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Manipulating objects with robotic hands is a complicated task. Not only the fingers of the hand, but also the pose of the robot's end effector need to be coordinated. Using human demonstrations of movements is an intuitive and data-efficient way of guiding the robot's behavior. We propose a modular framework with an automatic embodiment mapping to transfer recorded human hand motions to robotic systems. In this work, we use motion capture to record human motion. We evaluate our approach on eight challenging tasks, in which a robotic hand needs to grasp and manipulate either deformable or small and fragile objects. We test a subset of trajectories in simulation and on a real robot and the overall success rates are aligned.

Molten droplets emitted from the cathode of vacuum arcs have been investigated by using a time-of-flight setup along a vertical flight tube equipped with two light barriers at different distances from the cathode surface. The light scattered by particles passing the light barriers was registered. The velocity was determined by the flight time. Simultaneously, from the amount of the scattered light, the size of the passing particle was inferred by applying the Mie-scattering theory. Because the arrangement of the cathode could be oriented concerning the flight tube, a coarse angular distribution of the parameters was obtained. Due to a large amount of data, computerized processing by newly developed algorithms was required to identify and characterize the several tens of thousands of particle peaks. The number of particles per discharge depends strongly on the cathode material and varies remarkably with the angle between flight direction and cathode surface. Generally, smaller particles were found to have higher velocities and vice versa. The distribution of the particle sizes follows a power law. The distribution of the emission velocities exhibits more than one local maximum pointing to distinct particle populations having distinct typical velocities. These populations contribute differently to the total amount of particles at various angles.

Naturally, finding joint trajectories for robotic manipulators involves competing optimization goals. On the one hand, the end-effector should move along a predictable and short path while on the other hand joint movement and acceleration should be kept to a minimum. Obstacles in the workspace or joint limits complicate the situation even further. Constructing a metric that makes undesired configurations more expensive to travel through, we equip the joint space with a notion of cost. The motion planning task then reduces to the problem of finding cheapest paths connecting two configurations – so-called geodesics. We show how to construct suitable metrics for a variety of typical scenarios and present an efficient algorithm for the computation of the corresponding geodesics. Our approach makes it very easy to balance different optimization goals and produces natural and smooth manipulator movement.

The integrity of the solder joint is critical to ensure long-term reliability of power-LEDs under harsh environmental conditions. Many studies have focused on prediction of the lifetime for different lead-free solder joints in temperature cycling tests especially Ball Grid Arrays (BGA), flip chip, SMD, etc [1]. However, physics-of-failure (PoF) based solder fatigue modelling is an on-going struggle for microelectronics and microsystems industry since it heavily depends on the geometry of the solder solder (i.e. package type and therefore, correct implementation of the thermo-mechanical response) and, precise knowledge of valid process dependent material properties, above all for the solder material. Further, a comparison of lifetime data between different package types depends on a stringent definition of a suitable failure criterion and evaluation of the local failure parameter. This makes it challenging to establish a reliable and universal lifetime model for a specific solder material across package types. In LEDs L2 bonding by solder attach, due to thermal management requirements the use of Insulated Material Substrates (IMS) is compulsory. The combination of Metal-Core-PCB boards and the ceramic substrate in LEDs introduces a complexity factor caused by the large E-modulus and CTE mismatch which must be considered.In this paper, a model is developed to predict the lifetime of SAC305 solder joint in a LED on board setup using accelerated tests and finite element modelling where crack length is the failure criterion and the accumulated creep strain is the computational failure parameter to quantify damage. Moreover, influence of geometrical factors on reliability of LED is investigated. Moreover, it was observed that process uncertainties such as void could largely impact the lifetime which leads us to dive further in robustness evaluation within a physics of failure reliability paradigm.

