Draft:GAMMS
| GAMMS | |
|---|---|
| Funding agency | European Union Agency for the Space Programme (EUSPA) |
| Project coordinator | GeoNumerics |
| Partners | GEOSAT, Sensible4, DEIMOS Engenharia, EPFL, Solid Potato, PILDO Labs, ENIDE |
| Budget |
|
| Website | gamms.eu |
GAMMS (Galileo/GNSS-based Autonomous Mobile Mapping System) is an ongoing European Union research and innovation project under the Horizon 2020 programme. It aims to develop a terrestrial autonomous mobile mapping system (AMMS) for the automated generation of high-definition (HD) maps using GNSS, artificial intelligence, and autonomous vehicle technologies.[1]
Objectives
[edit]The GAMMS project seeks to create an autonomous mobile mapping system capable of acquiring geospatial data and generating HD maps with centimeter-level accuracy. These maps are critical for applications such as autonomous driving, urban air mobility, smart cities, and 3D augmented reality environments. Key objectives include:
- Developing an autonomous terrestrial mobile mapping system (AMMS) based on Level of Automation 4 (LoA-4) vehicles[2].
- Integrating multi-sensor fusion with GNSS, including Galileo (satellite navigation), GPS, GLONASS, and BeiDou[3].
- Utilizing Galileo's High Accuracy Service (HAS) and Navigation Message Authentication (OSNMA) for real-time and post-processed accuracy and security[4].
- Automating map creation using AI-powered software trained on geodata from cameras, inertial sensors, odometers, and laser scanners[5].
Technology
[edit]The GAMMS prototype integrates a range of sensors into a single platform. Sensor inputs include inertial measurement units (IMUs), odometers, atomic clocks, and visual sensors (cameras and LiDAR). These are combined with data from multi-constellation GNSS systems to compute the vehicle trajectory, including position, velocity, and attitude over time.[5]
GeoNumerics leads the development of the core mapping algorithms through its NEXA trajectory determination platform and GENA adjustment platform for dynamic networks. The integration of Galileo-specific features (such as the triple-frequency E1, E5 AltBOC, and E6 signals) enables precise trajectory determination.[6]
Galileo Integration
[edit]GAMMS is among the first projects to leverage the Galileo High Accuracy Service (HAS) and OSNMA for real-world mapping applications. These services provide global decimetric accuracy and signal-level message authentication.[4]
The G3STAR GNSS receiver developed by DEIMOS Engenharia supports decoding of Galileo’s E6 HAS signals and OSNMA bits in live navigation scenarios.[6]
Use Cases
[edit]The GAMMS platform is designed to address several domains requiring high-accuracy maps:
- HD mapping for autonomous ground vehicles
- 3D mapping for smart city planning and urban management
- Support for urban air mobility (UAM), such as drone delivery and aerial taxis
- Applications in robotics and location-based augmented reality[7]
Consortium
[edit]The project is coordinated by GeoNumerics (Spain) and involves eight partners across five countries:
- GEOSAT (France) – 3D mapping and AI integration
- Sensible4 (Finland) – Autonomous driving technologies
- DEIMOS Engenharia (Portugal) – GNSS receiver development
- EPFL (Switzerland) – Sensor and vehicle modelling
- Solid Potato (Finland) – Multispectral LiDAR technology
- PILDO Labs (Spain) – Regulatory and certification guidance
- ENIDE (Spain) – Communication and stakeholder engagement[1]
Funding
[edit]GAMMS is funded by the European Union Agency for the Space Programme (EUSPA) under the Horizon 2020 framework, through grant agreement No. 101004255. The total project budget exceeds €1.9 million.[1]
External links
[edit]References
[edit]- ^ a b c "GAMMS: Galileo/GNSS-based Autonomous Mobile Mapping System". CORDIS. Retrieved 6 May 2025.
- ^ "Robots Making Maps for Robots". Inside GNSS. 22 July 2021. Retrieved 6 May 2025.
- ^ "European project researches automated map creation for cars". GPS World. 6 August 2021. Retrieved 6 May 2025.
- ^ a b "Galileo HAS Market Development Report" (PDF). EUSPA. Retrieved 6 May 2025.
- ^ a b "Robots making maps for robots: the GAMMS project kicks off". GeoNumerics. 9 July 2021. Retrieved 6 May 2025.
- ^ a b Carvalho, Filipe (September 2024). High-Accuracy and Resilient GNSS Receiver for an Autonomous Vehicle. ION GNSS+ 2024. Institute of Navigation. pp. 316–332. Retrieved 6 May 2025.
- ^ "GAMMS H2020 Project". ENIDE. Retrieved 6 May 2025.