On-line Planning and Scheduling: An Application to Controlling Modular Printers

• Published in: arXiv.org
• Main Authors: Wheeler Ruml, Minh Binh Do, Zhou, Rong, Fromherz, Markus P J
• Format: Paper Journal Article
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 16.01.2014
• Subjects: Algorithms; Architecture; Artificial intelligence; Computer Science - Artificial Intelligence; Control equipment; Decision making; Embedded systems; Handles; High speed; Industrial applications; On-line systems; Planning; Printers; Scheduling; State of the art
• ISSN: 2331-8422
• DOI: 10.48550/arxiv.1401.3875

We present a case study of artificial intelligence techniques applied to the control of production printing equipment. Like many other real-world applications, this complex domain requires high-speed autonomous decision-making and robust continual operation. To our knowledge, this work represents the first successful industrial application of embedded domain-independent temporal planning. Our system handles execution failures and multi-objective preferences. At its heart is an on-line algorithm that combines techniques from state-space planning and partial-order scheduling. We suggest that this general architecture may prove useful in other applications as more intelligent systems operate in continual, on-line settings. Our system has been used to drive several commercial prototypes and has enabled a new product architecture for our industrial partner. When compared with state-of-the-art off-line planners, our system is hundreds of times faster and often finds better plans. Our experience demonstrates that domain-independent AI planning based on heuristic search can flexibly handle time, resources, replanning, and multiple objectives in a high-speed practical application without requiring hand-coded control knowledge.