CN113791621B - Automatic steering tractor and airplane docking method and system - Google Patents
Automatic steering tractor and airplane docking method and system Download PDFInfo
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- CN113791621B CN113791621B CN202111077939.4A CN202111077939A CN113791621B CN 113791621 B CN113791621 B CN 113791621B CN 202111077939 A CN202111077939 A CN 202111077939A CN 113791621 B CN113791621 B CN 113791621B
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- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64F—GROUND OR AIRCRAFT-CARRIER-DECK INSTALLATIONS SPECIALLY ADAPTED FOR USE IN CONNECTION WITH AIRCRAFT; DESIGNING, MANUFACTURING, ASSEMBLING, CLEANING, MAINTAINING OR REPAIRING AIRCRAFT, NOT OTHERWISE PROVIDED FOR; HANDLING, TRANSPORTING, TESTING OR INSPECTING AIRCRAFT COMPONENTS, NOT OTHERWISE PROVIDED FOR
- B64F1/00—Ground or aircraft-carrier-deck installations
- B64F1/22—Ground or aircraft-carrier-deck installations installed for handling aircraft
- B64F1/225—Towing trucks
- B64F1/228—Towing trucks remotely controlled, or autonomously operated
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- 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
- G05D1/0225—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving docking at a fixed facility, e.g. base station or loading bay
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- 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
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
- G05D1/0251—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision
Abstract
The invention belongs to the technical field of airplane traction operation, and particularly relates to a method and a system for docking an autopilot tractor with an airplane. The butt joint method comprises the following steps: the tractor reaches a starting point position for docking operation with the automatic driving tractor through the high-precision positioning module, and the course angle of the tractor is adjusted to be consistent with the course angle of the airplane; the automatic tractor starts to approach to the airplane, the tractor adjusts the pose through the camera sensor until the tractor bracket is aligned with the flying front landing gear, and the vehicle-mounted laser radar measures the distance between the tail end of the tractor bracket and the front landing gear of the airplane; when the tractor reaches a preset position, the speed of the vehicle is regulated to be contacted with the nose landing gear of the airplane; and finally, the butt joint is completed. The docking system comprises various sensors, an automatic driving platform and a vehicle-to-machine communication system, and all devices in the system are mutually matched. The invention aims to realize full-automatic butt joint of the automatic driving tractor and the airplane to be towed, ensure the safety of operators, reduce the amount of manual labor and improve the operation efficiency.
Description
Technical Field
The invention belongs to the technical field of airplane traction operation, and particularly relates to a method and a system for docking an autopilot tractor with an airplane.
Background
The aircraft tractor is an important device for guaranteeing the ground movement of an aircraft, and is divided into rod traction and rodless traction according to different traction modes, wherein the rod traction refers to that the aircraft tractor is connected with a nose landing gear of the aircraft through a traction rod, so that the traction or pushing of the aircraft is realized. The rodless tractor is an airplane tractor for carrying the nose landing gear of the airplane, and the tractor and the airplane form a whole to realize the traction or pushing of the airplane. The rodless traction operation is simple, the turning radius is small, the number of the workers is small, and the universality is good.
In the prior art, an aircraft tractor is usually a manual steering tractor, and a tractor driver needs to be responsible for steering the tractor on the basis of the well-known technical requirements (such as turning angle, traction speed, span, height and the like in a maintenance manual) of various aircraft tractors. The tractor and the airplane are in butt joint operation, wherein a driver drives the tractor to align to the front landing gear of the airplane to approach slowly, and the front landing gear of the airplane is clamped by a wheel holding clamping mechanism on the tractor after the tractor contacts the front landing gear, so that the traction or pushing of the airplane is realized. Because the visual field of the tractor driver is limited, at least two traction directors are needed to be equipped, the tractor driver is responsible for observing the clear distance between the tractor and the towed aircraft, between the towed aircraft and surrounding aircraft or fixed buildings, and the tractor driver is given early warning reminding through voice communication.
Still other prior art technologies provide for improving the safety of the tractor operation, optimizing the process of docking the tractor with the aircraft, adding sensors to the tractor to obtain traffic situation information around the tractor, and providing information affecting the safety of the operation to the tractor driver in a visual interface. However, this approach still fails to address the problems of stringent tractor driver requirements, personal hazards for the operator, the need for multiple personnel cooperation, and inefficiency.
Disclosure of Invention
This patent is based on the above-mentioned demand of prior art and proposes, and the technical problem that this patent will solve provides an autopilot tractor and aircraft interfacing method and system in order to realize autopilot tractor and treat the full-automatic interfacing of haulage aircraft, when guaranteeing operating personnel safety and reducing the manual labor volume, improves the operating efficiency.
