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

arXiv: https://arxiv.org/abs/2005.09127 · HTML: https://mlsanity.com/paper/2005.09127/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 May 2020.

## Built on by (most cited first, 7 of 7)

- [LEGO-Net: Learning Regular Rearrangements of Objects in Rooms](https://mlsanity.com/paper/2301.09629/) (2023)
- [Cooperative Task and Motion Planning for Multi-Arm Assembly Systems](https://mlsanity.com/paper/2203.02475/) (2022)
- [Toward Efficient Task Planning for Dual-Arm Tabletop Object Rearrangement](https://mlsanity.com/paper/2207.08078/) (2022)
- [Hypergraph-based Multi-Robot Task and Motion Planning](https://mlsanity.com/paper/2210.04333/) (2022)
- [Planning for Manipulation among Movable Objects: Deciding Which Objects Go Where, in What Order, and How](https://mlsanity.com/paper/2303.13385/) (2023)
- [Planning for Complex Non-prehensile Manipulation Among Movable Objects by Interleaving Multi-Agent Pathfinding and Physics-Based Simulation](https://mlsanity.com/paper/2303.13352/) (2023)
- [Virtues of Ordered Chaos: Planning with Topple Actions in Tabletop Stack Rearrangement](https://mlsanity.com/paper/2605.17815/) (2026)

## Abstract (arXiv)

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.