Micromachines2015, 6(5), 544-553; doi:10.3390/mi6050544 - published 23 April 2015 Show/Hide Abstract
Abstract: We report on optical components for integrated optics applications at the micro- and nanoscale. Versatile shapes and dimensions are achievable due to the liquid phase processability of SU8 resist. On the one hand, by adjusting the UV-lithography process, waveguiding structures are patterned and released from their original substrate. They can be replaced on any other substrate and also immerged in liquid wherein they still show off efficient light confinement. On the other hand, filled and hollow 1D-nanostructures are achievable by the wetting template method. By exploiting the large range of available SU8 viscosities, nanowires of diameter ranging between 50 nm and 240 nm, as well as nanotubes of controllable wall thickness are presented. Optical injection, propagation, and coupling in such nanostructures are relevant for highly integrated devices.
Micromachines2015, 6(4), 523-543; doi:10.3390/mi6040523 - published 22 April 2015 Show/Hide Abstract
Abstract: Indoor localization systems using WiFi received signal strength (RSS) or pedestrian dead reckoning (PDR) both have their limitations, such as the RSS fluctuation and the accumulative error of PDR. To exploit their complementary strengths, most existing approaches fuse both systems by a particle filter. However, the particle filter is unsuitable for real time localization on resource-limited smartphones, since it is rather time-consuming and computationally expensive. On the other hand, the light computation fusion approaches including Kalman filter and its variants are inapplicable, since an explicit RSS-location measurement equation and the related noise statistics are unavailable. This paper proposes a novel data fusion framework by using an extended Kalman filter (EKF) to integrate WiFi localization with PDR. To make EKF applicable, we develop a measurement model based on kernel density estimation, which enables accurate WiFi localization and adaptive measurement noise statistics estimation. For the PDR system, we design another EKF based on quaternions for heading estimation by fusing gyroscopes and accelerometers. Experimental results show that the proposed EKF based data fusion approach achieves significant localization accuracy improvement over using WiFi localization or PDR systems alone. Compared with a particle filter, the proposed approach achieves comparable localization accuracy, while it incurs much less computational complexity.
Micromachines2015, 6(4), 487-522; doi:10.3390/mi6040487 - published 22 April 2015 Show/Hide Abstract
Abstract: This paper presents a non-linear state observer-based integrated navigation scheme for estimating the attitude, position and velocity of micro aerial vehicles (MAV) operating in GPS-denied indoor environments, using the measurements from low-cost MEMS (micro electro-mechanical systems) inertial sensors and an RGB-D camera. A robust RGB-D visual odometry (VO) approach was developed to estimate the MAV’s relative motion by extracting and matching features captured by the RGB-D camera from the environment. The state observer of the RGB-D visual-aided inertial navigation was then designed based on the invariant observer theory for systems possessing symmetries. The motion estimates from the RGB-D VO were fused with inertial and magnetic measurements from the onboard MEMS sensors via the state observer, providing the MAV with accurate estimates of its full six degree-of-freedom states. Implementations on a quadrotor MAV and indoor flight test results demonstrate that the resulting state observer is effective in estimating the MAV’s states without relying on external navigation aids such as GPS. The properties of computational efficiency and simplicity in gain tuning make the proposed invariant observer-based navigation scheme appealing for actual MAV applications in indoor environments.
Micromachines2015, 6(4), 473-486; doi:10.3390/mi6040473 - published 22 April 2015 Show/Hide Abstract
Abstract: This article describes a primary calibration setup, and its uncertainty, for low flow liquid calibrations at Bronkhorst High-Tech. It will be used to calibrate reference flow meters from 1 to 200 g/h. By setting up an uncertainty budget for this setup, the calibration of the instruments can be compared to that of NMI’s (National Metrology Institutes). The uncertainty budget consists of mass, time and mass flow uncertainties/corrections that need to be taken in to account for determining the traceable mass flow. Tests results of different flow meters/actuators measured on the setup support the calculated uncertainty. By participating in an intercomparison with NMI’s the measurement and uncertainty of this setup is traceable to European NMI’s.
Micromachines2015, 6(4), 462-472; doi:10.3390/mi6040462 - published 22 April 2015 Show/Hide Abstract
Abstract: A sensitive colourimetric method for lead (PbII) detection is reported in this paper using a common tripeptide, glutathione (GSH), and label-free gold nanoparticles (AuNPs). A limit of detection of 6.0 ppb in water was achieved and the dynamic linear range was up to 500 ppb. Selectivity over fourteen potential interfering metal ions was tested and most of these metal ions do not interfere with the method.
Micromachines2015, 6(4), 452-461; doi:10.3390/mi6040452 - published 10 April 2015 Show/Hide Abstract
Abstract: In this paper we describe the development of a system and model to analyze the composition of gas mixtures up to four components. The system consists of a Coriolis mass flow sensor, density, pressure and thermal flow sensor. With this system it is possible to measure the viscosity, density, heat capacity and flow rate of the medium. In a next step the composition can be analyzed if the constituents of the mixture are known. This makes the approach universally applicable to all gasses as long as the number of components does not exceed the number of measured properties and as long as the properties are measured with a sufficient accuracy. We present measurements with binary and ternary gas mixtures, on compositions that range over an order of magnitude in value for the physical properties. Two platforms for analyses are presented. The first platform consists of sensors realized with MEMS fabrication technology. This approach allows for a system with a high level of integration. With this system we demonstrate a proof of principle for the analyses of binary mixtures with an accuracy of 10%. In the second platform we utilize more mature steel sensor technology to demonstrate the potential of this approach. We show that with this technique, binary mixtures can be measured within 1% and ternary gas mixtures within 3%.