Short answer: Agricultural robots are real but unevenly mature. Weeding — mechanical, laser and precision-spraying — is the most commercialised task, because the target is stationary and the cost of the chemical alternative is visible. Autonomous driving for tractors and implements is close behind, largely as retrofits. Harvesting delicate crops remains the hardest problem in the field: the perception and gentle-handling demands are an order higher, and most systems still work with human crews rather than instead of them.
Weeding: three ways to kill a plant precisely
Mechanical weeders cultivate between and within crop rows with blades, fingers or rotating tools, guided by cameras that tell crop from weed. They suit organic operations and herbicide-resistant weed pressure, and their limits are speed and soil conditions. Laser weeders identify weeds by vision and destroy the growing point with a laser — no soil disturbance, no chemistry, high capital cost per hectare covered. Carbon Robotics, profiled in the directory, built its name on this approach. Precision spraying keeps the sprayer but changes its eyes: camera systems detect weeds or crop and fire individual nozzles only where needed. The reference product line is See & Spray from Blue River Technology, the California company John Deere acquired in 2017 — a purchase that signalled the tractor industry's direction to the whole sector.
Autonomous tractors and retrofit kits
The largest machines on the farm automate differently: rather than new robot platforms, autonomy arrives as kits and factory options that drive existing tractors — guidance first, then supervised autonomy for tillage and seeding. The economics differ from weeding robots: the tractor already exists, the task is geometrically regular, and the value is operator hours across long, monotonous passes. Buyers should separate steering assistance (common, proven) from genuinely driverless operation (narrower, and regulated differently by region) when a supplier uses the word "autonomous".
Harvesting: the perception bottleneck
Picking soft fruit concentrates every hard problem at once: find ripe items among leaves, judge ripeness by colour and size, reach without bruising neighbours, detach without damaging the product, and do it at a cost per kilo that competes with seasonal labour. Progress is real in structured settings — greenhouse crops on rails and gutters, and top fruit with increasingly planned canopies — because the environment can be redesigned around the robot. Open-field soft fruit remains mostly pilot-stage. Any harvesting claim should be interrogated on three numbers the supplier can evidence: pick success rate, damage rate, and kilograms per hour sustained over a full shift, not a demonstration row.
Seasonality and the payback logic
Farm machinery earns in windows. A weeding robot may work intensively for some weeks a year and stand idle otherwise, which makes the arithmetic unlike a factory robot's three shifts. The responses are structural: machines sized to cover the farm inside its window, contractor and service models where one machine serves many farms in sequence, and crops chosen so the robot's window is long. Payback claims should be rebuilt from the buyer's own hectares, passes and chemical or labour costs — qualitatively, the more expensive and scarce the hand-weeding or spraying labour, and the larger the chemical saving from precision application, the stronger the case. Compare the offers collected in the complete robots section of the directory on those terms, not on launch videos.
Dealers, service radius and the season risk
A factory robot that breaks waits for a technician; a field robot that breaks in a ten-day spraying window may cost the season. The deciding purchase questions are therefore logistical: who services the machine within what radius, are parts stocked locally before the season, what does the supplier do when a unit fails mid-window — swap, loaner, or queue? Established dealer networks are the incumbent tractor brands' structural advantage, and the practical reason many growers meet field robotics first as an option on a familiar badge, or through the specialist makers listed on the Launchpad. Weigh the service answer as heavily as the specification.
Frequently asked questions
What is the most common job for agricultural robots today?
Weeding. Mechanical, laser and camera-guided precision-spraying systems are commercially deployed because the targets are stationary, the alternative costs — chemistry and hand labour — are easy to count, and the perception problem is tractable compared with picking ripe fruit.
Why is robotic harvesting so much harder than weeding?
Harvesting adds ripeness judgment, occlusion by foliage, and a gentleness requirement: the product is the fragile thing being handled. Weeding's target must merely be found and destroyed; harvesting's must be found, assessed, reached and detached undamaged, at a competitive cost per kilogram.
Are driverless tractors the same as agricultural robots?
They overlap. Much field autonomy is delivered as guidance and autonomy kits on conventional tractors rather than as new robot platforms. Buyers should distinguish steering assistance from genuinely driverless operation, which is less common and regulated differently by region.
What should a grower check before buying a field robot?
Demonstrated performance on the buyer's own crop and soil (success and damage rates over full shifts), the service network and parts stocking within reach of the farm, and what happens if the machine fails inside a short seasonal window. Seasonal downtime costs more than factory downtime.