  3D object reconfiguration encompasses common robot manipulation tasks in
which a set of objects must be moved through a series of physically feasible
state changes into a desired final configuration. Object reconfiguration is
challenging to solve in general, as it requires efficient reasoning about
environment physics that determine action validity. This information is
typically manually encoded in an explicit transition system. Constructing these
explicit encodings is tedious and error-prone, and is often a bottleneck for
planner use. In this work, we explore embedding a physics simulator within a
motion planner to implicitly discover and specify the valid actions from any
state, removing the need for manual specification of action semantics. Our
experiments demonstrate that the resulting simulation-based planner can
effectively produce physically valid rearrangement trajectories for a range of
3D object reconfiguration problems without requiring more than an environment
description and start and goal arrangements.