IEEE access 7, 155088-155106 (2019). doi:10.1109/ACCESS.2019.2947581, Published by IEEE, New York, NY

Analyzing runtime behavior is an important part of developing and verifying software systems. This is especially true for complex component-based systems used in the vehicle industry. Here, locating the actual cause of (mis-)behavior can be time-consuming, because the analysis is usually not performed on the architecture level, where the system has initially been designed. Instead, it often relies on source code debugging or visualizing signals and events. The results must then be correlated to what is expected regarding the architecture. With an ever-growing complexity of the systems, the advent of model-based development, code generators and the distributed nature of the development process, this becomes increasingly difficult. This paper therefore presents Architectural Runtime Verification (ARV), a generic approach to analyze system behavior on architecture level using the principles of Runtime Verification. It relies on the architecture description and on the runtime information that is collected in simulation-based tests. This allows an analyst to easily verify or refute hypotheses about system behavior regarding the interaction of components, without the need to inspect the source code. We have instantiated ARV as a framework that allows a client to make queries about architectural elements using a timed LTL-based constraint language. From this, ARV generates a Runtime Verification monitor and applies it to runtime data stored in a database. We demonstrate the applicability of this approach with a running example from the automotive industry.

Low-energy ion implantation technologies are of great interest for tuning the electrical, optical, mechanical, magnetic or morphological properties of solid state devices through structural modifications in advanced materials such as semiconductors, insulators, metals or polymers. The present paper describes low-energy ion implantation devices based on Electron Beam Ion Sources (EBIS) as well as Electron-Cyclotron Resonance Ion Sources (ECRIS). Both kind of ion sources allow it to produce ions of a wide variety of elements. With the available ion sources exist excellent tools to generate ion beam currents from the pA up to the mA range with ion beam energies in the range from some keV up to hundreds of keV. In the paper we give examples for EBIS- as well as ECRIS based implanter solutions and we discuss some applications as the use of high-current He+ irradiation in spintronics devices.

In order to make Internet of Things (IoT) applications easily available and cheap, simple sensors and devices have to be offered. To make this possible, our vision is to use simple hardware for measurements and to put more effort in the signal processing and data analysis to the cloud. In this paper, we present a machine learning algorithm and a simple technical implementation on a hardware platform for the localization of a low accuracy microphone via room impulse response. We give a proof-of-concept via a field test by localization of multiple positions of the IoT device. The field test shows that the recorded signals from the same source are unique at any position in a room due to unique reflections. In contrast to other methods, there is no need for high accuracy microphone arrays, however, at the expanse of multiple measurements and training samples. Our representative k-nearest-neighbor algorithm (RKNN) classifies a recording using a k-nearest-neighbor method (KNN) after choosing representatives for the KNN classifier, which reduces computing time and memory of the KNN classifier.

The increasing complexity of multi-channel SAR sensors and the real-time on-board phase/amplitude correction requirement pose new challenges for the calibration, which cannot rely on state-of-the-art calibration techniques. On the other hand, the digital hardware utilized in multi-channel SAR systems, offer new opportunities for the calibration such as on-board error correction and digital calibration. This paper addresses the internal calibration strategy for future digital beamforming SAR instruments and details the implementation of a dedicated calibration simulator software.

The reduction of CO and NO x from the cement process is a continued requirement for many cement manufacturers and often involves very expensive end-of-pipe pollution abatement solutions. The injection of highly reactive hot oxygen is a new approach that can be used to address lower emission requirements or complement under-performing existing solutions. The innovative oxygen lancing technology discussed in this paper is installed in the outlet of the kiln or calciner to address primarily CO from the system. Through careful excess oxygen reduction, the NO x generated in the main burner can be lowered as well because resulting CO can be oxidized with the oxygen injection. The technology consists of a lance that preheats oxygen to very high temperatures and effectively mixes this relatively small oxygen flow at high speed into much larger flue gas streams. The paper introduces the injection of oxygen into a cement kiln to reduce CO slip from the combustion process and includes data from a cement plant where the technology was implemented for the first time to simultaneously reduce CO and NO x .

Literature is abound with smart wheelchair platforms of various developments, yet to date there has been little technology to find its way to the market place. Many trials and much research has taken place over the last few decades however the end user has benefited precious little. There exists two fundamental difficulties when developing a smart powered wheelchair assistive system, the first is need for the system to be fully compatible with all of the manufacturers, and the second is to produce a technology and business model which is marketable and therefore desirable to the manufacturers. However this requires the researchers to have access to hardware which can be used to develop practical systems which will seamlessly integrate and communicate with existing manufacturer's wheelchair systems. We have developed a low-cost embedded system which integrates with 95% of the powered wheelchair controller market; our system allows researchers to access the low level embedded system with more powerful computational devices running sophisticated software enabling rapid development of algorithms and techniques. When they have been evaluated they can be easily ported to the embedded processor for real-time evaluation and clinical trial.

