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Towards Low-Latency High-Bandwidth Control of Quadrotors using Event Cameras


Dimitrova, Rika Sugimoto; Gehrig, Mathias; Brescianini, Dario; Scaramuzza, Davide (2020). Towards Low-Latency High-Bandwidth Control of Quadrotors using Event Cameras. In: 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 1 July 2020 - 1 October 2020. IEEE, 4294-4300.

Abstract

Event cameras are a promising candidate to enable high speed vision-based control due to their low sensor latency and high temporal resolution. However, purely event-based feedback has yet to be used in the control of drones. In this work, a first step towards implementing low-latency high-bandwidth control of quadrotors using event cameras is taken. In particular, this paper addresses the problem of one-dimensional attitude tracking using a dualcopter platform equipped with an event camera. The event-based state estimation consists of a modified Hough transform algorithm combined with a Kalman filter that outputs the roll angle and angular velocity of the dualcopter relative to a horizon marked by a black-and-white disk. The estimated state is processed by a proportional-derivative attitude control law that computes the rotor thrusts required to track the desired attitude. The proposed attitude tracking scheme shows promising results of event-camera-driven closed loop control: the state estimator performs with an update rate of 1 kHz and a latency determined to be 12 ms, enabling attitude tracking at speeds of over 1600°/s.

Abstract

Event cameras are a promising candidate to enable high speed vision-based control due to their low sensor latency and high temporal resolution. However, purely event-based feedback has yet to be used in the control of drones. In this work, a first step towards implementing low-latency high-bandwidth control of quadrotors using event cameras is taken. In particular, this paper addresses the problem of one-dimensional attitude tracking using a dualcopter platform equipped with an event camera. The event-based state estimation consists of a modified Hough transform algorithm combined with a Kalman filter that outputs the roll angle and angular velocity of the dualcopter relative to a horizon marked by a black-and-white disk. The estimated state is processed by a proportional-derivative attitude control law that computes the rotor thrusts required to track the desired attitude. The proposed attitude tracking scheme shows promising results of event-camera-driven closed loop control: the state estimator performs with an update rate of 1 kHz and a latency determined to be 12 ms, enabling attitude tracking at speeds of over 1600°/s.

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Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Software
Physical Sciences > Control and Systems Engineering
Physical Sciences > Artificial Intelligence
Physical Sciences > Electrical and Electronic Engineering
Scope:Discipline-based scholarship (basic research)
Language:English
Event End Date:1 October 2020
Deposited On:17 Dec 2020 09:00
Last Modified:06 Mar 2024 14:33
Publisher:IEEE
ISBN:978-1-7281-7395-5
OA Status:Green
Publisher DOI:https://doi.org/10.1109/icra40945.2020.9197530
Related URLs:https://ieeexplore.ieee.org/document/9197530
Other Identification Number:merlin-id:20311
  • Content: Accepted Version