  We present a centralized algorithm for labeled, disk-shaped Multi-Robot Path
Planning (MPP) in a continuous planar workspace with polygonal boundaries. Our
method automatically transform the continuous problem into a discrete,
graph-based variant termed the pebble motion problem, which can be solved
efficiently. To construct the underlying pebble graph, we identify inscribed
circles in the workspace via a medial axis transform and organize robots into
layers within each inscribed circle. We show that our layered pebble-graph
enables collision-free motions, allowing all graph-restricted MPP instances to
be feasible. MPP instances with continuous start and goal positions can then be
solved via local navigations that route robots from and to graph vertices. We
tested our method on several environments with high robot-packing densities (up
to $61.6\%$ of the workspace). For environments with narrow passages, such
density violates the well-separated assumptions made by state-of-the-art MPP
planners, while our method achieves an average success rate of $83\%$.
