Sub-lunar Tap-Yielding eXplorer, STYX

To diversify the idea pool that NASA has to draw from for future manned and unmanned missions to the Moon and Mars, a design/build competition has been posed to collegiate teams across the country. The challenge is to reach, extract, and purify underground ice reserves in a setting analogous to mars. Along the way, teams will be collecting telemetry to mimic prospecting objectives on the moon. The Sublunar Tap-Yielding eXplorer, STYX, is the team’s proposed design for the 2020 NASA RASC-AL competition. Some novel design features STYX will use are a rotary tool changer with swappable tools, a sleeve driving mode, and a pivoting heating probe. The STYX drill head will translate on two axes, use a rotary hammer drill to bore holes, sleeve boreholes with pipe to prevent collapse, and deliver water via a peristaltic pump and a two stage filtration system. Several of these design elements are innovative and conceptually proven through preliminary testing. These efforts are expected to net increased performance and differentiate STYX from other prototype submissions

A photometric stereo-based 3D imaging system using computer vision and deep learning for tracking plant growth

© The Author(s) 2019. Published by Oxford University Press. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Background: Tracking and predicting the growth performance of plants in different environments is critical for predicting the impact of global climate change. Automated approaches for image capture and analysis have allowed for substantial increases in the throughput of quantitative growth trait measurements compared with manual assessments. Recent work has focused on adopting computer vision and machine learning approaches to improve the accuracy of automated plant phenotyping. Here we present PS-Plant, a low-cost and portable 3D plant phenotyping platform based on an imaging technique novel to plant phenotyping called photometric stereo (PS). Results: We calibrated PS-Plant to track the model plant Arabidopsis thaliana throughout the day-night (diel) cycle and investigated growth architecture under a variety of conditions to illustrate the dramatic effect of the environment on plant phenotype. We developed bespoke computer vision algorithms and assessed available deep neural network architectures to automate the segmentation of rosettes and individual leaves, and extract basic and more advanced traits from PS-derived data, including the tracking of 3D plant growth and diel leaf hyponastic movement. Furthermore, we have produced the first PS training data set, which includes 221 manually annotated Arabidopsis rosettes that were used for training and data analysis (1,768 images in total). A full protocol is provided, including all software components and an additional test data set. Conclusions: PS-Plant is a powerful new phenotyping tool for plant research that provides robust data at high temporal and spatial resolutions. The system is well-suited for small- and large-scale research and will help to accelerate bridging of the phenotype-to-genotype gap

Addressing the Smart Systems Design Challenge: The SMAC Platform

This article presents the concepts, the organization, and the preliminary application results of SMAC, a smart systems co-design platform. The SMAC platform, which has been developed as Integrated Project (IP) of the 7th ICT Call under the Objective 3.2 \u201cSmart components and Smart Systems integration\u201d addresses the challenges of the integration of heterogeneous and conflicting domains that emerge in the design of smart systems. SMAC includes methodologies and EDA tools enabling multi-disciplinary and multi-scale modelling and design, simulation of multidomain systems, subsystems and components at different levels of abstraction, system integration and exploration for optimization of functional and non-functional metrics. The article presents the preliminary results obtained by adopting the SMAC platform for the design of a limb tracking smart system

Interactive Visual Analytics for Large-scale Particle Simulations

Particle based model simulations are widely used in scientific visualization. In cosmology, particles are used to simulate the evolution of dark matter in the universe. Clusters of particles (that have special statistical properties) are called halos. From a visualization point of view, halos are clusters of particles, each having a position, mass and velocity in three dimensional space, and they can be represented as point clouds that contain various structures of geometric interest such as filaments, membranes, satellite of points, clusters, and cluster of clusters. The thesis investigates methods for interacting with large scale data-sets represented as point clouds. The work mostly aims at the interactive visualization of cosmological simulation based on large particle systems. The study consists of three components: a) two human factors experiments into the perceptual factors that make it possible to see features in point clouds; b) the design and implementation of a user interface making it possible to rapidly navigate through and visualize features in the point cloud, c) software development and integration to support visualization

