Cooperative Task and Motion Planning for Multi-Arm Assembly Systems

TL;DR

This paper introduces a hierarchical task and motion planning framework for multi-robot assembly systems that optimizes for safety, efficiency, and low makespan in constructing complex structures, addressing proximity and precedence challenges.

Contribution

It presents a novel integrated planning approach combining MILP for high-level task allocation with multi-agent path finding for collision-free motion, including collision constraints during high-level planning.

Findings

Successfully plans assembly of structures with up to 23 objects.

Handles heterogeneous robots with different end-effectors.

Achieves low-makespan, collision-free assembly sequences.

Abstract

Multi-robot assembly systems are becoming increasingly appealing in manufacturing due to their ability to automatically, flexibly, and quickly construct desired structural designs. However, effectively planning for these systems in a manner that ensures each robot is simultaneously productive, and not idle, is challenging due to (1) the close proximity that the robots must operate in to manipulate the structure and (2) the inherent structural partial orderings on when each part can be installed. In this paper, we present a task and motion planning framework that jointly plans safe, low-makespan plans for a team of robots to assemble complex spatial structures. Our framework takes a hierarchical approach that, at the high level, uses Mixed-integer Linear Programs to compute an abstract plan comprised of an allocation of robots to tasks subject to precedence constraints and, at the low level, builds on a state-of-the-art algorithm for Multi-Agent Path Finding to plan collision-free robot motions that realize this abstract plan. Critical to our approach is the inclusion of certain collision constraints and movement durations during high-level planning, which better informs the search for abstract plans that are likely to be both feasible and low-makespan while keeping the search tractable. We demonstrate our planning system on several challenging assembly domains with several (sometimes heterogeneous) robots with grippers or suction plates for assembling structures with up to 23 objects involving Lego bricks, bars, plates, or irregularly shaped blocks.