Refine
H-BRS Bibliography
- yes (36)
Departments, institutes and facilities
- Fachbereich Informatik (36) (remove)
Document Type
- Conference Object (18)
- Article (12)
- Part of a Book (2)
- Patent (2)
- Report (2)
Year of publication
Keywords
- Skin detection (2)
- automated sensor-screening (2)
- biometrics (2)
- machine learning (2)
- optical sensor (2)
- semiconducting metal oxide gas sensor array (2)
- Circular saws (1)
- Collaborating industrial robots (1)
- Embedded system (1)
- Exergame (1)
- Field sequential imaging (1)
- Functional safety (1)
- Hand injuries (1)
- Light curtain (1)
- MOOC (1)
- MOX gas sensors (1)
- NIR (1)
- NIR-point sensor (1)
- OCT (1)
- PAD (1)
- Protective system (1)
- Safety guard (1)
- Smart InGaAs camera-system (1)
- Spectroscopy (1)
- Ultrasonic array (1)
- ambulatory monitoring (1)
- analog/digital signal processing (1)
- authentication (1)
- automatic measurement validation (1)
- camera-based person detection (1)
- collaborative learning (1)
- decision tree learning (1)
- detection (1)
- displacement measurement (1)
- estimation (1)
- feature (1)
- fingerprint (1)
- gamification (1)
- high degree of diagnostic coverage and reliability (1)
- high diagnostic coverage and reliability (1)
- high dynamic range resistance readout (1)
- holography (1)
- human-robot collaboration (1)
- industrial robots (1)
- international teams (1)
- light curtains (1)
- motion estimation (1)
- multi causal strain (1)
- multi-channel power sourcing (1)
- multidisciplinary (1)
- near infrared (1)
- near-infrared (1)
- optical coherence tomography (1)
- optical flow (1)
- optical safeguard sensor (1)
- optical triangulation (1)
- opto-electronic protective device (1)
- physical activity (1)
- physiological monitoring (1)
- presentation attack detection (1)
- presentation attack detection (PAD) (1)
- prioritizable ranking (1)
- project-based learning (1)
- sensor resilience (1)
- serious games (1)
- signal processing algorithm (1)
- skin detection (1)
- slope based signature (1)
- strain (1)
- stress (1)
- time series analysis (1)
- ultrasonic sensor (1)
- welfare technology (1)
Kollaborative Industrieroboter werden für produzierende Unternehmen immer kosteneffizienter. Während diese Systeme für den menschlichen Mitarbeiter eine große Hilfe sein können, stellen sie gleichzeitig ein ernstes Gesundheitsrisiko dar, wenn die zwingend notwendigen Sicherheitsmaßnahmen nur unzureichend umgesetzt werden. Herkömmliche Sicherheitseinrichtungen wie Zäune oder Lichtvorhänge bieten einen guten Schutz, aber solch statische Schutzvorrichtungen sind in neuen, hochdynamischen Arbeitsszenarien problematisch.
Im Forschungsprojekt BeyondSPAI wurde ein Funktionsmuster eines Multisensorsystems zur Absicherung solcher dynamischer Arbeitsszenarien entworfen, implementiert und im Feld getestet. Kern des Systems ist eine robuste optische Materialklassifikation, die mit Hilfe eines intelligenten InGaAs-Kamerasystems Haut von anderen typischen Werkstückoberflächen (z.B. Holz, Metalle od. Kunststoffe) unterscheiden kann. Diese einzigartige Eigenschaft wird genutzt, um menschliche Mitarbeiter zuverlässig zu erkennen, so dass ein konventioneller Roboter in Folge als personenbewusster Cobot arbeiten kann.
Das System ist modular und kann leicht mit weiteren Sensoren verschiedenster Art erweitert werden. Es kann an verschiedene Marken von Industrierobotern angepasst werden und lässt sich schnell an bestehenden Robotersystemen integrieren. Die vier vom System bereitgestellten Sicherheitsausgänge können dazu verwendet werden - abhängig von der durchdrungenen Überwachungszone - entweder eine Warnung auszugeben, die Bewegung des Roboters auf eine sichere Geschwindigkeit zu verlangsamen, oder den Roboter sicher anzuhalten. Sobald alle Zonen wieder als „eindeutig frei von Personen“ identifiziert sind, kann der Roboter wieder beschleunigen, seine ursprüngliche Bewegung wiederaufnehmen und die Arbeit fortsetzen.
