Felix helped develop the first revision of custom electronics and firmware for the quadrocopters used in the Flying Machine Arena.
Armin implemented original FMA-wide support for the Microsoft Kinect along with a user-tracking Kalman Filter to make the Kinect interaction more responsive.
Luzius implemented a collision avoidance system in his Master Thesis. The system is implemented centrally and prevents collisions by reserving airspace for individual vehicles. Vehicles are prevented from entering airspaces reserved by others, thereby guaranteeing vehicles steer clear of each other.
Dr. Guillaume Ducard
Guillaume contributed to the initial setup during his postdoc in 2008. He designed the very first flight control and guidance systems for the quadrocopters. He also developed the first version of the simulator, which enabled the design and debug of various flight controllers, guidance algorithms, and multi-vehicle coordinated flights.
Flavio, as part of his mini-quadrocopter semester project, helped reorganize and modularize the vehicle firmware code. Thanks in part to his contributions, we are able to use hobbyist servos and a wider spectrum of sensors and actuators without having to write new code.
Thomas implemented the Kalman-Filter-based fuel estimator that tells all FMA programs the battery state of each quadrocopter by filtering and analyzing system voltage and current data.
Dr. Sergei Lupashin
Sergei worked on the ETH Flying Machine Arena since its construction in 2008. His contributions include the FMA middleware, the Copilot, a variety of support libraries and programs used by the FMA and other projects, the onboard electronics, and other core infrastructure systems. He also helped realize the first external demonstrations of the FMA and contributed to key design and implementation decisions guiding the evolution of the FMA during its first five years.
Lorenz helped implement and characterize the low-latency wireless system used to send commands to the vehicles.
Fabian organized the shipping, infrastructure and demonstrations of the Flying Machine Arena at Hannover Messe 2012. Before this, he worked on quadrocopter learning in the FMA during his master thesis.
Dr. Angela Schoellig
Angela developed algorithms for learning-based trajectory tracking and rhythmic flight performances during her PhD with Prof. Raffaello D’Andrea from 2008 to 2012. Her trajectory tracking algorithms enable quadrocopters to improve their tracking performance through learning from past trials. Angela also led the Music in Motion project, where she developed the synchronization algorithms that enable rhythmic flight performances of multiple quadrocopters to music.
Dr. Michael Sherback
Michael wrote core estimation and motion-control software as a postdoc in 2009. This is still in use as of 2012. He also wrote a version of the overall flight control software with an architecture that allowed fully break-pointable simulation of flight, and created demo routines for this (spinning/flipping figure 8s, etc.).
Christoph developed and helped implement the original calibration methodology, used to compensate for propeller and motor wear on the flying vehicles.