The objective of the thesis is to develop an algorithm capable of real-time collision avoidance for drones.

An Avientus Drone

Background

Avientus specializes in developing cutting-edge, heavy-duty automated drone transportation systems designed to revolutionize logistics and industrial applications. To further enhance the safety and reliability of their drones, they are offering a Master Thesis opportunity in collaboration with V4RL on collision avoidance for drones.

Description

The objective of the thesis is to develop an algorithm capable of real-time collision avoidance for drones, ensuring safe operation even in environments with other air traffic, such as airplanes, helicopters, paragliders, and similar obstacles. The tasks include selecting and evaluating existing neural networks and algorithms, or designing a custom solution tailored to our requirements. The project also involves working with a high-performance hardware setup, with support for real-time execution on an NVIDIA Jetson Orin.

Work Packages

  • The tasks include selecting and evaluating existing neural networks and algorithms, or designing a custom solution tailored to our requirements.

Requirements

  • Strong competencies in computer vision & neural networks
  • Good knowledge in programming (Python and / or C++)
  • General interest in VTOL drones

References