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| Funder | Vinnova |
|---|---|
| Recipient Organization | Kth, Royal Institute of Technology |
| Country | Sweden |
| Start Date | Aug 01, 2024 |
| End Date | Feb 01, 2026 |
| Duration | 549 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | Swedish Research Council |
| Grant ID | 2024-01576_Vinnova |
Purpose and goal:
The ALARS project, a collaboration between KTH and Saab, aims to develop a drone-based autonomous system for launch and retrieval of autonomous underwater vehicles (AUVs). By utilizing AI and machine learning, the project seeks to improve detection under challenging conditions, maintain stability during lift, and enable operations with multiple AUVs. The goal is to enhance the navy´s ISR capabilities and operational efficiency, as well as strengthen Swedish maritime technology globally.
Expected results and effects:
The ALARS project is expected to enhance the navy´s ISR capacity through autonomous launch and retrieval of AUVs, enabling better intelligence and reconnaissance under challenging sea conditions. Automation reduces the need for manual intervention, saves time, minimizes risks, and allows for the simultaneous handling of multiple AUVs. The project also strengthens Swedish competitiveness in unmanned marine systems and promotes the development of AI and machine learning in autonomous navigation.
Approach and implementation: Requirements Analysis: Define system requirements for autonomous launch and retrieval AI Development: Develop algorithms for detection and stability under challenging conditions. Prototype: Build and test a ALARS prototype. Testing: Conduct simulations and field tests in marine environments.
Evaluation: Analyze results and optimize the system. Collaboration KTH: Responsible for AI research and autonomous systems. Saab: Contributes expertise in UAV/AUV technology and system integration.
Kth, Royal Institute of Technology
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