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 degrees per second.
Reference: Rika Sugimoto Dimitrova, Mathias Gehrig, Dario Brescianini, and Davide Scaramuzza. Towards Low-Latency High-Bandwidth Control of Quadrotors using Event Cameras.
IEEE International Conference on Robotics and Automation (ICRA), Paris, 2020.
PDF: http://rpg.ifi.uzh.ch/docs/ICRA20_Sugimoto.pdf
For more info about our research page on event based vision: http://rpg.ifi.uzh.ch/research_dvs.html
Other resources on event cameras:
https://github.com/uzh-rpg/event-based_vision_resources
Affiliations:
R. Dimitrova, M. Gehrig, D. Brescianini and D. Scaramuzza are with the Robotics and Perception Group, Dept. of Informatics, University of Zurich, and Dept. of Neuroinformatics, University of Zurich and ETH Zurich, Switzerland http://rpg.ifi.uzh.ch/
