Search results for: Alois Knoll

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Knoll</title> <meta name="description" content="Search results for: Alois Knoll"> <meta name="keywords" content="Alois Knoll"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler ml-auto" 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="Alois Knoll"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 3</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: Alois Knoll</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">3</span> Knowledge Based Behaviour Modelling and Execution in Service Robotics</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Suraj%20Nair">Suraj Nair</a>, <a href="https://publications.waset.org/abstracts/search?q=Aravindkumar%20Vijayalingam"> Aravindkumar Vijayalingam</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexander%20Perzylo"> Alexander Perzylo</a>, <a href="https://publications.waset.org/abstracts/search?q=Alois%20Knoll"> Alois Knoll</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the last decade robotics research and development activities have grown rapidly, especially in the domain of service robotics. Integrating service robots into human occupied spaces such as homes, offices, hospitals, etc. has become increasingly worked upon. The primary motive is to ease daily lives of humans by taking over some of the household/office chores. However, several challenges remain in systematically integrating such systems in human shared work-spaces. In addition to sensing and indoor-navigation challenges, programmability of such systems is a major hurdle due to the fact that the potential user cannot be expected to have knowledge in robotics or similar mechatronic systems. In this paper, we propose a cognitive system for service robotics which allows non-expert users to easily model system behaviour in an underspecified manner through abstract tasks and objects associated with them. The system uses domain knowledge expressed in the form of an ontology along with logical reasoning mechanisms to infer all the missing pieces of information required for executing the tasks. Furthermore, the system is also capable of recovering from failed tasks arising due to on-line disturbances by using the knowledge base and inferring alternate methods to execute the same tasks. The system is demonstrated through a coffee fetching scenario in an office environment using a mobile robot equipped with sensors and software capabilities for autonomous navigation and human-interaction through natural language. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cognitive%20robotics" title="cognitive robotics">cognitive robotics</a>, <a href="https://publications.waset.org/abstracts/search?q=reasoning" title=" reasoning"> reasoning</a>, <a href="https://publications.waset.org/abstracts/search?q=service%20robotics" title=" service robotics"> service robotics</a>, <a href="https://publications.waset.org/abstracts/search?q=task%20based%20systems" title=" task based systems"> task based systems</a> </p> <a href="https://publications.waset.org/abstracts/59980/knowledge-based-behaviour-modelling-and-execution-in-service-robotics" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/59980.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">243</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">2</span> Identification of Dynamic Friction Model for High-Precision Motion Control</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Martin%20Goubej">Martin Goubej</a>, <a href="https://publications.waset.org/abstracts/search?q=Tomas%20Popule"> Tomas Popule</a>, <a href="https://publications.waset.org/abstracts/search?q=Alois%20Krejci"> Alois Krejci</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper deals with experimental identification of mechanical systems with nonlinear friction characteristics. Dynamic LuGre friction model is adopted and a systematic approach to parameter identification of both linear and nonlinear subsystems is given. The identification procedure consists of three subsequent experiments which deal with the individual parts of plant dynamics. The proposed method is experimentally verified on an industrial-grade robotic manipulator. Model fidelity is compared with the results achieved with a static friction model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=mechanical%20friction" title="mechanical friction">mechanical friction</a>, <a href="https://publications.waset.org/abstracts/search?q=LuGre%20model" title=" LuGre model"> LuGre model</a>, <a href="https://publications.waset.org/abstracts/search?q=friction%20identification" title=" friction identification"> friction identification</a>, <a href="https://publications.waset.org/abstracts/search?q=motion%20control" title=" motion control"> motion control</a> </p> <a href="https://publications.waset.org/abstracts/51897/identification-of-dynamic-friction-model-for-high-precision-motion-control" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51897.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">413</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">1</span> Generation of Knowlege with Self-Learning Methods for Ophthalmic Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Klaus%20Peter%20Scherer">Klaus Peter Scherer</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Kn%C3%B6ll"> Daniel Kn枚ll</a>, <a href="https://publications.waset.org/abstracts/search?q=Constantin%20Rieder"> Constantin Rieder</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Problem and Purpose: Intelligent systems are available and helpful to support the human being decision process, especially when complex surgical eye interventions are necessary and must be performed. Normally, such a decision support system consists of a knowledge-based module, which is responsible for the real assistance power, given by an explanation and logical reasoning processes. The interview based acquisition and generation of the complex knowledge itself is very crucial, because there are different correlations between the complex parameters. So, in this project (semi)automated self-learning methods are researched and developed for an enhancement of the