  In this paper, we examine the problem of visibility-aware robot navigation
among movable obstacles (VANAMO). A variant of the well-known NAMO robotic
planning problem, VANAMO puts additional visibility constraints on robot motion
and object movability. This new problem formulation lifts the restrictive
assumption that the map is fully visible and the object positions are fully
known. We provide a formal definition of the VANAMO problem and propose the
Look and Manipulate Backchaining (LaMB) algorithm for solving such problems.
LaMB has a simple vision-based API that makes it more easily transferable to
real-world robot applications and scales to the large 3D environments. To
evaluate LaMB, we construct a set of tasks that illustrate the complex
interplay between visibility and object movability that can arise in mobile
base manipulation problems in unknown environments. We show that LaMB
outperforms NAMO and visibility-aware motion planning approaches as well as
simple combinations of them on complex manipulation problems with partial
observability.
