Detail of the student project

Topic:Algoritmy strojového učení pro nový typ hloubkového senzoru
Department:Katedra kybernetiky
Supervisor:Ahmed Yousif
Announce as:Diplomová práce, Semestrální projekt
Description:The simulation and HiL team within the validation department at Valeo develops and integrates physical sensor models which imitates and simulates the physical sensor behaviour used within the ADAS domain. This includes the new generation LIDAR by Valeo with high resolution point cloud.

The team uses a new type of sensor that combines LiDAR depth sensing and ambient light measurement along the measuring rays. The data contains 3D coordinates, intensity of the ray reflections and grayscale intensities.

The project will investigate applicability of the existing algorithms from depth imaging and LiDAR point clouds domain to new sensor.
Responsible person: Petr Pošík