16 research outputs found

    A new fuzzy ontology development methodology (FODM) proposal

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    There is an upsurge in applying fuzzy ontologies to represent vague information in the knowledge representation field. Current research in the fuzzy ontologies paradigm mainly focuses on developing formalism languages to represent fuzzy ontologies, designing fuzzy ontology editors, and building fuzzy ontology applications in different domains. Less focus falls on establishing a formal methodological approach for building fuzzy ontologies. Existing fuzzy ontology development methodologies, such as the IKARUS-Onto methodology and Fuzzy Ontomethodology, provide formalized schedules for the conversion from crisp ontologies into fuzzy ones. However, a formal guidance on how to build fuzzy ontologies from scratch still lacks in current research. Therefore, this paper presents the first methodology, named FODM, for developing fuzzy ontologies from scratch. The proposed FODM can provide a very good guideline for formally constructing fuzzy ontologies in terms of completeness, comprehensiveness, generality, efficiency, and accuracy. To explain how the FODM works and demonstrate its usefulness, a fuzzy seabed characterization ontology is built based on the FODM and described step-by-step

    MROS: Runtime Adaptation For Robot Control Architectures

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    Known attempts to build autonomous robots rely on complex control architectures, often implemented with the Robot Operating System platform (ROS). Runtime adaptation is needed in these systems, to cope with component failures and with contingencies arising from dynamic environments-otherwise, these affect the reliability and quality of the mission execution. Existing proposals on how to build self-adaptive systems in robotics usually require a major re-design of the control architecture and rely on complex tools unfamiliar to the robotics community. Moreover, they are hard to reuse across applications. This paper presents MROS: a model-based framework for run-time adaptation of robot control architectures based on ROS. MROS uses a combination of domain-specific languages to model architectural variants and captures mission quality concerns, and an ontology-based implementation of the MAPE-K and meta-control visions for run-time adaptation. The experiment results obtained applying MROS in two realistic ROS-based robotic demonstrators show the benefits of our approach in terms of the quality of the mission execution, and MROS' extensibility and re-usability across robotic applications

    Centralized learning and planning : for cognitive robots operating in human domains

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    An Ontology for Modeling Cultural Heritage Knowledge in Urban Tourism

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    Urban tourism information available on Internet has been of enormous relevance to motivate the tourism in many countries. There exist many applications focused on promoting and preserving the cultural heritage, through urban tourism, which in turn demand a well-defined and standard model for representing the whole knowledge of this domain, thus ensuring interoperable and flexible applications. Current studies propose the use of ontologies to formally model such knowledge. Nonetheless, most of them only represent partial knowledge of cultural heritage or are restrictive to an indoor perspective (i.e., museum ontologies). In this context, we propose the ontology CURIOCITY ( Cultural Heritage for Urban Tourism in Indoor/Outdoor environments of the CITY ), to represent the cultural heritage knowledge based on UNESCO’s definitions. CURIOCITY ontology has a three-level architecture (Upper, Middle, and Lower ontologies) in accordance with a purpose of modularity and levels of specificity. In this paper, we describe in detail all modules of CURIOCITY ontology and perform a comparative evaluation with state-of-the-art ontologies. Additionally, to demonstrate the suitability of CURIOCITY ontology, we show several touristic services offered through a framework supported in the ontology. The framework includes an automatic population process, that allows transforming a museum data repository (in CSV format) into RDF triples of CURIOCITY ontology to automatically populate the CURIOCITY repository, and facilities to develop a set of tourism applications and services, following the UNESCO’s definitions

    Robotic disassembly of waste electrical and electronic equipment

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    Waste electrical and electronic equipment (WEEE) is the world’s fastest growing form of waste. Inappropriate disposal of WEEE causes damage to ecosystems and local communities due to hazardous materials and toxic chemicals present in electronic products. High value metals in small quantities are dissipated and embodied energy from manufacturing are lost in shredding and crushing treatments of WEEE. On the other hand, manual disassembly is costly and presents safety concerns for human workers. Therefore, robotic disassembly is an ideal approach to addressing the treatment of WEEE. Despite extensive research in the field, large variations and uncertainties in product structures, models, and conditions is a major limitation to the implementation of automation and robotics in the waste industry. The ability of a robotic disassembly system to learn new product structures and reason about existing knowledge of product structure is vital to addressing this challenge. This thesis explores robotic disassembly for WEEE by building upon an existing research disassembly rig for LCD monitors and expanding it to address other product families. The updated disassembly system utilizes a modular framework consisting of a Cognition module, Perception module, and Operation module, in order to address the uncertainties present in end-of-life (EoL) products. A novel disassembly ontology is designed and developed with an upper and lower ontology structure to represent generic disassembly knowledge and product-family-specific knowledge respectively. Furthermore, a Learning framework enables automated expansion of the ontology using past disassembly experiences and user-demonstration. These presented methodologies form the main function of the Cognition module, which aids the Perception module and instructs the Operation module. The disassembly ontology and Learning framework are verified independently from the rest of the system prior to being integrated and validated with real disassembly runs of LCD monitors and keyboards. As such, the disassembly system’s ability to address both known and unknown EoL product types, as well as learn new product types, is demonstrated

    Autonomous Operation of a Reconfigurable Multi-Robot System for Planetary Space Missions

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    Reconfigurable robots can physically merge and form new types of composite systems. This ability leads to additional degrees of freedom for robot operations especially when dynamically composed robotic systems offer capabilities that none of the individual systems have. Research in the area of reconfigurable multi-robot systems has mainly been focused on swarm-based robots and thereby to systems with a high degree of modularity but a heavily restricted set of capabilities. In contrast, this thesis deals with heterogeneous robot teams comprising individually capable robots which are also modular and reconfigurable. In particular, the autonomous application of such reconfigurable multi-robot systems to enhance robotic space exploration missions is investigated. Exploiting the flexibility of a reconfigurable multi-robot system requires an appropriate system model and reasoner. Hence, this thesis introduces a special organisation model. This model accounts for the key characteristics of reconfigurable robots which are constrained by the availability and compatibility of hardware interfaces. A newly introduced mapping function between resource structures and functional properties permits to characterise dynamically created agent compositions. Since a combinatorial challenge lies in the identification of feasible and functionally suitable agents, this thesis further suggests bounding strategies to reason efficiently with composite robotic systems. This thesis proposes a mission planning algorithm which permits to exploit the flexibility of reconfigurable multi-robot systems. The implemented planner builds upon the developed organisation model so that multi-robot missions can be specified by high-level functionality constraints which are resolved to suitable combinations of robots. Furthermore, the planner synchronises robot activities over time and characterises plans according to three objectives: efficacy, efficiency and safety. The plannera s evaluation demonstrates an optimization of an exemplary space mission. This research is based on the parallel development of theoretical concepts and practical solutions while working with three reconfigurable multi-robot teams. The operation of a reconfigurable robotic team comes with practical constraints. Therefore, this thesis composes and evaluates an operational infrastructure which can serve as reference implementation. The identification and combination of applicable state-of-the-art technologies result in a distributed and dynamically extensible communication infrastructure which can maintain the properties of reconfigurable multi-robot systems. Field tests covering semi-autonomous and autonomous operation have been performed to characterise multi-robot missions and validate the autonomous control approach for reconfigurable multi-robot systems. The practical evaluation identified critical constraints and design elements for a successful application of reconfigurable multi-robot systems. Furthermore, the experiments point to improvements for the organisation model. This thesis is a wholistic approach to automate reconfigurable multi-robot systems. It identifies theoretical as well as practical challenges and it suggests effective solutions which permit an exploitation of an increased level of flexibility in future robotics missions
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