Published June 2002 | Version Published
Journal Article Open

Distributed odor source localization

  • 1. ROR icon California Institute of Technology

Abstract

This paper presents an investigation of odor localization by groups of autonomous mobile robots. First, we describe a distributed algorithm by which groups of agents can solve the full odor localization task. Next, we establish that conducting polymer-based odor sensors possess the combination of speed and sensitivity necessary to enable real world odor plume tracing and we demonstrate that simple local position, odor, and flow information, tightly coupled with robot behavior, is sufficient to allow a robot to localize the source of an odor plume. Finally, we show that elementary communication among a group of agents can increase the efficiency of the odor localization system performance.

Additional Information

© 2002 IEEE. Manuscript received August 16, 2001; revised May 20, 2002. This work was supported in part by the Center for Neuromorphic Systems Engineering as part of the National Science Foundation Engineering Research Center Program under Grant EEC-9402726, by DARPA Dog's Nose program under Grant DAAK60-97-K-9503, by the Office of Naval Research under Grant N00014-98-1-0821 Chemical Plume Tracing Via Biological Inspiration and Electronic Olfaction, and by the Army Research Office under MURI Grant DAAG55-98-1-0266 Understanding Olfaction: From Detection to Classification. A. T. Hayes was supported by a National Science Foundation Graduate Research Fellowship. The associate editor coordinating the review of this paper and approving it for publication was Dr. Krishna Persaud.

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Identifiers

Eprint ID
94416
Resolver ID
CaltechAUTHORS:20190403-142504387

Funding

Center for Neuromorphic Systems Engineering, Caltech
NSF
EEC-9402726
Defense Advanced Research Projects Agency (DARPA)
DAAK60-97-K-9503
Office of Naval Research (ONR)
N00014-98-1-0821
Army Research Office (ARO)
DAAG55-98-1-0266
NSF Graduate Research Fellowship

Dates

Created
2019-04-03
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Updated
2021-11-16
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