Information Theoretic Source Seeking Strategies for Multiagent Plume Tracking in Turbulent Fields
AbstractWe present information theoretic search strategies for single and multi-robot teams to localize the source of biochemical contaminants in turbulent flows. The robots synthesize the information provided by sporadic and intermittent sensor readings to optimize their exploration strategy. By leveraging the spatio-temporal sensing capabilities of a mobile sensing network, our strategies result in control actions that maximize the information gained by the team while minimizing the time spent localizing the biochemical source. By leveraging the team’s ability to obtain simultaneous measurements at different locations, we show how a multi-robot team is able to speed up the search process resulting in a collaborative information theoretic search strategy. We validate our proposed strategies in both simulations and experiments. View Full-Text
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Description: Simulation Videos: Single- and Multi- agent plume Source Seeking in a turbulent medium.
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Hajieghrary, H.; Mox, D.; Hsieh, M.A. Information Theoretic Source Seeking Strategies for Multiagent Plume Tracking in Turbulent Fields. J. Mar. Sci. Eng. 2017, 5, 3.
Hajieghrary H, Mox D, Hsieh MA. Information Theoretic Source Seeking Strategies for Multiagent Plume Tracking in Turbulent Fields. Journal of Marine Science and Engineering. 2017; 5(1):3.Chicago/Turabian Style
Hajieghrary, Hadi; Mox, Daniel; Hsieh, M. A. 2017. "Information Theoretic Source Seeking Strategies for Multiagent Plume Tracking in Turbulent Fields." J. Mar. Sci. Eng. 5, no. 1: 3.
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