CN110673141A - Mobile airport pavement foreign matter detection method and system - Google Patents
Mobile airport pavement foreign matter detection method and system Download PDFInfo
- Publication number
- CN110673141A CN110673141A CN201911050393.6A CN201911050393A CN110673141A CN 110673141 A CN110673141 A CN 110673141A CN 201911050393 A CN201911050393 A CN 201911050393A CN 110673141 A CN110673141 A CN 110673141A
- Authority
- CN
- China
- Prior art keywords
- fod
- image
- foreign matter
- detection robot
- robot
- 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
Images
Classifications
-
- 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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
-
- 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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
- G01S13/867—Combination of radar systems with cameras
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0219—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory ensuring the processing of the whole working surface
Abstract
The invention discloses a mobile airport pavement foreign matter detection method and system, belonging to the field of foreign matter detection, comprising a background monitoring system, an FOD detection robot and the following steps: the background monitoring system issues an inspection task to the FOD detection robot, wherein the inspection task comprises an operation instruction and an operation area; the FOD detection robot automatically acquires object image data of an airport runway according to a routing inspection task, and the FOD detection robot acquires the object image data by using a camera; adding position information to the real object image data; the acquired object image data is processed to obtain the volume information of the FOD, and by the method, the automatic foreign matter detection of the airport runway is realized, and the efficiency of the airport runway foreign matter detection is improved.
Description
Technical Field
The invention relates to the field of foreign matter detection, in particular to a mobile airport pavement foreign matter detection method and system.
Background
FOD (foreign Object debris), a foreign Object that can damage an aircraft, and common FODs are screws, nuts, washers, nails, coins, rubble, waterproof cloth, newspapers, bottles, and the like. The harm caused by FOD is very serious, and many cases prove that foreign objects on the airport pavement can be easily sucked into an engine to cause the engine to be out of work, fragments can be accumulated in a mechanical device to influence the normal operation of equipment such as landing gears, wings and the like, the airplane can be damaged, precious life can be lost, and huge economic loss is also caused. According to the statistics of national airport runway debris investigators, the direct economic loss of foreign debris on airport runways is up to $ 40 billion each year. If debris causes damage to the engine or fuselage, it may cause the runway to close, if not, it may cause passenger and crew to be killed. In the event of a 2000 harmonized aircraft air crash, the aircraft is crashed, both passengers and crew are in distress, as debris hits the engine.
The existing FOD detection system mainly adopts a radar detection technology and a video image identification technology. The existing airport runway foreign matter detection system selects the key position of a specific detected runway surface according to the length and the width of an airport runway, front end detection system equipment is installed on one side of the runway in different areas, a radar and a multi-sensor integrated monitoring front end and a corresponding servo device are installed on a runway side fixing frame (or a runway lamp) on a tower frame with the required height, the front end multi-sensor detection system transmits foreign matter position information to a monitoring system display end, the monitoring system adjusts a pan-tilt and an angle, a focal length, an aperture and the like according to the position, tracks, monitors and photographs foreign matters, performs intelligent analysis and processing, transmits related information to a main control system for analysis and processing of the main control system, uploads the detected foreign matter information to a command center, and sends out an alarm prompt.
The Tarsier system developed in the uk, the FODetect system developed in israel, the ifrret system developed in singapore and the FOD Finder system developed in the us are typical in the world at present. The Tarsier system, the FODetect system and the FOD Finder system adopt a means of mainly millimeter wave radar detection and secondarily video image identification technology to detect the FOD; the ifrret system only uses video image recognition technology for FOD detection. Systems based on radar technology do not react to color, while systems based on video image recognition technology can react to color and illumination contrast.
Therefore, traditional fixed FOD system comprises many radars and optoelectronic system among the prior art, and the cost is high, is applicable to large-scale airport and uses, does not possess the price advantage to present growing unmanned aerial vehicle market, and equipment fixing time is longer, causes great influence to the safe operation and the aviation flight at airport.
Traditional portable FOD system installs in moving platform's top, can't realize the full coverage to the runway detection, can't realize continuous scanning, and the multi-target resolving power is relatively poor.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: how to provide a movable airport pavement foreign matter detection method to automatically realize the detection of foreign matters on an airport runway, improve the efficiency of the detection of the foreign matters on the airport runway, improve the minimum detection target size of a system and provide reliable flight safety guarantee for the takeoff and landing of an airplane.
