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- W2945053513 abstract "A new nonparametric Bayesian-based motion planning algorithm for autonomous plume source term estimation (STE) and source seeking (SS) is presented in this paper. The algorithm is designed for mobile robots equipped with gas concentration sensors. Specifically, robots coordinate and utilize a Gaussian-plume likelihood model in a Bayesian-based STE process, then they simultaneously search for and navigate toward the source through model based, bioinspired SS methods such as biased-random-walk and surge-casting. Compared with the state-of-the-art Bayesian- and sensor-based STE/SS motion planners, the strategy described takes advantage of coordination between multiple robots and the estimated plume model for faster and more robust SS, rather than rely on direct or filtered sensor measurements. A set of Monte Carlo simulation studies are conducted to compare the performance between the uncoordinated and coordinated algorithms for different robot team sizes and starting conditions. Additionally, the algorithms are validated experimentally through a laboratory-safe, realistic humid-air plume that behaves similar to a gas plume, to test STE and SS using mobile ground robots equipped with humidity sensors. Simulation and experimental results show consistently that the algorithm involving coordination outperforms traditional bioinspired SS algorithms and it is approximately twice as fast as the uncoordinated case. Finally, the plume source is distorted to study the algorithm's limitations and impact on STE and SS, where results show that even for distorted plumes, useful source localization information can be obtained." @default.
- W2945053513 created "2019-05-29" @default.
- W2945053513 creator A5027538794 @default.
- W2945053513 creator A5033106404 @default.
- W2945053513 creator A5055520085 @default.
- W2945053513 date "2019-08-01" @default.
- W2945053513 modified "2023-09-24" @default.
- W2945053513 title "Coordinated Bayesian-Based Bioinspired Plume Source Term Estimation and Source Seeking for Mobile Robots" @default.
- W2945053513 cites W129701547 @default.
- W2945053513 cites W1424654272 @default.
- W2945053513 cites W1497531663 @default.
- W2945053513 cites W1513877745 @default.
- W2945053513 cites W1762022748 @default.
- W2945053513 cites W1967942240 @default.
- W2945053513 cites W1970555742 @default.
- W2945053513 cites W1973685723 @default.
- W2945053513 cites W1980887003 @default.
- W2945053513 cites W1992713863 @default.
- W2945053513 cites W1994356595 @default.
- W2945053513 cites W1994733549 @default.
- W2945053513 cites W1995331599 @default.
- W2945053513 cites W1995383487 @default.
- W2945053513 cites W1995699421 @default.
- W2945053513 cites W2009254284 @default.
- W2945053513 cites W2012421030 @default.
- W2945053513 cites W2016863073 @default.
- W2945053513 cites W2017742462 @default.
- W2945053513 cites W2018456698 @default.
- W2945053513 cites W2023416350 @default.
- W2945053513 cites W2023673857 @default.
- W2945053513 cites W2023716923 @default.
- W2945053513 cites W2023776958 @default.
- W2945053513 cites W2036952815 @default.
- W2945053513 cites W2038976388 @default.
- W2945053513 cites W2042247074 @default.
- W2945053513 cites W2046695302 @default.
- W2945053513 cites W2054289671 @default.
- W2945053513 cites W2055936398 @default.
- W2945053513 cites W2059305573 @default.
- W2945053513 cites W2060877910 @default.
- W2945053513 cites W2062044314 @default.
- W2945053513 cites W2066180421 @default.
- W2945053513 cites W2066568056 @default.
- W2945053513 cites W2067599125 @default.
- W2945053513 cites W2069168969 @default.
- W2945053513 cites W2069197722 @default.
- W2945053513 cites W2072931689 @default.
- W2945053513 cites W2087317639 @default.
- W2945053513 cites W2087711455 @default.
- W2945053513 cites W2093352222 @default.
- W2945053513 cites W2093912891 @default.
- W2945053513 cites W2098613108 @default.
- W2945053513 cites W2104684731 @default.
- W2945053513 cites W2108481352 @default.
- W2945053513 cites W2116336144 @default.
- W2945053513 cites W2119539043 @default.
- W2945053513 cites W2137789069 @default.
- W2945053513 cites W2145440801 @default.
- W2945053513 cites W2148182166 @default.
- W2945053513 cites W2152464086 @default.
- W2945053513 cites W2158987312 @default.
- W2945053513 cites W2160337655 @default.
- W2945053513 cites W2160891248 @default.
- W2945053513 cites W2169472969 @default.
- W2945053513 cites W2180719975 @default.
- W2945053513 cites W2222512263 @default.
- W2945053513 cites W2238394942 @default.
- W2945053513 cites W2276152404 @default.
- W2945053513 cites W2299576847 @default.
- W2945053513 cites W2400794236 @default.
- W2945053513 cites W2404694200 @default.
- W2945053513 cites W247092576 @default.
- W2945053513 cites W2531441339 @default.
- W2945053513 cites W2531896904 @default.
- W2945053513 cites W2543656076 @default.
- W2945053513 cites W2553399731 @default.
- W2945053513 cites W2566498105 @default.
- W2945053513 cites W2570895416 @default.
- W2945053513 cites W2578826387 @default.
- W2945053513 cites W2605414637 @default.
- W2945053513 cites W2737261803 @default.
- W2945053513 cites W2750707143 @default.
- W2945053513 cites W2767532364 @default.
- W2945053513 cites W2768119112 @default.
- W2945053513 cites W2945996237 @default.
- W2945053513 cites W2986543921 @default.
- W2945053513 cites W3101594387 @default.
- W2945053513 cites W3101754131 @default.
- W2945053513 cites W331831712 @default.
- W2945053513 cites W4212954311 @default.
- W2945053513 cites W4252648572 @default.
- W2945053513 cites W4364996291 @default.
- W2945053513 cites W750766922 @default.
- W2945053513 doi "https://doi.org/10.1109/tro.2019.2912520" @default.
- W2945053513 hasPublicationYear "2019" @default.
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