Towards a flexible hybrid planner for machine coordination in arable farming

Sebastian Stock, Kai Lingemann, Stefan Stiene, Joachim Hertzberg

Abstract: In this paper we propose a new approach to coordinate multiple machines in the grain harvesting process, based on meta-constraint reasoning. This way we obtain more flexible plans that can be adapted at execution time. As an example scenario we focus on silage maize harvesting. We argue that more sophisticated flexible planning mechanisms are needed in order to obtain flexible plans that can be adapted at runtime to changing parameters such as yield per area.