The invention provides a mobile airport pavement foreign matter detection method, which comprises a background monitoring system, an FOD detection robot and the following steps:
(1) the background monitoring system issues an inspection task to the FOD detection robot, and the inspection task comprises a work instruction and a work area.
(2) The FOD detection robot automatically acquires object image data of an airport runway according to a routing inspection task, and the FOD detection robot acquires the object image data by using a camera;
(3) processing the acquired object image data to obtain FOD volume information, and adding position information to the object image data; .
By the method, automatic foreign matter detection of the airport runway is realized, and the efficiency of detecting the foreign matter of the airport runway is improved.
Further, the detected FOD for more convenient cleaning, further includes,
(4) reporting the volume and position information of the FOD to a background monitoring system, so that detection personnel can conveniently obtain the FOD information;
(5) and when the FOD detection robot executes the inspection task, the FOD detection robot appoints manual work to arrive at the site for processing.
Further, in step (3), the method for processing the real image data includes,
(31) carrying out gray level stretching processing on the acquired real object image to obtain a first image;
(31) carrying out self-adaptive OTSU segmentation and eight-direction Sobel edge detection processing on the first image to obtain a second image;
(31) performing gradient-based pixel connection processing on the second image to obtain a third image;
(32) carrying out connectivity detection-based binary image denoising processing on the third image to obtain a fourth image;
(33) performing edge extraction and denoising processing on the fourth image to obtain a fifth image;
(34) performing foreign matter sub-block identification processing on the fifth image to obtain a sixth image;
(35) performing foreign matter sub-block connection processing based on an optimization model on the sixth image to obtain a seventh image;
(36) carrying out foreign matter sub-block growth processing for protecting the integrity of foreign matters on the seventh image to obtain an eighth image;
(37) and extracting a target pixel from the eighth image to obtain FOD volume information.
The minimum detected target size of the system is improved by further processing the acquired real object image data.
Furthermore, in order to facilitate the removal of the FOD information by the administrator, in the step (4), the FOD volume and the position information are displayed in an alarm mode and reported to the background monitoring system, and the background monitoring system automatically generates a task work order of the FOD position information.
Furthermore, in order to conveniently manage and query the FOD information in the future, the method also comprises the steps of storing and storing the inspection task and the processing result, and specifically comprises the cleaning record, the inspection process and the inspection result of the detected FOD.
Furthermore, the FOD detection robot comprises a differential GPS/total station, a gyroscope and a photoelectric encoder,
the method for acquiring the position information comprises the following steps:
acquiring an initial position of the FOD detection robot;
integrating the angular velocity of the gyroscope and the linear velocity of the photoelectric encoder to obtain position and attitude information of corresponding time;
and correcting the gyroscope and the photoelectric encoder by using a differential GPS/total station to eliminate errors.
By the method, more accurate position information can be obtained.
The invention also provides a mobile airport pavement foreign matter detection system, which comprises a background monitoring system and an FOD detection robot, wherein the FOD detection robot is in communication connection with the background monitoring system;
the background monitoring system comprises:
the remote monitoring auxiliary system is in communication connection with the FOD detection robot and is used for defining a job task and issuing a job instruction;
the task planner is in communication connection with the FOD detection robot and is used for acquiring position information of a field operation area and planning the operation area;
the FOD detection robot includes:
the mobile platform is responsible for autonomous movement of the FOD detection robot;
the image acquisition system is used for acquiring pavement information;
the wireless data transmission system is used for being in communication connection with the background monitoring system;
and the onboard control system is in communication connection with the mobile platform, the image acquisition system and the wireless data transmission system and is used for motion control and data acquisition of the FOD detection robot.
Furthermore, backstage monitored control system still includes hand-held type controller, with FOD inspection robot communication connection for remote control FOD inspection robot's activity to realize that the control personnel manual control FOD inspection robot when necessary.
Further, the onboard control system comprises
The navigation system is used for realizing the positioning and motion control of the mobile platform;
the navigation system comprises an on-board system including
The gyroscope is used for measuring and recurrently deducing the pose;
the photoelectric encoder is used for recording the walking mileage of the robot;
the system also comprises a differential system and a differential GPS base station/total station, wherein the differential system is in communication connection with the differential GPS base station and is used for accurate positioning so as to acquire more accurate position information.
