News

The GAMMS consortium field-tests mapping robots

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The EUSPA-funded research project GAMMS for the automated geodata collection and production of HD maps completes its 2nd test field campaign.

Graz, 9 May 2025. From the 5. to the 9. of May, a European consortium led by the Spanish geomatics and navigation technology company GEONUMERICS has been field-testing the integration of several technologies –autonomous vehicles, mobile mapping systems, satellite navigation and artificial intelligence– for the automated production of accurate high-definition maps (HD Maps). The tests have been conducted at the testing facilities of the Austrian research centre Virtual Vehicle (ViF), in Graz, Austria.  For this purpose, the French mapping company GEOSAT has installed its mobile mapping system in the driverless car prototype of ViF, DEIMOS Engenharia its Galileo/GPS receiver and GEONUMERICS its multi-sensor navigation software.

Robots making maps for robots: the GAMMS project kicks off

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The EUSPA-funded research project GAMMS for the automated geodata collection and production of HD maps is underway.

Castelldefels, 9 July 2021. Till the end of 2023, a European consortium, led by the French map service provider GEOSAT, will investigate how the combination of self-driving mapping cars —a.k.a. autonomous mobile mapping systems (AMMS)— and artificial intelligence-based mapping software can automate the production of high-definition (HD) maps. HD maps are the maps used by the driverless vehicles and shall be of provable/certifiable accuracy, completeness and up-to-dateness.

The challenge of the Galileo/GNSS-based AMMS (GAMMS) project is the fast, sustainable production of trustworthy maps. To face it, GAMMS brings together a wide spectrum of knowledge and experts: map making and machine learning (GEOSAT), multi-sensor fusion and accurate navigation (GeoNumerics), robotics and autonomous driving (Sensible4), GNSS and Galileo receiver development (DEIMOS Engenharia), sensor and vehicle dynamic modelling (EPFL) and multispectral laser scanning (Solid Potato). The consortium also includes regulatory (PILDO Labs) and communication (ENIDE) specialists. Galileo will be the main enabler of GAMMS given its precise, multi-path resistant measurements and its upcoming high-accuracy service (HAS). 

GeoNumerics has participated in Fira d'Empreses UB 2024

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A fabulous day at Fira d’Empreses of Barcelona’s University!

As every year, GeoNumerics has participated in Fira d’Empreses of Barcelona's University! It was a fabulous day and our colleagues (Núria and Guillem) assisted many students interested in apply their knowledge to our tecnology (maths, physics, enginyering, etc.). If you are one of them or you have a similar profile, do not hesitate to contact us. We have open positions for junior and/or internship. Join us!   https://geonumerics.es/index.php/work-with-us/open-positions

PhD research reveals new methods for accurate and resilient navigation

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Findings improve general fault detection and isolation in multi-sensor navigation systems by allowing access to all raw measurements' residuals.

Castelldefels, 15 January 2021.  On the 14th of January, Dr. Maria Eulàlia Parés defended her doctoral research in a "viva voce" examination before a committee of experts in geodesy, navigation and sensorics.  The granted doctoral degree belongs to the PhD Programme in Aerospace Science and Technology (DOCTA) of the Universitat Politècnica de Catalunya (UPC). The title of the doctorate thesis was "A geodetic approach to precise, accurate, available and reliable navigation."

Dr. Parés, a researcher of the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), presented the geodetic approach to navigation with emphasis on generic abstract modelling and general outlier detection for accurate and reliable navigation. Among other contributions, a highlight of her research was a non-linear simultaneous prediction and filtering (SiPF) method to be used in combination with predictive filters, e.g. the Kalman filter and its many variants. More specifically, she presented a method to estimate the residuals of the measurements that participate in predictions before they are spread into correlated errors affecting the predicted states. The thesis supervisor was GeoNumerics' Dr. Ismael Colomina.