In order to solve the above-mentioned problem, the technical scheme that this patent provided includes:
there is provided a method of interfacing an autopilot tractor with an aircraft, comprising: s1, an automatic steering platform acquires position information and attitude information of an aircraft to be towed through a high-precision positioning module, and a control module controls an automatic steering tractor to reach a starting point of docking operation with the aircraft to be towed; meanwhile, the automatic steering tractor is controlled to adjust the course angle to be consistent with the course angle of the airplane to be towed; s2, after the autopilot tractor reaches a docking operation starting point and the course angle of the autopilot tractor is consistent with the course angle of the airplane to be towed, the autopilot tractor starts to approach the airplane to be towed, a camera sensor on the autopilot tractor identifies the nose landing gear of the airplane to be towed, whether the autopilot tractor bracket is aligned with the nose landing gear of the airplane to be towed is judged, the distance between the tail end of the autopilot tractor bracket and the nose landing gear of the airplane to be towed and whether obstacles exist around the tail end of the autopilot tractor bracket and the nose landing gear of the airplane to be towed are detected through a plurality of vehicle-mounted laser radars respectively in real time, and the method for identifying the nose landing gear by the camera sensor is as follows: firstly, training a nose landing gear identification model of an airplane to be towed, inputting a captured image into an algorithm network by an automatic steering platform in the process of docking the automatic tractor and the airplane to be towed so as to realize the identification of the nose landing gear of the airplane, and simultaneously, installing 5 characteristic points on the nose landing gear of the airplane, wherein 4 edges of the landing gear are round, 1 center of the landing gear is rectangular, and positioning the characteristic points to obtain the relative position and posture between the nose landing gear of the airplane and a bracket of the automatic steering tractor so as to realize the positioning and posture identification of the nose landing gear of the airplane; s3, when the autopilot tractor reaches a preset position, the distance between the tail end of the autopilot tractor bracket and the nose landing gear of the airplane to be towed reaches a specified value, the autopilot system adjusts the speed of the autopilot tractor, the autopilot tractor runs in a uniform speed reduction mode, and meanwhile the speed of the autopilot tractor bracket is 0 when the tail end of the autopilot tractor bracket contacts with the nose landing gear of the airplane to be towed; s4, after the tail end of the bracket of the automatic steering tractor contacts with the nose landing gear of the airplane to be towed, the wheel holding clamping mechanism clamps the nose landing gear of the airplane, and the wheel holding jacking mechanism lifts the nose landing gear of the airplane, so that the docking is completed. The aircraft nose landing gear is provided with 5 feature points, the feature points are fixed, the structure is short, the identification is easy, and the identification accuracy is stable.
Preferably, when the autopilot tractor reaches the start of the docking operation, v 1 m/s speed reversing is close to the nose landing gear of the airplane to be pulled, and the camera sensor is used for identifying the nose landing gear of the airplane to be pulled in the reversing process, so that the pose is adjusted to the tractorWith carriage aligned with nose landing gear of aircraft, velocity v 1 Can be expressed as:
wherein L is the distance between the starting point position of the docking operation and the nose landing gear of the airplane, L 0 The distance between the position and the nose landing gear of the aircraft is preset for the tractor.
Preferably, the vehicle-mounted lidar comprises a first vehicle-mounted lidar and a second vehicle-mounted lidar, the distance between the tail end of the tractor bracket and the nose landing gear of the airplane to be towed can be calculated through the first vehicle-mounted lidar, the camera sensor data are combined with the first vehicle-mounted lidar data, and the distance l between the first vehicle-mounted lidar and the nose landing gear of the airplane to be towed is extracted 1 Calculating the distance l between the tail end of the bracket of the automatic steering tractor and the nose landing gear of the airplane to be towed 2 Denoted by l 2 ＝l 1 -a, wherein a is the distance of the first vehicle-mounted lidar from the end of the autopilot tractor carrier.
Preferably, when the automatic driving tractor reaches the tractor preset position, the automatic driving platform adjusts the speed of the automatic driving tractor to be v 2 m/s, the tractor performs uniform deceleration movement in the process that the tractor contacts from the preset position of the tractor to the tail end of the tractor bracket to the nose landing gear of the airplane to be towed, and the acceleration of the tractor is a 0 Expressed as:
the invention also provides an autopilot tractor and aircraft docking system comprising: the system comprises a plurality of sensors, a sensor module and a control module, wherein the sensors comprise a high-precision positioning module and are used for acquiring position information and course angle information of an airplane to be towed; a camera sensor for identifying the nose landing gear of the aircraft to be towed; the vehicle-mounted laser radar is used for measuring the distance between the tail end of the tractor bracket and the front landing gear of the airplane to be towed and the obstacle on the periphery of the tractor; the automatic driving platform comprises a sensing module, wherein the sensing module is used for receiving information acquired by various sensors and processing the information; the decision module is used for generating a tractor travelling track meeting specific constraint conditions according to the information processed by the sensing module; the control module is used for controlling an internal execution device of the tractor according to the information of the decision module combined with the actual situation; and the vehicle-to-machine communication equipment is used for information interaction between the tractor and the airplane to be towed.
Preferably, the decision module comprises a path planning layer, a behavior decision layer and a motion planning layer, wherein the path planning layer generates a global path, the behavior decision layer makes specific behavior decisions by combining information received from the sensing module after receiving the global path, and the motion planning layer plans to generate a track meeting specific constraint conditions according to the specific behavior decisions.
Preferably, the track planned by the motion planning layer is transmitted as input to the control module, as the final driving path of the vehicle.
Preferably, the sensing module is used for receiving information acquired by the multiple sensors, performing distributed fusion on the information, performing local processing on original data acquired by each independent sensor, and then sending the result to the information fusion center for intelligent optimization and combination to acquire a final result.
Compared with the prior art, the full-automatic docking of the automatic driving tractor and the airplane to be towed can be realized, the safety of operators is ensured, the manual labor is reduced, and the operation efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the present description or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments described in the embodiments of the present description, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a flow chart of the steps of a method of docking an autopilot tractor with an aircraft in accordance with the present invention;
FIG. 2 is a top view of various sensor placement locations on an autonomous tractor in one embodiment of the invention;
FIG. 3 is a side view of various sensor placement locations on an autonomous tractor in one embodiment of the invention;
fig. 4 is a schematic diagram of an autopilot tractor and aircraft docking system in one embodiment of the invention.
Reference numerals:
1. a high-precision positioning module; 2. a camera sensor; 3. a first vehicle-mounted lidar; 4. and a second vehicle-mounted lidar.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
For the purpose of facilitating an understanding of the embodiments of the present application, reference will now be made to the following description of specific embodiments, taken in conjunction with the accompanying drawings, in which the embodiments are not intended to limit the embodiments of the present application.
Example 1
The embodiment provides a docking method of an autopilot tractor and an airplane, and referring to fig. 1.
S1, an automatic steering platform acquires position information and attitude information of an aircraft to be towed through a high-precision positioning module, and a control module controls an automatic steering tractor to reach a starting point of docking operation with the aircraft to be towed; and meanwhile, the automatic steering tractor is controlled to adjust the course angle to be consistent with the course angle of the airplane to be towed.
The automatic driving platform acquires the position information of the airplane to be towed, and simultaneously calculates the position information of the starting point of the docking operation by combining the information provided by the high-precision positioning module, and the control module controls the automatic driving tractor to reach the starting point of the docking operation.
The starting point of the docking operation is the position of L m right in front of the nose landing gear of the airplane.
L is determined according to the requirement of the butt joint operation and the size of the field, and is 10-15m.
The high-precision positioning module comprises, but is not limited to, a satellite antenna, an inertial/satellite combined navigation host, upper computer software and the like, and is respectively used for receiving satellite signals, calculating and providing multi-parameter navigation information, assisting in positioning, analyzing data and the like.
When the automatic steering tractor reaches the starting point of the docking operation, the automatic steering platform controls the automatic steering tractor to adjust the course angle to be consistent with the course angle of the airplane to be towed through the control module under the assistance of the high-precision positioning module according to the acquired airplane gesture information.
S2, after the autopilot tractor reaches a docking operation starting point and the course angle of the autopilot tractor is consistent with the course angle of the airplane to be towed, the autopilot tractor starts to approach the airplane to be towed, a camera sensor on the autopilot tractor identifies the nose landing gear of the airplane to be towed, whether the autopilot tractor bracket is aligned with the nose landing gear of the airplane to be towed is judged, and the distance between the tail end of the autopilot tractor bracket and the nose landing gear of the airplane to be towed and whether obstacles exist around the autopilot tractor bracket are detected through a plurality of vehicle-mounted laser radars respectively.
