This paper describes the concept of a new algorithm to control an Unmanned Aerial System (UAS) for accurate autonomous indoor flight. Inside a greenhouse, Global Positioning System (GPS) signals are not reliable and not accurate enough. As an alternative, Ultra Wide Band (UWB) is used for localization. The noise is compensated by combining the UWB with the delta position signal from a novel optical flow algorithm through a Kalman Filter (KF). The end result is an accurate and stable position signal with low noise and low drift.
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Saturated hydraulic conductivity (Ks) of the filler layer in grassed swales are varying in the changing environment. In most of the hydrological models, Ks is assumed as constant or decrease with a clogging factor. However, the Ks measured on site cannot be the input of the hydrological model directly. Therefore, in this study, an Ensemble Kalman Filter (EnKF) based approach was carried out to estimate the Ks of the whole systems in two monitored grassed swales at Enschede and Utrecht, the Netherlands. The relationship between Ks and possible influencing factors (antecedent dry period, temperature, rainfall, rainfall duration, total rainfall and seasonal factors) were studied and a Multivariate nonlinear function was established to optimize the hydrological model. The results revealed that the EnKF method was satisfying in the Ks estimation, which showed a notable decrease after long-term operation, but revealed a recovery in summer and winter. After the addition of Multivariate nonlinear function of the Ks into hydrological model, 63.8% of the predicted results were optimized among the validation events, and compared with constant Ks. A sensitivity analysis revealed that the effect of each influencing factors on the Ks varies depending on the type of grassed swale. However, these findings require further investigation and data support.
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To better control the growing process of horticulture plants greenhouse growers need an automated way to efficiently and effectively find where diseases are spreading.The HiPerGreen project has done research in using an autonomous quadcopter for this scouting. In order for the quadcopter to be able to scout autonomously accurate location data is needed. Several different methods of obtaining location data have been investigated in prior research. In this research a relative sensor based on optical flow is looked into as a method of stabilizing an absolute measurement based on trilateration. For the optical flow sensor a novel block matching algorithm was developed. Simulated testing showed that Kalman Filter based sensor fusion of both measurements worked to reduce the standard deviation of the absolute measurement from 30 cm to less than 1 cm, while drift due to dead-reckoning was reduced to a maximum of 11 cm from over 36 cm.
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Due to the exponential growth of ecommerce, the need for automated Inventory management is crucial to have, among others, up-to-date information. There have been recent developments in using drones equipped with RGB cameras for scanning and counting inventories in warehouse. Due to their unlimited reach, agility and speed, drones can speed up the inventory process and keep it actual. To benefit from this drone technology, warehouse owners and inventory service providers are actively exploring ways for maximizing the utilization of this technology through extending its capability in long-term autonomy, collaboration and operation in night and weekends. This feasibility study is aimed at investigating the possibility of developing a robust, reliable and resilient group of aerial robots with long-term autonomy as part of effectively automating warehouse inventory system to have competitive advantage in highly dynamic and competitive market. To that end, the main research question is, “Which technologies need to be further developed to enable collaborative drones with long-term autonomy to conduct warehouse inventory at night and in the weekends?” This research focusses on user requirement analysis, complete system architecting including functional decomposition, concept development, technology selection, proof-of-concept demonstrator development and compiling a follow-up projects.
Met het groeien van de gemiddelde levensverwachting is ook de uitdaging gegroeid om een ieder zo lang mogelijk een actieve deelnemer van de samenleving te laten zijn. Duurzame zelfstandige mobiliteit is van groot belang voor het functioneren in de samenleving (op werkplek en in thuisomgeving), draagt bij aan het sociaal functioneren en de algemene sociale cohesie. Goede controle over de (dynamische) balans speelt hierbij een grote rol, zijnde de balanshandhaving tijdens het voortbewegen, ook bij gezonde, jonge mensen een continue compromis tussen effectiviteit en veiligheid. Voor ouderen geldt dit nog sterker, daar de gevolgen van een val vele malen ernstiger zijn en ook een grote invloed hebben op de levensverwachting. Mechanismen van handhaving van de dynamische balans in praktische omstandigheden zijn nog grotendeels onbegrepen. Laboratoria staat vaak ver af van praktische condities van de alledaage praktijk. Moderne sensortechnologie opent momenteel een deur naar systematisch onderzoek naar valrisico’s in het dagelijkse leven, echter deze schiet nog te kort in haalbare accuratesse en stabiltiteit over langere metingen. In verschillende projecten wordt momenteel een nieuwe generatie van methoden onderzocht, met als centraal kenmerk hiervan dat bewegingsensoren niet meer als losse onderdelen functioneren, maar in samenhang worden gebruikt. Het kersverse INSTANT project, bijvoorbeeld, onderzoekt hoe huidige bewegingsensoren kunnen worden uitgebreid met een extra sensormodaliteit en ‘meta-datafusion’ algorithmen. Hierdoor kunnen de sensoren elkaars positie waarnemen en naar verwachting een orde meer accuraat meten op een manier die bovendien stabieler is over langere metingen. Aan iets vergelijkbaars wordt gewerkt door collega’s in Torino en Sassari, Italie, zij het met een andere type sensortechnologie. Dit KIEM project onderzoekt in hoeverre beide methoden (en beide onderzoeksclusters) elkaar kunnen versterken door intensief samen te werken. Het plaatsen van een Italiaanse onderzoeker in het INSTANT onderzoekscluster in Enschede gedurende grote delen van een jaar borgt deze samenwerking.
In the past decade, particularly smaller drones have started to claim their share of the sky due to their potential applications in the civil sector as flying-eyes, noses, and very recently as flying hands. Network partners from various application domains: safety, Agro, Energy & logistic are curious about the next leap in this field, namely, collaborative Sky-workers. Their main practical question is essentially: “Can multiple small drones transport a large object over a high altitude together in outdoor applications?” The industrial partners, together with Saxion and RUG, will conduct feasibility study to investigate if it is possible to develop these collaborative Sky-workers and to identify which possibilities this new technology will offer. Design science research methodology, which focuses on solution-oriented applied research involving multiple iterations with rigorous evaluations, will be used to research the feasibility of the main technological building blocks. They are: • Accurate localization based on onboard sensors. • Safe and optimal interaction controller for collaborative aerial transport Within this project, the first proof-of-concepts will be developed. The results of this project will be used to expand the existing network and formulate a bigger project to address additional critical aspects in order to develop a complete framework for collaborative drones.
