Deep Drone Acrobatics

idw – Informationsdienst Wissenschaft

Nachrichten, Termine, Experten

Grafik: idw-Logo
Thema Corona

Science Video Project

Share on: 
06/23/2020 13:39

Deep Drone Acrobatics

Melanie Nyfeler Kommunikation
Universität Zürich

    A navigation algorithm developed at the University of Zurich enables drones to learn challenging acrobatic maneuvers. Autonomous quadcopters can be trained using simulations to increase their speed, agility and efficiency, which benefits conventional search and rescue operations.

    Since the dawn of flight, pilots have used acrobatic maneuvers to test the limits of their airplanes. The same goes for flying drones: Professional pilots often gage the limits of their drones and measure their level of mastery by flying such maneuvers in competitions

    Greater efficiency, full speed

    Working together with microprocessor company Intel, a team of researchers at the University of Zurich has now developed a quadrotor helicopter, or quadcopter, that can learn to fly acrobatic maneuvers. While a power loop or a barrel role might not be needed in conventional drone operations, a drone capable of performing such maneuvers is likely to be much more efficient. It can be pushed to its physical limits, make full use of its agility and speed, and cover more distance within its battery life.

    The researchers have developed a navigation algorithm that enables drones to autonomously perform various maneuvers – using nothing more than onboard sensor measurements. To demonstrate the efficiency of their algorithm, the researchers flew maneuvers such as a power loop, a barrel roll or a matty flip, during which the drone is subject to very high thrust and extreme angular acceleration. “This navigation is another step towards integrating autonomous drones in our daily lives,” says Davide Scaramuzza, robotics professor and head of the robotics and perception group at the University of Zurich.

    Trained in simulation

    At the core of the novel algorithm lies an artificial neural network that combines input from the onboard camera and sensors and translates this information directly into control commands. The neural network is trained exclusively through simulated acrobatic maneuvers. This has several advantages: Maneuvers can easily be simulated through reference trajectories and do not require expensive demonstrations by a human pilot. Training can scale to a large number of diverse maneuvers and does not pose any physical risk to the quadcopter.

    Only a few hours of simulation training are enough and the quadcopter is ready for use, without requiring additional fine-tuning using real data. The algorithm uses abstraction of the sensory input from the simulations and transfers it to the physical world. “Our algorithm learns how to perform acrobatic maneuvers that are challenging even for the best human pilots,” says Scaramuzza.

    Fast drones for fast missions

    However, the researchers acknowledge that human pilots are still better than autonomous drones. “Human pilots can quickly process unexpected situations and changes in the surroundings, and are faster to adjust,” says Scaramuzza. Nevertheless, the robotics professor is convinced that drones used for search and rescue missions or for delivery services will benefit from being able to cover long distances quickly and efficiently.


    Contact for scientific information:

    Prof. Dr. Davide Scaramuzza
    Department of Informatics
    University of Zurich
    Phone: +41 044 635 24 07
    Phone: +49 172 662 78 02

    Original publication:

    E. Kaufmann, A. Loquercio, R. Ranftl, M. Müller, V. Koltun, D. Scaramuzza: Deep Drone Acrobatics. Robotics: Science and Systems (RSS), 11 June 2020.

    More information:

    Criteria of this press release:
    Electrical engineering, Information technology, Social studies, Traffic / transport
    transregional, national
    Research results, Transfer of Science or Research


    Search / advanced search of the idw archives
    Combination of search terms

    You can combine search terms with and, or and/or not, e.g. Philo not logy.


    You can use brackets to separate combinations from each other, e.g. (Philo not logy) or (Psycho and logy).


    Coherent groups of words will be located as complete phrases if you put them into quotation marks, e.g. “Federal Republic of Germany”.

    Selection criteria

    You can also use the advanced search without entering search terms. It will then follow the criteria you have selected (e.g. country or subject area).

    If you have not selected any criteria in a given category, the entire category will be searched (e.g. all subject areas or all countries).

    Cookies optimize the use of our services. By surfing on you agree to the use of cookies. Data Confidentiality Statement