The autopilot tractor is provided with a camera sensor which can identify the nose landing gear of the aircraft to be towed and is used for judging whether the autopilot tractor bracket is aligned with the nose landing gear of the aircraft. Referring to fig. 2 and 3, the camera sensor is shown to be located on the midline of the end of the autopilot tractor cradle.
The camera sensor recognizes the nose landing gear of the airplane to be towed by adopting a computer vision measurement technology based on a CCD camera, namely, the nose landing gear of the airplane is provided with a limited number of characteristic points with known geometric dimensions and shapes, the automatic steering tractor is provided with the CCD camera, and a sensing module of the automatic steering platform obtains the relative position and the posture of the airplane and an automatic steering traction workshop through analyzing and processing images formed by the characteristic points on the CCD camera.
The CCD (Charge coupled Device) is a charge coupled device and may be referred to as a CCD image sensor. A CCD is a semiconductor device capable of converting an optical image into a digital signal. The tiny photosensitive substances implanted on the CCD are called pixels. The greater the number of pixels contained on a CCD, the higher the resolution of the picture it provides. The CCD acts like a film, but it converts image pixels into digital signals. The CCD has many capacitors arranged orderly, which can sense light and convert the image into digital signals. Each small capacitor can transfer its charge to its adjacent capacitor via control of an external circuit.
The camera sensor recognizes that the nose landing gear of the aircraft employs the YOLOv2 algorithm.
The YOLO algorithm solves the target detection as a regression problem, and completes the input from the original image to the output of the object position and class based on a single end-to-end network. The YOLOv2 introduces the idea of an anchor box in a fast R-CNN on the basis of YOLO, improves the design of each network structure and each layer, uses a convolution layer to replace a full-connection layer of YOLO as an output layer, and combines coco object detection labeling data and imagenet object classification labeling data to train an object detection model, thereby greatly improving the recognition accuracy, speed, positioning accuracy and the like.
The process of identifying the nose landing gear of the aircraft by the camera sensor is as follows: the training of the aircraft nose landing gear identification model is finished in advance through a target classification and detection combined training method, and in the butt joint operation process, an automatic driving platform inputs images captured by a camera sensor into a YOLOv2 algorithm to finish the identification and positioning of the aircraft nose landing gear. Meanwhile, the front landing gear of the aircraft is provided with a limited number of feature points with known geometric dimensions and shapes, and the relative position and posture between the front landing gear of the aircraft and the bracket of the autopilot tractor are obtained through positioning the feature points. The aircraft nose landing gear is provided with 5 characteristic points, wherein 4 landing gear edges are round, 1 landing gear center is rectangular, the aircraft nose landing gear is provided with 5 characteristic points, the characteristic points are fixed, the structure is short, the identification is easy, and the identification accuracy is stable.
The device for carrying the nose landing gear of the airplane by the autopilot tractor bracket, namely the autopilot tractor, comprises a wheel holding clamping mechanism and a wheel holding jacking mechanism.
Automatic driving tractor v 1 And (3) the m/s speed reversing is close to the nose landing gear of the airplane to be pulled, and the camera sensor is used for identifying the nose landing gear of the airplane in the reversing process, so that the pose is adjusted until the bracket of the autopilot tractor is aligned with the nose landing gear of the airplane.
Wherein L is 0 The distance between the position and the nose landing gear of the aircraft is preset for an autopilot tractor.
The automatic steering platform comprises a sensing module and a decision module, wherein the sensing module of the automatic steering platform sends the relative position and posture of the airplane and an automatic steering traction workshop to the decision module in the process that the automatic steering tractor approaches to the nose landing gear of the airplane to be towed, the decision module sends a motion instruction to the control module through analyzing the relative position and posture, and the control module controls the automatic steering tractor to adjust the posture until the bracket is aligned with the nose landing gear of the airplane.
In this embodiment, the autopilot tractor has two vehicle-mounted lidars, a first vehicle-mounted lidar and a second vehicle-mounted lidar.
The first vehicle-mounted laser radar is used for measuring the distance between the tail end of the bracket of the autopilot tractor and the nose landing gear of the airplane to be towed, and continuously feeding back the measured distance to the autopilot platform; the second vehicle-mounted laser radar is used for detecting whether any obstacle exists around.
The first vehicle-mounted laser radar uses a solid-state laser radar with a horizontal view angle and a vertical view angle of 120 degrees and 25 degrees respectively, wherein the range of the horizontal view angle is [ -60 degrees, +60 degrees ] ], and the range of the vertical view angle is [ -12.5 degrees, +12.5 degrees ] ]. The PTOF ranging method is adopted for measuring the distance between the tail end of the bracket of the autopilot tractor and the nose landing gear of the airplane to be towed. The PTOF distance measurement method has the core principle that a beam of laser with extremely short time is shot on a detected object, and the distance from the detector to a detected object is reversely pushed by directly measuring the flight time of the laser shot to the detected object and then returned to the detector.