By adopting the technical scheme, the invention has the beneficial effects that: a method for detecting foreign matters on a movable airport pavement is provided. Carry out full overlay type scanning to the runway through using FOD detection robot to control and detect the camera and gather the pavement information, and add the position label for image data, realize the foreign matter detection of airport runway automatically, promote the efficiency that airport runway foreign matter detected and improve the minimum target size of examining of system, provide reliable flight safety guarantee for taking off, descending of aircraft.
Drawings
The invention will now be described, by way of example, with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a method for detecting foreign objects on a mobile airport pavement according to the present invention;
FIG. 2 is a schematic structural diagram of a FOD detection robot system;
FIG. 3 is a schematic diagram of a mobile platform configuration;
FIG. 4 is a schematic structural diagram of a control system;
FIG. 5 is a schematic structural diagram of a navigation positioning system;
fig. 6 is a flowchart of a method of processing real object image data.
Detailed Description
All of the features disclosed in this specification, or all of the steps in any method or process so disclosed, may be combined in any combination, except combinations of features and/or steps that are mutually exclusive.
Any feature disclosed in this specification may be replaced by alternative features serving equivalent or similar purposes, unless expressly stated otherwise. That is, unless expressly stated otherwise, each feature is only an example of a generic series of equivalent or similar features.
The invention provides a mobile airport pavement foreign matter detection method and a system for realizing the method, which detect the foreign matter on the mobile airport pavement by adopting an FOD detection robot system, and specifically comprises a background monitoring system, an FOD detection robot and the following steps:
and the background monitoring system issues a polling task to the FOD detection robot.
FOD inspection robot carries out full coverage formula scanning and online real-time foreign matter automatic identification technique to the runway through using FOD inspection robot according to patrolling and examining the task before the flight, draws FOD volume and positional information voluntarily to the object image data of automatic acquisition airport runway.
And adding position information to the real object image data.
And processing the acquired real object image data to obtain the volume information of the FOD.
And reporting the volume and position information of the FOD to a detection result monitoring system of a background monitoring system in real time.
The specific detection method is shown in fig. 1:
the background system predefines a polling area for the FOD detection robot in advance, before flying, the robot automatically or manually enters the area to be operated, the predefined polling area detection is automatically completed according to the requirement, a polling task is automatically executed, real-time data processing is carried out in the detection process, and the FOD detection robot exits the operation area after the polling task is finished.
Wherein, the flow of FOD inspection robot real-time processing data includes: and for the found FOD information, reporting the FOD information to a background monitoring system in real time, displaying the FOD information on an interface in an alarm mode, automatically generating a task work order of the FOD position information, and after the standby robot executes a complete inspection task, appointing a worker to arrive at a site for processing. For all detected FOD, the background monitoring system stores the history records and the cleaning records of the FOD, and automatically stores all inspection processes and inspection results, so that the FOD inspection informatization is realized.
The FOD detection robot system shown in fig. 2 is composed of a plurality of hardware modules and a software system. The hardware part comprises a detection robot body, the FOD detection robot body comprises a mobile platform, an onboard control system and an image acquisition system, and the background monitoring system comprises a remote monitoring auxiliary system and a task planner. The onboard control system and the remote auxiliary system realize data transmission through a wireless data transmission system, and each part realizes the function of autonomous detection operation under the coordination of a whole set of robot software system. The image acquisition system consists of a detection camera. The mobile platform is used for realizing the autonomous movement function of the mobile robot, the FOD detection robot has high-precision autonomous positioning capability, can automatically complete the detection task issued by the remote monitoring auxiliary system, controls the detection camera to acquire pavement information, and adds a position tag for image data, thereby facilitating later maintenance. The remote monitoring auxiliary system has the functions of defining operation tasks, issuing operation instructions, monitoring operation states and the like. The task planner is used for collecting the position information of the field operation area and planning the operation task.
The mobile platform is mainly used as a power device of the robot and is responsible for the overall planar motion of the robot, as shown in fig. 3, the mobile platform of the robot adopts a four-turn four-wheel drive structure, each wheel is driven by a control driver, the control driver acquires control information through communicating with an upper computer, and the mobile platform further comprises an emergency stop input module for emergently stopping the robot, so that complex actions such as omnibearing translation, in-situ turning, no-coupling compound motion and the like can be realized, and the mobile platform is flexible to move. The mobile platform control driver receives the instructions of the upper computer through the serial communication interface and uploads the relevant data of the platform operation. The mobile platform carries a large-capacity lithium battery to supply power to the whole vehicle equipment. The detection camera can be mounted as required as a working device.
