Literature DB >> 24812052

Through the eyes of a bird: modelling visually guided obstacle flight.

Huai-Ti Lin1, Ivo G Ros, Andrew A Biewener.   

Abstract

Various flight navigation strategies for birds have been identified at the large spatial scales of migratory and homing behaviours. However, relatively little is known about close-range obstacle negotiation through cluttered environments. To examine obstacle flight guidance, we tracked pigeons (Columba livia) flying through an artificial forest of vertical poles. Interestingly, pigeons adjusted their flight path only approximately 1.5 m from the forest entry, suggesting a reactive mode of path planning. Combining flight trajectories with obstacle pole positions, we reconstructed the visual experience of the pigeons throughout obstacle flights. Assuming proportional-derivative control with a constant delay, we searched the relevant parameter space of steering gains and visuomotor delays that best explained the observed steering. We found that a pigeon's steering resembles proportional control driven by the error angle between the flight direction and the desired opening, or gap, between obstacles. Using this pigeon steering controller, we simulated obstacle flights and showed that pigeons do not simply steer to the nearest opening in the direction of flight or destination. Pigeons bias their flight direction towards larger visual gaps when making fast steering decisions. The proposed behavioural modelling method converts the obstacle avoidance behaviour into a (piecewise) target-aiming behaviour, which is better defined and understood. This study demonstrates how such an approach decomposes open-loop free-flight behaviours into components that can be independently evaluated.

Entities:  

Keywords:  flight guidance; obstacle negotiation; path planning; pigeon flight; proportional–derivative controller

Mesh:

Year:  2014        PMID: 24812052      PMCID: PMC4032538          DOI: 10.1098/rsif.2014.0239

Source DB:  PubMed          Journal:  J R Soc Interface        ISSN: 1742-5662            Impact factor:   4.118


  27 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2011-11-28       Impact factor: 11.205

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Journal:  Nature       Date:  1992-03-19       Impact factor: 49.962

Review 6.  The computational and neural basis of voluntary motor control and planning.

Authors:  Stephen H Scott
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Journal:  Vision Res       Date:  1987       Impact factor: 1.886

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Journal:  J Exp Anal Behav       Date:  1986-03       Impact factor: 2.468

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Journal:  Vision Res       Date:  1993-08       Impact factor: 1.886

10.  Visual control of flight speed in Drosophila melanogaster.

Authors:  Steven N Fry; Nicola Rohrseitz; Andrew D Straw; Michael H Dickinson
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  21 in total

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Authors:  Andrew M Hein; Michael A Gil; Colin R Twomey; Iain D Couzin; Simon A Levin
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4.  Finding the gap: a brightness-based strategy for guidance in cluttered environments.

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5.  Visual guidance of forward flight in hummingbirds reveals control based on image features instead of pattern velocity.

Authors:  Roslyn Dakin; Tyee K Fellows; Douglas L Altshuler
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6.  How biomechanics, path planning and sensing enable gliding flight in a natural environment.

Authors:  Pranav C Khandelwal; Tyson L Hedrick
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7.  A songbird inhibits blinking behaviour in flight.

Authors:  Jessica L Yorzinski
Journal:  Biol Lett       Date:  2020-12-16       Impact factor: 3.703

8.  Rules to fly by: pigeons navigating horizontal obstacles limit steering by selecting gaps most aligned to their flight direction.

Authors:  Ivo G Ros; Partha S Bhagavatula; Huai-Ti Lin; Andrew A Biewener
Journal:  Interface Focus       Date:  2017-02-06       Impact factor: 3.906

9.  Guppies (Poecilia reticulata) are deceived by visual illusions during obstacle negotiation.

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10.  Bumblebees display characteristics of active vision during robust obstacle avoidance flight.

Authors:  Sridhar Ravi; Tim Siesenop; Olivier J Bertrand; Liang Li; Charlotte Doussot; Alex Fisher; William H Warren; Martin Egelhaaf
Journal:  J Exp Biol       Date:  2022-02-18       Impact factor: 3.312

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