Precision agriculture for rice farming and smart methods such as aquaponics are vital to ensure a safe supply of fresh food for Europe while reducing our environmental footprint. In line with the Digitising European Industry initiative under their description of smart agriculture, the SOMIRO project will develop a flat-worm-inspired mm-scale swimming robot with month-long energy autonomy, local intelligence, and ability to continuously generate data and optically communicate to reduce farming’s environmental impact in terms of carbon footprint, over fertilization, pesticide use, and overfeeding. Swimming robots would cover a much larger area than stationary systems and could be rapidly deployed and self-redistribute where most needed. They may serve as a stand-alone monitoring solution for indoor farming or complement drone-based remote sensing in outdoors scenarios.
Until today, no energy autonomous (untethered and with local intelligence) milli-robot capable of hours of continuous operation has been demonstrated. The major reason for this is power limitation: locomotion requires much power and small robots have very limited energy storage and energy harvesting. Our milli-robot will be less than 1 cm long and show how soft and stretchable systems, with undulating swimming like flat worms, require far less energy for locomotion than other systems of comparable size. For power, it will not rely on any dedicated infrastructure but only on ambient light.
The design of SOMIRO focuses on its industry transfer: industrial partners will use cutting-edge assembly technologies that can scale up to production volumes with no change in process. The bulk materials are low-cost elastomers and polymers and the electronic circuits will be based on commercial components. Throughout the project, all application scenarios and exploitation plans will be developed in close collaboration among the SOMIRO partner enterprises and end-users, and external industrial stakeholders.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No.101016411.
