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Solving task planning problems involving multiple objects and multiplerobotic arms poses scalability challenges. Such problems involve not onlycoordinating multiple high-DoF arms, but also searching through possiblesequences of actions including object placements, and handoffs. The currentwork identifies a useful connection between multi-arm rearrangement and recentresults in multi-body path planning on graphs with vertex capacity constraints.Solving a synchronized multi-arm rearrangement at a high-level involvesreasoning over a modal graph, where nodes correspond to stable objectplacements and object transfer states by the arms. Edges of this graphcorrespond to pick, placement and handoff operations. The objects can be viewedas pebbles moving over this graph, which has capacity constraints. Forinstance, each arm can carry a single object but placement locations canaccumulate many objects. Efficient integer linear programming-based solvershave been proposed for the corresponding pebble problem. The current workproposes a heuristic to guide the task planning process for synchronizedmulti-arm rearrangement. Results indicate good scalability to multiple arms andobjects, and an algorithm that can find high-quality solutions fast andexhibiting desirable anytime behavior.

Synchronized Multi-Arm Rearrangement Guided by Mode Graphs with Capacity Constraints