Event-based visual guidance inspired by honeybees in a 3D tapered tunnel

In view of neuro-ethological findings on honeybees and our previously developed vision-based autopilot, in-silico experiments were performed in which a “simulated bee” was make to travel along a doubly tapering tunnel including for the first time event-based controllers. The “simulated bee” was equipped with: a minimalistic compound eye comprising 10 local motion sensors measuring the optic flow magnitude; two optic flow regulators updating the control signals whenever specific optic flow criteria changed; and three event-based controllers taking into account the error signals, each one in charge of its own translational dynamics. A MORSE/Blender based simulator-engine delivered what each of 20 “simulated photoreceptors” saw in the tunnel lined with high resolution natural 2D images. The “simulated bee” managed to travel safely along the doubly tapering tunnel without requiring any speed or distance measurements, using only a Gibsonian point of view, by: concomitantly adjusting the side thrust, vertical lift and forward thrust whenever a change was detected on the optic flow-based signal errors; avoiding collisions with the surface of the doubly tapering tunnel and decreasing or increasing its speed, depending on the clutter rate perceived by motion sensors.

[1]  Chiara Bartolozzi,et al.  Asynchronous frameless event-based optical flow , 2012, Neural Networks.

[2]  J. Koenderink,et al.  Facts on optic flow , 1987, Biological Cybernetics.

[3]  Mandyam V Srinivasan,et al.  Honeybees as a model for the study of visually guided flight, navigation, and biologically inspired robotics. , 2011, Physiological reviews.

[4]  M. Ibbotson.  Evidence for velocity–tuned motion-sensitive descending neurons in the honeybee , 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[5]  Nicolas Marchand,et al.  Further results on event-based PID controller , 2009, 2009 European Control Conference (ECC).

[6]  R. Hengstenberg,et al.  Estimation of self-motion by optic flow processing in single visual interneurons , 1996, Nature.

[7]  B. Hassenstein,et al.  Systemtheoretische Analyse der Zeit-, Reihenfolgen- und Vorzeichenauswertung bei der Bewegungsperzeption des Rüsselkäfers Chlorophanus , 1956 .

[8]  Nicolas Marchand,et al.  RT-MaG: An open-source SIMULINK toolbox for Linux-based real-time robotic applications , 2014, 2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014).

[9]  Gilberto Echeverria,et al.  Modular open robots simulation engine: MORSE , 2011, 2011 IEEE International Conference on Robotics and Automation.

[10]  Alexa Riehle,et al.  Directionally Selective Motion Detection by Insect Neurons , 1989 .

[11]  J. Zeil,et al.  Feed-forward and visual feedback control of head roll orientation in wasps (Polistes humilis, Vespidae, Hymenoptera) , 2013, Journal of Experimental Biology.

[12]  N. Franceschini,et al.  Modelling honeybee visual guidance in a 3-D environment , 2010, Journal of Physiology-Paris.

[13]  R. Hetherington.  The Perception of the Visual World , 1952 .

[14]  Franck Ruffier,et al.  Flying over uneven moving terrain based on optic-flow cues without any need for reference frames or accelerometers , 2015, Bioinspiration & biomimetics.

[15]  Ryad Benosman,et al.  Bioinspired event-driven collision avoidance algorithm based on optic flow , 2015, 2015 International Conference on Event-based Control, Communication, and Signal Processing (EBCCSP).

[16]  T. Delbruck,et al.  > Replace This Line with Your Paper Identification Number (double-click Here to Edit) < 1 , 2022 .

[17]  Dario Floreano,et al.  Miniature curved artificial compound eyes , 2013, Proceedings of the National Academy of Sciences.

[18]  K. Nakayama,et al.  Optical Velocity Patterns, Velocity-Sensitive Neurons, and Space Perception: A Hypothesis , 1974, Perception.

[19]  Tobi Delbrück,et al.  A 128$\times$ 128 120 dB 15 $\mu$s Latency Asynchronous Temporal Contrast Vision Sensor , 2008, IEEE Journal of Solid-State Circuits.

[20]  N. Franceschini,et al.  A Bio-Inspired Flying Robot Sheds Light on Insect Piloting Abilities , 2007, Current Biology.

[21]  Stéphane Viollet,et al.  A biomimetic vision-based hovercraft accounts for bees’ complex behaviour in various corridors , 2014, Bioinspiration & biomimetics.

[22]  Ryad Benosman,et al.  Asynchronous visual event-based time-to-contact , 2014, Front. Neurosci..

[23]  R.S.A. Brinkworth,et al.  Biomimetic Motion Detection , 2007, 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information.

[24]  Patrick Fabiani,et al.  Low-speed optic-flow sensor onboard an unmanned helicopter flying outside over fields , 2013, 2013 IEEE International Conference on Robotics and Automation.

[25]  Davide Scaramuzza,et al.  Low-latency event-based visual odometry , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).