Estimation of Gaussian Plume Model Parameters Using the Simulated Annealing Algorithm

  • Gonçalo Cabrita
  • Lino Marques
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 253)


This article presents a novel cost function for estimating the parameters of the Gaussian plume model using simulated annealing. The novel cost function takes into account the meandering and intermittency phenomena found on dispersing plumes. The proposed method was validated using real gas sensor data sampled by a swarm of 5 robots performing the Decentralized Asynchronous Particle Swarm Optimization for plume tracing under a controlled environment.


Gaussian plume model simulated annealing odor plume estimation swarm robotics 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Institute of Systems and RoboticsUniversity of CoimbraCoimbraPortugal

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