Modern mapping and remote sensing integrates themes from navigation, geodesy, photogrammetry, computer vision, machine learning and system control. This field is truly interdisciplinary both in the conception and operation of mobile mapping platforms, as well as in the calibration of their sensors and data processing. We study and develop new concepts of sensor calibration, quality control and data adjustment which are tested on platforms developed especially for this purpose. Together with the platforms we study and develop bespoke 3D reconstruction, digitalisation and analysis algorithms.
Our most resent interests are related to the area of fusion of novel LIDAR (Single-photon avalanche diode â SPAD) and RGB camera sensors for 3D digitalisation and mapping. We study the optimal fusion of classical 3D reconstruction algorithms such as photogrammetry with most resent developments in Machine Learning vision and data processing algorithms.
Particular focus is given to the following areas:
Calibration and integration of active and passive optical sensors
Sensor synchronisation and data acquisition
Development of 3D reconstruction algorithms
Composition of light-weight mapping systems and platforms (e.g.
Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2022.Vol. V-1-2022, p. 161 – 168. DOI : 10.5194/isprs-annals-V-1-2022-161-2022.
2020.International Society for Photogrammetry and Remote Sensing, Virtual, Septembre 1-2, 2020. p. 231 – 238. DOI : 10.5194/isprs-annals-V-1-2020-231-2020.
2017.International Conference on Unmanned Aerial Vehicles in Geomatics, Bonn, Germany, September 4â7, 2017. p. 1 – 7. DOI : 10.5194/isprs-annals-IV-2-W3-1-2017.
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences. 2017.Vol. 4, num. 2W3, p. 75 – 80. DOI : 10.5194/isprs-annals-IV-2-W3-75-2017.