The following work presents algorithms for semi-automatic validation, feature extraction and ranking of time series measurements acquired from MOX gas sensors. Semi-automatic measurement validation is accomplished by extending established curve similarity algorithms with a slope-based signature calculation. Furthermore, a feature-based ranking metric is introduced. It allows for individual prioritization of each feature and can be used to find the best performing sensors regarding multiple research questions. Finally, the functionality of the algorithms, as well as the developed software suite, are demonstrated with an exemplary scenario, illustrating how to find the most power-efficient MOX gas sensor in a data set collected during an extensive screening consisting of 16,320 measurements, all taken with different sensors at various temperatures and analytes.
The simultaneous operation of multiple different semiconducting metal oxide (MOX) gas sensors is demanding for the readout circuitry. The challenge results from the strongly varying signal intensities of the various sensor types to the target gas. While some sensors change their resistance only slightly, other types can react with a resistive change over a range of several decades. Therefore, a suitable readout circuit has to be able to capture all these resistive variations, requiring it to have a very large dynamic range. This work presents a compact embedded system that provides a full, high range input interface (readout and heater management) for MOX sensor operation. The system is modular and consists of a central mainboard that holds up to eight sensor-modules, each capable of supporting up to two MOX sensors, therefore supporting a total maximum of 16 different sensors. Its wide input range is archived using the resistance-to-time measurement method. The system is solely built with commercial off-the-shelf components and tested over a range spanning from 100Ω to 5 GΩ (9.7 decades) with an average measurement error of 0.27% and a maximum error of 2.11%. The heater management uses a well-tested power-circuit and supports multiple modes of operation, hence enabling the system to be used in highly automated measurement applications. The experimental part of this work presents the results of an exemplary screening of 16 sensors, which was performed to evaluate the system’s performance.
The choice of suitable semiconducting metal oxide (MOX) gas sensors for the detection of a specific gas or gas mixture is time-consuming since the sensor’s sensitivity needs to be characterized at multiple temperatures to find its optimal operating conditions. To obtain reliable measurement results, it is very important that the power for the sensor’s integrated heater is stable, regulated and error-free (or error-tolerant). Especially the error-free requirement can be only be achieved if the power supply implements failure-avoiding and failure-detection methods. The biggest challenge is deriving multiple different voltages from a common supply in an efficient way while keeping the system as small and lightweight as possible. This work presents a reliable, compact, embedded system that addresses the power supply requirements for fully automated simultaneous sensor characterization for up to 16 sensors at multiple temperatures. The system implements efficient (avg. 83.3% efficiency) voltage conversion with low ripple output (<32 mV) and supports static or temperature-cycled heating modes. Voltage and current of each channel are constantly monitored and regulated to guarantee reliable operation. To evaluate the proposed design, 16 sensors were screened. The results are shown in the experimental part of this work.
In the presented project, new approaches for the prevention of hand movements leading to hazards and for non-contact detection of fingers are intended to permit comprehensive and economical protection on circular saws. The basic principles may also be applied to other machines with manual loading and/or unloading. Two new detection principles are explained. The first is the distinction between skin and wood or other material by spectral analysis in the near infrared region. Using LED and photodiodes it is possible to detect fingers and hands reliable. With a kind of light curtain the intrusion into the dangerous zone near the blade can be prevented. The second principle is video image processing to detect persons, arms and fingers. In the first stage of development the detection of upper limb extremities within a defined hazard area by means of a computer based video image analysis is investigated.
Mobile Datenkommunikation basiert üblicherweise auf der drahtlosen Anbindung eines Endgerätes an eine Basisstation, die ihrerseits an eine feste Infrastruktur angebunden ist. In vielen Szenarien sind diese Voraussetzungen jedoch nicht gegeben. Beispiele hierfür sind Katastrophen wie Hochwasser, Erdbeben oder Flugzeugabstürze in dünn besiedelten Regionen. Einen Lösungsansatz für sich daraus ergebende Anforderungen bieten dynamisch aufgebaute Ad-Hoc Netze mit einer satellitengestützten Anbindung an eine Festnetz-Infrastruktur. In solchen Netzen stellen die mobilen Terminals die benötigte lokale Infrastruktur selbst dynamisch her. Ziel der hier vorgestellten Arbeiten ist es, die Zuverlässigkeit und Dienstqualität der verwendeten Technologien zu untersuchen und durch geeignete Mechanismen so anzupassen, dass die Anforderungen typischer Applikationen möglichst erfüllt werden. Zur Demonstration wurde ein Prototyp aufgebaut, der unter anderem die Anwendungen "Voice over IP" (VoIP), "Datenbankzugriff im Intranet" und "Internetzugang" (WWW) untersucht.