Olfactory Search At High Reynolds Number

Locating sources of odors is a common task faced by living organisms in order to find food, mate or a particular location. However because of the random nature of mixing in turbulent flow, source location presents a non-trivial problem. Based on a simplified model of turbulent odor plumes we propose an efficient search algorithm which combines the maximum likelihood inference of the source position with an active search. The search trajectories arising in this model exhibit the counterturning pattern similar to that observed with flying moths. We propose a quantitative description of the search behavior which can facilitate further experimental studies. The algorithm can also be implemented in an olfactory robot.