The control system is shown in FIG. 4: the system comprises a navigation system, a body control system and a data preprocessing system. The on-board control system consists of two industrial personal computers, one industrial personal computer is mainly responsible for robot motion control and positioning navigation, and the other industrial personal computer is responsible for sensor control and data acquisition. And the two industrial personal computers are respectively provided with linux and windows operating systems so as to adapt to different requirements. And meanwhile, an embedded power management board is also arranged to monitor the normal startup and shutdown of the two industrial personal computers and ensure that the power supply is cut off after the operating system is normally shut down.
The system architecture of the navigation positioning system is shown in fig. 5, the navigation system is composed of an on-vehicle system and a calibration module, the position and the posture of the robot body are detected, and the robot has an obstacle avoidance function in moving. The navigation system realizes the positioning and motion control of the mobile platform and comprises a set of differential GPS system or total station for precise positioning, a set of MEMS gyroscope for pose measurement and pose recursion, a set of odometer consisting of photoelectric encoders for recording the advancing mileage of the robot, and a set of laser radar capable of covering the motion range for safety early warning and obstacle avoidance; in addition, a plurality of monitoring cameras are respectively arranged on the front, the back, the left and the right of the robot body and used for remotely monitoring the surrounding environment of the robot.
Because the precise position of the robot needs to be obtained continuously and rapidly, only one sensor is not available, and the outputs of a plurality of sensors are integrated to perform position fusion. The differential GPS or the total station can obtain position information accurate to centimeter level, but the output frequency is very low, so that the requirement of a control system cannot be met; the gyroscope and the photoelectric encoder can obtain the angular velocity and the linear velocity of a very high frequency, relative positions and postures can be obtained by integrating the two velocities, but accumulated errors can be brought along with time by the integration, so that the gyroscope and the photoelectric encoder are corrected by using the difference gps, the accumulated errors are periodically eliminated, and the high-frequency and accurate robot position and posture information can be output.
In order to meet the communication requirements of the FOD detection machine, the background monitoring system and the internal system thereof, the FOD detection machine further comprises a wireless data transmission system, wherein the wireless data transmission system comprises three parts, namely data interaction of a differential GPS base station and a server, data interaction of a handheld controller and a robot body and data interaction of the robot body and a remote control center.
The data transmission of the differential GPS base station adopts two schemes, one scheme is that a serial port 4G module is installed, positioning data is uploaded to a public network server through a 4G network and is transmitted, and the other scheme is direct point-to-point transmission through 433MHz wireless data transmission equipment. The first scheme has the advantages that the base station can be installed in a far place, but the base station needs to be forwarded by a public network server, and the stability is limited. The second scheme has shorter transmission distance but is more stable, and has the defect that the wireless frequency band is limited and cannot be used in an airport.
Through the robot automatic detection system in the embodiment 1, the unmanned foreign matter automatic detection on the airport runway is realized, the robot automatic detection system can be rapidly arranged in medium and small airports and unmanned aerial vehicle airports, manpower and material resources required by traditional foreign matter detection are liberated, and the service efficiency of the detection system is improved.
Example 2
On the basis of embodiment 1, the present application further provides a method for processing the real object image data acquired in embodiment 1, and the FOD inspection robot system mainly performs image analysis by using an image segmentation method based on edge detection. Segmentation methods based on edge detection attempt to solve the segmentation problem by detecting edges that contain different regions, and the variation of pixel gray scale values on the edges between different regions is often relatively severe, which is one of the main assumptions that edge detection methods are implemented. The edge detection method generally uses the maximum value of the first derivative or the zero crossing point information of the second derivative of the image to provide the basic basis for judging the edge point. Edge detection techniques can be generally classified into serial edge detection and parallel edge detection according to the technique of processing. The serial edge detection is to determine whether the current pixel belongs to a point on the detected edge, depending on the verification result of the previous pixel. The parallel edge detection is that whether a pixel belongs to a point on the detected edge depends on the current pixel being detected and some adjacent pixels of the pixel.
The edge detection method can be a parallel differential operator method, and edge points are detected by using a first-order derivative or a second-order derivative according to the discontinuous property of pixel values of adjacent areas.
