Abstract
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.
Department
Computer Science
Publication Date
2-2011
Journal Title
Journal of Artificial Intelligence Research
Publisher
AI Access Foundation
Digital Object Identifier (DOI)
doi:10.1613/jair.3184
Document Type
Article
Recommended Citation
W. Ruml, M. B. Do, R. Zhou and M. P.J. Fromherz (2011) "On-line Planning and Scheduling: An Application to Controlling Modular Printers", Volume 40, pages 415-468
Rights
Copyright 2011 AI Access Foundation. All rights reserved.