Agricultural robots are typically performed in confined environments where their capabilities are limited and difficult to combine with other vehicles and equipment. The problem is that there are not enough solutions to control the quality of these processes. The innovative solutions presented by the winners of the Agritechnica 2023 Innovation Awards address these challenges.

One of the most promising developments in this area is AgXeed's 3A software, called Advanced Automation and Autonomy (3A). This software is designed to plan and execute work aimed at controlling robots in interaction with tractors and attachments. Its main advantage, however, is that it can detect and automatically repair malfunctions in processing equipment, such as clogging or loss of tines.

The DLG (German Agricultural Society) reports that this software detects faults and can rectify them using a variety of sensors that detect clogging, tine loss, packer roller speed and the intensity of the overload protection. An undoubted advantage is the system of open interfaces for pre-planning, which allows you to optimize the workflow in the field, eliminating the preliminary isolation of autonomous field robots that arises due to their closed system.

In particular, with the AgXeed Box and the 3A system, standard tractors and attachments can be integrated into the planning and autonomous execution process via the ISOBUS interface. This opens up new possibilities for the interaction of attachments with robots and tractors.

Practical tests of the system have already shown impressive results. The 3A network with the Amazone Autotill and Claas Autonomy connect is used for tillage. The machine works exactly as planned by the agronomist. The planning not only optimizes the routes, but also takes into account the ideal setting of the attachments, reducing errors and their consequences. This paves the way for further work simplification, as only seasonal adjustments need to be made.

Thus, AgXeed's 3A system marks a significant step towards the digitalization of crop production by enabling autonomous field robots to work efficiently and solving the problems associated with their limited functionality and isolation.