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Knowledge-Based Instrumentation and Control for Competitive Industry-Inspired Robotic Domains

  • Autonomy is an increasing trend in manufacturing industries. Several industry-inspired robotic competitions have been established in recent years to provide testbeds of comprehensible size. In this paper, we describe a knowledge-based instrumentation and control framework used in several of these competitions. It is implemented using a rule-based production system and creates the task goals for autonomous mobile robots. It controls the environment’s agency using sensor data from processing stations and instructs proper reactions. The monitoring and collection of various data allows for an effective instrumentation of the competitions for evaluation purposes. The goal is to achieve automated runs with no or as little human intervention as possible which would allow for more and longer lasting runs. It provides a general framework adaptable to suit many scenarios and is an interesting test case for knowledge-based systems in an industry-inspired setting.

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Document Type:Article
Author:Tim Niemueller, Sebastian Zug, Sven Schneider, Ulrich Karras
Parent Title (English):Künstl Intell (KI - Künstliche Intelligenz)
First Page:289
Last Page:299
Place of publication:Berlin, Heidelberg
Date of first publication:2016/08/06
T. Niemueller (RWTH Aachen) was supported by the German National Science Foundation (DFG) research unit FOR 1513 on Hybrid Reasoning for Intelligent Systems (http://www.hybrid-reasoning.org).
Tag:Autonomy; Benchmarking; Factory instrumentation; Industry 4.0; Mobile robotics; RoboCup industrial; Rule-based production systems; Smart factory
Departments, institutes and facilities:Fachbereich Informatik
Dewey Decimal Classification (DDC):0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Entry in this database:2016/08/12