Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment
AbstractFinding the source of an accidental or deliberate release of a toxic substance into the atmosphere is of great importance for national security. The paper presents a search algorithm for turbulent environments which falls into the class of cognitive (infotaxi) algorithms. Bayesian estimation of the source parameter vector is carried out using the Rao–Blackwell dimension-reduction method, while the robots are controlled autonomously to move in a scalable formation. Estimation and control are carried out in a centralised replicated fusion architecture assuming all-to-all communication. The paper presents a comprehensive numerical analysis of the proposed algorithm, including the search-time and displacement statistics. View Full-Text
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Ristic, B.; Angley, D.; Moran, B.; Palmer, J.L. Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment. Sensors 2017, 17, 918.
Ristic B, Angley D, Moran B, Palmer JL. Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment. Sensors. 2017; 17(4):918.Chicago/Turabian Style
Ristic, Branko; Angley, Daniel; Moran, Bill; Palmer, Jennifer L. 2017. "Autonomous Multi-Robot Search for a Hazardous Source in a Turbulent Environment." Sensors 17, no. 4: 918.
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