Machine vision systems using convolutional neural networks (CNNs) for robotic applications are increasingly being developed. Conventional vision CNNs are driven by camera frames at constant sample rate, thus achieving a fixed latency and power consumption tradeoff. This paper describes further work on the first experiments of a closed-loop robotic system integrating a CNN together with a Dynamic and Active Pixel Vision Sensor (DAVIS) in a predator/prey scenario. The DAVIS, mounted on the predator Summit XL robot, produces frames at a fixed 15 Hz frame-rate and Dynamic Vision Sensor (DVS) histograms containing 5k ON and OFF events at a variable frame-rate ranging from 15-500 Hz depending on the robot speeds. In contrast to conventional frame-based systems, the latency and processing cost depends on the rate of change of the image. The CNN is trained offline on the 1.25h labeled dataset to recognize the position and size of the prey robot, in the field of view of the predator. During inference, combining the ten output classes of the CNN allows extracting the analog position vector of the prey relative to the predator with a mean 8.7% error in angular estimation. The system is compatible with conventional deep learning technology, but achieves a variable latency-power tradeoff that adapts automatically to the dynamics. Finally, investigations on the robustness of the algorithm, a human performance comparison and a deconvolution analysis are also explored.


    Zugriff

    Download


    Exportieren, teilen und zitieren



    Titel :

    PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing


    Beteiligte:
    Moeys, Diederik Paul (Autor:in) / Neil, Daniel (Autor:in) / Corradi, Federico (Autor:in) / Kerr, Emmett (Autor:in) / Vance, Philip (Autor:in) / Das, Gautham (Autor:in) / Coleman, Sonya A (Autor:in) / McGinnity, Thomas M (Autor:in) / Kerr, Dermot (Autor:in) / Delbruck, Tobi (Autor:in)

    Erscheinungsdatum :

    2018-06-29


    Anmerkungen:

    Moeys, Diederik Paul; Neil, Daniel; Corradi, Federico; Kerr, Emmett; Vance, Philip; Das, Gautham; Coleman, Sonya A; McGinnity, Thomas M; Kerr, Dermot; Delbruck, Tobi (2018). PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing. In: 4th International Conference on Event-Based Control, Communication and Signal Processing (EBCCSP) 2018, Perpignan, 27 June 2018 - 29 June 2018.



    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629



    Mathematical modelling of prey-predator interaction with disease in prey

    Ghosh, Mini / Li, Xue-Zhi | British Library Online Contents | 2016


    Chasing down variable stars from a decade-long dataset

    Noughani, Nikki Giti / Kotulla, Ralf | TIBKAT | 2020


    Drone with self camera and photographer chasing function

    Europäisches Patentamt | 2017

    Freier Zugriff

    Drone with self camera and photographer chasing function

    Europäisches Patentamt | 2017

    Freier Zugriff

    DRONE WITH SELF CAMERA AND PHOTOGRAPHER CHASING FUNCTION

    JUNG KWAN SEEN | Europäisches Patentamt | 2016

    Freier Zugriff