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Develop and evaluate an autonomous robotic exploration strategy that uses kriging and a noncontact cosmic-ray sensor to map soil moisture efficiently.

January 1, 2020

Kriging‐based robotic exploration for soil moisture mapping using a cosmic‐ray sensor

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Develop and evaluate an autonomous robotic exploration strategy that uses kriging and a noncontact cosmic-ray sensor to map soil moisture efficiently.
Integrated Poisson-distributed measurements from a noncontact cosmic-ray soil moisture sensor into an online spatial kriging framework.
Formulated autonomous exploration algorithms using adaptive measurement intervals and adaptive sampling directed toward regions of highest model uncertainty.
Evaluated mapping accuracy and exploration efficiency using empirical soil moisture datasets collected from two agricultural fields.
Adaptive sampling and dynamic measurement intervals produced higher-quality soil moisture maps than non-adaptive exploration approaches.
The kriging framework successfully assimilated Poisson-distributed sensor noise to generate real-time spatial representations of field moisture.

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Implication

Experimental study demonstrates autonomous robotic soil moisture mapping using kriging and cosmic-ray sensing in agricultural fields, indicating improved spatial modeling efficiency.

Cite This Study

Fentanes et al. (2020) studied this question.

synapsesocial.com/papers/6aab8e39d09b2dc857171fe2 https://doi.org/10.1002/rob.21914

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Implication

Experimental study demonstrates autonomous robotic soil moisture mapping using kriging and cosmic-ray sensing in agricultural fields, indicating improved spatial modeling efficiency.

Kriging‐based robotic exploration for soil moisture mapping using a cosmic‐ray sensor

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Implication

Cite This Study

Kriging‐based robotic exploration for soil moisture mapping using a cosmic‐ray sensor

Key Points

Discussion

Implication

Cite This Study

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