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Journal Articles PLoS Computational Biology Year : 2018

Modeling visual-based pitch, lift and speed control strategies in hoverflies


To avoid crashing onto the floor, a free falling fly needs to trigger its wingbeats quickly and control the orientation of its thrust accurately and swiftly to stabilize its pitch and hence its speed. Behavioural data have suggested that the vertical optic flow produced by the fall and crossing the visual field plays a key role in this anti-crash response. Free fall behavior analyses have also suggested that flying insect may not rely on graviception to stabilize their flight. Based on these two assumptions, we have developed a model which accounts for hoverflies´positionhoverflies´position and pitch orientation recorded in 3D with a fast stereo camera during experimental free falls. Our dynamic model shows that optic flow-based control combined with closed-loop control of the pitch suffice to stabilize the flight properly. In addition, our model sheds a new light on the visual-based feedback control of fly´s pitch, lift and thrust. Since graviceptive cues are possibly not used by flying insects, the use of a vertical reference to control the pitch is discussed, based on the results obtained on a complete dynamic model of a virtual fly falling in a textured corridor. This model would provide a useful tool for understanding more clearly how insects may or not estimate their absolute attitude.
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hal-01693713 , version 1 (26-01-2018)



Roman Goulard, Jean-Louis Vercher, Stéphane Viollet. Modeling visual-based pitch, lift and speed control strategies in hoverflies. PLoS Computational Biology, 2018, 14 (1), pp.e1005894. ⟨10.1371/journal.pcbi.1005894⟩. ⟨hal-01693713⟩
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