Studies
Open Theses

Open Theses

This page lists open theses for bachelor and master students. Individual changes to the topics are possible, please contact the respective supervisor.

In addition, there is the possibility of writing a thesis on a topic of your choice. For this purpose, please contact an employee to discuss the topic in detail.

 

 

Are you looking for work that has already been completed?

OPEN BACHELOR THESES

  • Crowdsourcing turning restrictions from OpenstreetMap
    Road intersections are locations where different movement patterns are observed: traffic participant go ahead, turn right or left, according both to their needs and most importantly to the traffic restrictions applied everytime at the current location (traffic signs). The aim of this thesis is the implementation of a method, where vehicles trajectories acquired from OpenstreetMap (OSM) are analysed in terms of the turning possibilities that drivers have at each intersection location. Final objective is to find out what kind of turning restrictions are found at those locations, like those shown on the figure right.
    Leaders: Zourlidou
    Year: 2019
  • Navigation and Field Robotics: Pedestrian Navigation – Obstacle Avoidance with Depth Cameras and Electrical Muscle Stimulation
    This is a topic offered by the Human-Computer Interaction Group. In previous projects the Human-Computer Interaction Group investigated a novel approach to control pedestrians' walking direction for navigation. We showed that controlling the direction with electrical muscle stimulation is possible in outdoornavigation scenarios. As a follow-up project we would like to explore - in a collaborative project with the Institute of Cartography and Geoinformatics (IKG) - how this approach can be used for obstacle avoidance in pedestrian navigation scenarios.
    Leaders: Busch
    Year: 2017

OPEN MASTER THESES

  • Crowdsourcing turning restrictions from OpenstreetMap
    Road intersections are locations where different movement patterns are observed: traffic participant go ahead, turn right or left, according both to their needs and most importantly to the traffic restrictions applied everytime at the current location (traffic signs). The aim of this thesis is the implementation of a method, where vehicles trajectories acquired from OpenstreetMap (OSM) are analysed in terms of the turning possibilities that drivers have at each intersection location. Final objective is to find out what kind of turning restrictions are found at those locations, like those shown on the figure right.
    Leaders: Zourlidou
    Year: 2019
  • Navigation and Field Robotics: Pedestrian Navigation – Obstacle Avoidance with Depth Cameras and Electrical Muscle Stimulation
    This is a topic offered by the Human-Computer Interaction Group. In previous projects the Human-Computer Interaction Group investigated a novel approach to control pedestrians' walking direction for navigation. We showed that controlling the direction with electrical muscle stimulation is possible in outdoornavigation scenarios. As a follow-up project we would like to explore - in a collaborative project with the Institute of Cartography and Geoinformatics (IKG) - how this approach can be used for obstacle avoidance in pedestrian navigation scenarios.
    Leaders: Busch
    Year: 2017
  • Deep Learning: Automatisierte Identifikation von Geländestrukturen am Beispiel von Burgenanlagen
    Mittels Airborne Laserscanning können flächendeckende hochaufgelöste digitale Geländemodelle erstellt werden. Anders als manuell aufgenommene Daten sind diese Daten bis auf eine einfache Klassifikation in Boden und Vegetationspunkte nicht weiter interpretiert. Eine gezielte Interpretation von künstlich-historischen Geländestrukturen muss manuell durchgeführt und mittels Feldbegehung verifiziert werden.
    Leaders: Schulze, Thiemann
    Year: 2017

CONTACT FOR GENERAL QUESTIONS ON THESES

Dipl.-Ing. Frank Thiemann
Address
Appelstraße 9A
30167 Hannover
Building
Room
606
Dipl.-Ing. Frank Thiemann
Address
Appelstraße 9A
30167 Hannover
Building
Room
606