Autonomous Search for a Diffusive Source in an Unknown Structured Environment

Entropy

Branko Ristic¹  Alex Skvortsov² 

[1] Defence Science and Technology Organisation, 506 Lorimer Street, Melbourne, VIC 3207, Australia;

关键词: autonomous search;    Bayesian inference;    mapping and localisation;    particle filter;    observer control;    information gain;    diffusion;   

DOI  :  10.3390/e16020789

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland