blocks using an unmanned aerial vehicle equipped with both a multispectral camera and an RGB camera. After images are stitched, a deep neural network is being trained to learn the mapping from aerial images to soil moisture measurements. This step is necessary to ensure this approach scales to large ranches, as manually gathering soil moisture measurements is time-consuming.
After the system determines the soil moisture map, the output is examined by a human expert (e.g., the grower) who identifies areas needing more or less water. The result is a flow adjustment map, where a corrective action is determined for each emitter (or zone). To implement these corrections, a second component of the RAPID system is being developed, which is a system to mechanically adjust variable rate emitters with a custom-designed gripper mounted on a robotic arm. As irrigation infrastructure is costly to replace, our tenet is that it is possible to retrofit existing irrigation lines with inexpensive, off-the-shelf variable rate passive emitters (commercially available for pennies each). A custom gripper and camera is being developed to operate these emitters. Once placed in proximity of an emitter, computer vision software identifies the emitter and guides the robotic arm so that the gripper latches on the emitter and turns it clockwise or counterclockwise to augment or reduce the flow.
The third component of the system is a fleet of autonomous robots, each equipped with a robotic arm and the gripper. Each robot moves through the vineyard as a GPS receiver determines its position. This location is matched to the flow adjustment map, so the robot determines the appropriate adjustment for the variable rate emitters located in its proximity. When the mobile platform moves sufficiently close to an emitter, it stops, and the software controlling the robotic arm intervenes and performs the necessary adjustment on the emitter. When the operation terminates, the gripper releases the emitter, the arm retracts, and the robot moves on to the next emitter along the tree row.
The components of the RAPID system are being developed and tested in a commercial vine- yard in the California Central Valley. For more information, go
http://rapid.berkeley.edu.
The shortage of workers is still a major problem that is anticipated to get worse.
Stefano Carpin, PhD, is a professor of electrical engineering and computer science at the University of California, Merced. He leads the team of researchers who are building the RAPID system.
Ken Goldberg, PhD, is a professor and department chair in industrial engineering and operations research at the University of California, Berkley.
Stavros Vougioukas, PhD, is an associate professor in biological and agricultural engineering at the University of California, Davis.
Joshua Viers, PhD, is a professor and the co-director of UC Water and the director of the University of California, Merced branch of the Center for the Information Technology Research in the Interest of Society.
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