106530352B (en) | Intelligent snow grooming machines people positioning system and method | |
| CN112197741B (en) | Unmanned aerial vehicle SLAM technology inclination angle measuring system based on extended Kalman filtering | |
| CN107238373A (en) | Unmanned plane aerial photography measures the method and system of antenna for base station engineering parameter | |
| CN112363176B (en) | Elevator hoistway inspection and modeling method and device and inspection and modeling system | |
| CN111426302A (en) | Unmanned aerial vehicle high accuracy oblique photography measurement system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190312 |