A new European project is researching automated collection of geodata and production of high-definition maps.
The GAMMS project is funded by the European Union Agency for the Space Programme (EUSPA), and will take place until the end of 2023. Galileo will be the main enabler of GAMMS, given its precise, multipath-resistant measurements and its upcoming high-accuracy service (HAS).
A European consortium, led by the French map service provider GEOSAT, will investigate how the combination of self-driving mapping cars (autonomous mobile-mapping systems) and artificial intelligence-based mapping software can automate the production of high-definition maps.
These maps are used by driverless vehicles and need to be provably accurate, complete and up to date. Fast, sustainable production of trustworthy maps is the goal.
Consortium members include:
- GEOSAT — map-making and machine learning
- GeoNumerics — multi-sensor fusion and accurate navigation
- Sensible4 — robotics and autonomous driving
- DEIMOS Engenharia — GNSS and Galileo receiver development
- EPFL — sensor and vehicle dynamic modelling
- Solid Potato — multi-spectral laser scanning
- PILDO Labs — regulatory specialists
- ENIDE — communication specialists
“It is as challenging as interesting to bring together the geodetic estimation methods with the navigation ones in multi-sensor systems powered by EGNSS and its differentiators, VDMs (vehicle data management systems) and visual features,” said Marta Blázquez, responsible for GAMMS at GeoNumerics. “GAMMS will boost the development of NEXA, our trajectory determination platform, and GENA, our adjustment platform for dynamic networks, in the direction of trustworthy navigation.”
GeoNumerics is responsible for computing the mapping vehicle trajectory (a time series of position, velocity and attitude coordinates) by integrating the manifold of sensors available in a mapping vehicle.
Measurements of inertial units and atomic clocks will be fused with measurements of all available navigation satellites (GPS, GLONASS, Galileo and BeiDou), odometers, cameras and laser scanners. For this purpose, GeoNumerics’ GENA and NEXA systems will be further developed to include new sensor mathematical models and to improve its robust estimation methods.