Vehicular networking is at the corner from early research to final deployment. This phase requires more field testing and real-world experimentation. Most Field Operational Tests (FOTs) are based on proprietary commercial hardware that only allows for marginal modifications of the protocol stack. Furthermore, the roll-out of updated implementations for new or changing protocol standards often takes a prohibitively long time. We developed one of the first complete Open Source experimental and prototyping platform for vehicular networking solutions. Our system supports most of the ETSI ITS-G5 features and runs on standard Linux. New protocol features and updates could now easily be done by and shared with the vehicular networking R&D community.

An elevated interest in underwater optical communications has resulted in the development of numerous theoretical models to predict both signal attenuation and bandwidth (pulse spreading) for underwater optical links. Few, if any, of these models have been experimentally validated, owing mostly to the difficulty in measuring temporal dispersion in these challenging environments. In this work, we begin to close the loop between theory and experiment, by validating a numerical Monte Carlo model against experimental data. Channel attenuation and frequency response is measured out to 1 GHz over ∼ 20 attenuation lengths in a line-of-sight configuration.

Compressed bitmap indices are heavily used in scientific and commercial database systems because they largely improve query performance for various workloads. Early research focused on finding tailor-made index compression schemes that are amenable for modern processors. Improving performance further typically comes at the expense of a lower compression rate, which is in many applications not acceptable because of memory limitations. Alternatively, tailor-made hardware allows to achieve a performance that can only hardly be reached with software running on general-purpose CPUs. In this paper, we will show how to create a custom instruction set framework for compressed bitmap processing that is generic enough to implement most of the major compressed bitmap indices. For evaluation, we implemented WAH, PLWAH, and COMPAX operations using our framework and compared the resulting implementation to multiple state-of-the-art processors. We show that the custom-made bitmap processor achieves speedups of up to one order of magnitude by also using two orders of magnitude less energy compared to a modern energy-efficient Intel processor. Finally, we discuss how to embed our processor with database-specific instruction sets into database system environments.

A new backscatter suppression technique is applied to a wideband modulation scheme to enhance optical ranging in underwater environments. The statistical digital signal processing (DSP) approach of blind signal separation (BSS) [1–2] is applied to a frequency domain reflectometry (FDR) [3–4] ranging system. Applying BSS to the FDR system allows the backscatter return to be dynamically measured and cancelled out before computing range. Results from simulations and laboratory experiments are presented to demonstrate the combined FDR/BSS approach.

Ultra high intensity laser pulses are required by researchers for a growing number of applications such as laser-based particle acceleration for generation of ultrafast energetic electrons [1], laser based ion acceleration and attosecond light pulse generation.

Hybrid lidar-radar uses a combination of lidar and radar techniques to enhance underwater detection, ranging, and imaging. In turbid water, the lidar return signal includes a significant amount of backscatter in addition to the object-reflected light. System performance is highly limited by the backscatter which results from volumetric scattering of the transmitted light signal off the particulates existing in the water channel. A new backscatter reduction technique based on spatial frequency filtering will be discussed. The spatial filter algorithm leverages radar techniques developed to enhance through the wall imaging (TTWI) performance. Algorithm validation via experimental data is provided.

Summary form only given. Plasma-discharges using nanosecond repetitive high voltage pulses has been very effective for the stabilization of lean flame1. To explain the chemical mechanisms of active species production by pulsed discharges, a two-step mechanism was proposed to explain the production of high densities of atomic oxygen. This mechanism first creates excited electronic states of nitrogen, which then dissociate molecular oxygen through quenching reactions2. In this paper, we investigated the temperature of the gas during and after the discharge using Optical Emission Spectroscopy on the second positive system of nitrogen, and simulated spectra from SPECAIR. The spatial profiles of excited nitrogen species densities in the discharge were determined using Abel-inverted spectra of the first and second positive system of nitrogen. The time evolution of the absolute density of N2(B) and N2(C) was also determined and the quenching rates of N2(B) and N2(C) by collisions with O 2 were found to be 2.5 (±0.5) ×10−10 cm−3.s−1 and 5.2 (±0.5) ×10−10 cm−3.s −1 at 2000 K.

Summary form only given. High-voltage nanosecond pulses with reduced electric field in the range of 100 to 300 Td are a very efficient way to produce active chemical species in air1. We seek to explore whether interesting chemical species can be produced in water vapor.