The specific process of processing the real image data is shown in fig. 6: the method comprises the steps of carrying out gray level stretching processing on an acquired real object image to obtain a first image; carrying out self-adaptive OTSU segmentation and eight-direction Sobel edge detection processing on the first image to obtain a second image; performing gradient-based pixel connection processing on the second image to obtain a third image; carrying out connectivity detection-based binary image denoising processing on the third image to obtain a fourth image; performing edge extraction and denoising processing on the fourth image to obtain a fifth image; performing foreign matter sub-block identification processing on the fifth image to obtain a sixth image; performing foreign matter sub-block connection processing based on an optimization model on the sixth image to obtain a seventh image; carrying out foreign matter sub-block growth processing for protecting the integrity of foreign matters on the seventh image to obtain an eighth image; and extracting a target pixel from the eighth image to obtain FOD volume information.
By processing the real object image data, the multi-target resolution capability is effectively improved; through the use of 3D camera, high-efficient quick searching foreign matter is looked for the foreign matter source, has improved aircraft flight safety.
The invention provides a mobile airport pavement foreign matter detection method and a system for realizing the method. Carry out full overlay type scanning to the runway through using FOD detection robot to control and detect the camera and gather the pavement information, and add the position label for image data, realize the foreign matter detection of airport runway automatically, promote the efficiency that airport runway foreign matter detected and improve the minimum target size of examining of system, provide reliable flight safety guarantee for taking off, descending of aircraft.
While the foregoing description shows and describes a preferred embodiment of the invention, it is to be understood, as noted above, that the invention is not limited to the form disclosed herein, but is not intended to be exhaustive or to exclude other embodiments and may be used in various other combinations, modifications, and environments and may be modified within the scope of the inventive concept described herein by the above teachings or the skill or knowledge of the relevant art. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. A mobile airport pavement foreign matter detection method comprises a background monitoring system and is characterized in that: further comprises a FOD detection robot and the following steps,
(1) the background monitoring system issues a polling task to the FOD detection robot;
(2) the FOD detection robot automatically acquires object image data of the airport runway according to the inspection task;
(3) and processing the object image data to obtain the volume information of the FOD, and adding position information to the FOD.
2. The method for detecting foreign matter on a mobile airport pavement according to claim 1, wherein: also comprises the following steps of (1) preparing,
(4) reporting the volume and position information of the FOD to a background monitoring system;
(5) and when the FOD detection robot executes the inspection task, the FOD detection robot appoints manual work to arrive at the site for processing.
3. The method for detecting foreign matter on a mobile airport pavement according to claim 1, wherein: in the step (1), the inspection task comprises a work instruction and a work area.
4. The method for detecting foreign matter on a mobile airport pavement according to claim 1, wherein: step (3), the method for processing the object image data comprises,
(31) carrying out gray level stretching processing on the acquired real object image to obtain a first image;
(31) carrying out self-adaptive OTSU segmentation and eight-direction Sobel edge detection processing on the first image to obtain a second image;
(31) performing gradient-based pixel connection processing on the second image to obtain a third image;
(32) carrying out connectivity detection-based binary image denoising processing on the third image to obtain a fourth image;
(33) performing edge extraction and denoising processing on the fourth image to obtain a fifth image;
(34) performing foreign matter sub-block identification processing on the fifth image to obtain a sixth image;
(35) performing foreign matter sub-block connection processing based on an optimization model on the sixth image to obtain a seventh image;
(36) carrying out foreign matter sub-block growth processing for protecting the integrity of foreign matters on the seventh image to obtain an eighth image;
(37) and extracting a target pixel from the eighth image to obtain FOD volume information.
5. The method for detecting foreign matter on a mobile airport pavement according to claim 2, wherein: in the step (4), the FOD volume and the position information are displayed in an alarm mode and reported to a background monitoring system, and the background monitoring system automatically generates a task work order of the FOD position information.
6. The method of claim 2, further comprising storing the inspection task and the processing results.
7. The mobile airport pavement foreign object detection method of any of claims 1-2, wherein said FOD detection robot comprises a differential GPS/total station, a gyroscope, and a photoelectric encoder,
the method for acquiring the position information comprises the following steps:
acquiring an initial position of the FOD detection robot;
integrating the angular velocity of the gyroscope and the linear velocity of the photoelectric encoder to obtain position and attitude information of corresponding time;
and correcting the gyroscope and the photoelectric encoder by using a differential GPS/total station to eliminate errors.
