Understanding bat flight as a model for bio-inspired aircraft designs


Meeting Abstract

91.2  Tuesday, Jan. 6 13:45  Understanding bat flight as a model for bio-inspired aircraft designs FULLER, NW*; THERIAULT, DH; KONG, Z; WANG, S; BETKE, M; BAILLIEUL, J; Boston University; Boston University; Boston University; Boston University; Boston University; Boston University nwfuller@bu.edu http://people.bu.edu/nwfuller/

Flight behaviors of bats provide an extraordinary study system for scientists to understand collective behavior, obstacle avoidance, and sensory systems of flying organisms. Until recently, the technologies needed to study bat flight in detail have not existed, thus only simple observations of their flight behaviors could be studied. Using an advanced thermal imaging system, custom software, and 3D imaging techniques, we have constructed detailed analyses of bat flight behaviors. Our objectives are twofold. First, we aim to use bats as a model organism to understand group behavior of flying animals using the large flight columns of the Brazilian free-tailed bat, Tadarida brasiliensis, as a model organism. Second, we use the cave bat, Myotis velifer, as a model organism for obstacle avoidance strategies employed by bats. This presentation will detail several of our past studies of bat flight behavior, including behavioral forces experienced by bats flying in a column of 200 conspecifics and variations in flight behaviors exhibited by bats that are challenged with a novel obstacle. Our results show that groups of bats often show counter-intuitive behaviors when flying in a group (i.e., accelerating or turning toward other individuals) and that echolocation call frequency and obstacle approach will change over time as bats adjust to the presence of new hazards in their flight corridor. These data will be used by our collaborators in an effort to define simplified models of the variables the govern flight and collective behavior. Eventually these models will be integrated into intelligent flight control algorithms that will lead to the development of a new generation of bio-inspired unmanned aircraft.

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