Vision-based precision landing for UAVs

This project aims to develop a robust vision-based precision landing system that enables drones to dock accurately in challenging environmental conditions including rain, fog, and darkness. The system leverages computer vision technology mounted on an ARA-408 drone to identify visual markers on a docking station, calculate trajectory, and execute precise landings when traditional GPS guidance may be compromised. This collaborative effort between ARA Robotique and Polytechnique Montreal represents an advancement in autonomous drone capabilities for monitoring applications, ensuring reliable operations in environments where conventional navigation systems might fail.

Faculty Supervisor:

Giovanni Beltrame

Student:

Partner:

ARA Robotique

Discipline:

Computer science

Sector:

Manufacturing; Professional, scientific and technical services

University:

Polytechnique Montréal

Program: