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A biomimetic robot for tracking specific odors in turbulent plumes

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Abstract

Two basic tasks must be performed by an olfactory robot tracking a specific odor source: navigate in a turbulent odor plume and recognize an odor regardless of its concentration. For these two tasks, we propose simple biologically inspired strategies, well suited for building dedicated circuits and for on-board implementation on real robots. The odor recognition system is based on a spiking neural network using a synchronization coding scheme. The robot navigation system is based on the use of bilateral comparison between two spatially separated gas sensors arrays at either side of the robot. We propose binary or analog navigation laws depending on the nature of the available sensory information extracted from the plume structure (isolated odor patches or smoother concentration field).

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Authors and Affiliations

  1. LORIA, Campus Scientifique, BP 239, 54506, Vandoeuvre-Les-Nancy, France

    Dominique Martinez, Oliver Rochel & Etienne Hugues

Authors
  1. Dominique Martinez
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  2. Oliver Rochel
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  3. Etienne Hugues
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Additional information

Dominique Martinez received his PhD degree in electrical and electronic engineering from the University Paul Sabatier in Toulouse, France, in 1992. He was a post-doctoral fellow at MIT, Dept. Brain and Cog. Sciences, and Harvard, VLSI group, in Cambridge, MA, USA, in 1992 and 1994, respectively. From 1993 to 1999 he worked at LAAS-CNRS in Toulouse where his research interests were concerned with machine learning (artificial neural networks, support vector machines). In 2000 he joined LORIA in Nancy and his research interests currently focus on biologically-plausible spiking neural networks for sensory processing, with particular application to artificial olfaction (neuromorphic electronic noses).

Olivier Rochel obtained his PhD from the LORIA/Université H. Poincaré, in Nancy, France, where he was working on modelling large and complex networks of biological neurons, and bio-inspired robotics. Now working in the Biosystems Group at the university of Leeds, his research interests lie in multi-disciplinary studies in computational neuroscience, modelling and simulation techniques in general, and biological data analysis.

Etienne Hugues has received his Ph.D. in theoretical physics from Paris XI University (Orsay). He has been a postdoctoral researcher at INRIA where he worked on olfactory perception in animals and robots. He is now a postdoctoral researcher in the Physics Department of SUNY at Buffalo. His main research interest is in computational neuroscience.

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Martinez, D., Rochel, O. & Hugues, E. A biomimetic robot for tracking specific odors in turbulent plumes. Auton Robot 20, 185–195 (2006). https://doi.org/10.1007/s10514-006-7157-1

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  • DOI: https://doi.org/10.1007/s10514-006-7157-1

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