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Rapid Inversion: Running Animals and Robots Swing like a Pendulum under Ledges

Overview of attention for article published in PLOS ONE, June 2012
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Title
Rapid Inversion: Running Animals and Robots Swing like a Pendulum under Ledges
Published in
PLOS ONE, June 2012
DOI 10.1371/journal.pone.0038003
Pubmed ID
Authors

Jean-Michel Mongeau, Brian McRae, Ardian Jusufi, Paul Birkmeyer, Aaron M. Hoover, Ronald Fearing, Robert J. Full

Abstract

Escaping from predators often demands that animals rapidly negotiate complex environments. The smallest animals attain relatively fast speeds with high frequency leg cycling, wing flapping or body undulations, but absolute speeds are slow compared to larger animals. Instead, small animals benefit from the advantages of enhanced maneuverability in part due to scaling. Here, we report a novel behavior in small, legged runners that may facilitate their escape by disappearance from predators. We video recorded cockroaches and geckos rapidly running up an incline toward a ledge, digitized their motion and created a simple model to generalize the behavior. Both species ran rapidly at 12-15 body lengths-per-second toward the ledge without braking, dove off the ledge, attached their feet by claws like a grappling hook, and used a pendulum-like motion that can exceed one meter-per-second to swing around to an inverted position under the ledge, out of sight. We discovered geckos in Southeast Asia can execute this escape behavior in the field. Quantification of these acrobatic behaviors provides biological inspiration toward the design of small, highly mobile search-and-rescue robots that can assist us during natural and human-made disasters. We report the first steps toward this new capability in a small, hexapedal robot.

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Geographical breakdown

Country Count As %
United States 5 6%
Germany 3 4%
France 1 1%
Austria 1 1%
Brazil 1 1%
Australia 1 1%
Thailand 1 1%
Denmark 1 1%
Unknown 67 83%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 28%
Researcher 13 16%
Student > Master 9 11%
Professor 7 9%
Student > Bachelor 6 7%
Other 12 15%
Unknown 11 14%
Readers by discipline Count As %
Engineering 29 36%
Agricultural and Biological Sciences 17 21%
Computer Science 4 5%
Medicine and Dentistry 4 5%
Psychology 3 4%
Other 10 12%
Unknown 14 17%