Robohub.org
 

Quadrotor automatically recovers from failure or aggressive launch, without GPS

Credit: Robotics & Perception Group, University of Zurich.

Photo credit: Robotics & Perception Group, University of Zurich.

When a drone flies close to a building, it can temporarily lose its GPS signal and position information, possibly leading to a crash. To ensure safety, a fall-back system is needed to help the quadrotor regain stable flight as soon as possible. We developed a new technology that allows a quadrotor to automatically recover and stabilize from any initial condition without relying on external infrastructure like GPS. The technology allows the quadrotor system to be used safely both indoors and out, to recover stable flight after a GPS loss or system failure. And because the recovery is so quick, it even works to recover flight after an aggressive throw, allowing you to launch a quadrotor simply by tossing it in the air like a baseball.

How it works

Photo credit: Robotics & Perception Group, University of Zurich.

Photo credit: Robotics & Perception Group, University of Zurich.

Our quadrotor is equipped with a single camera, an inertial measurement unit, and a distance sensor (Teraranger One). The stabilization system of the quadrotor emulates the visual system and the sense of balance within humans. As soon as a toss or a failure situation is detected, our computer-vision software analyses the images for distinctive landmarks in the environment, and uses these to restore balance.

All the image processing and control runs on a smartphone processor on board the drone. The onboard sensing and computation renders the drone safe and able to fly unaided. This allows the drone to fulfil its mission without any communication or interaction with the operator.

The recovery procedure consists of multiple stages. First, the quadrotor stabilizes its attitude and altitude, and then it re-initializes its visual state-estimation pipeline before stabilizing fully autonomously. To experimentally demonstrate the performance of our system, in the video we aggressively throw the quadrotor in the air by hand and have it recover and stabilize all by itself. We chose this example as it simulates conditions similar to failure recovery during aggressive flight. Our system was able to recover successfully in several hundred throws in both indoor and outdoor environments.

More info: Robotics and Perception Group, University of Zurich.


References

M. Faessler, F. Fontana, C. Forster, D. Scaramuzza. Automatic Re-Initialization and Failure Recovery for Aggressive Flight with a Monocular Vision-Based Quadrotor. IEEE International Conference on Robotics and Automation (ICRA), Seattle, 2015.

M. Faessler, F. Fontana, C. Forster, E. Mueggler, M. Pizzoli, D. Scaramuzza. Autonomous, Vision-based Flight and Live Dense 3D Mapping with a Quadrotor Micro Aerial Vehicle. Journal of Field Robotics, 2015.



If you liked this article, you may also be interested in:

See all the latest robotics news on Robohub, or sign up for our weekly newsletter.

 



tags: , , , , , ,


Matthias Fässler is a PhD student at Prof. Scaramuzza's Robotics and Perception Group of the University of Zurich.
Matthias Fässler is a PhD student at Prof. Scaramuzza's Robotics and Perception Group of the University of Zurich.

Flavio Fontana is a PhD candidate at the Robotics and Perception Group.
Flavio Fontana is a PhD candidate at the Robotics and Perception Group.

Elias Müggler is a PhD student at Prof. Scaramuzza's Robotics and Perception Group of the University of Zurich.
Elias Müggler is a PhD student at Prof. Scaramuzza's Robotics and Perception Group of the University of Zurich.

Christian Forster is a PhD student at the Robotics and Perception Group.
Christian Forster is a PhD student at the Robotics and Perception Group.

Davide Scaramuzza is Assistant Professor of Robotics at the University of Zurich.
Davide Scaramuzza is Assistant Professor of Robotics at the University of Zurich.


Subscribe to Robohub newsletter on substack



Related posts :

Robot Talk Episode 147 – Miniature living robots, with Maria Guix

  06 Mar 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Maria Guix from the University of Barcelona about combining electronics and biology to create biohybrid robots with emergent properties.

Developing an optical tactile sensor for tracking head motion during radiotherapy: an interview with Bhoomika Gandhi

  05 Mar 2026
Bhoomika Gandhi discusses her work on an optical sensor for medical robotics applications.

Humanoid home robots are on the market – but do we really want them?

  03 Mar 2026
Last year, Norwegian-US tech company 1X announced “the world’s first consumer-ready humanoid robot designed to transform life at home”.

Robot Talk Episode 146 – Embodied AI on the ISS, with Jamie Palmer

  27 Feb 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Jamie Palmer from Icarus Robotics about building a robotic labour force to perform routine and risky tasks in orbit.

I developed an app that uses drone footage to track plastic litter on beaches

  26 Feb 2026
Plastic pollution is one of those problems everyone can see, yet few know how to tackle it effectively.

Translating music into light and motion with robots

  25 Feb 2026
Robots the size of a soccer ball create new visual art by trailing light that represents the “emotional essence” of music

Robot Talk Episode 145 – Robotics and automation in manufacturing, with Agata Suwala

  20 Feb 2026
In the latest episode of the Robot Talk podcast, Claire chatted to Agata Suwala from the Manufacturing Technology Centre about leveraging robotics to make manufacturing systems more sustainable.

Reversible, detachable robotic hand redefines dexterity

  19 Feb 2026
A robotic hand developed at EPFL has dual-thumbed, reversible-palm design that can detach from its robotic ‘arm’ to reach and grasp multiple objects.



Robohub is supported by:


Subscribe to Robohub newsletter on substack




 















©2026.02 - Association for the Understanding of Artificial Intelligence