MARS research project
AGCO/Fendt, together with the University of Ulm, is carrying out research on the use of autonomous robots in farming. The research project MARS (Mobile Agricultural Robot Swarms), studies satellite-supported sowing of maize by field robots. The field robots are transported to their operating site with a logistics unit. From there, they perform sowing operations, automatically and highly precisely, and enable site-specific adjustment of the sowing pattern and sowing rate as well as the exact documentation of each seed. This procedure promotes sustainable, economic handling of food and pesticides and increases the potential of higher yield. Through their battery-powered, electric drive, low weight and autonomous operation, sowing can also take place under conditions where conventional farming usually cannot be used, due to light and ground conditions or noise emissions. The system can be accessed using an app on a smart device and can therefore be controlled independent of location.
Planning sowing operations with the MARS app
The MARS app permits easy planning of sowing operations. Using the interface, the desired field, seeds, seeding pattern and density as well as the number of robots can be selected from the available data. An intelligent algorithm (OptiVisor) plans the robot operations based on the parameters that have been entered and calculates the time required to complete the task. As soon as the logistics unit has been positioned, the use of the robots can be started with the app. While they are working, the robots communicate with the cloud so that geo coordinates can be saved for the location of each seed. The OptiVisor algorithm guarantees reliable sowing of maize kernels at all times. If a robot should ever fail, its task is immediately taken over by the other units. Work progress can be followed live with the app. The proprietary OptiVisor algorithm monitors the charging state of the robots’ batteries and ensures that all batteries are recharged in due time at the logistics unit. Information about the placement of the seed is stored in the cloud and can also be used for further growth processes, such as applying fertilisers and harvesting. Afterwards it can be used for analysis and process optimisation. The research project is sponsored by the European Union within the framework of the FP7 programme and is part of Echord++.
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