05 Fakultät Informatik, Elektrotechnik und Informationstechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6

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Subject: search.filters.subject.620Subject: search.filters.subject.004Start date: 2014

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Now showing 1 - 10 of 28
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    Efficient sampling of transition constraints for motion planning under sliding contacts
    (2020) Khoury, Marie Therese
    In contact-based motion planning we consider for humanoid and multiped robots problems like going up a staircase, walking over an uneven surface or climbing a steep hill. Solving such tasks requires finding sequences of fixed and sliding contacts and planning the transition from one contact in the environment to another. However, most existing algorithms do not take sliding contacts into account for navigation problems or consider them only for manipulation scenarios. We propose an approach to contact-based planning that uses sliding contacts and exploits contact transitions. Such transitions are elementary operations required for whole contact sequences. To model sliding contacts, we develop a sliding contact constraint that permits the robot to slide on an object’s surface. To exploit contact transitions, we utilize three constraint modes to enable passage: contact with a start surface, no contact and contact with a goal surface. We develop a sampler that samples these transition modes uniformly. In this thesis we focus on the motion of one robot link’s end from an initial contact point toward a designated goal surface while the other end of the robot remains in sliding contact with the initial surface. Our method is evaluated by testing it on manipulator arms of two, three and seven degrees of freedom with different objects and various sampling-based planning algorithms. From the considered manipulator arm, it would be possible to transfer our concept to more complex robots and scenarios and extend it to a whole sequence of contacts.
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    Software product line testing : a systematic literature review
    (2024) Agh, Halimeh; Azamnouri, Aidin; Wagner, Stefan
    A Software Product Line (SPL) is a software development paradigm in which a family of software products shares a set of core assets. Testing has a vital role in both single-system development and SPL development in identifying potential faults by examining the behavior of a product or products, but it is especially challenging in SPL. There have been many research contributions in the SPL testing field; therefore, assessing the current state of research and practice is necessary to understand the progress in testing practices and to identify the gap between required techniques and existing approaches. This paper aims to survey existing research on SPL testing to provide researchers and practitioners with up-to-date evidence and issues that enable further development of the field. To this end, we conducted a Systematic Literature Review (SLR) with seven research questions in which we identified and analyzed 118 studies dating from 2003 to 2022. The results indicate that the literature proposes many techniques for specific aspects (e.g., controlling cost/effort in SPL testing); however, other elements (e.g., regression testing and non-functional testing) still need to be covered by existing research. Furthermore, most approaches are evaluated by only one empirical method, most of which are academic evaluations. This may jeopardize the adoption of approaches in industry. The results of this study can help identify gaps in SPL testing since specific points of SPL Engineering still need to be addressed entirely.
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    Design and scaling of exoskeleton power units considering load cycles of humans
    (2022) Waldhof, Marcel; Wochner, Isabell; Stollenmaier, Katrin; Parspour, Nejila; Schmitt, Syn
    Exoskeletons are powerful tools for aiding humans with pathological conditions, in dangerous environments or in manually exhausting tasks. Typically, they are designed for specific maximum scenarios without taking into account the diversity of tasks and the individuality of the user. To address this discrepancy, a framework was developed for personalizing an exoskeleton by scaling the components, especially the electrical machine, based on different simulated human muscle forces. The main idea was to scale a numerical arm model based on body mass and height to predict different movements representing both manual labor and daily activities. The predicted torques necessary to produce these movements were then used to generate a load/performance cycle for the power unit design. Considering these torques, main operation points of this load cycle were defined and a reference power unit was scaled and optimized. Therefore, a scalability model for an electrical machine is introduced. This individual adaptation and scaling of the power unit for different users leads to a better performance and a lighter design.
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    Sprachassistierter Entwicklungsprozess für automatisierungstechnische Systeme : ein Ansatz zur Strukturierung komplexer Entwicklungsprozesse
    (2020) White, Dustin; Weyrich, Michael
    Der Systementwicklungsprozess nimmt immer mehr an Komplexität zu, da die Systeme selbst immer komplexer werden. Gleichzeitig Vermischen sich die verschiedenen Disziplinen wie Maschinenbau, Elektrotechnik und Softwaretechnik zunehmend, so dass Unternehmen einer Disziplin sprunghafte Komplexitätszuwächse bei ihren Systemen und in ihrer Entwicklung haben. Deshalb wird in dieser Veröffentlichung ein Konzept eines Sprachassistenten erarbeitet, der durch eine Entwicklungsphase führt. Daraus geht hervor, dass die Software zur Unterstützung der Entwicklung ein Informationsmodell benötigt, um die Daten des entwickelten Systems zu speichern und diese mit dem vorhandenen Wissen zu verbinden. Dieses Wissen kann entweder intern oder im Web vorhanden sein. Der Entwicklungsprozess soll daher Kooperation unterstützen, so dass die Assistenzsoftware und Ingenieure miteinander interagieren.
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    Improving the accuracy of musculotendon models for the simulation of active lengthening
    (2023) Millard, Matthew; Kempter, Fabian; Stutzig, Norman; Siebert, Tobias; Fehr, Jörg
    Vehicle accidents can cause neck injuries which are costly for individuals and society. Safety systems could be designed to reduce the risk of neck injury if it were possible to accurately simulate the tissue-level injuries that later lead to chronic pain. During a crash, reflexes cause the muscles of the neck to be actively lengthened. Although the muscles of the neck are often only mildly injured, the forces developed by the neck’s musculature affect the tissues that are more severely injured. In this work, we compare the forces developed by MAT_156, LS-DYNA’s Hill-type model, and the newly proposed VEXAT muscle model during active lengthening. The results show that Hill-type muscle models underestimate forces developed during active lengthening, while the VEXAT model can more faithfully reproduce experimental measurements.
