Felix helped develop the first revision of custom electronics and firmware for the quadrocopters used in the Flying Machine Arena.
Dr. Federico Augugliaro
Federico started working on the Flying Machine Arena in 2008, contributing to the Music in Motion project. During his PhD from 2011 and 2015, Federico developed algorithms for multi-vehicle coordinated flight, physical human-quadrocopter interaction, and aerial construction. He concluded his work by using flying machines to build a 7.4 m long rope bridge you can walk on.
Dr. Dario Brescianini
Dario carried out his doctoral research in the Flying Machine Arena from 2013 to 2018. His research focused on the design and control of novel flying machines, trajectory planning, attitude control and learning. He was the main developer of the Omnicopter, a high performance flying machine that can generate thrusts and torques in any direction and enables novel flight maneuvers. Additionally, he contributed to various core algorithms of the Flying Machine Arena including the control and simulation algorithms.
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.
Dr. Luca Gherardi
Luca focused on improving the Flying Machine Arena software architecture. During his PostDoc, he designed and implemented flexible communication protocols used to exchange information between vehicles and offboard control software. This information includes quasi real-time command, high level command, configuration parameters, and state information. Additionally he contributed to the design of a new, more modular, and more flexible simulator.
Dr. Rajan Gill
Rajan Gill was part of the Flying Machine Arena team from 2015 to 2019. His research had an interdisciplinary focus covering various aspects relating to VTOL UAVs: 1) deriving low-order, yet computationally efficient aerodynamic models for propellers in wide regimes; 2) improving upon state-of-the-art Kalman filtering methods for states involving attitudes, and 3) the design and control of an annular wing VTOL UAV. He also worked on path following control algorithms for quadrotors that can, for example, achieve a platoon formation while maintaining a path constraint.
Dr. Markus Hehn
Markus worked on the Flying Machine Arena from 2009 to 2014. He contributed to and maintained the system’s core control, estimation, calibration, and simulation algorithms. Markus also developed real-time trajectory generation algorithms, collision avoidance methods, control laws for improving tracking performance in repeated motions, and task-specific controllers for aerobatic flight such as interception maneuvers and balancing an inverted pendulum on a flying robot.
Dr. Anton Ledergerber
Anton Ledergerber was part of the Flying Machine Arena team from 2015 to 2019. His research focused on ultra-wideband localization and state estimation. In particular, he developed a one-way communication protocol, a calibration procedure and a novel angle of arrival estimation method that allowed for accurate localization of multiple robots. Additionally, he worked on a state estimate recovery algorithm for autonomous quadcopters and an ultra-wideband radar network.
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.
Dr. Mark Mueller
Mark worked on the Flying Machine Arena from 2011 to 2015. His research work focused on computationally efficient trajectory generation, fail-safe control for multicopters, the creation of novel multicopter designs with fewer propellers, and state estimation. Additionally, he contributed to and helped maintain various parts of the system’s infrastructure. He’s an all-round swell guy.
Dr. Robin Ritz
Robin was part of the Flying Machine Arena team from 2012 to 2017. His research investigated various topics aiming at enhancing the capabilities of small, unmanned aerial vehicles. In particular, he worked on methods that addressed problems such as carrying a non-rigid payload with multiple cooperating vehicles, improving performance of a repetitive task through onboard learning, and designing and controlling a vehicle that combines hover capabilities with efficient aerodynamic forward flight.
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.).
Weixuan Zhang was part of the Flying Machine Arena team from 2015 to 2018. His research focused on the Monospinner, a mechanical simple flying vehicle with only one moving part. In particular, he was responsible for the modeling, design, controller synthesis and controllability analysis of the Monospinner.
Master’s Thesis Students
Dancing quadrocopters: trajectory generation, feasibility, and user interface
State Estimate Recovery for Autonomous Quadcopters
State Estimation Using UWB Radios and Inertial Sensors
Quadrocopter Pole Acrobatics
Quadrotor Collision Avoidance
Lorenzo Garbani Marcantini
Quadrocopter Pendulum Swing-up
Mission-design Tool for Cooperating Robots
Can we do better than humans do? Learning aerobatic maneuvers from observation
Knowledge Transfer for High-Performance Quadrocopter Maneuvers
Augmenting Ultra-Wideband Localization with Computer Vision for Accurate Flight
Modelling, System Identification and Control of N-Coptercopters
Model Predictive Control for Tailsitters
Implementation and evaluation of iterative learning algorithms for precise quadrocopter trajectory tracking
Quadrocopter Ball Juggling
Cooperative Quadrocopter Ball Throwing and Catching
Rope Deployment with Quadrocopters: Modeling, Simulation and Estimation
High-Speed Flight of a Tethered Quadrocopter
Bas van der Heijden
Iterative Bias Estimation for an Ultra-Wideband Localization System
Parameter Identification for an Autonomous Quadrotor
Design, Modelling and Control of a Single Propeller Vehicle
Aerial Disturbances on Quadrocopters
Semester Project Students
System Identification of the Omnicopter
Extending iterative learning control to multi-agent systems
Improving the pendulum throw
A platform for dance performances with multiple quadrocopters: graphical user interface and demonstration
Fault detection and user interface for the FMA
Quadrotor Ball Launching
Control Allocation for a Variable-Pitch Quadrocopter
Nonlinear Quadrocopter Attitude Control
Enabling Fast Reversing on an Open-Source BLDC Controller
Improving the throw of the Monospinner
Improving the Quadrocopter Blind Hover
Design and Control of an Agile Tiltrotor Vehicle
Quadrocopter Localization via Landmarks and Monocular Vision
Path-constrained human interaction with quadrotors
Control Strategy for the Over-Actuated Omnicopter
Path following for quadrotors
Low-Latency Wireless Communication
Quadrocopter Control by Shifting Masses
Automatic Tuning of PID Controllers for Flight Control
Online Measurement Model Adaption
Integrating fixed wing UAVs in the FMA
Accurate Inertial Measurements on MAVs
Time-optimal Quadrotor Control
Music-Driven Trajectory Generation
Manufacturing an annual wing
Flying With Payloads
Brushless Motor Controller Firmware for the FMA
Flying a Circular Trajectory with Two Quadrocopters Connected by a String
Quadrocopter time optimal angular rate control
Implementation of a quaternion-based LQR controller for quadrocopters
Fly! Iterative learning control for quadrocopters
Quadrotor platooning with virtual path constraints
Precise synchronized periodic quadrocopter motion in three dimensions based on feed-forward parameter
New synchronized quadrocopter motions: bounce motions in 2D
Application of Machine Learning to Quadrocopter Slalom Flying
Catching rings on a quadrocopter
Design of building primitives
Randomised Trajectory Generation
Bachelor’s Thesis Students
Sensor characterization for outdoor flight
Interaction with a Quadrotor via the Kinect
Synchronizing motion and music beat – a dancing quadrocopter
Motor Torque Control
Force Estimator Validation
Modeling And Control of Lighter Than Air Robots
Improving the Throw of the Monospinner using Model Predictive Control and Controller Parameter Tuning
Tailsitter System Modeling
Implementation of a direct method for the computation of time optimal quadrotor maneuvers
The tricoptercopter and state estimation
Taming LiPo Batteries
Using Magnetometers and Barometers During Indoor Flight
Improved Filter for Ball Tracking/Prediction
Extensions to the rhythmic side-to-side motion
A Flying Camera
Generation of acrobatic trajectories for quadrocopters
Quadrocopter ball juggling optimization
Balancing the Omnicopter
Zhi Hao Luo
Kiera van der Sande