Method for fabricating an artificial compound eye

A method for fabricating an imaging system, the method comprising providing a flexible substrate (200), a first layer (220) comprising a plurality of microlenses (232) and a second layer (240) comprising a plurality of image sensors (242). The method further comprises stacking the first and the second layer (220; 240) onto the flexible substrate (200) by attaching the plurality of image sensors (242) to the flexible substrate, such that each of the plurality of microlenses (232) and image sensors (242) are aligned to form a plurality of optical channels (300) , each optical channel comprising at least one microlens and at least one associated image sensor, and mechanically separating the optical channels (300) such that the separated optical channels remain attached to the flexible substrate (200) to form a mechanically flexible imaging system

Device Free Indoor Localization Of Human Target Using WIFI Fingerprinting

Indoor localization of human objects has many important applications nowadays. Proposed here is a new device free approach where all the transceiver devices are fixed in an indoor environment so that the human target doesn\u27t need to carry any transceiver device with them. This work proposes radio-frequency fingerprinting for the localization of human targets which makes this even more convenient as radio-frequency wireless signals can be easily acquired using an existing wireless network in an indoor environment. This work explores different avenues for optimal and effective placement of transmitter devices for better localization. In this work, an experimental environment is simulated using the popular software Feko. The indoor geometry under study is first divided into several zones and then the received signal-strength indicators (RSSIs) are measured by the receiving antennae which serve as input features to our designed innovative machine-learning model to identify within which zone the target is. Our proposed machine-learning model, a multi-resolution random-forest classifier is composed of a cascade architecture that integrates and distills learned results over various zoning resolutions. The proposed new multi-resolution approach greatly outperforms the existing random-forest classifier. The average Euclidean-distance error resulting from our proposed new technique is 1.25 meters

An overview of RoboCup-2002 Fukuoka/Busan

© 2003, American Association for Artificial Intelligence (AAAI). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY), https://creativecommons.org/licenses/by/4.0/This article reports on the Sixth Robot World Cup Competition and Conference (RoboCup-2002) Fukuoka/Busan, which took place from 19 to 25 June in Fukuoka, Japan. It was the largest RoboCup since 1997 and held the first humanoid league competition in the world. Further, the first ROBOTREX (robot trade and exhibitions) was held with about 50 companies, universities, and institutes represented. A total of 117,000 spectators witnessed this marvelous event, To the best of our knowledge, this was the largest robotic event in history.Peer reviewe

3D Scene Geometry Estimation from 360∘^\circ Imagery: A Survey

This paper provides a comprehensive survey on pioneer and state-of-the-art 3D scene geometry estimation methodologies based on single, two, or multiple images captured under the omnidirectional optics. We first revisit the basic concepts of the spherical camera model, and review the most common acquisition technologies and representation formats suitable for omnidirectional (also called 360$^\circ$, spherical or panoramic) images and videos. We then survey monocular layout and depth inference approaches, highlighting the recent advances in learning-based solutions suited for spherical data. The classical stereo matching is then revised on the spherical domain, where methodologies for detecting and describing sparse and dense features become crucial. The stereo matching concepts are then extrapolated for multiple view camera setups, categorizing them among light fields, multi-view stereo, and structure from motion (or visual simultaneous localization and mapping). We also compile and discuss commonly adopted datasets and figures of merit indicated for each purpose and list recent results for completeness. We conclude this paper by pointing out current and future trends.Comment: Published in ACM Computing Survey

Real-time Visual Flow Algorithms for Robotic Applications

Vision offers important sensor cues to modern robotic platforms. Applications such as control of aerial vehicles, visual servoing, simultaneous localization and mapping, navigation and more recently, learning, are examples where visual information is fundamental to accomplish tasks. However, the use of computer vision algorithms carries the computational cost of extracting useful information from the stream of raw pixel data. The most sophisticated algorithms use complex mathematical formulations leading typically to computationally expensive, and consequently, slow implementations. Even with modern computing resources, high-speed and high-resolution video feed can only be used for basic image processing operations. For a vision algorithm to be integrated on a robotic system, the output of the algorithm should be provided in real time, that is, at least at the same frequency as the control logic of the robot. With robotic vehicles becoming more dynamic and ubiquitous, this places higher requirements to the vision processing pipeline. This thesis addresses the problem of estimating dense visual flow information in real time. The contributions of this work are threefold. First, it introduces a new filtering algorithm for the estimation of dense optical flow at frame rates as fast as 800 Hz for 640x480 image resolution. The algorithm follows a update-prediction architecture to estimate dense optical flow fields incrementally over time. A fundamental component of the algorithm is the modeling of the spatio-temporal evolution of the optical flow field by means of partial differential equations. Numerical predictors can implement such PDEs to propagate current estimation of flow forward in time. Experimental validation of the algorithm is provided using high-speed ground truth image dataset as well as real-life video data at 300 Hz. The second contribution is a new type of visual flow named structure flow. Mathematically, structure flow is the three-dimensional scene flow scaled by the inverse depth at each pixel in the image. Intuitively, it is the complete velocity field associated with image motion, including both optical flow and scale-change or apparent divergence of the image. Analogously to optic flow, structure flow provides a robotic vehicle with perception of the motion of the environment as seen by the camera. However, structure flow encodes the full 3D image motion of the scene whereas optic flow only encodes the component on the image plane. An algorithm to estimate structure flow from image and depth measurements is proposed based on the same filtering idea used to estimate optical flow. The final contribution is the spherepix data structure for processing spherical images. This data structure is the numerical back-end used for the real-time implementation of the structure flow filter. It consists of a set of overlapping patches covering the surface of the sphere. Each individual patch approximately holds properties such as orthogonality and equidistance of points, thus allowing efficient implementations of low-level classical 2D convolution based image processing routines such as Gaussian filters and numerical derivatives. These algorithms are implemented on GPU hardware and can be integrated to future Robotic Embedded Vision systems to provide fast visual information to robotic vehicles