The first vehicle-mounted laser radar emits a laser beam to the front of the first vehicle-mounted laser radar, calculates and analyzes the distance of the obstacle, and feeds back the distance to the automatic driving platform. The automatic driving platform extracts the distance l between the first vehicle laser radar and the nose landing gear of the airplane to be towed by analyzing and combining the camera sensor data 1 Thereby calculating the distance l between the end of the automatically piloted tractor carrier and the nose landing gear of the aircraft to be towed 2 。
l 2 ＝l 1 -a
Wherein a is the distance between the first vehicle-mounted laser radar and the tail end of the bracket of the automatic driving tractor, and a can be determined according to the size of the automatic driving tractor and is 0.2m-0.5m.
The second vehicle-mounted laser radar uses 32-line laser radars with a horizontal view angle and a vertical view angle of 360 degrees and 40 degrees respectively, namely the second vehicle-mounted laser radar can emit 32 lasers for scanning the surrounding environment. The second vehicle-mounted laser radar emits laser beams to the periphery, the generated point cloud is processed, the three-dimensional boundary box is used for detecting obstacles, the drivable area is segmented in real time, and information is fed back to the automatic driving platform.
And S3, when the autopilot tractor reaches a preset position, the distance between the tail end of the autopilot tractor bracket and the nose landing gear of the airplane to be towed reaches a specified value, the autopilot system adjusts the speed of the autopilot tractor and drives in a uniform deceleration mode, and meanwhile, the speed of the autopilot tractor bracket is 0 when the tail end of the autopilot tractor bracket contacts with the nose landing gear of the airplane to be towed.
And the distance between the tail end of the bracket of the autopilot tractor and the nose landing gear of the airplane to be towed reaches a specified value, namely the autopilot tractor reaches a preset position. The preset position is the front of the nose landing gear of the airplaneSquare L 0 m, at this time, the control module of the autopilot platform adjusts the speed of the autopilot tractor to v 2 m/s。
Due to the set v 1 And v 2 Are very small and have small phase difference, and the speed reduction process during conversion can be ignored
L 0 According to the requirements of the docking operation and the size of the field, 2-3m can be taken.
v 2 According to the requirements of the butt joint operation and the determination of L0, 0.5-0.6m/s can be adopted.
The automatic steering tractor just decelerates to 0 speed and the acceleration is a when the tail end of the bracket of the automatic steering tractor contacts with the nose landing gear of the airplane to be towed 0 。
S4, after the tail end of the bracket of the automatic steering tractor contacts with the nose landing gear of the airplane to be towed, the wheel holding clamping mechanism clamps the nose landing gear of the airplane, and the wheel holding jacking mechanism lifts the nose landing gear of the airplane, so that the docking is completed.
Example 2
The present embodiment provides an autopilot tractor and aircraft docking system, with reference to fig. 4.
The autopilot tractor and aircraft docking system includes a variety of sensors, autopilot platforms, and an aircraft communication device.
The sensor comprises a high-precision positioning module, a camera sensor and a vehicle-mounted laser radar.
The high-precision positioning module comprises, but is not limited to, a satellite antenna, an inertial/satellite combined navigation host, upper computer software and the like, and is respectively used for receiving satellite signals, calculating and providing multi-parameter navigation information, assisting in positioning, analyzing data and the like.
The camera sensor is used for identifying the nose landing gear of the aircraft to be towed.
The camera sensor recognizes that the nose landing gear of the airplane to be towed adopts a computer vision measurement technology based on a CCD camera, namely, the nose landing gear of the airplane is provided with a limited number of feature points with known geometric dimensions and shapes, the automatic steering tractor is provided with the CCD camera, and a sensing module of the automatic steering platform obtains the relative position and the posture of the airplane and an automatic steering traction workshop through the analysis and the processing of images formed by the feature points on the CCD camera.
The CCD (Charge coupled Device) is a charge coupled device and may be referred to as a CCD image sensor. A CCD is a semiconductor device capable of converting an optical image into a digital signal. The tiny photosensitive substances implanted on the CCD are called pixels. The greater the number of pixels contained on a CCD, the higher the resolution of the picture it provides. The CCD acts like a film, but it converts image pixels into digital signals. The CCD has many capacitors arranged orderly, which can sense light and convert the image into digital signals. Each small capacitor can transfer its charge to its adjacent capacitor via control of an external circuit.
