Robot Packing with Known Items and Nondeterministic Arrival Order
Abstract
This paper formulates two variants of packing problems in which the set of items is known but the arrival order is unknown. The goal is to certify that the items can be packed in a given container, and/or to optimize the size or cost of a container so that that the items are guaranteed to be packable, regardless of arrival order. The Nondeterministically ordered packing (NDOP) variant asks to generate a certificate that a packing plan exists for every ordering of items. Quasi-online packing (QOP) asks to generate a partially-observable packing policy that chooses the item location as each subsequent item is revealed. Theoretical analysis demonstrates that even the simple subproblem of verifying feasibility of a packing policy is NP-complete. Despite this worst-case complexity, practical solvers for both NDOP and QOP are developed, and experiments demonstrate their application to packing irregular 3D shapes with manipulator loading constraints.