Publications [#323880] of Silvia Ferrari

Papers Published

1. Clawson, TS; Ferrari, S; Fuller, SB; Wood, RJ, Spiking neural network (SNN) control of a flapping insect-scale robot, 2016 Ieee 55th Conference on Decision and Control, Cdc 2016 (December, 2016), pp. 3381-3388, IEEE, ISBN 9781509018376 [doi]
   (last updated on 2021/09/05)

   Abstract:
   The flapping microrobot known as RoboBee is the first robot to demonstrate insect-scale flight, as well as the most capable flying robotic insect to date. Controlled hover, trajectory-following, and perching have been accomplished by means of onboard sensors and actuators fabricated with the robot using a 'pop-up book MEMS' process based on smart composite microstructures. This paper presents a RoboBee bio-inspired controller that closes the loop between the onboard sensors and actuators by means of a leaky integrate-and-fire spiking neural network that adapts in flight using a reward-modulated Hebbian plasticity mechanism.