Intelligent task scheduling, planning and control for manufacturing work-cells

Abstract

This paper presents a novel approach for solving the challenging problem in intelligent control of manufacturing systems, i.e. the integration of low-level system sensing and simple control with high-level system behavior and perception. The proposed Max-Plus Algebra model combined with event-based planning and control provides a mechanism to efficiently integrate task scheduling, sensing, planning and real-time execution so that task scheduling, which usually deals with discrete types of events, as well as action planning, which usually deals with continuous events, can be treated systematically in a unified analytical model. More importantly, the unique feature of this approach is that interactions between discrete and continuous events can be considered in a unified framework. This feature allows the manufacturing system to intelligently cope with unexpected events and uncertainties so that the efficiency and reliability of the task schedule and action plan can increase significantly. A robotic manufacturing system is used to illustrate the proposed approach. The experimental results clearly demonstrate the advantages of the proposed approach.