Bridging the gap between high-level reasoning and low-level control

Abstract

We present a formal framework where a nonmonotonic formalism (the action description language ${\cal C}+$) is used to provide robots with high-level reasoning, such as planning, in the style of cognitive robotics. In particular, we introduce a novel method that bridges the high-level discrete action planning and the low-level continuous behavior by trajectory planning. We show the applicability of this framework on two LEGO MINDSTORMS NXT robots, in an action domain that involves concurrent execution of actions that cannot be serialized.