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  Specialty Crop Automation

The project uses autonomous tractor development work by NREC and John Deere as the foundation for developing precision agricultural applications.

The precision sprayer uses sensors to enable each sprayer nozzle to spray only when directed towards foliage, and not air, swale banks or weeds, thereby reducing chemical usage.

The Tree Inventory System mounts quickly on any vehicle, such as a pickup truck or a tractor, and builds a searchable database of trees as fast as the vehicles can travel. The same information can be obtained from the sensors integrated in the autonomous tractor.

Raw data obtained from the tree canopy sensors, colored by height.

Overhead map indicating tree sizes.

Visual odometry enables vehicles to follow a predetermined course accurately when GPS is unavailable or unreliable.

Visual odometry relies on detecting features (red dots) and tracking them (yellow lines) to localize the moving vehicle.

View shows the path to follow (blue), the path actually driven (red) and the position reported by a standalone GPS receiver (green). Vehicle drives along correct path despite incorrectly reported GPS position due to the visual odometry system.

Spectral signature of representative healthy, nutrient deficient, and HLB-infected leaf samples.

Low-cost mini-helicopter platform for collecting disease detection data quickly and cheaply.


The Integrated Automation for Sustainable Specialty Crops Farming project has several developmental thrusts.

Orchard automation
NREC and John Deere built unmanned tractors to perform grove operations such as spraying and mowing. These tractors operate autonomously while being monitored remotely by grove personnel. They also serve as platforms for the precision agriculture technologies we are developing.

NREC is developing a GPS-Free Navigation system to enable autonomous operations when GPS is lost due to overhanging trees, tall structures or for other reasons. The system uses visual odometry and an inertial measurement unit (IMU) and can operate as a stand-alone system and as a supplement to GPS.

Disease detection
NREC and the University of Florida are developing automated systems that use remote sensing to detect citrus diseases. These systems make use of the localization abilities of the autonomous tractors to pinpoint the location of diseased trees, allowing targeted scouting and treatment of disease outbreaks.

Yield estimation
NREC and the University of Florida are developing improved yield estimation methods utilizing the perception sensing and localization capabilities of autonomous tractors to model tree canopies. Used in conjunction with historical yield data, these measurements can provide more accurate yield estimates.

Precision spraying
NREC, Cornell University and the University of Florida are developing tree-level precision spraying. The effort makes use of the sensing, data collection and localization capabilities of the autonomous tractors to enable each sprayer nozzle to spray only when directed towards foliage, and not air, swale banks or weeds, thereby reducing chemical usage.  

Precision Ag-in-a-Box
NREC is packaging the core components of these precision agriculture systems in a single, bolt-on unit that can be used on any type of farm tractor. This allows growers to use the precision spraying, yield estimation, and disease detection applications on their existing tractor fleet.

Mechanical harvesting
The project is analyzing mechanical harvester designs that use advanced sensing and manipulation technologies to harvest fruit economically and avoid the canopy damage that's a side effect of the current generation of harvesters.

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