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Monitoring weeder robots and anticipating their functioning by using advanced topological data analysis

Tarek Frahi, Abel Sancarlos, Matthieu Galle, Xavier Beaulieu, Anne Chambard, Antonio Falco, Elias Cueto, Francisco Chinesta

发表年份
2021
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摘要

The present paper aims at analyzing the topological content of the complex trajectories that weeder-autonomous robots follow in operation. We will prove that the topological descriptors of these trajectories are affected by the robot environment as well as by the robot state, with respect to maintenance operations. Topological Data Analysis will be used for extracting the trajectory descriptors, based on homology persistence. Then, appropriate metrics will be applied in order to compare that topological representation of the trajectories, for classifying them or for making efficient pattern recognition.

关键词

cs.ROcs.AI

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