The CCD camera sensor has small volume, light weight, no influence of magnetic field, vibration resistance and impact resistance.
The vehicle-mounted laser radar comprises a vehicle-mounted laser radar A and a vehicle-mounted laser radar B.
The vehicle-mounted laser radar A is used for measuring the distance between the tail end of the bracket of the autopilot tractor and the nose landing gear of the airplane to be towed, and continuously feeding back the measured distance to the autopilot platform; the vehicle-mounted laser radar B is used for detecting whether any obstacle exists around.
The vehicle-mounted laser radar A uses a solid-state laser radar with a horizontal view angle and a vertical view angle of 120 degrees and 25 degrees respectively, wherein the range of the horizontal view angle is [ -60 degrees, +60 degrees ] ], and the range of the vertical view angle is [ -12.5 degrees, +12.5 degrees ] ]. The PTOF ranging method is adopted for measuring the distance between the tail end of the bracket of the autopilot tractor and the nose landing gear of the airplane to be towed. The PTOF distance measurement method has the core principle that a beam of laser with extremely short time is shot on a detected object, and the distance from the detector to a detected object is reversely pushed by directly measuring the flight time of the laser shot to the detected object and then returned to the detector.
The vehicle-mounted laser radar B uses 32-line laser radars with a horizontal view angle and a vertical view angle of 360 degrees and 40 degrees respectively, namely, the vehicle-mounted laser radar B can emit 32 lasers for scanning the surrounding environment. The laser radar B emits laser beams to the periphery, the generated point cloud is processed, the three-dimensional boundary box is used for detecting obstacles, the drivable area is segmented in real time, and information is fed back to the automatic driving platform.
The automatic driving platform mainly comprises a sensing module, a decision module and a control module.
The sensing module is used for receiving information acquired by the multiple sensors and carrying out distributed fusion on the information, namely, carrying out local processing on the original data acquired by each independent sensor, and then sending the result into the information fusion center for intelligent optimization and combination to acquire a final result.
The decision modules are divided into three layers: path planning, behavior decision-making, and motion planning. Firstly, a path planning layer generates a global path, a behavior decision layer combines information received from a perception module to make a specific behavior decision after receiving the global path, and finally, a motion planning layer plans and generates a track meeting specific constraint conditions according to the specific behavior decision, and the track is used as input of a control module to determine a final running path of a vehicle.
The control module adopts PID control, and generates control commands for the bottom accelerator, the brake, the steering wheel and the gear shift lever of the automatic driving tractor according to the planned driving track and speed and the current position, gesture and speed, so that the automatic driving tractor can drive along the target track at the target speed and acceleration.
The vehicle-mounted communication equipment comprises an onboard terminal installed on an airplane and a vehicle-mounted terminal installed on an autopilot tractor, and a communication network between the onboard terminal and the vehicle-mounted terminal is established through 5G aeroMACS.
In the automatic steering tractor and airplane docking system, a sensing module of the automatic steering platform receives information, which is acquired by a plurality of sensors including a high-precision positioning module, a camera sensor and a vehicle-mounted laser radar, about the position information and the attitude information of the airplane to be towed, the distance between the tail end of a bracket of the airplane to be towed and the nose landing gear of the airplane to be towed and whether any obstacle exists around the bracket of the automatic steering tractor, and the information of the original data acquired by the plurality of sensors is independently processed, and then the processed result is input to an information fusion center for intelligent optimization and combination to acquire a final result.
The decision modules are divided into three layers: path planning, behavior decision-making, and motion planning.
The path planning layer generates a global path.
After the behavior decision layer receives the generated global path, information is read from the perception module:
and obtaining the starting point position of the docking operation of the autopilot tractor and the airplane to be towed and the course angle of the airplane to be towed by the high-precision positioning module.
And identifying the nose landing gear of the airplane to be towed by a camera sensor, and obtaining the relative position and the posture of the airplane and an autopilot towing workshop through image analysis and processing on the camera sensor, so as to check whether the autopilot tractor bracket is aligned with the nose landing gear of the airplane to be towed.
And measuring the distance between the tail end of the bracket of the autopilot tractor and the nose landing gear of the airplane to be towed by the vehicle-mounted laser radar A, and feeding back the distance in real time.
And detecting whether any obstacle exists around the running path of the automatic driving tractor by the vehicle-mounted laser radar B.