8. A mobile airport pavement foreign matter detection system comprises a background monitoring system and is characterized by further comprising an FOD detection robot, wherein the FOD detection robot is in communication connection with the background monitoring system;
the background monitoring system comprises:
the remote monitoring auxiliary system is in communication connection with the FOD detection robot and is used for defining a job task and issuing a job instruction;
the task planner is in communication connection with the FOD detection robot and is used for acquiring position information of a field operation area and planning the operation area;
the FOD detection robot includes:
the mobile platform is responsible for autonomous movement of the FOD detection robot;
the image acquisition system is used for acquiring pavement information;
the wireless data transmission system is used for being in communication connection with the background monitoring system;
and the onboard control system is in communication connection with the mobile platform, the image acquisition system and the wireless data transmission system and is used for motion control and data acquisition of the FOD detection robot.
9. The mobile airport pavement foreign object detection system of claim 8, wherein: the background monitoring system further comprises a handheld controller which is in communication connection with the FOD detection robot and used for remotely controlling the movement of the FOD detection robot.
10. The mobile airport pavement foreign object detection system of claim 8, wherein: the onboard control system comprises
The navigation system is used for realizing the positioning and motion control of the mobile platform;
the navigation system comprises an on-board system including
The gyroscope is used for measuring and recurrently deducing the pose;
the photoelectric encoder is used for recording the walking mileage of the robot;
the system also comprises a differential system and a differential GPS base station/total station, wherein the differential system is in communication connection with the differential GPS base station and is used for accurate positioning.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911050393.6A CN110673141A (en) | 2019-10-31 | 2019-10-31 | Mobile airport pavement foreign matter detection method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911050393.6A CN110673141A (en) | 2019-10-31 | 2019-10-31 | Mobile airport pavement foreign matter detection method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110673141A true CN110673141A (en) | 2020-01-10 |
Family
ID=69085140
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911050393.6A Pending CN110673141A (en) | 2019-10-31 | 2019-10-31 | Mobile airport pavement foreign matter detection method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110673141A (en) |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111781937A (en) * | 2020-08-07 | 2020-10-16 | 江苏普达迪泰科技有限公司 | Unmanned formation control system of foreign matter detection and cleaning system and control method thereof |
| CN111897025A (en) * | 2020-08-06 | 2020-11-06 | 航泰众联(北京)科技有限公司 | Airport pavement foreign matter detection equipment and system based on 3D/2D integration detection |
| CN112505050A (en) * | 2020-11-12 | 2021-03-16 | 中科蓝卓(北京)信息科技有限公司 | Airport runway foreign matter detection system and method |
| CN113009507A (en) * | 2021-03-07 | 2021-06-22 | 航泰众联(北京)科技有限公司 | Distributed airport runway FOD monitoring system and method based on laser radar |
| CN113046982A (en) * | 2021-05-08 | 2021-06-29 | 田勇 | Intelligent table scanning and ironing equipment for billiard table and table surface treatment method |
| CN116224349A (en) * | 2022-12-12 | 2023-06-06 | 珠海创智科技有限公司 | Robot positioning method, system and electronic device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010039268A1 (en) * | 2008-10-03 | 2010-04-08 | Trex Enterprises Corporation | Mobile millimeter wave imaging radar system |
| CN105549110A (en) * | 2015-12-08 | 2016-05-04 | 北京无线电计量测试研究所 | Airport runway foreign object debris detection device and airport runway foreign object debris detection method |
| CN107263511A (en) * | 2017-05-26 | 2017-10-20 | 哈尔滨工程大学 | A kind of omnidirectional's airfield runway detection robot system and its control method |
| WO2018125014A1 (en) * | 2016-12-26 | 2018-07-05 | Argosai Teknoloji Anonim Sirketi | A method for foreign object debris detection |
| CN108269322A (en) * | 2017-12-28 | 2018-07-10 | 浙江捷尚人工智能研究发展有限公司 | A kind of method for inspecting |
| CN108535789A (en) * | 2018-05-23 | 2018-09-14 | 成都圭目机器人有限公司 | A kind of foreign matter identifying system based on airfield runway |
