Videos

Estimating the angle of arrival of a ultra-wideband radio signal using a single, static antenna. Researchers: Anton Ledergerber and Raffaello D’Andrea.

State estimate recovery for autonomous quadcopters using onboard IMU and air pressure sensor data only. Researchers: Luciano Beffa, Anton Ledergerber, Raffaello D’Andrea.

The vehicle combines the advantages of a quadrotor (mechanically simple, robust hover capability, vertical takeoff and land, etc.) and a fixed wing vehicle (efficient high speed forward flight). The annular wing provides lift, enshrouds the propeller blades for safety, and can lead to noise reduction. The vehicle is autonomous. Researchers: Rajan Gill and Raffaello D’Andrea.

Supplementary video for the open invited track on ‘Iterative Learning Control and Repetitive Control’ at the 21st IFAC World Congress in Berlin. Researchers: Bas van der Heijden, Anton Ledergerber, Rajan Gill, Rafaello D’Andrea.

Supplementary video for the 2019 IEEE Conference on Control Technology and Applications. Authors: Jianwei Sun & Rajan Gill.

This video shows the experimental results discussed in the paper entitled ‘Tilt-Prioritized Quadrocopter Attitude Control’. Researchers: Dario Brescianini and Raffaello D’Andrea.

This video shows a quadrotor performing a looping trajectory while balancing an inverted pendulum at the same time. By Julien Kohler, Michael Mühlebach, Dario Brescianini, and Raffaello D’Andrea.

A computationally efficient trajectory generator for fully actuated multirotor vehicles is used to enable an omni-directional eight-rotor vehicle to fetch a thrown ball. Researchers: Dario Brescianini and Raffaello D’Andrea.

Award-winning PhD Federico Augugliaro will give you an insight on how to coordinate drones, create drone shows, and how to even start building our infrastructure using these little flying machines at a TEDx event.

An omni-directional six degrees-of-freedom flying machine. Researchers: Dario Brescianini and Raffaello D’Andrea.

The first prototype of the Flying Ring flying tethered. The annular wing (or ring) has a flat airfoil shape. Researchers: Rajan Gill and Raffaello D’Andrea.

An agile and robust flying vehicle combining hover capabilities with efficient forward flight. Researchers: Robin Ritz and Raffaello D’Andrea.

An introduction to the monospinner, the mechanically simplest controllable flying machine in existence. It has only one moving part (the rotating propeller). The vehicle features no additional actuators or aerodynamic surfaces. Researchers: Weixuan Zhang, Mark W. Mueller and Raffaello D’Andrea.

This video introduces the Flying Platform, a flying machine actuated by electric ducted fans. Lead Researchers: Michael Muehlebach and Raffaello D’Andrea.

Quadcopters autonomously assembling a rope bridge. This is part of a body of research in aerial construction, a field that addresses the construction of structures with the aid of flying machines. Researchers: Federico Augugliaro, Ammar Mirjan, Fabio Gramazio, Matthias Kohler, and Raffaello D’Andrea.

Two quadcopters capable of not only balancing an inverted pendulum, but also of launching it off the vehicle and catching it again. Researchers: Dario Brescianini, Markus Hehn, and Raffaello D’Andrea.

A new algorithm for robust hover control of a tailsitter flying machine. The tailsitter is able to recover from any orientation, including upside down. Researchers: Robin Ritz and Raffaello D’Andrea.

High-speed steady flight in confined spaces for tethered quadcopters. Researchers: Maximilian Schulz, Federico Augugliaro, Robin Ritz, and Raffaello D’Andrea.

A novel type of flying vehicle, which uses multiple rotors spinning in the same direction. Researchers: Mark W. Mueller and Raffaello D’Andrea.

An algorithm allowing a quadcopter to maintain stable flight despite the complete loss of a motor/propeller. Researchers: Mark W. Mueller, Simon Berger, and Raffaello D’Andrea.

At TEDx, Markus Hehn showcased his research, which lies in the field of algorithms for the control of aerial vehicles, with a specific focus on exploiting the exceptional agility of the quadrotor vehicles that are used in the Flying Machine Arena.

An automatic failsafe algorithm that allows a quadcopter to gracefully cope with the loss of a propeller. The propeller was mounted without a nut, and thus eventually vibrates itself loose. Researchers: Mark W. Mueller and Raffaello D’Andrea.

An iterative learning algorithm that allows for accurate trajectory tracking for quadcopters executing periodic maneuvers. Researchers: Markus Hehn and Raffaello D’Andrea.

Quadcopters assembling prototypical tensile structures. This is part of a body of research in aerial construction, a field that addresses the construction of structures with the aid of flying machines. Researchers: Federico Augugliaro, Ammar Mirjan, Fabio Gramazio, Matthias Kohler, and Raffaello D’Andrea.

A method for rapidly generating and evaluating quadcopter interception trajectories. Researchers: Mark W. Mueller, Markus Hehn, and Raffaello D’Andrea.