After obtaining the information of the starting point position of the docking operation of the autopilot tractor and the airplane to be towed and the course angle of the airplane to be towed, the behavior decision layer makes a specific behavior decision, approaches to the starting point position of the docking operation, and adjusts the course angle of the autopilot tractor and the course angle of the airplane to be towed in the approach process. And the motion planning layer generates a track meeting specific constraint conditions according to the specific behavior decision plan, and the track is used as input of the control module to determine the final driving path of the vehicle.
After the autopilot tractor reaches the starting point position of the docking operation, the autopilot tractor approaches to the nose landing gear of the airplane to be towed, the nose landing gear of the airplane to be towed is identified through a camera sensor in the approaching process, whether the autopilot tractor bracket is aligned with the nose landing gear of the airplane to be towed or not is observed in real time, and the autopilot tractor bracket and the nose landing gear of the airplane to be towed are continuously adjusted so as to be aligned. And the motion planning layer generates a track meeting specific constraint conditions according to the specific behavior decision plan, and the track is used as input of the control module to determine the final driving path of the vehicle. And enabling the autopilot tractor to approach the aircraft to be towed in a uniform deceleration mode, and finally enabling the speed of the autopilot tractor to be 0 when the autopilot tractor bracket is in contact with the nose landing gear of the aircraft to be towed.
In the approach process, the vehicle-mounted laser radar A measures the distance between the tail end of the bracket of the autopilot tractor and the nose landing gear of the airplane to be towed in real time and continuously feeds the distance back to the autopilot platform, and the vehicle-mounted laser radar B detects whether any obstacle exists around. The motion planning layer plans a path to avoid the obstacle, and the physical quantity such as the advancing speed, angle and the like of the automatic driving tractor are timely adjusted.
The control module processes the data information transmitted by the motion planning layer, and generates control commands for the bottom accelerator, the brake, the steering wheel and the gear shift lever of the automatic driving tractor according to the planned driving track and speed and the current position, posture and speed, so that the automatic driving tractor can drive along the target track at the target speed and acceleration.
An onboard terminal is installed on the aircraft and an onboard terminal is installed on the autopilot tractor, both communicating through 5G AeroMACS. The AeroMACS is Aeronautical Mobile Airport Communications System, namely an aviation airport mobile communication system.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present application, and are not meant to limit the scope of the invention, but to limit the scope of the invention.
Claims (8)
1. A method of interfacing an autopilot tractor with an aircraft, comprising:
s1, an automatic steering platform acquires position information and attitude information of an aircraft to be towed through a high-precision positioning module, and a control module controls an automatic steering tractor to reach a starting point of docking operation with the aircraft to be towed; meanwhile, the automatic steering tractor is controlled to adjust the course angle to be consistent with the course angle of the airplane to be towed;
s2, after the autopilot tractor reaches a docking operation starting point and the course angle of the autopilot tractor is consistent with the course angle of the airplane to be towed, the autopilot tractor starts to approach the airplane to be towed, a camera sensor on the autopilot tractor identifies the nose landing gear of the airplane to be towed, whether the autopilot tractor bracket is aligned with the nose landing gear of the airplane to be towed is judged, the distance between the tail end of the autopilot tractor bracket and the nose landing gear of the airplane to be towed and whether obstacles exist around the tail end of the autopilot tractor bracket and the nose landing gear of the airplane to be towed are detected through a plurality of vehicle-mounted laser radars respectively in real time, and the method for identifying the nose landing gear by the camera sensor is as follows: firstly, training a nose landing gear identification model of an airplane to be towed, inputting a captured image into an algorithm network by an autopilot platform in the process of docking the autopilot tractor with the airplane to be towed so as to realize the identification of the nose landing gear of the airplane, and simultaneously, installing 5 characteristic points on the nose landing gear of the airplane, wherein 4 edges of the landing gear are round, 1 center of the landing gear is rectangular, and positioning the characteristic points to obtain the relative position and posture between the nose landing gear of the airplane and the bracket of the autopilot tractor so as to realize the positioning and posture identification of the nose landing gear of the airplane;
s3, when the automatic steering tractor reaches a preset position, the automatic steering system adjusts the speed of the automatic steering tractor and drives in a uniform deceleration mode, so that the speed of the automatic steering tractor is 0 when the tail end of the bracket of the automatic steering tractor is contacted with the nose landing gear of the airplane to be towed;
s4, after the tail end of the bracket of the automatic steering tractor contacts with the nose landing gear of the airplane to be towed, the wheel holding clamping mechanism clamps the nose landing gear of the airplane, and the wheel holding jacking mechanism lifts the nose landing gear of the airplane, so that the docking is completed.
