Pursuant to 35 U.S.C. § 119 and the Paris Convention Treaty, this application claims foreign priority to Chinese Patent Application No. 202010363994.9 filed Apr. 30, 2020, the contents of which, including any intervening amendments thereto, are incorporated herein by reference. Inquiries from the public to applicants or assignees concerning this document or the related applications should be directed to: Matthias Scholl P. C., Attn.: Dr. Matthias Scholl Esq., 245 First Street, 18th Floor, Cambridge, Mass. 02142.
The disclosure relates to the field of automatic control field. Specifically, it relates to a method of calculating the wheel frame walking strategy based on using feedback information extracted from a visual sensor and the current attributes of the passenger boarding bridge in the automatic docking of the boarding bridge.
A boarding bridge is a movable passage which commonly extends from a terminal building (or an airplane terminal gate) to an airplane, allowing passengers to board and disembark.
At present, the docking and evacuation of passenger boarding bridges are controlled by operators in manual mode. The operation process of passenger boarding bridges is very complicated, which places high requirements on the operating skills of operators.
Improper operation can cause very serious problems, such as deformation or damage of the aircraft fuselage, damage of the engine cowling, etc. In addition, the training and management of passenger boarding bridge operators also require higher costs. Therefore, it is necessary to realize the automatic docking of the boarding bridge.
If the boarding bridge can realize automatic docking, it will be more efficient and safer than manual docking. In the intelligent automatic docking of boarding bridges, people have explored in many ways how to realize the automatic docking of boarding bridges, but so far, no practical application has been found.
With the continuous development of computer vision technology and automation control technology, it is possible to automate the docking of the boarding bridge. After consulting a large number of studies, no walking control strategy for the automatic docking system of passenger boarding bridges was found. Therefore, it is necessary to timely study a set of methods for calculating wheel frame control strategies for the passenger boarding bridge automatic docking system.
The purpose of the disclosure is to propose a method for calculating the optimal wheel position control angle of the passenger boarding bridge docking with the aircraft door. By modeling the process of passenger boarding bridge docking with aircraft door, and calculating the best walking angle according to the current state attributes of passenger boarding bridge to improve docking efficiency.
The disclosure proposes a method for calculating the optimal wheel position control angle of a boarding bridge docking an aircraft door, which needs to ensure the following three premises.
Ensuring that the bridgehead of the boarding bridge is at the same height as the aircraft door and that the bridgehead is parallel to the aircraft fuselage (that is, the outer edge of the boarding bridge is parallel to the aircraft fuselage). This premise can be achieved by installing distance detection sensors (such as ultrasonic sensors) on the left and right sides of the bridgehead, and adjusting the angle of the bridgehead so that the distance measurement values of the two ultrasonic sensors are the same to achieve the bridgehead parallel to the aircraft fuselage.
Obtaining the relative position of the door of the aircraft to be docked and the bridgehead of the passenger boarding bridge through visual sensors or other methods. This premise can be achieved by installing a visual sensor on the inner side of the boarding bridge head (the disclosure is to install a visual sensor to obtain the relative distance between the bridge head and the aircraft door). Using vision to locate the aircraft door, and using a camera ranging method (such as the principle of Monocular Ranging, the RGBD camera with depth information, the principle of binocular distance measurement, etc.) to calculate the relative position of the bridge head of the boarding bridge and the aircraft door.
Measuring and obtaining the current attribute information of the passenger boarding bridge via sensors, the specific process is as follows:
(1) The straight-line distance from the center point of the wheel frame of the boarding bridge to the center point of the bridgehead (fixed value)
(2) The length of the boarding bridge body can be obtained by the distance sensor that comes with the boarding bridge (change value)
(3) The bridgehead angle of the boarding bridge can be obtained by the bridgehead angle sensor that comes with the boarding bridge (change value)
Under the above three premises, the process of docking the boarding bridge with the cabin door is analyzed. Because the control angle of the boarding bridge wheel position is the angle in the horizontal direction, the horizontal direction of the boarding bridge docking process is analyzed and modeled.
The boarding bridge docking model is shown in
In order to calculate the target wheel frame angle (∠M′MH), the length of D′D″ in the right triangle ΔDD′D″ is measured by the bridgehead distance sensor, and the length of DD′ is obtained by the vision sensor. So, the length of DD″ and the size of ∠DD′D″ can be obtained from the Pythagorean theorem and the law of cosines. The specific calculation process is as follows:
Known: the length of DD′ and D′D″ in the right angle ΔDD′D″ is known
Solving: the length of the line segment DD″ and the angle of ∠DD″D′
From the Pythagorean theorem:
DD″=√{square root over (DD′2+D′D″2)}
Obtained by the law of cosines:
The 110 DD′D″ solved in the above process is equal to the bridge head offset angle ∠A in
1. When the actual position of the aircraft door and the pillar are on the same side of the center point of the bridgehead as shown in
2. When the actual position of the aircraft door and the pillar are on both sides of the center point of the bridgehead as shown in
3. As shown in
4. As shown in
5. As shown in
Extracting ΔPMHH′M′ from
Known: In ΔPMHH′M′, the length of PH, MH, M′H′, HH′ and the outer angle ∠O are known, and MH=M′H′.
