Autonomous mobility mapping
Introduction
GAMMS (acronym for Galileo/GNSS-based Autonomous Mobile Mapping System, in Spanish: Sistema Autónomo de Mapping Móvil Based on Galileo/GNSS) is an ongoing European research and innovation project, funded by the European Union within the Horizon 2020 program. Its main objective is to develop a ground-based autonomous mobile mapping system (AMMS) for the automated generation of high-definition maps (HD maps), using technologies from GNSS, artificial intelligence and autonomous vehicles.[1].
Goals
The GAMMS project aims to develop an autonomous solution capable of acquiring geospatial data and producing HD maps with centimeter precision. These maps are essential for autonomous driving, urban air mobility, smart cities and augmented reality applications. Among its main objectives are:
• - Develop an autonomous vehicle-based land mobile mapping system with Level of Automation 4 (LoA-4).[2].
• - Integrate multi-sensor fusion with multi-constellation GNSS: Galileo (navigation system) "Galileo (satellite navigation)"), GPS, GLONASS and BeiDou.[3].
• - Use Galileo's High Precision Service (HAS) and Navigation Message Authentication Service (OSNMA) to improve accuracy and security in real time and in post-processing.[4].
• - Automate the generation of maps using AI-based software trained with data from visual sensors, inertial units, odometers and laser scanners.[5].
Technology
The AMMS system integrates multiple sensors: inertial measurement units (IMU), odometers, atomic clocks and visual sensors (cameras and LiDAR), combined with multi-constellation GNSS signals to calculate the vehicle trajectory in terms of position, speed and orientation.[5].
GeoNumerics leads the development of navigation algorithms through the NEXA (path determination) and GENA (dynamic network adjustment) platforms. The use of Galileo-specific signals "Galileo (satellite navigation)") (E1, E5 AltBOC and E6) improves the accuracy of trajectory estimation.[6].