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Archivio digitale delle tesi discusse presso l’Università di Pisa

Tesi etd-06192021-142812


Tipo di tesi
Tesi di laurea magistrale
Autore
RIZZI, ANDREA
URN
etd-06192021-142812
Titolo
Obstacle Detection and Sensor Fusion from a 2DLaser and an RGB-D Camera
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
INGEGNERIA ROBOTICA E DELL'AUTOMAZIONE
Relatori
relatore Prof.ssa Pallottino, Lucia
relatore Dott. Settimi, Alessandro
Parole chiave
  • camera
  • detection
  • fusion
  • laser
  • obstacle
  • RGBD
  • sensor
  • tracking
Data inizio appello
08/07/2021
Consultabilità
Completa
Riassunto
A self-driving vehicle, to be deployed in indoor driving environments, must be capable of reliably detecting and effectively tracking of nearby moving objects. This thesis presents a moving object detection and tracking algorithm from an RGB-D camera and a 2D Laser sensor. The system is capable to detect and tracking objects separately from a camera and a laser, then combining the lists of tracks with a simple sensor fusion approach. The images from the camera are also used to classify the objects through the YOLO network, and this information is also included in the final list of tracks. Dempster Shafer theory is used for data association and a comparison with the global nearest neighbor is presented. The algorithm was implemented on ROS and tested with Gazebo simulations, giving fulfill results.
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