Smart Grow-Bots Put to Work on the Farm, Increasing Yield

Artificial intelligence and machine learning enable autonomous robots to grow, analyze, and harvest produce in greenhouse environments. Robots reduce labor costs, increase crop yield, and improve sustainability.

 

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Image credit: Iron Ox 

Labor shortages and drought conditions are impacting the growth of crops, driving up costs and limiting supply. The pandemic and crackdowns at the border have added to the dearth of field help, which is sure to impact prices as labor and harvest account for nearly half the total production costs for lettuce and more than one-third for tomatoes and spinach.

To level the playing field, agriculture tech companies have been developing robots to help grow and harvest crops in greenhouses. Among these is Iron Ox, a California start-up that grows multiple varieties of lettuce, greens, and herbs in greenhouses. The company operates two hydroponic farms in California and is building a third facility in Texas.

Angus the Work Ox

Iron Ox can grow about 26,000 leafy greens in its 8,000 square foot facility, about 30 times more than a traditional farm. Hydroponic farming has a lot of touch points, and that is expensive. “Labor is over 50 percent of the cost to grow right now,” Brandon Alexander, Iron Ox CEO & Co-founder says. Iron Ox’s autonomous robots use artificial intelligence to transplant, grow, and harvest plants around the clock, reducing labor costs and increasing yield.

Plants are grown in large, shallow tubs. Initial planting and packaging is handled by humans, but the stars of the farming operation are two robots. One robot transfers individual plants from vat to vat as they grow. Then a large, wheeled robot named Angus carefully moves the tubs of plants around the warehouse. The Iron Ox robots combine computer vision and machine learning with robotic mobility and precise manipulation to move each plant without damaging it and to rotate the vats without spilling the growing solution.

The entire system is controlled by software the company refers to simply as “the Brain.” The Brain uses AI to monitor growing conditions, check plant health, and adjust the required nutrients and gasses to promote growth. The Brain will alert human operators when help is needed.  

A Souped-Up Robot

With its sights on tomato harvesting, MetoMotion is crushing it with its Greenhouse Robotic Worker, or GRoW robot. The autonomous robot drives through the greenhouse, guided by LiDAR sensors and algorithms for motion control and path determination. Using AI, machine vision, and 3D perception, GRoW analyzes the ripeness of each tomato to identify which fruits to harvest. GRoW has two robotic arms, so it can pick from both sides of the row, and it harvests one tomato at a time and places it in the packing box. Future iterations will enable GRoW to handle other tasks, such as pruning and de-leafing, and to harvest other produce and cannabis.

MetoMotion, based in Israel, has been testing GRoW at a greenhouse in the Netherlands. During a recent test, GRoW harvested a row of tomatoes with 90 percent accuracy and no human intervention. The company has launched additional pilot programs in North America and Europe.

Images of tomatoes with screens showing different percentages of ripeness

Image credit: MetoMotion

During the pandemic, the MetoMotion pilot was delayed and eventually adjusted to enable employees in Israel to control and manage the GRoW robots. That scenario is a glimpse into the future. Remote access will enable robots to work continuously, while supervision and support are conducted offsite. That will prevent disease from being introduced or spreading in the greenhouse and increase profitability. MetoMotion claims GRoW can cut labor hours by 80 percent and slash costs by 50 percent.

GRoW was designed to reduce labor costs in the greenhouse and meet increasing demand for produce, but the AI also collects crop growth and environmental data, which is sent to the cloud in real-time. That information will help growers determine yield forecasts.

 

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