Description

This thesis proposal "Multi-sensor data fusion for positioning and navigation of heavy load vehicles" aims to study how to merge information from multiple sensors to achieve precise and robust positioning and navigation systems for applications in restricted environments. In particular, the thesis aims to investigate how to integrate measures of pseudo-distance from the constellation of satellites of the European Galileo system to estimates obtained through proprioceptive positioning techniques including lidar data, inertial sensors, odometry or computer vision.
The thesis is framed in the context of the European project "Logimatic - Tight integration of EGNSS and on-board vehicle sensors for port automation". This project is an Innovation Action in the 2014-2020 EGNSS Application Framework Programme "Horizon 2020" with EURECAT Foundation, CSIC, and Technology Hellas as main partners.

The work is under the scope of the following projects:

• RobInstruct: Instructing robots using natural communication skills (web)
• LOGIMATIC: Tight integration of EGNSS and on-board sensors for port vehicle automation (web)