Skip to main content
RISE logo

Master thesis: Efficient 3-D Topology and Trajectory of UAV Swarm using AI

We are looking for dedicated master’s students to join us in the Connected Intelligence Unit at RISE.

The Connected Intelligence Unit is part of RISE Computer Science in Kista. The current research focus is on edge computing, 5G/6G networks, and immersive media systems. Among the group's key technologies are the IoT network and UAV networks. The unit conducts projects together with industry and academic partners from Sweden and across the world.

Thesis Description
Unknown environment poses challenges to UAVs in ascertaining obstacles during flying. Furthermore, trajectory and UAV swarm topology affect the lifetime of these networks. The focus of this project is to devise efficient UAV swarm network topology and trajectory in an unknown environment using artificial intelligence and image/ video processing.

Terms:

  • Start Time: As soon as possible
  • Scope: 30 hp
  • Location: RISE Computer Science, Kista, Stockholm

Who are you?
We expect you to have good programming skills and knowledge of UAV networks and image/video processing. An interest in machine learning models and artificial intelligence is also a prerequisite.

Welcome with your application!
If this sounds interesting and you would like to know more, please contact Chetna Singhal (email: chetna.singhal@ri.se). Applications should include a brief personal letter, CV, and recent grades. Candidates are encouraged to send in their application as soon as possible but at the latest on the 15th of January 2022. Suitable applicants will be interviewed as applications are received. We do not accept applications via email.

Our union representatives are Lazaros Tsantaridis, SACO, 010 516 62 21 and Bertil Svensson, Unionen, 010-516 53 56.

Master thesis, UAV network, Topology, Trajectory, UAV network, UAV Swarm, Artificial intelligence, unknown environment, RISE, Stockholm

About the position

City

Kista

Contract type

Temporary position 3-6 months

Job type

Student - Master Thesis/Internship

Contact person

Chetna Singhal
chetna.singhal@ri.se

Reference number

2022/653

Last application date

2023-01-15

Submit your application