Aircraft tractor docking method based on intelligent technology

Abstract

The invention discloses an aircraft tractor docking method based on an intelligent technology, which comprises a sensor fusion system, an automatic control system and a man-machine interaction system, the sensor fusion system is responsible for comprehensively sensing the surrounding environment, the automatic control system is responsible for realizing smooth docking action, and the man-machine interaction system is responsible for performing man-machine interaction on the sensor fusion system. The man-machine interaction system is responsible for monitoring and intervening in the docking process, and the safety and reliability of operation are ensured. Compared with a traditional manual operation mode, the aircraft tractor docking method based on the intelligent technology shows remarkable advantages in the aspects of docking precision, efficiency and safety, docking time can be remarkably shortened, and operation risks can be remarkably reduced.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of airport special vehicles, and is an aircraft towing vehicle docking method based on intelligent technology. BACKGROUND

[0002] In recent years, automation technology has been widely applied in the aviation industry. Automation technology can realize autonomous execution of tasks and intelligent decision-making, thereby reducing the dependence on manual operation and improving the efficiency and accuracy of the docking process.

[0003] With the continuous development of the aviation industry and the increase in the number of flights, the efficiency and safety of aircraft ground operations have become a focus of attention. The towing and docking process of aircraft is crucial to aviation operations, but the traditional aircraft towing vehicle docking method usually relies on manual operation, which is limited by personnel skills and experience, and may have certain instability and errors. In order to improve the accuracy, efficiency and safety of the aircraft towing vehicle docking process, intelligent technology is introduced into the research and application of the aircraft towing vehicle docking method. SUMMARY

[0004] The application discloses an aircraft towing vehicle docking method based on intelligent technology. The technology integrates sensor data, autonomous navigation and control, and the intelligent system and the human-machine interface intervene in the intelligent system to realize accurate docking of the aircraft and improve the automation level and efficiency of the docking process.

[0005] In order to achieve the above-mentioned purposes, the application adopts the following technical solutions:

[0006] As a preferred embodiment of the application, a plurality of sensors are used to perceive the surrounding environment and the position of the aircraft, and a real-time environment model is established using sensor data.

[0007] As a preferred embodiment of the application, a path planning algorithm using deep learning technology (such as neural network) is used for complex airport environments and aircraft configurations. The algorithm can learn and generate path planning results directly from sensor data. These algorithms can better adapt to complex scenarios and achieve high path planning performance after training. These algorithms can determine the optimal towing vehicle motion trajectory to accurately dock the target aircraft along the predetermined path.

[0008] As a preferred embodiment of the application, the intelligent system continuously monitors the status of the aircraft towing vehicle and the aircraft to ensure the stability and safety of the docking process. When necessary, the operator can intervene in the intelligent system through the human-machine interface, such as adjusting the target position, modifying the path planning, etc.

[0009] The application adopts the above scheme, and through integration of sensor data, autonomous navigation and control, the intelligent system can reduce instability in the docking process of the aircraft tractor and improve accuracy, efficiency and safety of the docking process. BRIEF DESCRIPTION OF DRAWINGS

[0010] Figure 1 is a main system of the aircraft tractor docking method based on intelligent technology;

[0011] Figure 2 is Figure 1 a flowchart of the sensor fusion system in the embodiment;

[0012] Figure 3 is Figure 1 a flowchart of autonomous navigation and control in the embodiment. DETAILED DESCRIPTION

[0013] The technical solutions of the application are further described below with reference to the drawings.

[0014] Figure 1 shows a main system of the aircraft tractor docking method based on intelligent technology:

[0015] The sensor fusion system integrates and fuses data from different sensors to improve the accuracy and reliability of environmental perception.

[0016] Specifically, the vehicle is provided with ultrasonic modules, laser radars, cameras, GPS, and other sensor modules. Each sensor regularly collects environmental data such as distance, position, speed, and attitude. The collected data may have noise, errors, and uncertainties. The collected data is preprocessed, including filtering, denoising, calibration, etc., to reduce data errors and improve accuracy. The data of different sensors may not be consistent in time sequence, so the data is time-aligned to ensure that the data is consistent in time. Then, the data from different sensors is associated to establish the corresponding relationship between them for subsequent fusion processing. The selected fusion algorithm integrates and fuses the data of different sensors to generate a consistent environmental model. The application uses a multi-hypothesis tracking algorithm to integrate and fuse the data of different sensors to generate a consistent environmental model. With the passage of time and continuous collection of sensor data, the environmental model is constantly updated to reflect the current state of the environment. The fused environmental model is output to other parts of the system (such as path planning, target detection, etc.) for more accurate and reliable environmental perception.

[0017] The autonomous navigation and control system uses the environmental model output by the sensor fusion system to achieve navigation and docking functions using deep learning algorithms.

[0018] Specifically, based on the environment model output by the sensor fusion system, the target aircraft position and obstacle information, the optimal path of the aircraft tug to the target aircraft is calculated using a path planning algorithm. The results of path planning are converted into actual motion trajectories, and a trajectory tracking controller is designed to enable the tug to move accurately according to the planned trajectory. The aircraft tug continuously perceives the surrounding environment and the state of the target aircraft through the real-time updated environment model, ensuring real-time acquisition of the required information. Positioning technologies such as GPS, laser radar, etc. are used to estimate the position of the tug in real time, maintaining the perception of the environment. An autonomous controller is designed to calculate the speed, steering angle and other control instructions of the tug based on the results of path planning and trajectory tracking. The control instructions are continuously updated to enable the tug to make appropriate adjustments according to the actual situation, ensuring the stability and safety of the docking process.

[0019] The human-computer interaction system assists the intelligent control system.

[0020] Specifically, the human-computer interaction system is wirelessly connected with the aircraft tug, and through the human-computer interaction interface, intervention on the intelligent system can be realized, such as adjusting the target position, modifying the path planning, etc., and immediate feedback can be provided to ensure that the user can clearly understand the state and running results of the aircraft tug when operating.

[0021] In the actual docking process, the present application reduces the error caused by a single sensor based on the environment model output by the sensor fusion system, realizes real-time path planning, considers factors such as the current position, predicted position and target position of the docking target, adapts to different docking scenarios and dynamic environmental changes, and also uses the human-computer interaction system to realize monitoring and intervention on the tug, ensuring the efficiency and safety of the docking process.

Claims

1. An intelligent technology-based aircraft tug docking method, characterized by Comprise: Sensing components: sensors for collecting the surrounding environment, including lidar, camera, ultrasonic sensor, etc., to perceive the position and state of the target aircraft and surrounding obstacles in real time. Path planning component: through the use of path planning algorithm, based on map information and target aircraft position, calculate the optimal path from the aircraft tractor to the target aircraft. Sensor fusion system: based on the sensing components, through the fusion algorithm, realize the construction and maintenance of the airport ground map information, and update the map in real time to adapt to environmental changes Autonomous navigation and control system: based on the sensor fusion system and path planning component, realize the autonomous navigation of the aircraft tractor, ensure its safe and efficient arrival at the target aircraft position.

2. The method of claim 1, wherein, Further including human-computer interaction interface, for operator and system interaction, monitoring the docking process, intervention and adjustment of the tractor action, to ensure the safety of docking.

3. The method of claim 1, wherein, The intelligent technology includes multi-hypothesis tracking algorithm and deep learning algorithm, which is used to realize more accurate and intelligent environment perception and docking control.

Images