About The Project

• This project solves a sub-problem related to another mission planning project for drones and UAVs. You can find another sub-problem of the mission planning project in this article.
• Note: Please refer to extract-article.pdf to learn more on the construction of the algorithm.

Getting Started

Prerequisites

Install tkinter

sudo apt-get install python3-tk

Installation

1. Clone the repo

   git clone https://github.com/mdiamantino/cyclic-flight-plan-travelling-salesman-problem.git

2. Enter the cloned directory and create a virtual environment

   cd cyclic-flight-plan-travelling-salesman-problem/

   python3 -m venv venv

3. Activate the virtual environment

   . venv/bin/activate

4. Install requirements

   pip3 install -r requirements.txt

Usage

• Run demo.py to find the cyclic path of maximal coverage inside the polygon [(0, 0), (6, 10), (6, 20), (10, 10), (10, 20), (14, 10), (14, 20), (20, 10), (14, 0), (14, 6)]

  python3 demo.py

• Or, use your own polygon's coordinates and vision radius : a value representing the field of vision of the drone (refer to the brief article). This value should be a multiple of 0.5 AND where 0.5 is the minimum value):

  python3 main.py

• Or, use the project as module:

  1. (if you are using the command-line interface)

  python3

  >>> from flight_plan_generator import get_best_route

  3. get_best_route(YOUR COORDINATES HERE, YOUR vision_radious HERE, [debug=True|False]) Example:

  >>> get_best_route([(5, 0), (2, 2), (0, 6), (6, 6), (6, 14), (12, 12), (16, 8), (20, 15), (20, 5), (16, 0)], 0.5, debug=True)

Contact

Mark Diamantino Caribé - Mark.Diamantinocaribe@student.kulevuen.be - LinkedIn

Project Link: https://github.com/mdiamantino/cyclic-flight-plan-travelling-salesman-problem