-
2019
- 2019-10-31 CN CN201911050393.6A patent/CN110673141A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2010039268A1 (en) * | 2008-10-03 | 2010-04-08 | Trex Enterprises Corporation | Mobile millimeter wave imaging radar system |
| CN105549110A (en) * | 2015-12-08 | 2016-05-04 | 北京无线电计量测试研究所 | Airport runway foreign object debris detection device and airport runway foreign object debris detection method |
| WO2018125014A1 (en) * | 2016-12-26 | 2018-07-05 | Argosai Teknoloji Anonim Sirketi | A method for foreign object debris detection |
| CN107263511A (en) * | 2017-05-26 | 2017-10-20 | 哈尔滨工程大学 | A kind of omnidirectional's airfield runway detection robot system and its control method |
| CN108269322A (en) * | 2017-12-28 | 2018-07-10 | 浙江捷尚人工智能研究发展有限公司 | A kind of method for inspecting |
| CN108535789A (en) * | 2018-05-23 | 2018-09-14 | 成都圭目机器人有限公司 | A kind of foreign matter identifying system based on airfield runway |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111897025A (en) * | 2020-08-06 | 2020-11-06 | 航泰众联(北京)科技有限公司 | Airport pavement foreign matter detection equipment and system based on 3D/2D integration detection |
| CN111781937A (en) * | 2020-08-07 | 2020-10-16 | 江苏普达迪泰科技有限公司 | Unmanned formation control system of foreign matter detection and cleaning system and control method thereof |
| CN112505050A (en) * | 2020-11-12 | 2021-03-16 | 中科蓝卓(北京)信息科技有限公司 | Airport runway foreign matter detection system and method |
| CN113009507A (en) * | 2021-03-07 | 2021-06-22 | 航泰众联(北京)科技有限公司 | Distributed airport runway FOD monitoring system and method based on laser radar |
| CN113046982A (en) * | 2021-05-08 | 2021-06-29 | 田勇 | Intelligent table scanning and ironing equipment for billiard table and table surface treatment method |
| CN113046982B (en) * | 2021-05-08 | 2023-02-28 | 田勇 | Intelligent table scanning and ironing equipment for billiard table and table top processing method |
| CN116224349A (en) * | 2022-12-12 | 2023-06-06 | 珠海创智科技有限公司 | Robot positioning method, system and electronic device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110673141A (en) | Mobile airport pavement foreign matter detection method and system | |
| US10518411B2 (en) | Robotic repair or maintenance of an asset | |
| EP3738892A1 (en) | In-service maintenance process using unmanned aerial vehicles | |
| CN105812733B (en) | A kind of scene monitoring guiding system of air traffic control | |
| CN102590882B (en) | Foreign body monitoring system for airport road surface | |
| US20020109625A1 (en) | Automatic method of tracking and organizing vehicle movement on the ground and of identifying foreign bodies on runways in an airport zone | |
| CN109376587A (en) | Communication iron tower intelligent inspection system and method are surveyed in detection based on Internet of Things | |
| CN101109640A (en) | Unmanned aircraft landing navigation system based on vision | |
| WO2019047338A1 (en) | Port machinery inspection device and inspection method | |
| Liu et al. | Deep learning-based localization and perception systems: Approaches for autonomous cargo transportation vehicles in large-scale, semiclosed environments | |
| CN107521678A (en) | The UAS and its method for positioning and capturing for nuclear radiation radioactive source | |
| WO2020000790A1 (en) | Vertical mine shaft detection method and system | |
| CN103266559A (en) | BP bridge safety inspection vehicle and method for obtaining bridge surface physiognomy | |
| CN102328751A (en) | System for assisting airport runway perambulation inspection | |
| CN105738909B (en) | One kind being suitable for low latitude plant protection unmanned helicopter operation boundary extraction method | |
| CN111910566A (en) | Airport runway foreign matter automatic detection and clearance system | |
| CN113568427B (en) | Unmanned aerial vehicle autonomous landing mobile platform method and system | |
| CN204297108U (en) | Helicopter obstacle avoidance system | |
| CN111230890A (en) | Airport runway detection robot | |
| CN105760855A (en) | Multi-source photoelectric information fusion aircraft wreckage identification system | |
| Bauda et al. | 3D scanner positioning for aircraft surface inspection | |
| CN103879559A (en) | Aircraft take-off and landing monitoring device | |
| JP2019082377A (en) | Road surface state detection device, and road surface state detection system | |
| CN113050671A (en) | Unmanned aerial vehicle system for detecting natural gas leakage and detection method | |
| CN106802417A (en) | The method and apparatus for implementing the method for detection airport installation collision |
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: 20200110 |