Traditional IMU based PDR systems suffer from rapidly growing drift effects due to the inherent bias of the inertial sensor. Many existing solutions to mitigate this problem use aiding sensors or information as heuristics or map data. We propose a new optimization framework to solve the PDR estimation problem where the sensors biases are explicitly included as state variables and therefore be used to correct for bias effects in the PDR. By using a smoothing approach and exploiting the rigid structure of a MIMU array one can solve for the slowly varying sensor biases. This paper presents the method and gives an exemplary result of a walking trial. Good agreements in the position and orientation with an optical reference system were found. Moreover, accelerometer and gyroscope biases could be estimated accordingly. Further research includes the performance of more experiments under various conditions such that a more quantitative evaluation can be obtained. In addition, an exploration of a (pseudo) realtime filter version would be valuable such that the system can be applied online.
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CC-BY-NC-ND This paper was presented at the IADIS Multi Conference on Computer Science and Information Systems MCCSIS2020 There is an increasing interest in indoor occupation and guidance information for business and societal purposes. Scientific literature has paid attention to various ways of detecting occupation using different sensors as data source including various algorithms for estimating occupation rates from this data. Gaining meaningful insights from the data still faces challenges because the potential benefits are not well understood. This study presents a proof-of-concept of an indoor occupation information system, following the design science methodology. We review various types of sensor data that are typically available or easy-to-install in buildings such as offices, classrooms and meeting rooms. This study contributes to current research by incorporating business requirements taken from expert interviews and tackling one of the main barriers for business by designing an affordable system on a common existing infrastructure. We believe that occupation information systems call for further research, in particular also in the context of social distancing because of covid19.
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Within the profile Technical Information Technology (ICT Department) the most important specializations are Embedded Software and Industrial Automation. About half of the Technical Information curriculum consists of learning modules, the other half is organized in projects. The whole study lasts four years. After two-and-a-half year students choose a specialization. Before the choice is made students have several occasions in which they learn something about the possible fields of specialization. In the first and second year there are two modules about Industrial Automation. First there is a module on actuators, sensors and interfacing, later a module on production systems. Finally there is an Industrial Automation project. In this project groups of students get the assignment to develop the control for a scale model flexible automation cell or to develop a monitoring system for this cell. In the last year of their studies students participate in a larger Industrial Automation project, often with an assignment from Industry. Here also the possibility exists to join multidisciplinary projects (IPD; integrated product development).
In het project Flexible Manufacturing onderzoeken we hoe generieke industriële robots optimaal gebruikt kunnen worden in het bedrijfsleven. Het gaat daarbij om de inzet van software en ICT bij robots om de productie te optimaliseren. Op dit moment worden robots voornamelijk ingezet voor relatief eenvoudig, gestructureerd en repetitief werk. In combinatie met verschillende sensorensystemen kunnen robots echter juist hele complexe taken uitvoeren waarbij de robots zich aanpassen aan de situatie. Een mogelijke verklaring voor bovenstaande situatie is dat robots niet gemakkelijk en snel genoeg kunnen worden ge(her)programmeerd, gecombineerd met verschillende sensorsystemen en gecombineerd met andere softwarepakketten om ze nieuwe taken te laten uitvoeren. In het voortraject van dit projectvoorstel kwam een opvallend verschil tussen de werkwijze op enerzijds hogescholen en universiteiten en anderzijds het bedrijfsleven naar voren. In het bedrijfsleven gebruikt men hoofdzakelijk de commerciële en merkspecifieke software van de robotfabrikanten. Op hogescholen en universiteiten wordt daarentegen hoofdzakelijk gebruik gemaakt van open-source en generieke ontwikkelframeworks. Het framework dat wereldwijd het meest wordt gebruikt is Robot Operating System, oftewel ROS. In dit project willen we meer inzicht krijgen in deze twee verschillende benaderingen. Daarvoor analyseren we de bestaande commerciële software voor de grote merken van robotarmen en vergelijken deze met ROS. Naast een studie naar de overeenkomsten en verschillen wordt binnen het project een grote bijeenkomst georganiseerd met bedrijven uit de regio om te achterhalen welke overwegingen bedrijven maken bij het toepassen van robots en welke hindernissen ze ondervinden bij het daadwerkelijke gebruik van robots. Deze aanvraag wordt parallel gedaan met de Raak KIEM Smart Industry aanvraag: Twentse ROS. Het doel van de huidige aanvraag is om tot de kern van het probleem te komen: waarom worden robots nog niet optimaal ingezet in industrie? Het doel is om op basis van beide KIEM aanvragen een Raak PRO te ontwikkelen op dit onderwerp.
What if living organisms communicated signals from the environment to us and thereby offered a sustainable alternative to electronic sensors? Within the field of biodesign, designers and scientists are collaborating with living organisms to produce new materials with ecological benefits. The company Hoekmine, in collaboration with designers, has been researching the potential of flavobacteria for producing sustainable colorants to be applied on everyday products. These non-harmful bacteria can change their form, texture and iridescent color in response to diverse environmental factors, such as humidity and temperature. Here, billions of cells are sensing and integrating the results as color. Therefore, Hoekmine envisions biosensors, which would minimize the use of increasingly demanded electronic sensors, and thus, the implementation of scarce and toxic materials. Developing a living sensor by hosting flavobacteria in a biobased and biodegradable flexible material offers opportunities for sustainable alternatives to electronic sensors. Aiming to take this concept to the next level, we propose a research collaboration between Avans, Hoekmine and a company specialized in biobased and biodegradable labels, Bio4Life. Together with this interdisciplinary team, we aim to bridge microbiology and embodiment design, and contribute to the development of a circular economy where digital technology and organic systems merge in the design of Living Circular Labels (LCLs). Throughout the project we will use an iterative approach between designing and testing LCLs that host living flavobacteria and additionally, methods for the end user to activate the bacteria’s growth at a given time.
This project is part of an interdisciplinary and international collaboration bringing together experts in nanomaterials, sensor technology, and engineering from the University of Technology of Troyes (UTT, France), Eindhoven University of Technology (TU/e, The Netherlands) and Hanze University of Applied Sciences (HUAS, The Netherlands). It presents an innovative, integrated approach including design, fabrication, characterization, and integration of flexible sensors dedicated to wind turbine blade monitoring, aiming to advance smart monitoring and renewable energy research. The sensor will be developed using functional polymer films decorated with conductive nanoparticles. A novel manufacturing approach will be applied, combining additive manufacturing techniques with the colloidal deposition of silver or gold nanoparticles.
