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

TL;DR

This paper introduces a heuristic method for multi-arm rearrangement task planning that leverages mode graphs and capacity constraints, improving scalability and solution quality in complex robotic scenarios.

Contribution

It presents a novel heuristic approach guided by mode graphs with capacity constraints, connecting multi-arm rearrangement to multi-body path planning on graphs.

Findings

Scales well to multiple arms and objects

Finds high-quality solutions quickly

Exhibits desirable anytime behavior

Abstract

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.