Finding optimal decoupled plans for multiple teams of robots in cognitive factories

We introduce a novel method to find optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots between each other, subject to the following constraints: 1) teams (and the mediator) do not know about each other´s workspace or tasks (e.g., for privacy purposes); 2) every team can lend or borrow robots, but not both (e.g., transportation/calibration of robots between/for different workspaces is usually costly). We introduce a novel method to solve this problem using state-of-the-art SAT solvers and ASP solvers. We show applicability and usefulness of our approach by experiments on various scenarios of cognitive factories.