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• W2775495931 abstract "The demands from precision agriculture (PA) for high-quality information at the individual plant level require to re-think the approaches exploited to date for remote sensing as performed by unmanned aerial vehicles (UAVs). A swarm of collaborating UAVs may prove more efficient and economically viable compared to other solutions. To identify the merits and limitations of a swarm intelligence approach to remote sensing, we propose here a decentralised multi-agent system for a field coverage and weed mapping problem, which is efficient, intrinsically robust and scalable to different group sizes. The proposed solution is based on a reinforced random walk with inhibition of return, where the information available from other agents (UAVs) is exploited to bias the individual motion pattern. Experiments are performed to demonstrate the efficiency and scalability of the proposed approach under a variety of experimental conditions, accounting also for limited communication range and different routing protocols." @default.
• W2775495931 created "2017-12-22" @default.
• W2775495931 creator A5055111984 @default.
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• W2775495931 date "2017-09-01" @default.
• W2775495931 modified "2023-09-26" @default.
• W2775495931 title "Field coverage and weed mapping by UAV swarms" @default.
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• W2775495931 doi "https://doi.org/10.1109/iros.2017.8206296" @default.
• W2775495931 hasPublicationYear "2017" @default.
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