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    Distributed cooperative deep transfer learning for industrial image recognition
    (2020) Maschler, Benjamin; Kamm, Simon; Jazdi, Nasser; Weyrich, Michael
    In this paper, a novel light-weight incremental class learning algorithm for live image recognition is presented. It features a dual memory architecture and is capable of learning formerly unknown classes as well as conducting its learning across multiple instances at multiple locations without storing any images. In addition to tests on the ImageNet dataset, a prototype based upon a Raspberry Pi and a webcam is used for further evaluation: The proposed algorithm successfully allows for the performant execution of image classification tasks while learning new classes at several sites simultaneously, thereby enabling its application to various industry use cases, e.g. predictive maintenance or self-optimization.
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    Maschinelles Lernen für intelligente Automatisierungssysteme mit dezentraler Datenhaltung am Anwendungsfall Predictive Maintenance
    (2019) Maschler, Benjamin; Jazdi, Nasser; Weyrich, Michael
    Für eine hohe Ergebnisqualität sind Machine Learning Algorithmen auf eine breite Datenbasis angewiesen. Studien zeigen jedoch, dass viele Unternehmen nicht bereit sind, ihre Daten mit anderen Unternehmen, beispielsweise in Form einer gemeinsamen Daten-Cloud, zu teilen. Ziel sollte es daher sein, effizientes maschinelles Lernen mit einer dezentralen Datenhaltung, die den Verbleib vertraulicher Daten im jeweiligen Ursprungs-Unternehmen ermöglicht, zu ermöglichen. In diesem Artikel wird diesbezüglich ein neuartiges Konzept vorgestellt und hinsichtlich seiner Potentiale für intelligente Automatisierungssysteme am Beispiel des Anwendungsfalls Predictive Maintenance analysiert. Die Umsetzbarkeit des Konzepts unter Nutzung verschiedener bestehender Ansätze wird diskutiert, bevor schließlich auf potentielle Mehrwerte für Anlagenbetreiber sowie -hersteller unter besonderer Berücksichtigung der Perspektive kleiner und mittlerer Unternehmen eingegangen wird.
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    Deep learning based soft sensors for industrial machinery
    (2020) Maschler, Benjamin; Ganssloser, Sören; Hablizel, Andreas; Weyrich, Michael
    A multitude of high quality, high-resolution data is a cornerstone of the digital services associated with Industry 4.0. However, a great fraction of industrial machinery in use today features only a bare minimum of sensors and retrofitting new ones is expensive if possible at all. Instead, already existing sensors’ data streams could be utilized to virtually ‘measure’ new parameters. In this paper, a deep learning based virtual sensor for estimating a combustion parameter on a large gas engine using only the rotational speed as input is developed and evaluated. The evaluation focusses on the influence of data preprocessing compared to network type and structure regarding the estimation quality.
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    Cervical muscle reflexes during lateral accelerations
    (2023) Millard, Matthew; Hunger, Susanne; Broß, Lisa; Fehr, Jörg; Holzapfel, Christian; Stutzig, Norman; Siebert, Tobias
    Autonomous vehicles will allow a variety of seating orientations that may change the risk of neck injury during an accident. Having a rotated head at the time of a rear-end collision in a conventional vehicle is associated with a higher risk of acute and chronic whiplash. The change in posture affects both the movement of the head and the response of the muscles. We are studying the reflexes of the muscles of the neck so that we can validate the responses of digital human body models that are used in crash simulations. The neck movements and muscle activity of 21 participants (11 female) were recorded at the Stuttgart FKFS mechanical driving simulator. During the maneuver we recorded the acceleration of the seat and electromyographic (EMG) signals from the sternocleidomastoid (STR) muscles using a Biopac MP 160 system (USA). As intuition would suggest, the reflexes of the muscles of the neck are sensitive to posture and the direction of the acceleration.
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    Intelligentes Rekonfigurationsmanagement selbstorganisierter Produktionssysteme in der diskreten Fertigung
    (2020) Müller, Timo; Jazdi, Nasser; Weyrich, Michael
    Die Häufigkeit von Änderungen der Produktionsanforderungen nimmt aufgrund wirtschaftlicher Volatilität, kürzerer Innovationszyklen und Produktlebenszyklen kontinuierlich zu. Daher ist eine Vorhersage aller möglichen Ziele eines Produktionssystems zur Entwurfszeit unmöglich und es ergibt sich erhöhter Rekonfigurationsbedarf zur Betriebszeit. Derzeit weist die Rekonfiguration von Produktionssystemen jedoch einige Schwachstellen auf, die in diesem Beitrag aufgezeigt werden. Außerdem wird die Zukunft der industriellen Automatisierung von Cyber-Physischen Produktionssystemen dominiert werden, welche vielversprechende Potentiale bieten. Folglich werden die Cyber-Physischen Produktionssysteme und einige ihrer Potentiale im Hinblick auf Rekonfiguration diskutiert. Um diese theoretischen Potentiale tatsächlich nutzen zu können, sind allerdings entsprechende Konzepte erforderlich, weshalb dieser Forschungsbeitrag ein grundlegendes Konzept für ein selbstorganisiertes Rekonfigurationsmanagement präsentiert.