Prediction based Auto-Pilot Interface for Drone to Object Chasing using Historical TSPI Data

🍻 TEAM : Beer per Day

👨‍💻 MEMBERS

Name	Univ.	Dept.
🤴 Shinhyoung Jang	Chungnam Natl. Univ.	Computer Science & Engineering
😃 Byeonghwi Park	Chungnam Natl. Univ.	Computer Science & Engineering
😃 Juheon Jeong	Chungnam Natl. Univ.	Computer Science & Engineering
😃 Jack Mahedy	Purdue Univ.	Computer and Information Technology
😃 Nebey Gebreslassie	Purdue Univ.	Computer and Information Technology

Research problem statement

🛸 Motivation : How to classify the object drone or not?

1. Using digital zoom in the picture
2. Using lens with good performance

• But these have the problems that lossing data or high cost

🍀 So, what is the best "Approach" for the prediction?

• Suggest making drone to chase the object
• It also provides to use combat drone like self-destructive

🔧 Requirement

1. To improve chasing, use the prediction algorithm or machine learning model because of the latency of processes
2. Make a interface to chase specified position

📚 Research novelty

Making interface for drone chasing using historical TSPI Data

📁 Directory

└── Beer_per_Day/
    ├── code/
    │   └── feature/
    │       └── overview.png
    |   └── Interface/
    |       └── GoogleMap/
    |       └── ReadMe.md
    │   └── predictTrajectory/
    |       └── UAVDataset/
    |       └── DroneTrajectory.ipynb
    |   └── testPos_code/
    |       └── test_location/
    |       └── Readme.md
    ├── paper/
    │   └── paper.pdf
    ├── presentation/
    │   └── KSW 2023 Winter mid_presentation Beer_per_Day.pptx
    ├── weeklyreport/
    │   ├── K-SW 2023 Winter 01120203 Beer_per_Day.pdf
    │   ├── K-SW 2023 Winter 01200203 Beer_per_Day.pdf
    │   ├── K-SW 2023 Winter 01270203 Beer_per_Day.pdf
    │   ├── K-SW 2023 Winter 02030203 Beer_per_Day.pdf
    │   ├── K-SW 2023 Winter 02100203 Beer_per_Day.pdf
    │   └── K-SW 2023 Winter 02170203 Beer_per_Day.pdf
    └── Readme.md

🗒 Code

• Interface: Android Application Interface
• predictTrajectory: Machine Learning models to predict coordinates
• testPos_code: save the array which has list of coordinates

🌍 Environment settings

To know the Environment settings, please refer the table

Code	Directory
Interface	📂 Beer_per_Day/code/Interface/ReadMe.md
predictTrajectory	📂 Beer_per_Day/code/predictTrajectory/DroneTrajectory.ipynb
testPos_code	📂 Beer_per_Day/code/testPos_code/ReadMe.md