- Underwater docking
- Classification of sonar data with deep learning
- Vehicle system performance optimisation
- Hydrobatics simulator
- Autonomous underwater perception
- Underwater navigation
- Robust, flexible and transparent mission planning and execution
- Multi-agent mission planning and execution
- Air-independent energy storage
- Autonomous situation awareness and world modeling
- Underwater communication
- Demonstrator program
The aim of this project is to investigate vehicle-related performance factors for long-range autonomous underwater vehicles (AUVs). The focus lies on multi-variable optimization regarding the electro- and hydromechanical design as well as on operational factors. Through a holistic approach, we analyse factors such as propulsion, flight mechanics, scale factors, and hotel load usage. This project is conducted in close collaboration with the large demonstrator program (AUV LoLo, SMaRC SP13).
In preparation for upcoming scientific expeditions, we are currently equipping LoLo with a broad scientific sensor suite, which includes both environmental and acoustic sensors, such as Kongsberg’s EK80 system. Furthermore, we are collaborating with SMaRC SP09 (and external partners) on integrating an operational fuel cell/battery hybrid system in LoLo.
Jakob Kuttenkeuler, Professor Centre of Naval architecture KTH – Project leader
Clemens Deutsch – Post-doc