Your browser doesn't support javascript. This means that the content or functionality of our website will be limited or unavailable. If you need more information about Vinnova, please contact us.

Test and evaluation of distributed multi-domain perception via FMV BattleWeek 2026

Reference number
Coordinator Xymbiotec System AB
Funding from Vinnova SEK 500 000
Project duration June 2026 - December 2026
Status Ongoing
Venture Civil-military synergies
Call Support to small and medium-sized enterprises for testing and evaluating technology solutions that contribute to defense innovation

Purpose and goal

Xymbiotec has 15 years of experience in perception and ADAS for customers such as Denso and Mirise. In this project we further develop our platform Laplacian – in civilian operation since 2024 – for defence. At FMV BattleWeek 2026 we test a tower where Laplacian fuses EO, IR and acoustics to detect and classify drones threatening critical infrastructure. The goal is to demonstrate the capability to FMV, scale up to a network of cooperating towers and establish a business relationship with FMV.

Expected effects and result

We achieve a verified capability to detect, track and classify drones through Laplacian´s fusion of EO, IR and acoustic sensors, independently evaluated in a realistic environment together with FMV. The result is cost-effective protection of critical infrastructure against drone threats, built on COTS hardware and scalable from a single tower to a network of cooperating towers. The project strengthens Xymbiotec´s business relationship with FMV and contributes to a safer NATO.

Planned approach and implementation

At FMV BattleWeek 2026 we test Laplacian´s fusion of an EO camera, an IR camera and an acoustic sensor against drones in a realistic scenario. As a drone approaches the tower, the acoustic sensor gives an early indication, after which the cameras track and classify the target with higher precision. The test is carried out (weeks 38–39) together with FMV and is followed by analysis and evaluation as a basis for further scaling.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 12 July 2026

Reference number 2026-01613