open access publication

Article, 2023

A framework for multi-robot control in execution of a Swarm Production System

Computers in Industry, ISSN 0166-3615, Volume 151, 10.1016/j.compind.2023.103981

Contributors

Avhad A. 0000-0002-9358-9912 (Corresponding author) [1] Schou C. 0000-0001-7831-311X [1] Madsen O. 0000-0003-2133-2541 [1]

Affiliations

  1. [1] Aalborg University
  2. [NORA names: AAU Aalborg University; University; Denmark; Europe, EU; Nordic; OECD]

Abstract

Swarm Production Systems adopt an agile, reconfigurable and flexible production philosophy using mobile robot platforms for workstations and material transport. As a result, the factory floor can continuously restructure itself to an optimal spatial topology suited to any given production mix. This new production paradigm has to deal with frequently changing factory layouts and an execution plan for a fleet of autonomous robots in the planning stage. For every reconfiguration in the event of a change of order, the carrier and process robots require an initial task plan prior to runtime production and a reactive mechanism to adapt to uncertainties on the shop floor. An interoperable management system across the production and robotics domain called the Swarm Manager handles the task planning, allocation and scheduling for process and product transport robots. This research provides conceptualization with an abstract framework and an architecture describing methods with required functionalities for a Swarm Manager. A generic framework based on multi-agent systems addresses the explicit functional scope for individual agents inside the Swarm Manager. Based on the functional needs, a system-level architecture is proposed to explain algorithms within task planning, allocation and scheduling agents, and information flow within them.

Keywords

Agile manufacturing, Autonomous Robots, Multi-agent framework, Reconfigurable Manufacturing, Swarm Production

Funders

  • MADE FAST
  • Innovation Fund Denmark within the Manufacturing Academy of Denmark

Data Provider: Elsevier