Evolutionary Optimization of Neurocontroller for Physically Simulated Compliant-Wing Ornithopter

Yoonsik Shim

doi:https://doi.org/10.9708/jksci.2019.24.12.025

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2019, 24(12), pp.25-33
DOI :https://doi.org/10.9708/jksci.2019.24.12.025
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Yoonsik Shim ¹

¹ 고려대학교

ABSTRACT

This paper presents a novel evolutionary framework for optimizing a bio-inspired fully dynamic neurocontroller for the maneuverable flapping flight of a simulated bird-sized ornithopter robot which takes advantage of the morphological computation and mechansensory feedback to improve flight stability. In order to cope with the difficulty of generating robust flapping flight and its maneuver, the wing of robot is modelled as a series of sub-plates joined by passive torsional springs, which implements the simplified version of feathers attached to the forearm skeleton. The neural controller is designed to have a bilaterally symmetric structure which consists of two fully connected neural network modules receiving mirrored sensory inputs from a series of flight navigation sensors as well as feather mechanosensors to let them participate in pattern generation. The synergy of wing compliance and its sensory reflexes gives a possibility that the robot can feel and exploit aerodynamic forces on its wings to potentially contribute to the agility and stability during flight. The evolved robot exhibited target-following flight maneuver using asymmetric wing movements as well as its tail, showing robustness to external aerodynamic disturbances.
KEYWORDS

Flapping flight , Evolutionary robotics , Neural network , Simulation , Compliance
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