Solving: angle ∠HMM′
In the triangle ΔPHH′, from the law of cosines:
(PM′+M′H′)2=(PH)2+HH′2−2*(PH)*HH′*cos(π−∠O)
PM′=√{square root over ((PH)2+HH′2−2*(PH)*HH′*cos(π−∠O))}−M′H′
From the law of sines:
In the triangle ΔPMM′:
Simplify the above steps into a functional expression using only known quantities PH, MH, HH′, ∠O:
In the above formula:
Σ=√{square root over ((PH)2+HH′2−2*(PH)*HH′*cos(π−∠O))}
Through the above analysis and calculation process, the angle of the target wheel frame angle (∠HMM′) is obtained, which is the best wheel frame angle for controlling the docking of the boarding bridge under the above scenario.
The method for calculating the optimal wheel position control angle of a boarding bridge docking an aircraft door, comprising the steps of:
Step 1: Realizing premise 1 of this technology so that the bridgehead is parallel to the fuselage of the aircraft. Specific steps are as follows:
1. Installing a distance measuring sensor (such as an ultrasonic distance measuring sensor) on both sides of the bridgehead of the passenger boarding bridge, respectively. The recommended installation position is shown in
2. Collecting the ranging information of the sensors to rotate the bridgehead direction, making the bridgehead parallel to the aircraft fuselage.
3. Judging whether the bridgehead is parallel to the fuselage by comparing the measured values of the two distance measuring sensors. The standard is shown in
Step 2: Realizing premise 2 of this technology, installing a camera on the bridgehead to locate the position of the aircraft door relative to the bridgehead. Specific steps are as follows:
1. Installing a camera on the bridgehead. The installation position of the camera should be such that when the docking is completed, the center of the aircraft door coincides with the center of the camera picture, and the picture is placed in a horizontal and vertical direction (not inclined). The recommended installation location is shown in
2. Using machine learning, image processing and other methods to locate the precise position of the center of the aircraft door in the screen.
3. According to the distance measurement method such as monocular distance measurement principle or binocular distance measurement principle, the distance value of the deviation of the aircraft door in the horizontal direction is calculated as DD′.
4. Recording the distance from the current bridgehead to the aircraft as D′D″.
Step 3: Calculating the bridgehead tilt angle ∠DD″D′ size and DD″ length according to the following formula.
Step 4: Achieving premise 3 of this technology, measuring the horizontal distance from the center point of the wheel frame to the center point of the bridgehead and recording it as MH. Measuring the current bridge length and recording as PH. Measuring and recording the bridgehead angle as ∠B.
Step 5: Calculating the best wheel position control angle based on the results of the above steps. The specific calculation is as follows:
HH′=DD″, ∠A=∠DD″D′, ∠O=∠A+∠B
Then the four parameters of PH, MH, HH′ and outer angle ∠O are all known. ∠HMM′ can be obtained by the following formula which is the optimal wheel position control angle.
In the above formula:
Σ=√{square root over ((PH)2+HH′2−2*(PH)*HH′*cos(π−∠O))}
Step 6: After adjusting the wheel frame angle of the passenger boarding bridge calculated in step 5, the wheel frame is controlled to move forward and straight, and the bridgehead is automatically adjusted to make the bridgehead parallel to the aircraft fuselage according to the distance measuring sensors on both sides of the bridgehead. Controlling the boarding bridge to stop moving when the bridgehead is 5 cm away from the aircraft, and the docking ends.
The disclosure is mainly applied in the scenario where the automatic driving of the boarding bridge docks with the aircraft door, and requires certain hardware facilities and environment. When the data collected by the sensor is accurate, the disclosure can accurately calculate the optimal control angle of the wheel position, improve efficiency for docking, and avoid the situation of repeatedly operating the wheel position. In the disclosure, the optimal control angle of the wheel position can be obtained by only one calculation. In addition, the disclosure can perform multiple calculations during the docking process to reduce the deviation caused by the measurement accuracy of the sensor and improve the docking accuracy of the cabin door. After actual testing, the optimal wheel position control angle calculated by the disclosure can be more accurately docked with the hatch.
In the drawings, the following reference numbers are used: 1. Upright pillar (Fixed point), 2-1. Wheel frame center point, 2-2. Expected wheel frame center point, 2-3. Bridgehead center point, 2-4. Expected bridgehead center point, 2-5. Camera installation position, 2-6. Expected camera position, 2-7. Expected the aircraft door center, 3-1. Expected wheel frame angle, 3-2. Bridgehead angle ∠B, 3-3. Bridgehead offset angle ∠A, 3-4. Expected bridgehead tilt angle, 3-5. Outer angle ∠O=(∠A+∠B), 4. Camera perspective, 5-1. Expected aircraft door position, 5-2. Actual position of aircraft door, 6. Aircraft wing, 7. Aircraft nose, 8. Aircraft fuselage, 9. Upright pillars fixed point, 10. Current point of wheel frame, 11. Wheel frame target point, 12. Current point of bridgehead, 13. Bridgehead target point, 14-1. Installation location for the right distance sensor, 14-2. Installation location for the left distance sensor, 15. Aisle, 16. Bridgehead, 17. Side wall roller shutter, 18. Manual console, 19. Awnings, 20. Raised floor, 21. Pick-up platform, 22. Door protector, 23. Touch sensor, 24. Leveling wheel, 25. Front window, 26. Working lamp.
It will be obvious to those skilled in the art that changes and modifications may be made, and therefore, the aim in the appended claims is to cover all such changes and modifications.
Number | Date | Country | Kind |
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202010363994.9 | Apr 2020 | CN | national |