Künstliche Intelligenz 30(3+4) - Oktober 2016

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Zeitschriftenartikel
Knowledge-Based Instrumentation and Control for Competitive Industry-Inspired Robotic Domains
(KI - Künstliche Intelligenz: Vol. 30, No. 0, 2016) Niemueller, Tim; Zug, Sebastian; Schneider, Sven; Karras, Ulrich
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.