2,308 research outputs found

    A Model-Driven Engineering Approach for ROS using Ontological Semantics

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    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

    Intuitive Instruction of Industrial Robots : A Knowledge-Based Approach

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    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

    Conclusions and implications of automation in space

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    Space facilities and programs are reviewed. Space program planning is discussed

    Multi-level manual and autonomous control superposition for intelligent telerobot

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    Space telerobots are recognized to require cooperation with human operators in various ways. Multi-level manual and autonomous control superposition in telerobot task execution is described. The object model, the structured master-slave manipulation system, and the motion understanding system are proposed to realize the concept. The object model offers interfaces for task level and object level human intervention. The structured master-slave manipulation system offers interfaces for motion level human intervention. The motion understanding system maintains the consistency of the knowledge through all the levels which supports the robot autonomy while accepting the human intervention. The superposing execution of the teleoperational task at multi-levels realizes intuitive and robust task execution for wide variety of objects and in changeful environment. The performance of several examples of operating chemical apparatuses is shown

    Adaptive Robot Framework: Providing Versatility and Autonomy to Manufacturing Robots Through FSM, Skills and Agents

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    207 p.The main conclusions that can be extracted from an analysis of the current situation and future trends of the industry,in particular manufacturing plants, are the following: there is a growing need to provide customization of products, ahigh variation of production volumes and a downward trend in the availability of skilled operators due to the ageingof the population. Adapting to this new scenario is a challenge for companies, especially small and medium-sizedenterprises (SMEs) that are suffering first-hand how their specialization is turning against them.The objective of this work is to provide a tool that can serve as a basis to face these challenges in an effective way.Therefore the presented framework, thanks to its modular architecture, allows focusing on the different needs of eachparticular company and offers the possibility of scaling the system for future requirements. The presented platform isdivided into three layers, namely: interface with robot systems, the execution engine and the application developmentlayer.Taking advantage of the provided ecosystem by this framework, different modules have been developed in order toface the mentioned challenges of the industry. On the one hand, to address the need of product customization, theintegration of tools that increase the versatility of the cell are proposed. An example of such tools is skill basedprogramming. By applying this technique a process can be intuitively adapted to the variations or customizations thateach product requires. The use of skills favours the reuse and generalization of developed robot programs.Regarding the variation of the production volumes, a system which permits a greater mobility and a faster reconfigurationis necessary. If in a certain situation a line has a production peak, mechanisms for balancing the loadwith a reasonable cost are required. In this respect, the architecture allows an easy integration of different roboticsystems, actuators, sensors, etc. In addition, thanks to the developed calibration and set-up techniques, the system canbe adapted to new workspaces at an effective time/cost.With respect to the third mentioned topic, an agent-based monitoring system is proposed. This module opens up amultitude of possibilities for the integration of auxiliary modules of protection and security for collaboration andinteraction between people and robots, something that will be necessary in the not so distant future.For demonstrating the advantages and adaptability improvement of the developed framework, a series of real usecases have been presented. In each of them different problematic has been resolved using developed skills,demonstrating how are adapted easily to the different casuistic

    A Low-Cost Manipulator for Space Research and Undergraduate Engineering Education

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    Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/83596/1/AIAA-2010-3394-549.pd

    A Posture Sequence Learning System for an Anthropomorphic Robotic Hand

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    The paper presents a cognitive architecture for posture learning of an anthropomorphic robotic hand. Our approach is aimed to allow the robotic system to perform complex perceptual operations, to interact with a human user and to integrate the perceptions by a cognitive representation of the scene and the observed actions. The anthropomorphic robotic hand imitates the gestures acquired by the vision system in order to learn meaningful movements, to build its knowledge by different conceptual spaces and to perform complex interaction with the human operator

    Capability-based Frameworks for Industrial Robot Skills: a Survey

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    The research community is puzzled with words like skill, action, atomic unit and others when describing robots? capabilities. However, for giving the possibility to integrate capabilities in industrial scenarios, a standardization of these descriptions is necessary. This work uses a structured review approach to identify commonalities and differences in the research community of robots? skill frameworks. Through this method, 210 papers were analyzed and three main results were obtained. First, the vast majority of authors agree on a taxonomy based on task, skill and primitive. Second, the most investigated robots? capabilities are pick and place. Third, industrial oriented applications focus more on simple robots? capabilities with fixed parameters while ensuring safety aspects. Therefore, this work emphasizes that a taxonomy based on task, skill and primitives should be used by future works to align with existing literature. Moreover, further research is needed in the industrial domain for parametric robots? capabilities while ensuring safety
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