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Thema



Efficient Operation of Unmanned Aerial Vehicle for Industrial Fire Fighters (mehrere Themen / several theses)

Aufgabenstellung



In the research project \"Efficient Operation of Unmanned Aerial Vehicle for Industrial Fire Fighters (EffFeu)\" the DAI-Lab focuses on autonomous drone operation including advanced situation detection capabilities. The topics listed below focus on autonomous navigation and object detection.

More information about the project can be found here: http://www.dai-labor.de/en/cog/ongoing_projects/efffeu/

Topics related to the higher-level mission control can be found here: https://www.aot.tu-berlin.de/index.php?id=813&dID=416

Possible topics

1.Development of a ROS module for optical-flow-based velocity determination (visual odometry) combining information from a monocular camera, IMU data, and distance measures (e.g. ultrasonic range finders) (master/bachelor)

2.Development of an advanced labeling tool for machine learning on image data (bachelor)

3.Development of object detection/tracking module for UAVs (master)

Requirements
•Python/C++ depending on the particular topic
•Experience with ROS (Robot Operating System) and Linux are an advantage
•Experience with Qt for UI related topics
•(optional) Experience with computer vision and machine learning

Literature
•http://wiki.ros.org/ROS/Tutorials
•http://docs.opencv.org/3.2.0/d7/d8b/tutorial_py_lucas_kanade.html
•https://pixhawk.org/modules/px4flow

Contact
Supervisors: Christopher-Eyk Hrabia, Yuan Xu
Mail: christopher-eyk.hrabia@tu-berlin.de; yuan.xu@dai-labor.de

If you are interested in this research field please contact me by mail and include a CV as well as your current transcript of records (Notenübersicht).

Betreuer



Betreuer:  Christopher-Eyk Hrabia
Email:   christopher-eyk.hrabiatu-berlin.de

Bearbeiter



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