quality of such a decision support system. Methods: For ophthalmic data sets of real patients in a hospital, advanced data mining procedures seem to be very helpful. Especially subgroup analysis methods are developed, extended and used to analyze and find out the correlations and conditional dependencies between the structured patient data. After finding causal dependencies, a ranking must be performed for the generation of rule-based representations. For this, anonymous patient data are transformed into a special machine language format. The imported data are used as input for algorithms of conditioned probability methods to calculate the parameter distributions concerning a special given goal parameter. Results: In the field of knowledge discovery advanced methods and applications could be performed to produce operation and patient related correlations. So, new knowledge was generated by finding causal relations between the operational equipment, the medical instances and patient specific history by a dependency ranking process. After transformation in association rules logically based representations were available for the clinical experts to evaluate the new knowledge. The structured data sets take account of about 80 parameters as special characteristic features per patient. For different extended patient groups (100, 300, 500), as well one target value as well multi-target values were set for the subgroup analysis. So the newly generated hypotheses could be interpreted regarding the dependency or independency of patient number. Conclusions: The aim and the advantage of such a semi-automatically self-learning process are the extensions of the knowledge base by finding new parameter correlations. The discovered knowledge is transformed into association rules and serves as rule-based representation of the knowledge in the knowledge base. Even more, than one goal parameter of interest can be considered by the semi-automated learning process. With ranking procedures, the most strong premises and also conjunctive associated conditions can be found to conclude the interested goal parameter. So the knowledge, hidden in structured tables or lists can be extracted as rule-based representation. This is a real assistance power for the communication with the clinical experts. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=an%20expert%20system" title="an expert system">an expert system</a>, <a href="https://publications.waset.org/abstracts/search?q=knowledge-based%20support" title=" knowledge-based support"> knowledge-based support</a>, <a href="https://publications.waset.org/abstracts/search?q=ophthalmic%20decision%20support" title=" ophthalmic decision support"> ophthalmic decision support</a>, <a href="https://publications.waset.org/abstracts/search?q=self-learning%20methods" title=" self-learning methods"> self-learning methods</a> </p> <a href="https://publications.waset.org/abstracts/76514/generation-of-knowlege-with-self-learning-methods-for-ophthalmic-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76514.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">253</span> </span> </div> </div> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET celebrates its 16th foundational anniversary</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Account <li><a href="https://waset.org/profile">My Account</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Explore <li><a href="https://waset.org/disciplines">Disciplines</a></li> <li><a href="https://waset.org/conferences">Conferences</a></li> <li><a href="https://waset.org/conference-programs">Conference Program</a></li> <li><a href="https://waset.org/committees">Committees</a></li> <li><a href="https://publications.waset.org">Publications</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Research <li><a href="https://publications.waset.org/abstracts">Abstracts</a></li> <li><a href="https://publications.waset.org">Periodicals</a></li> <li><a href="https://publications.waset.org/archive">Archive</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Open Science <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Philosophy.pdf">Open Science Philosophy</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Science-Award.pdf">Open Science Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Open-Society-Open-Science-and-Open-Innovation.pdf">Open Innovation</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Postdoctoral-Fellowship-Award.pdf">Postdoctoral Fellowship Award</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/Scholarly-Research-Review.pdf">Scholarly Research Review</a></li> </ul> </div> <div class="col-md-2"> <ul class="list-unstyled"> Support <li><a href="https://waset.org/page/support">Support</a></li> <li><a href="https://waset.org/profile/messages/create">Contact Us</a></li> <li><a href="https://waset.org/profile/messages/create">Report Abuse</a></li> </ul> </div> </div> </div> </div> </div> <div class="container text-center"> <hr style="margin-top:0;margin-bottom:.3rem;"> <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank" class="text-muted small">Creative Commons Attribution 4.0 International License</a> <div id="copy" class="mt-2">© 2024 World Academy of Science, Engineering and Technology</div> </div> </footer> <a href="javascript:" id="return-to-top"><i class="fas fa-arrow-up"></i></a> <div class="modal" id="modal-template"> <div class="modal-dialog"> <div class="modal-content"> <div class="row m-0 mt-1"> <div class="col-md-12"> <button type="button" class="close" data-dismiss="modal" aria-label="Close"><span aria-hidden="true">×</span></button> </div> </div> <div class="modal-body"></div> </div> </div> </div> <script src="https://cdn.waset.org/static/plugins/jquery-3.3.1.min.js"></script> <script src="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/js/bootstrap.bundle.min.js"></script> <script src="https://cdn.waset.org/static/js/site.js?v=150220211556"></script> <script> jQuery(document).ready(function() { /*jQuery.get("https://publications.waset.org/xhr/user-menu", function (response) { jQuery('#mainNavMenu').append(response); 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Search results for: Alois Knoll