Interactive exploration of historic information via gesture recognition

Developers of interactive exhibits often struggle to �nd appropriate input devices that enable intuitive control, permitting the visitors to engage e�ectively with the content. Recently motion sensing input devices like the Microsoft Kinect or Panasonic D-Imager have become available enabling gesture based control of computer systems. These devices present an attractive input device for exhibits since the user can interact with their hands and they are not required to physically touch any part of the system. In this thesis we investigate techniques to enable the raw data coming from these types of devices to be used to control an interactive exhibit. Object recognition and tracking techniques are used to analyse the user's hand where movement and clicks are processed. To show the e�ectiveness of the techniques the gesture system is used to control an interactive system designed to inform the public about iconic buildings in the centre of Norwich, UK. We evaluate two methods of making selections in the test environment. At the time of experimentation the technologies were relatively new to the image processing environment. As a result of the research presented in this thesis, the techniques and methods used have been detailed and published [3] at the VSMM (Virtual Systems and Multimedia 2012) conference with the intention of further forwarding the area

Real-Time Markerless Tracking the Human Hands for 3D Interaction

This thesis presents methods for enabling suitable human computer interaction using only movements of the bare human hands in free space. This kind of interaction is natural and intuitive, particularly because actions familiar to our everyday life can be reflected. Furthermore, the input is contact-free which is of great advantage e.g. in medical applications due to hygiene factors. For enabling the translation of hand movements to control signals an automatic method for tracking the pose and/or posture of the hand is needed. In this context the simultaneous recognition of both hands is desirable to allow for more natural input. The first contribution of this thesis is a novel video-based method for real-time detection of the positions and orientations of both bare human hands in four different predefined postures, respectively. Based on such a system novel interaction interfaces can be developed. However, the design of such interfaces is a non-trivial task. Additionally, the development of novel interaction techniques is often mandatory in order to enable the design of efficient and easily operable interfaces. To this end, several novel interaction techniques are presented and investigated in this thesis, which solve existing problems and substantially improve the applicability of such a new device. These techniques are not restricted to this input instrument and can also be employed to improve the handling of other interaction devices. Finally, several new interaction interfaces are described and analyzed to demonstrate possible applications in specific interaction scenarios.Markerlose Verfolgung der menschlichen Hände in Echtzeit für 3D Interaktion In der vorliegenden Arbeit werden Verfahren dargestellt, die sinnvolle Mensch- Maschine-Interaktionen nur durch Bewegungen der bloßen Hände in freiem Raum ermöglichen. Solche "natürlichen" Interaktionen haben den besonderen Vorteil, dass alltägliche und vertraute Handlungen in die virtuelle Umgebung übertragen werden können. Außerdem werden auf diese Art berührungslose Eingaben ermöglicht, nützlich z.B. wegen hygienischer Aspekte im medizinischen Bereich. Um Handbewegungen in Steuersignale umsetzen zu können, ist zunächst ein automatisches Verfahren zur Erkennung der Lage und/oder der Art der mit der Hand gebildeten Geste notwendig. Dabei ist die gleichzeitige Erfassung beider Hände wünschenswert, um die Eingaben möglichst natürlich gestalten zu können. Der erste Beitrag dieser Arbeit besteht aus einer neuen videobasierten Methode zur unmittelbaren Erkennung der Positionen und Orientierungen beider Hände in jeweils vier verschiedenen, vordefinierten Gesten. Basierend auf einem solchen Verfahren können neuartige Interaktionsschnittstellen entwickelt werden. Allerdings ist die Ausgestaltung solcher Schnittstellen keinesfalls trivial. Im Gegenteil ist bei einer neuen Art der Interaktion meist sogar die Entwicklung neuer Interaktionstechniken erforderlich, damit überhaupt effiziente und gut bedienbare Schnittstellen konzipiert werden können. Aus diesem Grund wurden in dieser Arbeit einige neue Interaktionstechniken entwickelt und untersucht, die vorhandene Probleme beheben und die Anwendbarkeit eines solchen Eingabeinstruments für bestimmte Arten der Interaktion verbessern oder überhaupt erst ermöglichen. Diese Techniken sind nicht auf dieses Eingabeinstrument beschränkt und können durchaus auch die Handhabung anderer Eingabegeräte verbessern. Des Weiteren werden mehrere neue Interaktionsschnittstellen präsentiert, die den möglichen Einsatz bloßhändiger Interaktion in verschiedenen, typischen Anwendungsgebieten veranschaulichen

A large-scale three-dimensional imaging system based on laser speckle

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 61-62).by Michael Stephen Mermelstein.M.S