The Distributed Flight Array is a modular robotic vehicle consisting of multiple autonomous single-rotor units that are able to drive, dock with its peers, and coordinate with one another in order to drive and fly together. Researchers: Raymond Oung and Raffaello D’Andrea.

Quadcoptor ‘dance’ trajectories are pre-designed and parameterized based off the structure of analyzed music. Researchers: Federico Augugliaro, Angela P. Schoellig and Raffaello D’Andrea.

A quadcopter learning to fly slalom courses.

Autonomous modular flight of the Distributed Flight Array for up to 12 modules. Researchers: Raymond Oung and Raffaello D’Andrea.

Flight of the Distributed Flight Array using 6 modules flown outdoors in a variety of configurations. Researchers: Raymond Oung and Raffaello D’Andrea.

A quadcopter learning to fly arbitrarily configured slalom courses in minimum time. Researchers: Angela Schoellig, Fabian Mueller and Raffaello D’Andrea.

To toss the ball, the quadcopters accelerate rapidly outward to stretch the net tight between them and launch the ball up. Once recovered, the quadrotors cooperatively position the net below the ball in order to catch it. Researchers: Robin Ritz, Mark W. Müller, Markus Hehn, and Raffaello D’Andrea.

A showcase of the Flying Machine Arena and its quadcoptors, which are shown executing maneuvers and moving in formations.

As hard-working PhD students went home on a Christmas evening, Juliet, a little quadcopter, found herself awake and unable to sleep…so she decided to build her own tree! By Sergei Lupashin, Claudia Fischer, Angela Schoellig, and Markus Waibel.

A Dance of the Quadcopters in the ETH Flying Machine Arena to the music track ‘Armageddon’. Researchers: Federico Augugliaro, Angela Schoellig and Raffaello D’Andrea.

Fast and safe transitions of multiple quadcopters are often required in the Flying Machine Arena. In this video, we use an algorithm based on convex optimization to plan collision-free trajectories. Researchers: Federico Augugliaro, Angela Schoellig and Raffaello D’Andrea.

Enabling autonomous systems – such as the flying robot in the video – to ‘learn’ the way humans do: through practice. Researchers: Angela Schoellig, Fabian Mueller and Raffaello D’Andrea.

A demo of a fast, dynamic interaction with a quadrotor vehicle using the Kinect in the Flying Machine Arena.

Ball juggling experiments with quadrotors in the ETH Flying Machine Arena. Researchers: Mark Müller, Sergei Lupashin and Raffaello D’Andrea.

Video overview of the ETH Flying Machine Arena (FMA) as of 2010. Researchers: Sergei Lupashin, Angela Schöllig, Markus Hehn, Raffaello D’Andrea.

One of our little quadcopters, ‘Echo’, took some time off from her busy little schedule one evening and decided to play a little something for the holidays. Researchers: Sergei Lupashin, Markus Hehn, Angela Schöllig and Raffaello D’Andrea

A quadcopter attempting to juggle a ball. Researchers: Mark Muller, Sergei Lupashin, Raffaello D’Andrea.

Yes, we dance again! Researchers: Angela Schoellig, Federico Augugliaro, and Raffaello D’Andrea.

A concept animation of the Distributed Flight Array (DFA). This multi-rotor vehicle consists of autonomous single-rotor modules that are able to drive, dock with its peers, and fly in a coordinated fashion. Researchers: Raymond Oung and Raffaello D’Andrea.

A quadcopter balances a pole. Researchers: Markus Hehn and Raffaello D’Andrea.

We work towards a platform for rhythmic flight with multiple quadcopters: We envision an expressive multi-media dance performance that is automatically composed and controlled, given a random piece of music. Researchers: Angela Schoellig, Federico Augugliaro, Raffaello D’Andrea.

Two quadcopters move in rhythm to the music in a dance performance. Researchers: Angela Schoellig, Federico Augugliaro, Sergei Lupashin and Raffaello D’Andrea.

Dancing Quadcopters. Researchers: Angela Schollig and Federico Augugliaro

‘A Simple Learning Strategy for High-Speed Quadrocopter Multi-Flips’,
Sergei lupashin, Angela Schöllig, Michael Sherback, Raffaello D’Andrea,
Sept 2009.

Synchronizing the Motion of a Quadcopter to Music. Researchers: Angela Schoellig, Federico Augugliaro, and Raffaello D’Andrea.

A short video which introduces the Distributed Flight Array (DFA). Experimental demonstrations in docking, driving, and flying have proven its feasibility as a research platform for investigating techniques in distributed estimation and control. Researchers: Raymond Oung and Raffaello D’Andrea.

Synchronized Motion of a Quadcopter. Researchers: Angela Schoellig, Federico Augugliaro, Raffaello D’Andrea.

A person holds a ‘wand’ with markers on it. Simple wand gestures tell the system what to do.

840deg/s autonomous flips in the ETH Zurich Flying Machine Arena.