Autonomous Search for a Diffusive Source in an Unknown Structured Environment
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Entropy 2014, 16(2), 789-813; https://doi.org/10.3390/e16020789
Received: 16 December 2013 / Revised: 28 January 2014 / Accepted: 29 January 2014 / Published: 10 February 2014
(This article belongs to the Special Issue Entropy Methods in Guided Self-Organization)
The paper presents a framework for autonomous search for a diffusive emitting source of a tracer (e.g., aerosol, gas) in an environment with an unknown map of randomly placed and shaped obstacles. The measurements of the tracer concentration are sporadic, noisy and without directional information. The search domain is discretised and modelled by a finite two-dimensional lattice. The links in the lattice represent the traversable paths for emitted particles and for the searcher. A missing link in the lattice indicates a blocked path due to an obstacle. The searcher must simultaneously estimate the source parameters, the map of the search domain and its own location within the map. The solution is formulated in the sequential Bayesian framework and implemented as a Rao-Blackwellised particle filter with entropy-reduction motion control. The numerical results demonstrate the concept and its performance.
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Keywords:
autonomous search; Bayesian inference; mapping and localisation; particle filter; observer control; information gain; diffusion
This is an open access article distributed under the Creative Commons Attribution License
MDPI and ACS Style
Ristic, B.; Skvortsov, A.; Walker, A. Autonomous Search for a Diffusive Source in an Unknown Structured Environment. Entropy 2014, 16, 789-813.
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