Object detection using LIDAR in maritime scenarios
Wessman, Michael (2018)
Åbo Akademi
2018
Julkaisu on tekijänoikeussäännösten alainen. Teosta voi lukea ja tulostaa henkilökohtaista käyttöä varten. Käyttö kaupallisiin tarkoituksiin on kielletty.
Julkaisun pysyvä osoite on
http://urn.fi/URN:NBN:fi-fe2018051824225
http://urn.fi/URN:NBN:fi-fe2018051824225
Tiivistelmä
The purpose of this thesis is to understand the methods that can be used to detect
objects in the autonomous vehicle industry with the help of sensors, specifically
LIDAR technology. This thesis will focus on the development of an object detection
algorithm for maritime vessels which can function in different surroundings,
such as low light and fog.
For identifying objects from the data that LIDAR cameras produce, a clustering
method is needed. This thesis will present how the data is used and analyzed,
the challenges that emerge when parsing the data, and how the challenges are
resolved with our object detection solution. Afterwards, we test the adaptability
of our solution by running it in different scenarios, and lastly, we compare our
results with an integrated LIDAR object detection application.
objects in the autonomous vehicle industry with the help of sensors, specifically
LIDAR technology. This thesis will focus on the development of an object detection
algorithm for maritime vessels which can function in different surroundings,
such as low light and fog.
For identifying objects from the data that LIDAR cameras produce, a clustering
method is needed. This thesis will present how the data is used and analyzed,
the challenges that emerge when parsing the data, and how the challenges are
resolved with our object detection solution. Afterwards, we test the adaptability
of our solution by running it in different scenarios, and lastly, we compare our
results with an integrated LIDAR object detection application.