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Auflistung Künstliche Intelligenz 33(2) - Juni 2019 nach Titel
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- ZeitschriftenartikelA Jumpstart Framework for Semantically Enhanced OPC-UA(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Katti, Badarinath; Plociennik, Christiane; Schweitzer, MichaelDecentralization is the norm of future smart production as it assists in contextual dynamic decision-making and thereby increases the flexibility required to produce highly customized products. When manufacturing business software is operated as a cloud based solution, it experiences network latency and connectivity issues. To overcome these problems, the production control should be delegated to the manufacturing edge layer and hence, the argument of decentralization is even more applicable to this narrative. In order to accomplish the assigned manufacturing task effectively, the edge layer is required to possess contextual awareness to make run-time decisions in production. Semantic technologies, on the other hand, assist in discerning the meaning, reasoning and drawing inferences from the data. There are several specifications and frameworks to automate the discovery, orchestration and invocation of web services; the prominent are OWL-S, SAWSDL and WSMO. This paper derives a hybrid approach that integrates OWL-S and SAWSDL specifications to overcome the downsides, yet retain the benefits of both approaches to the OPC-UA application methods. Consequently, the proposed semantically enriched OPC-UA concept enables the edge layer to create flexible production orchestration plans in a manufacturing scenario controlled by cloud MES. Furthermore, the derived hybrid approach is applied to a real use case to demonstrate its feasibility in industrial environments.
- ZeitschriftenartikelA Semantic-Based Method for Teaching Industrial Robots New Tasks(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Ramirez-Amaro, Karinne; Dean-Leon, Emmanuel; Bergner, Florian; Cheng, GordonThis paper presents the results of the Artificial Intelligence (AI) method developed during the European project “Factory-in-a-day”. Advanced AI solutions, as the one proposed, allow a natural Human–Robot-collaboration, which is an important capability of robots in industrial warehouses. This new generation of robots is expected to work in heterogeneous production lines by efficiently interacting and collaborating with human co-workers in open and unstructured dynamic environments. For this, robots need to understand and recognize the demonstrations from different operators. Therefore, a flexible and modular process to program industrial robots has been developed based on semantic representations. This novel learning by demonstration method enables non-expert operators to program new tasks on industrial robots.
- ZeitschriftenartikelA Service-Based Production Ecosystem Architecture for Industrie 4.0(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Kuhn, Thomas; Sadikow, Siwara; Antonino, PabloChangeability is one major goal of Industrie 4.0. Existing production architectures limit changeability, because programmable logic controllers (PLC) that are responsible for the execution of real-time production steps also define the order of production steps that are executed for every product. PLC programming therefore implicitly defines the production process. Consequently, any change of a production process requires changes in PLC code, causes potential side effects due to unknown controller dependencies, and requires extensive testing. We propose a service-based architecture approach that encapsulates production steps into re-useable services. Production cells invoke services, and comparable to multi-agent systems autonomously decide about optimal service invocations based on shared information. In this article, we outline our service-based architecture concept and describe a use-case that illustrates the decentral organization of production systems and the cooperative optimization of production steps.
- ZeitschriftenartikelCatering to Real-Time Requirements of Cloud-Connected Mobile Manipulators(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Walter, Christoph; Scholle, Julian-Benedikt; Elkmann, NorbertIn this contribution, we explore real-time requirements of mobile manipulators, a class of intelligent robots, in the context of the ongoing fast-robotics ( https://de.fast-zwanzig20.de/industrie/fast-robotics/ ) project. The project aims at implementing such robots based on (edge-) cloud-services using wireless communication in order to make them more capable and efficient. Instead of trying to universally achieve hard real-time in such a system, we present a mixed real-time approach with an application centered fault tolerance scheme based on transition points and pre-computed alternate plans. We argue that deliberatively addressing uncertainties in timing is similarly important than handling uncertainties e.g. in perception for future intelligent robots.
- ZeitschriftenartikelCorrection to: A Jumpstart Framework for Semantically Enhanced OPC-UA(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Katti, Badarinath; Plociennik, Christiane; Schweitzer, MichaelThe original article can be found.
- ZeitschriftenartikelEditorial(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Ragni, Marco
- ZeitschriftenartikelEpisodic Memories for Safety-Aware Robots(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Bartels, Georg; Beßler, Daniel; Beetz, MichaelIn the factories and distribution centers of the future, humans and robots shall work together in close proximity and even physically interact. This shift to joint human–robot teams raises the question of how to ensure worker safety. In this manuscript, we present a novel episodic memory system for safety-aware robots. Using this system, the robots can answer questions about their actions at the level of safety concepts. We built this system as an extension of the KnowRob framework and its notion of episodic memories. We evaluated the system in a safe physical human–robot interaction (pHRI) experiment, in which a robot had to sort surgical instruments while also ensuring the safety of its human co-workers. Our experimental results show the efficacy of the system to act as a robot’s belief state for online reasoning, as well as its ability to support offline safety analysis through its fast and flexible query interface. To this end, we demonstrate the system’s ability to reconstruct its geometric environment, course of action, and motion parameters from descriptions of safety-relevant events. We also show-case the system’s capability to conduct statistical analysis.
- ZeitschriftenartikelFrom Research to Market: Building the Perception Systems for the Next Generation of Industrial Robots(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Bartels, Georg; Beetz, Michael
- ZeitschriftenartikelNews(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019)
- ZeitschriftenartikelOn Cognitive Reasoning for Compliant Manipulation Tasks in Smart Production Environments(KI - Künstliche Intelligenz: Vol. 33, No. 2, 2019) Leidner, DanielHighly automated smart production environments require robots with autonomous planning mechanisms as well as effect-based performance inference methods. This report discusses the possibilities of cognitive reasoning for compliant manipulation tasks to satisfy these demands. The article builds on the representations for compliant wiping actions and their effects which are fundamental to many tasks in industrial manufacturing. It is described how these actions can be planned, executed, and interpreted by means of generic action descriptions and qualitative models.