Robohub.org
 

Quadrocopter failsafe algorithm: Recovery after propeller loss


by
04 March 2014



share this:
Drone-Failsafe-Algorithm

UPDATE 04/03/2014:

In this video update, we show that a quadrocopter can be safely piloted by hand after a motor fails, without the aid of a motion capture system. This follows our previous video, where we demonstrated how a complete propeller failure can be automatically detected, and that a quadrocopter can still maintain stable flight despite the complete loss of a propeller. 

In the earlier video, we relied on an external motion capture system to measure the quadrocopter’s position and orientation.  By moving more of the algorithm onto the vehicle, the quadrocopter can now be piloted by hand after the failure. The algorithm is executed on the quadrocopter’s onboard micro-controller, and the only sensors required are the quadrocopter’s angular rate gyroscopes. We use blinking LEDs, mounted on the quadrocopter’s arms, to indicate a virtual yaw angle, so that the pilot can control the vehicle with the same remote control commands after the failure. As an alternative to the LED system, an onboard magnetometer could be used to track the vehicle’s yaw angle. Alternatively, by using more sophisticated algorithms, the system could be made to work using only the rate gyroscopes.

ORIGINAL STORY 02/12/2013

The video in this article shows an automatic failsafe algorithm that allows a quadrocopter to gracefully cope with the loss of a propeller. The propeller was mounted without a nut, and thus eventually vibrates itself loose. The failure is detected automatically by the system, after which the vehicle recovers and returns to its original position. The vehicle finally executes a controlled, soft landing, on a user’s command.

The failsafe controller uses only hardware that is readily available on a standard quadrocopter, and could thus be implemented as an algorithmic-only upgrade to existing systems. Until now, the only way a multicopter could survive the loss of a propeller (or motor), is by having redundancy (e.g. hexacopters, octocopters). However, this redundancy comes at the cost of additional structural weight, reducing the vehicle’s useful payload. Using this technology, (more efficient) quadrocopters can be used in safety critical applications, because they still have the ability to gracefully recover from a motor/propeller failure.

Failsafe_algorithm_sequence
(A) shows the quadrocopter in normal operation. In (B) the propeller detaches due to vibrations, and the quadrocopter starts pitching over in (C) – (E). In (F) the vehicle has regained control, and is flying stably.

The key functionality of the failsafe controller is a novel algorithm that I developed as part of my doctoral research at the Institute for Dynamic Systems and Control at ETH Zurich. This new approach allows such a vehicle to remain in flight despite the loss of one, two, or even three propellers. Having lost one (or more) propellers, the vehicle enters a continuous rotation — we then control the direction of this axis of rotation, and the total thrust that the vehicle produces, allowing us to control the vehicle’s acceleration and thus position.

Even if the vehicle can no longer produce sufficient thrust to support its own weight, this technology would still be useful: one could, for example, try to minimize the multicopter’s velocity when it hits the ground, or steer the multicopter away from dangerous situations such as water, or people on the ground.

This control approach can also be applied to design novel flying vehicles — we will be releasing some related results soon.

This technology is patent pending.

For more information, have a look at the Flying Machine Arena website, the IDSC research page, or just post your question in the comments below.

 

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: , , , , , , , , , , , , , , ,


Mark Mueller is a researcher at ETH Zurich's Flying Machine Arena.
Mark Mueller is a researcher at ETH Zurich's Flying Machine Arena.





Related posts :



Robot Talk Episode 119 – Robotics for small manufacturers, with Will Kinghorn

  02 May 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Will Kinghorn from Made Smarter about how to increase adoption of new tech by small manufacturers.

Multi-agent path finding in continuous environments

  01 May 2025
How can a group of agents minimise their journey length whilst avoiding collisions?

Interview with Yuki Mitsufuji: Improving AI image generation

  29 Apr 2025
Find out about two pieces of research tackling different aspects of image generation.

Robot Talk Episode 118 – Soft robotics and electronic skin, with Miranda Lowther

  25 Apr 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Miranda Lowther from the University of Bristol about soft, sensitive electronic skin for prosthetic limbs.

Interview with Amina Mević: Machine learning applied to semiconductor manufacturing

  17 Apr 2025
Find out how Amina is using machine learning to develop an explainable multi-output virtual metrology system.

Robot Talk Episode 117 – Robots in orbit, with Jeremy Hadall

  11 Apr 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Jeremy Hadall from the Satellite Applications Catapult about robotic systems for in-orbit servicing, assembly, and manufacturing.

Robot Talk Episode 116 – Evolved behaviour for robot teams, with Tanja Kaiser

  04 Apr 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Tanja Katharina Kaiser from the University of Technology Nuremberg about how applying evolutionary principles can help robot teams make better decisions.

AI can be a powerful tool for scientists. But it can also fuel research misconduct

  31 Mar 2025
While AI is allowing scientists to make technological breakthroughs, there’s also a darker side to the use of AI in science: scientific misconduct is on the rise.





Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


©2024 - Association for the Understanding of Artificial Intelligence


 












©2021 - ROBOTS Association