Research and technology

As the NASA center responsible for assembly, checkout, servicing, launch, recovery, and operational support of Space Transportation System elements and payloads, Kennedy Space Center (KSC) is placing increasing emphasis on KSC's research and technology program. In addition to strengthening those areas of engineering and operations technology that contribute to safer, more efficient, and more economical execution of the current mission, the technological tools needed to execute KSC's mission relative to future programs are being developed. The Engineering Development Directorate encompasses most of the laboratories and other KSC resources that are key elements of research and technology program implementation and is responsible for implementation of the majority of the projects in this KSC 1990 annual report. Projects under the following topics are covered: (1) materials science; (2) hazardous emissions and contamination monitoring; (3) biosciences; (4) autonomous systems; (5) communications and control; (6) meteorology; (7) technology utilization; and (8) mechanics, structures, and cryogenics

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world

Bio-inspired electronics for micropower vision processing

Vision processing is a topic traditionally associated with neurobiology; known to encode, process and interpret visual data most effectively. For example, the human retina; an exquisite sheet of neurobiological wetware, is amongst the most powerful and efficient vision processors known to mankind. With improving integrated technologies, this has generated considerable research interest in the microelectronics community in a quest to develop effective, efficient and robust vision processing hardware with real-time capability. This thesis describes the design of a novel biologically-inspired hybrid analogue/digital vision chip ORASIS1 for centroiding, sizing and counting of enclosed objects. This chip is the first two-dimensional silicon retina capable of centroiding and sizing multiple objects2 in true parallel fashion. Based on a novel distributed architecture, this system achieves ultra-fast and ultra-low power operation in comparison to conventional techniques. Although specifically applied to centroid detection, the generalised architecture in fact presents a new biologically-inspired processing paradigm entitled: distributed asynchronous mixed-signal logic processing. This is applicable to vision and sensory processing applications in general that require processing of large numbers of parallel inputs, normally presenting a computational bottleneck. Apart from the distributed architecture, the specific centroiding algorithm and vision chip other original contributions include: an ultra-low power tunable edge-detection circuit, an adjustable threshold local/global smoothing network and an ON/OFF-adaptive spiking photoreceptor circuit. Finally, a concise yet comprehensive overview of photodiode design methodology is provided for standard CMOS technologies. This aims to form a basic reference from an engineering perspective, bridging together theory with measured results. Furthermore, an approximate photodiode expression is presented, aiming to provide vision chip designers with a basic tool for pre-fabrication calculations

NASA Tech Briefs, January 1990

Topics include: Electronic Components and Circuits. Electronic Systems, Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Fabrication Technology, Mathematics and Information Sciences, and Life Science

Generation Of An Accurate, Metric Spatial Database Of A Large Multi Storied Building

This thesis presents the development of a novel method to generate an accurate, metric spatial database of a large multi storied building during construction. The algorithm uses the 3D CAD model of the building and the video of the structure captured by an Unmanned Aircraft System (UAS). The spatial database is then used to perform several inspection procedures such as, metric data analysis, spatial query for images, visualization through 3D textured model. The video is processed using a simultaneous localization and mapping (SLAM) system. SLAM generates a sparse 3D map of the environment. Our algorithm registers the 3D map with the 3D CAD model to generate the accurate metric spatial database. The user can click on the desired part of the CAD model for inspection and the image of that part will be shown by using the spatial indexing between the CAD model and the spatially distributed images. The image returned by the spatial query can be used to extract metric information. The spatial database is also used to generate a 3D textured model which provides a visual as-built documentation. The metric data calculation and textured model reconstruction methods have been compared to the state of the art Pix4D software (Latest Release (Version 3.1)). The proposed method has a mean squared error (MSE) of 31.9 cm2 and standard deviation of 4.28 cm where Pix4D had a higher MSE of 45.6 cm2 and standard deviation of 4.91 cm. Using statistical t-test and ANOVA tests we have shown that we are statistically 99% confident that the proposed algorithm has performed better than Pix4D

Advanced Platform Systems Technology study. Volume 2: Trade study and technology selection

Three primary tasks were identified which include task 1-trade studies, task 2-trade study comparison and technology selection, and task 3-technology definition. Task 1 general objectives were to identify candidate technology trade areas, determine which areas have the highest potential payoff, define specific trades within the high payoff areas, and perform the trade studies. In order to satisfy these objectives, a structured, organized approach was employed. Candidate technology areas and specific trades were screened using consistent selection criteria and considering possible interrelationships. A data base comprising both manned and unmanned space platform documentation was used as a source of system and subsystem requirements. When requirements were not stated in the data base documentation, assumptions were made and recorded where necessary to characterize a particular spacecraft system. The requirements and assumptions were used together with the selection criteria to establish technology advancement goals and select trade studies. While both manned and unmanned platform data were used, the study was focused on the concept of an early manned space station

Discrete Wavelet Transforms

The discrete wavelet transform (DWT) algorithms have a firm position in processing of signals in several areas of research and industry. As DWT provides both octave-scale frequency and spatial timing of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Algorithms and Applications reviews the recent progress in discrete wavelet transform algorithms and applications. The book covers a wide range of methods (e.g. lifting, shift invariance, multi-scale analysis) for constructing DWTs. The book chapters are organized into four major parts. Part I describes the progress in hardware implementations of the DWT algorithms. Applications include multitone modulation for ADSL and equalization techniques, a scalable architecture for FPGA-implementation, lifting based algorithm for VLSI implementation, comparison between DWT and FFT based OFDM and modified SPIHT codec. Part II addresses image processing algorithms such as multiresolution approach for edge detection, low bit rate image compression, low complexity implementation of CQF wavelets and compression of multi-component images. Part III focuses watermaking DWT algorithms. Finally, Part IV describes shift invariant DWTs, DC lossless property, DWT based analysis and estimation of colored noise and an application of the wavelet Galerkin method. The chapters of the present book consist of both tutorial and highly advanced material. Therefore, the book is intended to be a reference text for graduate students and researchers to obtain state-of-the-art knowledge on specific applications

Calibration and 3D Model Generation for a Low-Cost Structured Light Foot Scanner

The need for custom footwear among the consumers is growing every day. Serious research is being undertaken with regards to the fit and comfort of the footwear. The integration of scanning systems in the footwear and orthotic industries have played a significant role in generating 3D digital representation of the foot for automated measurements from which a custom footwear or an orthosis is manufactured. The cost of such systems is considerably high for many manufacturers due to their expensive components, complex processing algorithms and difficult calibration techniques. This thesis presents a fast and robust calibration technique for a low-cost 3D laser scanner. The calibration technique is based on determining the mathematical relationship that relates the image coordinates to the real world coordinates. The relationship is determined by mapping the known real world coordinates of a reference object to its corresponding image coordinates by multivariate polynomial regression. With the developed mathematical relationship, 3D data points can be obtained from the 2D images of any object placed in the scanner. An image processing script is developed to detect the 2D image points of the laser profile in a series of scan images from 8 cameras. The detected 2D image points are reconstructed into 3D data points based on the mathematical model developed by the calibration process. Following that, the output model is achieved by triangulating the 3D data points as a mesh model with vertices and normals. The data is exported as a computer aided design (CAD) software readable format for viewing and measuring. This method proves to be less complex and the scanner was able to generate 3D models with an accuracy of +/-0.05 cm. The 3D data points from the output model were compared against a reference model scanned by an industrial grade scanner to verify and validate the result. The devised methodology for calibrating the 3D laser scanner can be employed to obtain accurate and reliable 3D data of the foot shape and it has been successfully tested with several participants