A Model-Driven Engineering Approach for ROS using Ontological Semantics

This paper presents a novel ontology-driven software engineering approach for the development of industrial robotics control software. It introduces the ReApp architecture that synthesizes model-driven engineering with semantic technologies to facilitate the development and reuse of ROS-based components and applications. In ReApp, we show how different ontological classification systems for hardware, software, and capabilities help developers in discovering suitable software components for their tasks and in applying them correctly. The proposed model-driven tooling enables developers to work at higher abstraction levels and fosters automatic code generation. It is underpinned by ontologies to minimize discontinuities in the development workflow, with an integrated development environment presenting a seamless interface to the user. First results show the viability and synergy of the selected approach when searching for or developing software with reuse in mind.Comment: Presented at DSLRob 2015 (arXiv:1601.00877), Stefan Zander, Georg Heppner, Georg Neugschwandtner, Ramez Awad, Marc Essinger and Nadia Ahmed: A Model-Driven Engineering Approach for ROS using Ontological Semantic

A ROS2 based communication architecture for control in collaborative and intelligent automation systems

Collaborative robots are becoming part of intelligent automation systems in modern industry. Development and control of such systems differs from traditional automation methods and consequently leads to new challenges. Thankfully, Robot Operating System (ROS) provides a communication platform and a vast variety of tools and utilities that can aid that development. However, it is hard to use ROS in large-scale automation systems due to communication issues in a distributed setup, hence the development of ROS2. In this paper, a ROS2 based communication architecture is presented together with an industrial use-case of a collaborative and intelligent automation system.Comment: 9 pages, 4 figures, 3 tables, to be published in the proceedings of 29th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2019), June 201

Towards adaptive multi-robot systems: self-organization and self-adaptation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.The development of complex systems ensembles that operate in uncertain environments is a major challenge. The reason for this is that system designers are not able to fully specify the system during specification and development and before it is being deployed. Natural swarm systems enjoy similar characteristics, yet, being self-adaptive and being able to self-organize, these systems show beneficial emergent behaviour. Similar concepts can be extremely helpful for artificial systems, especially when it comes to multi-robot scenarios, which require such solution in order to be applicable to highly uncertain real world application. In this article, we present a comprehensive overview over state-of-the-art solutions in emergent systems, self-organization, self-adaptation, and robotics. We discuss these approaches in the light of a framework for multi-robot systems and identify similarities, differences missing links and open gaps that have to be addressed in order to make this framework possible

From a Competition for Self-Driving Miniature Cars to a Standardized Experimental Platform: Concept, Models, Architecture, and Evaluation

Context: Competitions for self-driving cars facilitated the development and research in the domain of autonomous vehicles towards potential solutions for the future mobility. Objective: Miniature vehicles can bridge the gap between simulation-based evaluations of algorithms relying on simplified models, and those time-consuming vehicle tests on real-scale proving grounds. Method: This article combines findings from a systematic literature review, an in-depth analysis of results and technical concepts from contestants in a competition for self-driving miniature cars, and experiences of participating in the 2013 competition for self-driving cars. Results: A simulation-based development platform for real-scale vehicles has been adapted to support the development of a self-driving miniature car. Furthermore, a standardized platform was designed and realized to enable research and experiments in the context of future mobility solutions. Conclusion: A clear separation between algorithm conceptualization and validation in a model-based simulation environment enabled efficient and riskless experiments and validation. The design of a reusable, low-cost, and energy-efficient hardware architecture utilizing a standardized software/hardware interface enables experiments, which would otherwise require resources like a large real-scale test track.Comment: 17 pages, 19 figues, 2 table

Software Abstractions for Simulation and Control of a Continuum Robot

Nordmann A, Rolf M, Wrede S. Software Abstractions for Simulation and Control of a Continuum Robot. In: SIMPAR2012 - SIMULATION, MODELING, and PROGRAMMING for AUTONOMOUS ROBOTS. 2012

A computer-based product classification and component detection for demanufacturing processes

This is an Author's Accepted Manuscript of an article published in International Journal of Computer Integrated Manufacturing, 24(10), 900-914, 2011 [copyright Taylor & Francis], available online at: http://www.tandfonline.com/10.1080/0951192X.2011.579169.The aim of this paper is to propose a novel computer-based product classification, component detection and tracking for demanufacturing and disassembly process. This is achieved by introducing a series of automated and sequential product scanning, component identification, image analysis and sorting – leading to the development of a bill of material (BOM). The produced BOM can then be associated with the relevant disassembly/demanufacture proviso. The proposed integrated image sorting and product classification (ISPC) approach can be considered as a step forward in automation of demanufacturing activities. The ISPC model proposed in this paper utilises and builds on the state-of-the-art technology and current body of research in computer-integrated demanufacturing and remanufacturing (CIDR). An appraisal of the latest research material and the factors that inhibit CIDR methods inpractice are presented. A novel solution for the integration of imaging and material identification techniques toovercome some of the existing shortcomings of automated recycling processes is proposed in this paper. The proposed product scanning and component detection ISPC software consists of four distinct models: the repertory database, the search engine, the product-attributes updater and the image sorting and classification algorithm. The software framework that integrates the four components is presented in this paper. Finally, an overall assessment of applying ISPC at various stages of CIDR processes concludes the article.University of Ibadan MacArthur Foundation Gran

Intuitive Instruction of Industrial Robots : A Knowledge-Based Approach

With more advanced manufacturing technologies, small and medium sized enterprises can compete with low-wage labor by providing customized and high quality products. For small production series, robotic systems can provide a cost-effective solution. However, for robots to be able to perform on par with human workers in manufacturing industries, they must become flexible and autonomous in their task execution and swift and easy to instruct. This will enable small businesses with short production series or highly customized products to use robot coworkers without consulting expert robot programmers. The objective of this thesis is to explore programming solutions that can reduce the programming effort of sensor-controlled robot tasks. The robot motions are expressed using constraints, and multiple of simple constrained motions can be combined into a robot skill. The skill can be stored in a knowledge base together with a semantic description, which enables reuse and reasoning. The main contributions of the thesis are 1) development of ontologies for knowledge about robot devices and skills, 2) a user interface that provides simple programming of dual-arm skills for non-experts and experts, 3) a programming interface for task descriptions in unstructured natural language in a user-specified vocabulary and 4) an implementation where low-level code is generated from the high-level descriptions. The resulting system greatly reduces the number of parameters exposed to the user, is simple to use for non-experts and reduces the programming time for experts by 80%. The representation is described on a semantic level, which means that the same skill can be used on different robot platforms. The research is presented in seven papers, the first describing the knowledge representation and the second the knowledge-based architecture that enables skill sharing between robots. The third paper presents the translation from high-level instructions to low-level code for force-controlled motions. The two following papers evaluate the simplified programming prototype for non-expert and expert users. The last two present how program statements are extracted from unstructured natural language descriptions