CBL - Campus del Baix Llobregat

Projecte llegit

Títol: GUIDING DRON USING COMPUTER VISION


Estudiants que han llegit aquest projecte:


Director/a: REMONDO BUENO, DAVID

Departament: ENTEL

Títol: GUIDING DRON USING COMPUTER VISION

Data inici oferta: 15-02-2021     Data finalització oferta: 15-10-2021



Estudis d'assignació del projecte:
    MU DRONS
Tipus: Individual
 
Lloc de realització: Fora UPC    
 
        Supervisor/a extern: Narcís Codina Candel
        Institució/Empresa: elarco design
        Titulació del Director/a: Design Engineering Degree
 
Paraules clau:
computer vision, uav, electronic design, product design,
 
Descripció del contingut i pla d'activitats:
The tasks and aim of this collaboration will be focused on the
analysis, development and application of a functional prototype
drone that uses pose recognition and obstacle avoidance for indoor
activities.
 
Overview (resum en anglès):
The project aims to use computer vision and machine learning to control Tello and Tello Edu Drones.
The main use of this project is for educational and experimental purposes for upcoming future uses. I got inspired by the developments in the field of computer vision and pose estimation. As people are doing some much instructing and innovative things using this Drone and combined it with AI, Computer Vision, and Machine learning.
This project helps anyone who likes to learn from the beginning even they don¿t have any prior knowledge of programming or Computer Vision. They can able to build a simple application and also provide the basic knowledge for the development of a more complex application. As a final objective, the main application is proposed, are consists of a drone that can be controlled using body poses or the movement of the body i.e., following the person by maintaining a constant safety distance and following the commands given by the instructor.
To start programming Tello or Tello EDU drone, it is based on a series of scripts and functions which is already been developed. So, that SDK is used as a guide to developing a new tello custom SDK to develop a complex and interactive application.
By using this custom template, we can develop several basic mission scripts/programs.
For the main application, different experiments were carried out to check which method is better in extracting the body key points/Landmarks in real-time in which low computing power is required or in other words no or less GPU power is required. As a result, I come across the Google AI open source ¿MediaPipe Machine Learning¿ platform, which provides a cross-platform, customizable ML solution for live and streaming media. Which is used for advanced application in this project.


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