On the Synthesis of Guaranteed-Quality Plans for Robot Fleets in Logistics Scenarios via Optimization Modulo Theories

TL;DR

This paper presents a novel approach using Optimization Modulo Theories to generate guaranteed-quality, optimal multi-robot schedules in manufacturing logistics, improving over heuristic methods.

Contribution

It introduces an OMT-based method for multi-robot scheduling that guarantees optimal solutions, along with insights into its development process.

Findings

The OMT approach guarantees optimality in robot scheduling.

The method outperforms heuristic approaches in solution quality.

Insights into the development of OMT-based scheduling methods.

Abstract

In manufacturing, the increasing involvement of autonomous robots in production processes poses new challenges on the production management. In this paper we report on the usage of Optimization Modulo Theories (OMT) to solve certain multi-robot scheduling problems in this area. Whereas currently existing methods are heuristic, our approach guarantees optimality for the computed solution. We do not only present our final method but also its chronological development, and draw some general observations for the development of OMT-based approaches.