Success Stories

GPS Correction Technology Lets Tractors Drive Themselves


A long partnership with the Jet Propulsion Laboratory helped John Deere spread self-driving tractor capabilities all over the world, lowering costs and improving yields for farmers while popularizing the idea of precision agriculture.

There has been much talk of self-driving cars lately, but farmers have enjoyed self-driving tractors for more than a decade, in part due to a partnership between John Deere and the Jet Propulsion Laboratory (JPL).

In the 1990s, scientists at JPL, where the first global tracking system for Global Positioning System (GPS) satellites had been developed, were working to stream satellite tracking data in real time via the Internet. The result was the Real-Time GIPSY (RTG) software. GIPSY refers to the GNSS-Inferred Positioning System, wherein GNSS stands for Global Navigation Satellite System.

RTG ended up being one of NASA’s most important contributions to modern society, enabling accurate GPS navigation anywhere on the planet.

In 2001, NavCom, owned by John Deere, licensed the RTG software and also contracted with JPL to receive data from the center’s global network of reference stations. John Deere, based in Moline, Illinois, had already developed its own GPS receivers for tractor guidance, but when the company released the first receivers to tap into NASA’s ground stations and incorporate JPL’s software in 2004, it could finally offer self-driving equipment worldwide.

The trackers were accurate down to about four inches, not quite as accurate as John Deere’s real-time kinematics (RTK)-based trackers, but much more affordable. The RTK system required the purchase of one or more signal towers.

Typically, when a farmer crisscrosses a field pulling a seeder, plow, or other equipment, the rows overlap by about 10 percent, meaning a significant portion of the field receives double the necessary resources, and the job takes longer than necessary. Eliminating overlap also cuts down on fuel costs and wear and tear on the machinery. And higher accuracy also means more reliable yield maps, which are created by combining location data with mass flow data from sensors on a harvesting combine.



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