  Solving task planning problems involving multiple objects and multiple
robotic arms poses scalability challenges. Such problems involve not only
coordinating multiple high-DoF arms, but also searching through possible
sequences of actions including object placements, and handoffs. The current
work identifies a useful connection between multi-arm rearrangement and recent
results in multi-body path planning on graphs with vertex capacity constraints.
Solving a synchronized multi-arm rearrangement at a high-level involves
reasoning over a modal graph, where nodes correspond to stable object
placements and object transfer states by the arms. Edges of this graph
correspond to pick, placement and handoff operations. The objects can be viewed
as pebbles moving over this graph, which has capacity constraints. For
instance, each arm can carry a single object but placement locations can
accumulate many objects. Efficient integer linear programming-based solvers
have been proposed for the corresponding pebble problem. The current work
proposes a heuristic to guide the task planning process for synchronized
multi-arm rearrangement. Results indicate good scalability to multiple arms and
objects, and an algorithm that can find high-quality solutions fast and
exhibiting desirable anytime behavior.
