QTCOPTER TECHNION

We built a platform to be used to create autonomous indoor flight capable drones and implemented a system based on computer vision to utilize and demonstrate this platform by performing four tasks, as described by a national contest sponsored by the Pearls of Wisdom voluntary association.

Our Project

Project Description

We built a platform to be used to create autonomous indoor flight capable drones and implemented a system based on computer vision to utilize and demonstrate this platform by performing four tasks, as described by a national contest sponsored by the Pearls of Wisdom voluntary association. Currently, such platforms are researched from commercial and academic points of view, but no finished products have been released.

The computer vision part of the project is responsible for communicating with the quadcopter’s navigation module, in order to guide the quadcopter to the next target, identify key objects and trigger the execution of various required auxiliary actions. The software will run on an ARM-based companion computer running Linux, mounted on the drone. It will receive images from one or multiple high speed cameras on the quadcopter and ROS messages from the navigation module running on the same computer. The OpenCV library will be used to implement the required functionalities.

The Team

Noam Yogev

Control

Roee Mazor

Image Processing

Efi Shtain

Control

Vasily Vitchevsky

Image Processing

Sergey buh

Integration

Alex Bogachenko

Integration

Daniel Joseph

Mechanics

Fun Times and Crash Times

Doing some lab testing 1

Testing basic commands 1

Some painful crash

Doing some lab testing 2

Doing some lab testing 3

Testing basic commands 2