On Process Recognition by Logical Inference

The ability to recognize and to understand processes allows a robot operating in a dynamic environment to rationally respond to dynamic changes. In this paper we demonstrate how a mobile robot can recognize storage processes in a warehouse environment, solely using perception data and an abstract specification of the processes. We specify processes symbolically in linear temporal logic (LTL) and pose process recognition as a model verification problem. The key feature of our logic based approach is its ability to infer missing pieces of information by logic-based reasoning. The evaluation demonstrates that this approach is able to reconstruct histories of good movements in a lab-simulated warehouse.