Electrical Engineering

Titel:&nbsp;Autonomous Fixed-Wing Drone Landing on Maritime Vessels
Presenters: William Almqvist &amp; &nbsp;Ludvig Möller
Place: E2 Room 5430 Femman Time:10:00, &nbsp;8 September&nbsp;
Examiner: Jonas Sjöberg
Abstract: To improve the effectiveness of maritime search and rescue (SAR) operations, the Swedish Sea Rescue Society (SSRS) is developing autonomous fixed-wing drones through its Eyes-On-Scene project. While these drones can autonomously launch and loiter over areas of interest, they currently lack automated recovery capabilities.
This thesis presents a guidance and navigation framework that enables fixed-wing drones to autonomously land on moving SSRS rescue vessels without requiring modifications to either platform. The system integrates AIS and camera-based tracking through an Extended Kalman Filter to estimate vessel position. A multi-stage landing algorithm is introduced, consisting of follow, descent, and diversion phases, designed to ensure safety under uncertain conditions. The algorithm enables controlled landing velocities and supports flexible approach angles for robust operations.
The complete system is tested in a simulated environment under various disturbances, including wind, position, altitude, and speed fluctuations. Simulation results demonstrate high landing accuracy, indicating the feasibility of autonomous landings in realistic SAR scenarios. The results highlight the potential to strengthen SSRS’s autonomous drone capabilities and contribute toward more efficient recovery in future SAR operations. The work has been carried out in cooperation with the Swedish Sea Rescue Society
Welcome! William, Ludvig and Jonas

Title: Robust MPC-based Trajectory Planning for Autonomous Driving under Occlusion Presenters: Abishek Swaminathan and Junyan Tian Opponents: Qirui Yang (CID:qirui), Haoming Yi (CID:haoming) Examiner: &nbsp;Nikolce Murgovski Time: Friday, 2025-09-12, 09:00 Room: E2 Room 3364 EDIT-rummet, Hörsalsvägen 11, 3rd floor Zoom link: <a rel="noopener" href="https://chalmers.zoom.us/j/68628440925" target="_blank">https://chalmers.zoom.us/j/68628440925&nbsp;</a>
Abstract: In the field of AD/ADAS research, safety remains paramount. One of the avenues of research incorporating safety involves the inclusion of road users that are occluded by other vehicles or infrastructural elements into the decision making. This thesis focuses on the implementation and inclusion of occlusion aware obstacle avoidance for trajectory planning using a Model Predictive Controller (MPC). The controller is designed to incorporate different types of obstacles such as static, dynamic and more importantly occluded obstacles. The design followed two approaches for modeling of the occluded road users one where the parameters (velocities) of the road users were modeled probabilistically and the other with the use of reachability analysis to account for all possible actions of a road user. The controller was tested in a few urban scenarios involving parked cars as well as driving through an intersection. These experiments demonstrated the capability of the controller to safely navigate through the occluded areas while maintaining comfort. This also showed that the methodology of modeling of road users can be expanded to different use cases.
Welcome! Abishek, Junyan and Nikolce

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Presentation of master thesis

Master thesis presentations at Electrical Engineering

8 September

10.00-11.00 William Almqvist & Ludvig Möller, MPCAS

12 September

09.00-10.00 Abishek Swaminathan & Junyan Tian, MPSYS