07 October 2026, California: John Deere’s autonomous orchard-spraying unit, GUSS Automation, is fitting a new generation of color lidar sensors to its robot fleet, aiming to solve one of self-driving agriculture’s oldest headaches: satellite navigation that falls apart under a dense tree canopy. The Kingsburg, California-based company, now a wholly owned subsidiary of Deere & Company, announced the upgrade on August 26, 2026, in a joint statement with Ouster Inc, the lidar sensor maker whose hardware will go into GUSS’s Orchard GUSS and Mini GUSS autonomous sprayers.
The problem the new sensors are meant to fix is a familiar one in orchard robotics. Under open sky, GPS, the satellite positioning system most autonomous farm equipment relies on, works reliably. Inside an orchard, though, tree canopies, trunks and dense foliage bounce and block satellite signals, a problem engineers call multipath interference. That interference can cause autonomous machines to drift off row, lose their position entirely, or stop and wait for a human to intervene, which has been one of the main barriers to running driverless sprayers in permanent tree crops rather than open row crops like corn or soybeans.
Lidar, short for light detection and ranging, is one of the main technologies engineers use to get around that problem. It works by firing rapid pulses of laser light outward and timing how long each pulse takes to bounce back off a surface, which lets a sensor build a three-dimensional map of everything around it without needing a clear view of the sky. GUSS is adopting Ouster’s Rev8 OS0 sensor, which the company describes as its first “native color” digital lidar, built on Ouster’s own L4 sensing chip rather than components bought from outside suppliers. The OS0 model has an unusually wide field of view, letting one sensor see tree trunks, row edges and ground contours on both sides of a sprayer at once, instead of needing several narrower sensors stitched together.
What the lidar actually sees and measures
In practice, the sensor builds what’s called a point cloud: a dense collection of millions of individual distance measurements that together outline the shape of the orchard row. The sprayer’s onboard computer compares that live point cloud against a pre-mapped row structure to hold its course and detect obstacles, largely without leaning on GPS at all. Deere and Ouster say the hardware is also built to keep working through the three conditions that typically degrade sensors in a working orchard: airborne dust, chemical spray mist drifting back off the nozzles, and dense overhanging vegetation that can confuse cameras or older sensor types.
The companies frame the upgrade as a navigation and safety improvement rather than a new product line. Jason Brantley, Deere’s vice president for production systems in its small agriculture and turf division, said the added sensing was intended to help the machines keep operating reliably in complex orchard settings. Ouster chief executive Angus Pacala called the integration an important step for autonomous equipment more broadly, a sign, in his telling, of how specialized sensing hardware is becoming core infrastructure for farm robotics rather than an experimental add-on.
GUSS’s existing autonomous sprayers already let one human operator supervise several robots at once from a laptop at the edge of a field rather than riding in a tractor cab spraying chemicals by hand. With the new sensor platform, Deere says a single supervisor will be able to oversee up to eight machines spraying simultaneously, up from the fleet ratios the company has run previously. Spraying is the first task Deere plans to run on the upgraded sensors, with mowing and other canopy-adjacent orchard work seen internally as likely next steps once the lidar-based navigation is proven out commercially.
The target market is California’s permanent tree crop sector: almond, walnut and pistachio orchards, along with stone fruit and, the companies said, vineyards. That sector has spent several years dealing with rising labor costs and a shrinking pool of workers willing to apply pesticides and fungicides by hand in high heat and dense canopy conditions, which is the practical pressure behind the push toward autonomous spray rigs in the first place
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