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Accommodating unobservability to control flight attitude with optic flow.

Guido C H E de CroonJulien J G DupeyrouxChristophe De WagterAbhishek ChatterjeeDiana A OlejnikFranck Ruffier
Published in: Nature (2022)
Attitude control is an essential flight capability. Whereas flying robots commonly rely on accelerometers 1 for estimating attitude, flying insects lack an unambiguous sense of gravity 2,3 . Despite the established role of several sense organs in attitude stabilization 3-5 , the dependence of flying insects on an internal gravity direction estimate remains unclear. Here we show how attitude can be extracted from optic flow when combined with a motion model that relates attitude to acceleration direction. Although there are conditions such as hover in which the attitude is unobservable, we prove that the ensuing control system is still stable, continuously moving into and out of these conditions. Flying robot experiments confirm that accommodating unobservability in this manner leads to stable, but slightly oscillatory, attitude control. Moreover, experiments with a bio-inspired flapping-wing robot show that residual, high-frequency attitude oscillations from flapping motion improve observability. The presented approach holds a promise for robotics, with accelerometer-less autopilots paving the road for insect-scale autonomous flying robots 6 . Finally, it forms a hypothesis on insect attitude estimation and control, with the potential to provide further insight into known biological phenomena 5,7,8 and to generate new predictions such as reduced head and body attitude variance at higher flight speeds 9 .
Keyphrases
  • high frequency
  • physical activity
  • transcranial magnetic stimulation
  • machine learning
  • working memory
  • optical coherence tomography
  • high resolution