Event cameras are recent sensors with large potential for high speed and high dynamic range robotic applications. Recent works have shown promising results in using event cameras on board resource constrained platforms such as quadrotors to perform tasks where the standard cameras usually fail, for example due to fast motion and challenging illumination conditions.
In this thesis, we will use state-of-the-art methods in event based vision and/or adapt standard computer vision algorithms to develop a reliable line tracking system.
A successful thesis will lead to the deployment of the developed algorithm on a real quadrotor platform for power-line inspection.
Requirements: - Experience with event cameras preferable but not required - Passionate about robotics - Programming experience in C++ and Python.
Event cameras are recent sensors with large potential for high speed and high dynamic range robotic applications. Recent works have shown promising results in using event cameras on board resource constrained platforms such as quadrotors to perform tasks where the standard cameras usually fail, for example due to fast motion and challenging illumination conditions. In this thesis, we will use state-of-the-art methods in event based vision and/or adapt standard computer vision algorithms to develop a reliable line tracking system. A successful thesis will lead to the deployment of the developed algorithm on a real quadrotor platform for power-line inspection. Requirements: - Experience with event cameras preferable but not required - Passionate about robotics - Programming experience in C++ and Python.
In this project we will develop a light-weight event-based line tracking algorithm and deploy on a real quadrotor.
In this project we will develop a light-weight event-based line tracking algorithm and deploy on a real quadrotor.
Giovanni Cioffi (cioffi@ifi.uzh.ch) and Javier Hidalgo-CarriĆ³ (jhidalgocarrio@ifi.uzh.ch)
Giovanni Cioffi (cioffi@ifi.uzh.ch) and Javier Hidalgo-CarriĆ³ (jhidalgocarrio@ifi.uzh.ch)