From discrete task plans to continuous trajectories

Abstract

We present a logic-based framework to provide robots with high-level reasoning, such as planning. This framework uses the action description language C+ to represent actions and changes, and the system CCALC to reason about them. In particular, we can represent action domains that involve concurrent actions and additive fluents; based on this description, we can compute shortest plans to a planning problem that involves cost constraints. We show the applicability of this framework on two LEGO MINDSTORMS NXT robots: we compute a discrete task plan (possibly with concurrency) with a cost less than a specified value, and transform this plan into a continuous collision-free trajectory.