Resumen
One of the goals in adopting more sustainable agricultural practices is to reduce green-house-gas emissions from current practices by replacing fossil-fuel-based heavy machinery with lighter, electrical ones. In a not-so-distant scenario where a single farmer owns a fleet of small electrical tractors/robots that can operate in an autonomous/semi-autonomous manner, this will bring along some logistic challenges. It will be highly impractical that the farmer follows each time a given vehicle moves to the charging point to manually charge it. We present in this paper the design and implementation of an autonomous charging station to be used for that purpose. The charging station is a combination of a holonomic mobile platform and a collaborative robotic arm. Vision-based navigation and detection are used in order to plug the power cable from the wall-plug to the vehicle and back to the wall-plug again when the vehicle has recharged its batteries or reached the required level to pursue its tasks in the field. A decision-tree-based scheme is used in order to define the necessary pick, navigate, and plug sequences to fulfill the charging task. Communication between the autonomous charging station and the vehicle is established in order to make the whole process completely autonomous without any manual intervention. We present in this paper the charging station, the docking mechanism, communication scheme, and the deployed algorithms to achieve the autonomous charging process for agricultural electrical vehicles. We also present real experiments performed using the developed platform on an electrical robot-tractor.