2. The method of docking an autopilot tractor with an aircraft of claim 1 wherein v when the autopilot tractor reaches the start of the docking operation 1 m/s speed reversing is close to the nose landing gear of the airplane to be pulled, the camera sensor is used for identifying the nose landing gear of the airplane to be pulled in the reversing process, the pose is adjusted until the tractor bracket is aligned with the nose landing gear of the airplane, and the speed v 1 Can be expressed as:
wherein L is the distance between the starting point position of the docking operation and the nose landing gear of the airplane, L 0 The distance between the position and the nose landing gear of the aircraft is preset for the tractor.
3. The method for interfacing an autopilot tractor with an aircraft according to claim 1, wherein the onboard lidar comprises a first onboard lidar and a second onboard lidar, wherein the distance between the tail end of the tractor bracket and the nose landing gear of the aircraft to be towed can be calculated by the first onboard lidar, and the distance l between the first onboard lidar and the nose landing gear of the aircraft to be towed is extracted by combining the first onboard lidar data with the camera sensor data 1 Calculating the distance l between the tail end of the bracket of the automatic steering tractor and the nose landing gear of the airplane to be towed 2 Denoted by l 2 ＝l 1 -a, wherein a is the distance of the first vehicle-mounted lidar from the end of the autopilot tractor carrier.
4. The autopilot tractor and aircraft docking method of claim 1 wherein the autopilot platform adjusts the autopilot tractor speed v when the autopilot tractor reaches a tractor preset position 2 m/s, from a tractor preset position to the tractor at the autopilot tractorIn the process of contacting the tail end of the carriage with the nose landing gear of the airplane to be towed, the tractor performs uniform deceleration movement, and the acceleration of the tractor is a 0 Expressed as:
5. an autopilot tractor and aircraft docking system employing an autopilot tractor and aircraft docking method of claim 1, comprising:
the system comprises a plurality of sensors, a sensor module and a control module, wherein the sensors comprise a high-precision positioning module and are used for acquiring position information and course angle information of an airplane to be towed; a camera sensor for identifying the nose landing gear of the aircraft to be towed; the vehicle-mounted laser radar is used for measuring the distance between the tail end of the tractor bracket and the front landing gear of the airplane to be towed and the obstacle on the periphery of the tractor;
the automatic driving platform comprises a sensing module, wherein the sensing module is used for receiving information acquired by various sensors and processing the information; the decision module is used for generating a tractor travelling track meeting specific constraint conditions according to the information processed by the sensing module; the control module is used for controlling an internal execution device of the tractor according to the information of the decision module combined with the actual situation;
and the vehicle-to-machine communication equipment is used for information interaction between the tractor and the airplane to be towed.
6. The autopilot tractor and aircraft docking system of claim 5 wherein the decision making module includes a path planning layer, a behavior decision layer and a motion planning layer, the path planning layer generating a global path, the behavior decision layer, upon receiving the global path, combining information received from the perception module to make a specific behavior decision, the motion planning layer planning to generate a trajectory meeting a specific constraint condition based on the specific behavior decision.
7. An autopilot tractor and aircraft docking system as set forth in claim 6 wherein the trajectory planned by the motion planning layer is transmitted as input to the control module as the final vehicle travel path.
8. The autopilot tractor and aircraft docking system of claim 5 wherein the sensing module is configured to receive information acquired by the plurality of sensors and to perform distributed fusion of the information, to locally process raw data acquired by each of the plurality of independent sensors, and to send the results to the information fusion center for intelligent optimization and combination to obtain final results.
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| CN114810697A (en) * | 2022-06-02 | 2022-07-29 | 上海天华云应用技术有限公司 | Hydraulic system of wheel holding mechanism |
| CN115352648A (en) * | 2022-09-21 | 2022-11-18 | 亿航智能设备（广州）有限公司 | Aircraft towing device |
| CN115556958A (en) * | 2022-12-05 | 2023-01-03 | 江苏天一航空工业股份有限公司 | Automatic wheel system of embracing of butt joint of aircraft rodless tractor |
| CN116300971B (en) * | 2023-05-17 | 2023-09-01 | 中国民航大学 | Traction sliding control method and device for civil aircraft, tractor and storage medium |
| CN116573152B (en) * | 2023-07-13 | 2023-09-19 | 中国人民解放军空军工程大学 | Omnidirectional driving aircraft rescue carrier with dynamic self-adjusting platform |
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