/MASC-Architecture

This projects addresses unmanned aerial vehicle (UAV) navigation and path planning under engine-out case for landing under severe weather using a Multi-Level Adaptation approach. This is a milestone in a novel autopilot framework, which enables a UAV under large uncertainties to perform safety maneuvers that are traditionally reserved for human pilots with sufficient experience. In addition, we present a high-fidelity simulation environment for fixed-wing aircraft to test and validate the approach under various uncertainties. For the proposed Multi-Level Adaptation autopilot framework, we present the design and analysis as well as the simulation results for the case of emergency landing due to engine failure under severe weather conditions, a challenging task for an autonomous aircraft.

Primary LanguageMATLABBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

Multi Level Adaptation for Automatic Landing with Engine Failure under Turbulence Uncertainties

This repository contains MASC Online navigation scheme, with support of Non linear guidance logic, a high fidelity simulation environment(X-Plane 11), and User Datagram Protocol (UDP) based interface. The system takes in landing zone coordinates and position coordinates where engine is malfunction. It later navigates the engine-out airplane to the approachable safty landing position in real-time. A demonstration of the system in clear weather can be found here

👀 Demo Videos

Alt text

This picture below is MASC Online Path Planning Architecture.

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📖 Useful material

[Paper]   [SITL Simulation Video In Clear Weather]   [SITL Simulation Video In Turbulent Weather]   [PPT slides]

[Stevens Institute of Technology SAS Lab]  

Features

  • Nonlinear Guidance Logic
  • Precise trajectory tracking
  • High fidelity simulation environment(X-Plane)
  • User Datagram Protocol (UDP) based Publisher and Subscriber
  • Decoupled longitudinal and lateral motion control
  • Light weight online path planning framework(Low computation demanded)

🔧 Dependencies

🔧 Installation

Set up input data channel and output data channel in X-Plane 11

drawing

Configure IP address in MATLAB/Simulink

  • The fixedWingPathFollowing model integrates the nonlinear guidane logic , UDP intterface with the high fidelity simulation environment. This model is to extract necessary information from the airplane status output bus signal and feed them into the waypoint follower to form a control loop. The model assembles the control and environment inputs for the guidance model block.

    open_system('fixedWingPathFollowing');

  • Configure sender and publisher: Please follow instructions shown in the picture to set up IP adddress for subscriber and publisher. Likewise IP address configuration box in X-Plane.

    drawing

Running MASC Examples

  1. Open the program in which define the engine-out latitude,longitude and altitude. and then first to put airplane to wherever the engine is broken. And then click the stop button at the up right corner of the X-Plane window. Client matlab program
  2. Set up the engine out global position in malfunction position configuration block
  3. Set up the airport coordinates in simulink framework
  4. Click the run button to start the simulink model first. After 10 to 15 seconds, click the start button in the up right corner of the X-Plane window. Only by doing this can avoid the possible X-plane crash.
sim("fixedWingPathFollowing");
  1. Run command in the matlab terminal to end this simulation.
close_system("fixedWingPathFollowing");

Step Response Test

  • Step response for high fidelity autopilot

     open_system('stepResponse');

  • Step response for low fidelity autopilot

     open_system('uavStepResponse');

Cite MASC

If MASC framework is helpful, please help to ⭐ this repo or recommend it to your friends 😊

Thank you for citing our MASC paper if you use any of this code:

@article{gu2022multi,
  title={Multi-level Adaptation for Automatic Landing with Engine Failure under Turbulent Weather},
  author={Gu, Haotian and Jafarnejadsani, Hamidreza},
  journal={arXiv preprint arXiv:2209.04132},
  year={2022}
}

📧 Contact

If you encounter some issue when reproducing this project, please email haotiangu1993@gmail.com or hgu8@stevens.edu.