Pubblicazione scientifica

Using collision cones to assess biological deconfliction methods

FILONE TECNOLOGICO	TEMA
trasformazione e commercializzazione

RIASSUNTO

Biological systems consistently outperform autonomous systems governed by engineered algorithms in their ability to reactively avoid collisions. To better understand this discrepancy, a collision avoidance algorithm was applied to frames of digitized video trajectory data from bats, swallows and fish (Myotis velifer, Petrochelidon pyrrhonota and Danio aequipinnatus). Information available from visual cues, specifically relative position and velocity, was provided to the algorithm which used this information to define collision cones that allowed the algorithm to find a safe velocity requiring minimal deviation from the original velocity. The subset of obstacles provided to the algorithm was determined by the animal's sensing range in terms of metric and topological distance. The algorithmic calculated velocities showed good agreement with observed biological velocities, indicating that the algorithm was an informative basis for comparison with the three species and could potentially be improved for engineered applications with further study.

DATA

Data di pubblicazione: 01/09/2016

AUTORI

BRACE NATALIE L
HEDRICK TYSON L
THERIAULT DIANE H
FULLER NATHAN W
WU ZHENG
BETKE MARGRIT
PARRISH JULIA K
GRUNBAUM DANIEL
MORGANSEN KRISTI A

ENTE DI AFFERENZA

WILLIAM E BOEING DEPT AERONAUTICS & ASTRONAUTICS UNIV WASHINGTON SEATTLE WA USA
DEPT BIOLOGY UNIV NORTH CAROLINA CHAPEL HILL NC USA
DEPT COMPUTER SCIENCE BOSTON UNIV BOSTON MA USA
SCHOOL OF AQUATIC & FISHERY SCIENCES UNIV WASHINGTON SEATTLE WA USA
SCHOOL OF OCEANOGRAPHY UNIV WASHINGTON SEATTLE WA USA

RIVISTA

Journal of the Royal Society Interface, 13(122), 20160502

IMPACT FACTOR

3,300

indietro