Following the machines, people and ideas shaping agriculture. Selected developments, clear context and a link to the original source.
Robotics. Intelligence. Agriculture.
274 stories matching “ANT”.
Adaptive AgroTech’s updated organizer programme outlines a June 2027 tour through German and Danish research, industry and field sites, connecting agricultural robotics and digital farming with practical demonstrations and technical exchange.
Carbon Robotics introduced LaserWeeder G2 in February 2025, offering multiple working widths and revised lasers, cameras, computing and cooling to extend its tractor-mounted weeding approach across different farm layouts.
John Deere introduced JD, a question-and-answer AI assistant intended to help farmers interpret operational, field and machine information in its existing management platform.
A Wageningen PhD project investigates robots that move their cameras and learn which viewpoint will provide better information about obscured plants.
TYM has introduced an autonomous paddy robot in South Korea that suppresses weeds by stirring water and sediment rather than applying herbicide.
Researchers are using repeated LiDAR and panoramic mapping to build a vineyard digital twin that reflects seasonal changes affecting autonomous navigation.
A 2026 research paper investigates a mobile data-collection robot designed to observe individual strawberry plants and support greenhouse harvesting decisions.
Researchers from NTNU and Kilter developed and simulated a multi-robot approach to precision weed treatment. Their results suggest that distributing fieldwork among several AX-1 robots could reduce completion times.
AGCO used its 2026 field technology event to show how autonomous operations, AI tools and equipment from different brands could work in a connected farm workflow.
A new study reports that plant architecture—including stalk length and fruit position—can markedly affect cucumber-harvesting robot performance.
A three-year study of fruit-growing operations finds that AI-enabled machinery changes agricultural work rather than simply removing the need for skilled people.
Brazilian researchers compared several soil-sensing methods across three farms, finding that carefully chosen combinations could retain useful predictive performance while avoiding the complexity of adding redundant measurements.
