Pre-image backchaining in belief space for mobile manipulation

Abstract

There have been several recent approaches to planning and control in uncertain domains, based on online planning in a determinized approximation of the belief-space dynamics, and replanning when the actual belief state diverges from the predicted one. In this work, we extend this approach to planning for mobile manipulation tasks with very long horizons, using a hierarchical combination of logical and geometric representations. We present a novel approach to belief-space preimage backchaining with logical representations, an efficient method for on-line execution monitoring and replanning, and preliminary results on mobile manipulation tasks.