Reconfigurable Antenna Systems: Platform implementation and low-power matters

Antennas are a necessary and often critical component of all wireless systems, of which they share the ever-increasing complexity and the challenges of present and emerging trends. 5G, massive low-orbit satellite architectures (e.g. OneWeb), industry 4.0, Internet of Things (IoT), satcom on-the-move, Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles, all call for highly flexible systems, and antenna reconfigurability is an enabling part of these advances. The terminal segment is particularly crucial in this sense, encompassing both very compact antennas or low-profile antennas, all with various adaptability/reconfigurability requirements. This thesis work has dealt with hardware implementation issues of Radio Frequency (RF) antenna reconfigurability, and in particular with low-power General Purpose Platforms (GPP); the work has encompassed Software Defined Radio (SDR) implementation, as well as embedded low-power platforms (in particular on STM32 Nucleo family of micro-controller). The hardware-software platform work has been complemented with design and fabrication of reconfigurable antennas in standard technology, and the resulting systems tested. The selected antenna technology was antenna array with continuously steerable beam, controlled by voltage-driven phase shifting circuits. Applications included notably Wireless Sensor Network (WSN) deployed in the Italian scientific mission in Antarctica, in a traffic-monitoring case study (EU H2020 project), and into an innovative Global Navigation Satellite Systems (GNSS) antenna concept (patent application submitted). The SDR implementation focused on a low-cost and low-power Software-defined radio open-source platform with IEEE 802.11 a/g/p wireless communication capability. In a second embodiment, the flexibility of the SDR paradigm has been traded off to avoid the power consumption associated to the relevant operating system. Application field of reconfigurable antenna is, however, not limited to a better management of the energy consumption. The analysis has also been extended to satellites positioning application. A novel beamforming method has presented demonstrating improvements in the quality of signals received from satellites. Regarding those who deal with positioning algorithms, this advancement help improving precision on the estimated position

Omni-directional Broadband Antireflection coating for solar cells using Indium Tin Oxide (ITO) based Fractal Structures

Department of Materials Science EngineeringSolar cells have extrinsic loss from reflection of the front surface which is one such loss mechanism and has been managed in the past with the usage of planar antireflection coatings. But these coatings are each limited to a single wavelength of light and do not account for varying incident angles of the incoming light. Various nanostructures made from wet or dry etching, solution processes have shown the capability to restrict reflection for differing wavelengths and angles of incidence. Especially Graded Refractive Index nanostructures based on Indium Tin Oxide (ITO) were modeled and show a broadband, multi angled reflectance decrease due to an effective grading of the refractive index. Indium Tin Oxide (ITO) is advantageous for its ease of production, large amount, conventional process and refractive index matching to the air source region and silicon substrate. In this study we have demonstrated Indium Tin Oxide (ITO) Fractal structures which has Graded Refractive Index (GRIN) profile for Omni-directional Broadband anti-reflection coating to silicon solar cells. Indium Tin Oxide (ITO) Graded Refractive Index Fractal structures were deposited on silicon surfaces through self-catalyst vapor liquid solid(VLS) growth mechanism using conventional Oblique Angle Deposition (OAD) with computational ? controlled servo assisted electron beam evaporator while elevating substrate temperature below 200℃. We introduced two types of silicon solar cells. The first one has polished planar surfaces and second one has pyramid structure commonly used for industrial production. Graded Refractive Index (GRIN) Fractal structures were successfully applied to planar silicon surface and exhibits both superior optical and electrical properties. With GRIN structure height 1um, planar solar cell`s efficiency was increased 48.9% due to reduced series resistance and reflectance while maintaining shunt resistance at normal incident angle 90˚. But in the omni-directional point of view due to reduced angular reflectance up to 70˚ below 10%, 2um GRIN structure reveals the best annual power density enhancement 73.9% compared to 68.2%. Furthermore we investigated conventional pyramid textured silicon surfaces which has self ? induced oblique angle, Indium Tin Oxide (ITO) GRIN structures were deposited onto pyramid without tilting servo (normal flux incident angle 90˚). The deposited GRIN 1um exhibits total reflection in 300 to 1100nm wavelength length region below 5% that can enhance its annual power density 44% compared to the non-coating textured silicon solar cell. Still the surface passivation issues which is important role in crystalline silicon solar cell efficiency is remained. These issues are not discussed in this study but will be investigated further. Our results in achieving increasing annual power density using Graded refractive index anti-reflection coating is greatly encouraging as regards the development of solar cell industry.ope

Survey on Aerial Multirotor Design: a Taxonomy Based on Input Allocation

This paper reviews the impact of multirotor aerial vehicles designs on their abilities in terms of tasks and system properties. We propose a general taxonomy to characterize and describe multirotor aerial vehicles and their design, which we apply exhaustively on the vast literature available. Thanks to the systematic characterization of the designs we exhibit groups of designs having the same abilities in terms of achievable tasks and system properties. In particular, we organize the literature review based on the number of atomic actuation units and we discuss global properties arising from their choice and spatial distribution in the designs. Finally, we provide a discussion on the common traits of the designs found in the literature and the main future open problems