\u3cem\u3eGRASP News\u3c/em\u3e, Volume 6, Number 1

A report of the General Robotics and Active Sensory Perception (GRASP) Laboratory, edited by Gregory Long and Alok Gupta

GRASP News Volume 9, Number 1

A report of the General Robotics and Active Sensory Perception (GRASP) Laboratory

Image Understanding at the GRASP Laboratory

Research in the GRASP Laboratory has two main themes, parameterized multi-dimensional segmentation and robust decision making under uncertainty. The multi-dimensional approach interweaves segmentation with representation. The data is explained as a best fit in view of parametric primitives. These primitives are based on physical and geometric properties of objects and are limited in number. We use primitives at the volumetric level, the surface level, and the occluding contour level, and combine the results. The robust decision making allows us to combine data from multiple sensors. Sensor measurements have bounds based on the physical limitations of the sensors. We use this information without making a priori assumptions of distributions within the intervals or a priori assumptions of the probability of a given result

CMOS-3D smart imager architectures for feature detection

This paper reports a multi-layered smart image sensor architecture for feature extraction based on detection of interest points. The architecture is conceived for 3-D integrated circuit technologies consisting of two layers (tiers) plus memory. The top tier includes sensing and processing circuitry aimed to perform Gaussian filtering and generate Gaussian pyramids in fully concurrent way. The circuitry in this tier operates in mixed-signal domain. It embeds in-pixel correlated double sampling, a switched-capacitor network for Gaussian pyramid generation, analog memories and a comparator for in-pixel analog-to-digital conversion. This tier can be further split into two for improved resolution; one containing the sensors and another containing a capacitor per sensor plus the mixed-signal processing circuitry. Regarding the bottom tier, it embeds digital circuitry entitled for the calculation of Harris, Hessian, and difference-of-Gaussian detectors. The overall system can hence be configured by the user to detect interest points by using the algorithm out of these three better suited to practical applications. The paper describes the different kind of algorithms featured and the circuitry employed at top and bottom tiers. The Gaussian pyramid is implemented with a switched-capacitor network in less than 50 μs, outperforming more conventional solutions.Xunta de Galicia 10PXIB206037PRMinisterio de Ciencia e Innovación TEC2009-12686, IPT-2011-1625-430000Office of Naval Research N00014111031

The intelligent recoater: a new solution for in-situ monitoring of geometric and surface defects in powder bed fusion

Powder bed homogeneity, contaminations, and printed surface quality are crucial in powder bed-based AM processes to obtain a defect-free part, but the scale at which these defects are seen is not compatible with the resolution of current industrial image-based monitoring solutions. In this work, we explore the implementation of an optical scanner in an industrial laser powder bed fusion (L-PBF) machine to detect powder bed and part-related defects. The sensor is mounted ”parasitically” on the recoater and exploits its movement to scan across the build platform before and after powder deposition to obtain high-resolution images. The acquisition seamlessly integrates with the process, without delaying the production as the acquisition occurs in parallel with the new layer deposition. The system was used to monitor test builds as well as longer builds (1000+ layers) to prove its robustness to the challenging L-PBF chamber environment. The in-situ powder bed images of the new monitoring system were compared to the acquisitions of a standard external camera setup. The improved image quality and resolution of the new system were demonstrated on both large-scale (>1 mm) and small-scale features. The new system proved to be capable of capturing printed surface topography anomalies and powder bed contaminations (<100 µm), opening a whole new range of possibilities for detecting small-scale defects via in-situ monitoring

\u3cem\u3eGRASP News\u3c/em\u3e: Volume 9, Number 1

The past year at the GRASP Lab has been an exciting and productive period. As always, innovation and technical advancement arising from past research has lead to unexpected questions and fertile areas for new research. New robots, new mobile platforms, new sensors and cameras, and new personnel have all contributed to the breathtaking pace of the change. Perhaps the most significant change is the trend towards multi-disciplinary projects, most notable the multi-agent project (see inside for details on this, and all the other new and on-going projects). This issue of GRASP News covers the developments for the year 1992 and the first quarter of 1993

Holography

Holography - Basic Principles and Contemporary Applications is a collection of fifteen chapters, describing the basic principles of holography and some recent innovative developments in the field. The book is divided into three sections. The first, Understanding Holography, presents the principles of hologram recording illustrated with practical examples. A comprehensive review of diffraction in volume gratings and holograms is also presented. The second section, Contemporary Holographic Applications, is concerned with advanced applications of holography including sensors, holographic gratings, white-light viewable holographic stereograms. The third section of the book Digital Holography is devoted to digital hologram coding and digital holographic microscopy

An Active Observer

In this paper we present a framework for research into the development of an Active Observer. The components of such an observer are the low and intermediate visual processing modules. Some of these modules have been adapted from the community and some have been investigated in the GRASP laboratory, most notably modules for the understanding of surface reflections via color and multiple views and for the segmentation of three dimensional images into first or second order surfaces via superquadric/parametric volumetric models. However the key problem in Active Observer research is the control structure of its behavior based on the task and situation. This control structure is modeled by a formalism called Discrete Events Dynamic Systems (DEDS)

\u3cem\u3eGRASP News\u3c/em\u3e, Volume 8, Number 1

A report of the General Robotics and Active Sensory Perception (GRASP) Laboratory. Edited by Thomas Lindsay