Imagine a drone trying to land on a rocky planet without any GPS or human help. This project builds a 'digital brain' and tiny cameras that let the drone recognize craters and landmarks to find its way. It's like giving a robot a map and a pair of eyes that work even in completely unknown territory.
Space missions currently struggle with safe, precise landings and navigation on distant planetary bodies due to a lack of autonomous on-board processing and reliance on Earth-based communication.
The project developed smart algorithms, optimized software, and miniaturized hardware modules for optical navigation, validated in laboratory settings.
If you are a probe manufacturer dealing with the risk of landing failure on asteroids or moons — this project developed smart algorithms and miniaturized hardware that enable autonomous landing. This reduces the need for constant Earth-based control and increases mission success rates.
If you are a drone developer dealing with navigation in environments where GPS is unavailable — this project developed an adaptive vision concept and high-performance processing. This allows drones to navigate using only visual landmarks and on-board processing.
If you are an equipment provider dealing with the need for lightweight, high-performance data processing in the field — this project developed miniaturized HW modules using COTS components. This allows for high-speed image processing in small, power-constrained platforms.
Based on available project data, specific pricing or cost structures are not provided as the project focuses on technology development.
The project aims to reach TRL4, meaning it is validated in laboratory environments. It is not yet at a full industrial production scale.
Based on available project data, the IP is managed by a consortium of 4 partners, but specific licensing terms are not disclosed.
The project focuses on miniaturized HW modules and the use of COTS components to ensure integration into small space platforms.
The project period runs from 2022-12-01 to 2026-03-31.
The consortium is heavily industry-driven with a 75% industry ratio, consisting of 4 partners. It combines the agility of an SME (M2M Solutions) with established industrial players (TTTech Computertechnik AG, iTUBS) and the deep research capabilities of DLR, suggesting a strong pipeline from lab research to industrial application.
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