An Algorithm for Odor Source Localization based on Source Term Estimation

Finding sources of airborne chemicals with mobile sensing systems finds applications across the security, safety, domestic, medical, and environmental domains. In this paper, we present an algorithm based on source term estimation for odor source localization that is coupled with a navigation method based on partially observable Markov decision processes. We propose an innovative strategy to balance exploration and exploitation in navigation. The method has been evaluated systematically through high-fidelity simulations and in a wind tunnel emulating realistic and repeatable conditions. The impact of multiple algorithmic and environmental parameters has been studied in the experiments.

Presented at:
IEEE International Conference on Robotics and Automation 2019, Montreal, Canada, May 20-24, 2019

 Record created 2019-03-27, last modified 2019-08-12

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