Multi-sensor data fusion and quality evaluation in challenging weather environment

A key factor to deliver reliable intelligent vehicles is the proper exploitation of data gathered from the different sensors equipping the vehicle. To do so, a data fusion algorithm is applied. However, the reliability of the sensors can change (for example due to weather conditions), therefore, a solution to evaluate the quality of the data gathered from each sensor must be investigated, to automatically adapt the data fusion algorithm and avoid the use of less reliable sensors or credible data or information these sensors provide directly or they derive through processing techniques.

Investigate sensors management and fusion algorithms to orchestrate data/information collection from different sensors (with various reliabilities) and in weather-challenging environments

The objective of the internship is to better evaluate/quantify the quality of sources in a challenging weather environment and adapt the behavior of the sensor-fusion algorithm accordingly. For example, if two cameras are mounted on the car, and one is obstructed (or partially obstructed) by snow, second camera should become more reliable in this condition.

Robust project scheduling policies for naval refit operations at Thales Group

In large-scale construction projects such as naval refits or aircraft overhauls, project execution is subject to considerable uncertainty and a baseline schedule quickly becomes unachievable.  For naval environments, high variability in work scope and duration occur at every stage.  Furthermore, tools and equipment can fail or not be on-site when needed.  Human resources are drawn from a pool of workers coming from a mix of fixed-capacity-unionized workers and contractors.  To limit the effect of unexpected but inevitable schedule disruptions, resource (equipment and workers) buffers are us

Robust project scheduling policies for naval refit operations at Thales Group

In large-scale construction projects such as naval refits or aircraft overhauls, project execution is subject to considerable uncertainty and a baseline schedule quickly becomes unachievable.  For naval environments, high variability in work scope and duration occur at every stage.  Furthermore, tools and equipment can fail or not be on-site when needed.  Human resources are drawn from a pool of workers coming from a mix of fixed-capacity-unionized workers and contractors.  To limit the effect of unexpected but inevitable schedule disruptions, resource (equipment and workers) buffers are us