Compact Robots Take on Vineyard Weeds

2026-05-18

Researchers say smaller machines could ease one of viticulture’s most labor-intensive jobs while reducing soil compaction.

Compact robots are emerging as a practical tool for one of the most labor-intensive jobs in vineyards: managing weeds under the vine row. In a field where repeated passes are needed to control spontaneous vegetation close to the trunks without harming the plants or roots, researchers and equipment makers are testing smaller machines that can work in narrow spaces, reduce soil compaction and take over tasks that still depend heavily on manual labor.

The issue is not minor for winegrowers. Weeds compete with vines for water, light and nutrients. They can also interfere with field operations, harbor pests and help diseases spread. That makes under-row management, known in Italian as “sottofila,” one of the most delicate and costly operations in viticulture, especially in vineyards with tight spacing or difficult terrain.

A recent article by Lorenzo Gagliardi, Sofia Matilde Luglio, Christian Frasconi, Marco Fontanelli, Andrea Peruzzi and Michele Raffaelli of the Department of Agriculture, Food and Agro-Environmental Sciences at the University of Pisa examines the state of compact robotics for this task. The piece appeared in Il Corriere Vinicolo on May 11 in the Robotica & Automazione section and offers a broad look at systems already available or still under development.

The appeal of these machines goes beyond replacing repetitive work. Smaller robots can move through narrow vineyard layouts, turn in limited spaces and operate with less pressure on the soil. That matters because heavy machinery can compress the ground, reducing porosity, aeration and fertility over time. For growers trying to protect soil health while keeping labor costs under control, that is a significant advantage.

The technologies described include electric platforms, tracked carriers and multifunctional units designed for mowing, mechanical weeding, spraying and monitoring. Some rely on GNSS RTK positioning for precise navigation, while others use LiDAR sensors to detect rows and obstacles. Together, these tools point to a broader shift in vineyard management toward automation that is more targeted than traditional large-scale mechanization.

Still, the researchers stress that adoption depends on real-world conditions. Slope, row width, battery life, machine weight, available implements and safety all shape whether a robot can be used effectively in a given vineyard. A system that works well in one site may be impractical in another if the terrain is steep or the rows are too narrow.

For wine producers facing rising labor costs and pressure to farm more sustainably, compact robots could become part of a new operating model in which routine under-row work is handled with less manual effort and less disturbance to the soil. The challenge now is matching each machine to the vineyard conditions where it can deliver reliable results without adding complexity to an already demanding job.