Home /Research /RAPID-MOLT: A Meso-scale, Open-source, Low-cost Testbed for Robot Assisted Precision Irrigation and Delivery
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RAPID-MOLT: A Meso-scale, Open-source, Low-cost Testbed for Robot Assisted Precision Irrigation and Delivery

Marius Wiggert, Leela Amladi, Ron Berenstein, Stefano Carpin, Joshua H. Viers, Stavros Vougioukas, Ken Goldberg

Year
2019
Citations
8

Abstract

To study the automation of plant-level precision irrigation, specifically learning-based irrigation controllers, we present a modular, open-source testbed that enables real-time, fine-grained data collection and irrigation actuation. RAPID-MOLT costs USD $600 and has floor space of 0.37m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . The functionality of the platform is evaluated by measuring the correlation between plant growth (Leaf Area Index) and water stress (Crop Water Stress Index) with irrigation volume. In line with biological studies, the observed plant growth is positively correlated with irrigation volume while water stress is negatively correlated. Construction directions, experimental data, CAD models, and related software are available at github.com/BerkeleyAutomation/RAPID-MOLT.

Keywords

TestbedIrrigationComputer scienceModular designOpen sourceAgricultural engineeringAutomationScale (ratio)Volume (thermodynamics)Software

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