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Driverless tractor system navigates to public debut

Autonomous tractor technology developed in California wine grapes; could soon be used in pistachios.

When Connor Kingman launched a boat several years ago, sans-skipper or anyone else aboard, from Newport Beach, Calif. to Santa Catalina Island 32 miles away, he was already thinking about pistachios. While he still has that in mind, the mechanical engineering graduate is perfecting driverless tractor technology in a Central Valley wine grape vineyard.

The 2017 mechanical engineering graduate from University of California, Irvine is the brains behind a project in partnership with Ted Sheely, owner of Azcal Management Company. Together the pair are working to perfect a system to do mechanized chores that until now required a driver to operate the machinery.

Kingman’s tractor designs will be on display and demonstrated June 12, at 10 a.m. when Sheely hosts a field day at his Kings County farm. Azcal is located at 28088 Avenal Cutoff Rd., Stratford, Calif.

The autonomous tractor continues to be tested and used in Sheely’s vineyards, pulling discs, floats and spray rigs. Kingman says efforts are being completed to do box trimming and under-vine trimming with the system.


Kingman started with a common tractor design that he quickly changed, removing the driver’s seat and steering wheel, adding his own touches to the system that now includes several patents. The system includes cameras, lights, a remote sensing method called “Light Detection and Ranging” (LIDAR), a 55-gallon diesel tank to give the vehicle extra range, and an air-conditioned enclosure for the computer system that can be controlled from a computer or smart phone app. A specialized bumper is connected through the computer system as a fail-safe to stop the tractor if it drives into an object.

The LIDAR and cameras complement each other right now, Kingman says. Eventually the LIDAR will be discontinued from the system, allowing just the cameras to steer the tractor. 

The system does not rely upon GPS, or global positioning. Kingman says GPS is much more expensive than the camera system he uses. The goal is a system that is more affordable and easier to use without the addition of expensive tracking devices. Moreover, the system appears to work well in the dust and foggy winter conditions.

“Since we’ve built the tractor over a year ago, I’ve never cleaned the cameras or LIDAR,” Kingman said. “I’ve never had problems with the system seeing things, and that includes when we used it in the fog out here.”


Ted Sheely, who farms wine grapes, pistachios, cotton, wheat, watermelons and other crops on about 8,000 acres of land in California and Arizona, says the partnership with Kingman works well because Kingman is capable of engineering systems that Sheely can then “ground-truth” based on his years of experience as a successful farmer.

Sheely was an early adopter of global positioning in the United States. He purchased the first-ever GPS system for tractors in the U.S. While GPS works, it’s significantly more expensive than LIDAR and camera technology Kingman now employs.

The two met several years ago after Kingman contacted Sheely’s son, Zack, via LinkedIn. Kingman was looking for a place to test his autonomous system and wanted a farmer willing to allow the testing on his farm. Five minutes later Kingman’s phone was ringing. It was Zack Sheely, wanting more information on the system. Shortly thereafter Ted offered him a job and an opportunity to partner in the project.

“We thought this was a perfect fit for us,” said Jake Sheely, Zack’s brother.

The benefits of the driverless tractor Kingman developed, versus other autonomous systems on the market today, is that it’s a standard a tractor capable of pulling implements farmers already own, Jake says. Therefore, aside from the tractor itself, it does not require farmers to buy new, specialized pieces of equipment to do things they already have the equipment for.

Sheely says his wine grapes are only a starting point. He eventually wants to use the driverless system in his pistachios. Eventually he’d like to commercialize the system as he believes it is more utilitarian for California and Arizona farming operations.

“I want Connor to be very successful because of what he’s developing,” Ted said. “I can’t do what he’s doing. I’m looking at this with an eye to the future.”


During an exclusive interview with Western Farm Press, Sheely quickly calculated some of the savings the system could bring: over 1,000 hours per year in human labor reductions – a cost that continues to increase with the annual changes in wage and hour regulations.

Kingman says human error and other issues factor into the benefits of the system. Proper application of crop protection materials means maintaining a fixed speed, which the driverless technology allows.

“Spraying requires a lot of accuracy,” Kingman says. “If you’re spraying at a specific amount that requires you to drive 2.5 mph, then you can’t go faster or slower because you’ll apply too much or too little.”

“We know these are issues we can address with this system” Sheely continued.

For non-spray operations the tractor speed can be managed for optimal fuel consumption and is not subject to the whims of a driver simply wanting to get the job done sooner. It also avoids common tractor stoppages that come with mandatory work breaks. Minus times to fuel the tractor, it can run non-stop, day or night.

“We’re trying to run the tractor in such a way that we’re using the minimum amount of fuel per hour to complete the job,” Kingman says.

The system can work on farms anywhere in California, he continued.


Aside from the chores the tractor can complete without a driver, Sheely sees the installed camera system as a valuable tool for crop inspections that can provide valuable information on plant health and lead to more-effective yield predictions.

“Imagine being able to do bunch-counts and see crop load ahead of time,” Sheely said. “One would think the winery would want to know things like this.”

Kingman says algorithms can be created to predict, within 5 percent accuracy, what the yield might be at harvest. Even so, things like this won’t happen immediately. Systems will need to be verified, modifications made, and improvements realized to achieve these kinds of results, but he’s confident the technology and science is there to achieve this.

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