Robust state estimation for small unmanned airplanes (bibtex)
by S Leutenegger, A Melzer, K Alexis and R Siegwart
Reference:
Robust state estimation for small unmanned airplanes (S Leutenegger, A Melzer, K Alexis and R Siegwart), In 2014 IEEE Conference on Control Applications (CCA), 2014. 
Bibtex Entry:
@inproceedings{leutenegger2014robust,
 title = {Robust state estimation for small unmanned airplanes},
 author = {S Leutenegger and A Melzer and K Alexis and R Siegwart},
 booktitle = {2014 IEEE Conference on Control Applications (CCA)},
 pages = {1003--1010},
 year = {2014},
 organization = {IEEE},
 keywords = {drones},
}
Powered by bibtexbrowser
Robust state estimation for small unmanned airplanes (bibtex)
Robust state estimation for small unmanned airplanes (bibtex)
by S Leutenegger, A Melzer, K Alexis and R Siegwart
Reference:
Robust state estimation for small unmanned airplanes (S Leutenegger, A Melzer, K Alexis and R Siegwart), In 2014 IEEE Conference on Control Applications (CCA), 2014. 
Bibtex Entry:
@inproceedings{leutenegger2014robust,
 title = {Robust state estimation for small unmanned airplanes},
 author = {S Leutenegger and A Melzer and K Alexis and R Siegwart},
 booktitle = {2014 IEEE Conference on Control Applications (CCA)},
 pages = {1003--1010},
 year = {2014},
 organization = {IEEE},
 keywords = {drones},
}
Powered by bibtexbrowser
research:drones

Drones

Multicopters (SRL Imperial College)

We run OKVIS on our multicopter drones as a basis for fully autonomous operation. We are exploring several Model-Predictive Controllers (MPC) and are working on model-based motion planning for save navigation through free space that is reconstructed by our dense SLAM algorithms.

We have participated in the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2017 in Abu Dhabi together with members from Imperial’s Aerial Robotics Lab. We were admitted to the finals with some of the most well-known robotics groups from all over the world. We also regularly demonstrate our drone-related research at the Imperial Festival.

More recently, we have also been exploring aggressive drone flight and motor failure identification and recovery employing Non-linear Model Predictive Control (NMPC). The scheme lets the drones fly aerobatic maneouvers it has never seen (learnt) before and deal with failures in an optimal way by considering the identified non-linear drone dynamics.

Former collaborators:

Collaboration within the Aerial Additive Manufacturing project:

Solar Aeroplanes (ETH Zurich)

The described multi-sensor estimators with and without computer vision involved have been deployed on UAS. Both long-endurance solar aeroplanes as well as multicopter platforms were used to this end.

Former collaborators at ETH Zurich: