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

Marius Wiggert(University of California, Berkeley), Leela Amladi(University of California, Berkeley), Ron Berenstein(Berkeley Systems (United States)), Stefano Carpin(University of California, Merced), Joshua H. Viers(Watershed), Stavros Vougioukas(University of California, Davis), Ken Goldberg(Berkeley Systems (United States))
Unknown
August 1, 2019
10.1109/coase.2019.8842877
Cited by 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.

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