Taking Advantage of Selective Change Driven Processing for 3D Scanning

This article deals with the application of the principles of SCD (Selective Change Driven) vision to 3D laser scanning. Two experimental sets have been implemented: one with a classical CMOS (Complementary Metal-Oxide Semiconductor) sensor, and the other one with a recently developed CMOS SCD sensor for comparative purposes, both using the technique known as Active Triangulation. An SCD sensor only delivers the pixels that have changed most, ordered by the magnitude of their change since their last readout. The 3D scanning method is based on the systematic search through the entire image to detect pixels that exceed a certain threshold, showing the SCD approach to be ideal for this application. Several experiments for both capturing strategies have been performed to try to find the limitations in high speed acquisition/processing. The classical approach is limited by the sequential array acquisition, as predicted by the Nyquist - Shannon sampling theorem, and this has been experimentally demonstrated in the case of a rotating helix. These limitations are overcome by the SCD 3D scanning prototype achieving a significantly higher performance. The aim of this article is to compare both capturing strategies in terms of performance in the time and frequency domains, so they share all the static characteristics including resolution, 3D scanning method, etc., thus yielding the same 3D reconstruction in static scenes

Systems Issues in Solid Freeform Fabrication

This paper is concerned with the systems aspects of the Solid Freeform Fabrication (SFF) technology, i.e., the issues that deal with getting an external geometric CAD model to automatically control the physical layering fabrication process as directly as possible, regardless ofthe source of the model. The general systems issues are described, the state of systems research is given, and open research questions are posed.Mechanical Engineerin

Master slave en-face OCT/SLO

Master Slave optical coherence tomography (MS-OCT) is an OCT method that does not require resampling of data and can be used to deliver en-face images from several depths simultaneously. As the MS-OCT method requires important computational resources, the number of multiple depth en-face images that can be produced in real-time is limited. Here, we demonstrate progress in taking advantage of the parallel processing feature of the MS-OCT technology. Harnessing the capabilities of graphics processing units (GPU)s, information from 384 depth positions is acquired in one raster with real time display of up to 40 en-face OCT images. These exhibit comparable resolution and sensitivity to the images produced using the conventional Fourier domain based method. The GPU facilitates versatile real time selection of parameters, such as the depth positions of the 40 images out of the set of 384 depth locations, as well as their axial resolution. In each updated displayed frame, in parallel with the 40 en-face OCT images, a scanning laser ophthalmoscopy (SLO) lookalike image is presented together with two B-scan OCT images oriented along rectangular directions. The thickness of the SLO lookalike image is dynamically determined by the choice of number of en-face OCT images displayed in the frame and the choice of differential axial distance between them

Thermophysical Phenomena in Metal Additive Manufacturing by Selective Laser Melting: Fundamentals, Modeling, Simulation and Experimentation

Among the many additive manufacturing (AM) processes for metallic materials, selective laser melting (SLM) is arguably the most versatile in terms of its potential to realize complex geometries along with tailored microstructure. However, the complexity of the SLM process, and the need for predictive relation of powder and process parameters to the part properties, demands further development of computational and experimental methods. This review addresses the fundamental physical phenomena of SLM, with a special emphasis on the associated thermal behavior. Simulation and experimental methods are discussed according to three primary categories. First, macroscopic approaches aim to answer questions at the component level and consider for example the determination of residual stresses or dimensional distortion effects prevalent in SLM. Second, mesoscopic approaches focus on the detection of defects such as excessive surface roughness, residual porosity or inclusions that occur at the mesoscopic length scale of individual powder particles. Third, microscopic approaches investigate the metallurgical microstructure evolution resulting from the high temperature gradients and extreme heating and cooling rates induced by the SLM process. Consideration of physical phenomena on all of these three length scales is mandatory to establish the understanding needed to realize high part quality in many applications, and to fully exploit the potential of SLM and related metal AM processes

A Selective Change Driven System for High-Speed Motion Analysis

Vision-based sensing algorithms are computationally-demanding tasks due to the large amount of data acquired and processed. Visual sensors deliver much information, even if data are redundant, and do not give any additional information. A Selective Change Driven (SCD) sensing system is based on a sensor that delivers, ordered by the magnitude of its change, only those pixels that have changed most since the last read-out. This allows the information stream to be adjusted to the computation capabilities. Following this strategy, a new SCD processing architecture for high-speed motion analysis, based on processing pixels instead of full frames, has been developed and implemented into a Field Programmable Gate-Array (FPGA). The programmable device controls the data stream, delivering a new object distance calculation for every new pixel. The acquisition, processing and delivery of a new object distance takes just 1.7 μ s. Obtaining a similar result using a conventional frame-based camera would require a device working at roughly 500 Kfps, which is far from being practical or even feasible. This system, built with the recently-developed 64 × 64 CMOS SCD sensor, shows the potential of the SCD approach when combined with a hardware processing system

Change blindness: eradication of gestalt strategies

Arrays of eight, texture-defined rectangles were used as stimuli in a one-shot change blindness (CB) task where there was a 50% chance that one rectangle would change orientation between two successive presentations separated by an interval. CB was eliminated by cueing the target rectangle in the first stimulus, reduced by cueing in the interval and unaffected by cueing in the second presentation. This supports the idea that a representation was formed that persisted through the interval before being 'overwritten' by the second presentation (Landman et al, 2003 Vision Research 43149–164]. Another possibility is that participants used some kind of grouping or Gestalt strategy. To test this we changed the spatial position of the rectangles in the second presentation by shifting them along imaginary spokes (by ±1 degree) emanating from the central fixation point. There was no significant difference seen in performance between this and the standard task [F(1,4)=2.565, p=0.185]. This may suggest two things: (i) Gestalt grouping is not used as a strategy in these tasks, and (ii) it gives further weight to the argument that objects may be stored and retrieved from a pre-attentional store during this task

Ono: an open platform for social robotics

In recent times, the focal point of research in robotics has shifted from industrial ro- bots toward robots that interact with humans in an intuitive and safe manner. This evolution has resulted in the subfield of social robotics, which pertains to robots that function in a human environment and that can communicate with humans in an int- uitive way, e.g. with facial expressions. Social robots have the potential to impact many different aspects of our lives, but one particularly promising application is the use of robots in therapy, such as the treatment of children with autism. Unfortunately, many of the existing social robots are neither suited for practical use in therapy nor for large scale studies, mainly because they are expensive, one-of-a-kind robots that are hard to modify to suit a specific need. We created Ono, a social robotics platform, to tackle these issues. Ono is composed entirely from off-the-shelf components and cheap materials, and can be built at a local FabLab at the fraction of the cost of other robots. Ono is also entirely open source and the modular design further encourages modification and reuse of parts of the platform