Turning High-Level Plans into Robot Programs in Uncertain Domains

The actions of a robot like lifting an object are often best thought of as low-level processes with uncertain outcome. A high-level robot plan can be seen as a description of a task which combines these processes in an appropriate way and which may involve nondeterminism in order to increase a plan's generality. In a given situation, a robot needs to turn a given plan into an executable program for which it can establish, through some form of projection, that it satisfies a given goal with some probability. In this paper we will show how this can be achieved in a logical framework. In particular, low-level processes are modelled as programs in pGOLOG, a probabilistic variant of the action language GOLOG. High-level plans are like ordinary GOLOG programs except that during projection the names of low-level processes are replaced by their pGOLOG-definitions.