The FEAST eigenvalue algorithm of Polizzi [1] is extended to solve the complex band structure problem.

High scattering environments, such as fog, sand, and turbid ocean water, severely degrade the performance of typical line-of-sight(LOS)/pseudo-monostatic imaging systems where the laser and receiver are on the same platform. Researchers at NAVAIR have developed a unique non-line-of-sight (NLOS)/bistatic imaging system where the illuminator and receiver are on separate platforms and are linked via wireless optical communication signal that is carried via the target-reflected light. The illuminator is placed close to the target, eliminating a majority of the forward and back scatter that occurs on the way to the target. This system is not hindered by multiple scattering in the path from the object to the receiver which allows it to achieve good image quality through much higher attenuation lengths than typical LOS imaging systems. A compact, dual optical wavelength system has been developed and is currently being tested in a laboratory environment. Results from this testing will be presented and plans for future work will be discussed.

Over the last decade, Si 1−x Ge x has increasingly been used as a channel material in MOSFETs. Though many studies have dealt with the real bandstructure of Si 1−x Ge x , the effect of germanium mole fraction x on complex bandstructure has been unexplored. Complex bands fundamentally determine band to band tunneling (BTBT) current. For example, using the orientation dependent complex bandstructure of silicon [1], it has been shown [2] that the BTBT current in the [110] direction is an order of magnitude larger than that along the [100] direction. BTBT contributes significantly to off-current I off in conventional MOSFETs, via the mechanism of gate induced drain leakage (GIDL). Additionally, BTBT determines the on current I on in tunneling FETs, which have been suggested as next generation devices. Further, BTBT is more dominant in Si 1−x Ge x than silicon, owing to a narrower bandgap. In this work, we determine the orientation dependent complex bandstructure of Si 1−x Ge x along common crystallographic directions and predict trends in BTBT current.

Based on unique patented technologies, ASC's 3D Flash LIDAR enables each pixel in the camera's focal plane to measure the range (r) and intensity (i) of every point and object in the camera's 3D field of view without scanning. Capturing 16,384 pixels per eye-safe laser pulse up to 30 frames per second, ASC's 3D Flash LIDAR Cameras create video streams of 128 × 128 3D point clouds of the scene in front of the non-mechanical, solid state camera. The short capture time (typically ½ a microsecond or less) emphasizes the camera's ability to capture 3D images without motion distortion. Additionally, the camera provides geometrically accurate 3D point cloud data (x,y,r) with the added benefit of co-registered intensity (i) on each pixel in the scene, from which velocity and position vectors of various objects can be calculated in real-time. The camera can image through obscuration (e.g. dust, smoke, fog), is very light and compact and has an effective capture range from 5cm to 1km. The TigerEye 3D Flash LIDAR Camera can be found in unmanned ground and air vehicles, is used for Automated Rendezvous & Docking for space applications, is useful for aviation and helicopter brownout and automotive applications. With a a number of lens and laser options, the Ethernet enabled TigerEye is finding a wide range of new applications arenas including the Entertainment industry. We will discuss ASC's disruptive technology and the implications to content creators who have relied on prior generations of technologies such as scanning ladar, 2D stereoscopy and other sensing technologies and methodologies to create 3D content.

Tunneling field-effect transistors (TFETs) are attracting a lot of interest because of their potential to reduce power dissipation in logic applications [1–3]. Performance of TFETs is expected to improve with increasing electrostatic control as provided by ultra-thin body (UTB) based single-gate (SG), double-gate (DG), and nanowire based gate-all-around (GAA) structures, respectively (Fig. 1) [4]. Increasing geometrical confinement, however, could also lead to significant quantum confinement effects [4, 5], especially in III–V materials, which is detrimental to TFET performance. A previous study compared the operation of InAs based SG, DG, and GAA TFETs using quantum transport simulations [4]. Because of the use of the tight-binding model for the device structure in [4], however, the important tradeoff between electrostatics vs. quantum confinement in different geometries could not be clearly distinguished. In this work, we use detailed analytical calculations to compare the operation of SG, DG, and GAA TFETs in InAs (Fig. 1), and examine the competing effects of electrostatics vs. quantum confinement. We demonstrate an important tradeoff between the superior electrostatic control vs. current injection efficiency in TFETs with increasing lateral confinement, which will be an essential consideration for future TFET design.