Augmented reality device for first response scenarios

A prototype of a wearable computer system is proposed and implemented using commercial off-shelf components. The system is designed to allow the user to access location-specific information about an environment, and to provide capability for user tracking. Areas of applicability include primarily first response scenarios, with possible applications in maintenance or construction of buildings and other structures. Necessary preparation of the target environment prior to system\u27s deployment is limited to noninvasive labeling using optical fiducial markers. The system relies on computational vision methods for registration of labels and user position. With the system the user has access to on-demand information relevant to a particular real-world location. Team collaboration is assisted by user tracking and real-time visualizations of team member positions within the environment. The user interface and display methods are inspired by Augmented Reality1 (AR) techniques, incorporating a video-see-through Head Mounted Display (HMD) and fingerbending sensor glove.*. 1Augmented reality (AR) is a field of computer research which deals with the combination of real world and computer generated data. At present, most AR research is concerned with the use of live video imagery which is digitally processed and augmented by the addition of computer generated graphics. Advanced research includes the use of motion tracking data, fiducial marker recognition using machine vision, and the construction of controlled environments containing any number of sensors and actuators. (Source: Wikipedia) *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation). The CD requires the following system requirements: Adobe Acrobat; Microsoft Office; Windows MediaPlayer or RealPlayer

Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

Tactile Arrays for Virtual Textures

This thesis describes the development of three new tactile stimulators for active touch, i.e. devices to deliver virtual touch stimuli to the fingertip in response to exploratory movements by the user. All three stimulators are designed to provide spatiotemporal patterns of mechanical input to the skin via an array of contactors, each under individual computer control. Drive mechanisms are based on piezoelectric bimorphs in a cantilever geometry. The first of these is a 25-contactor array (5 × 5 contactors at 2 mm spacing). It is a rugged design with a compact drive system and is capable of producing strong stimuli when running from low voltage supplies. Combined with a PC mouse, it can be used for active exploration tasks. Pilot studies were performed which demonstrated that subjects could successfully use the device for discrimination of line orientation, simple shape identification and line following tasks. A 24-contactor stimulator (6 × 4 contactors at 2 mm spacing) with improved bandwidth was then developed. This features control electronics designed to transmit arbitrary waveforms to each channel (generated on-the-fly, in real time) and software for rapid development of experiments. It is built around a graphics tablet, giving high precision position capability over a large 2D workspace. Experiments using two-component stimuli (components at 40 Hz and 320 Hz) indicate that spectral balance within active stimuli is discriminable independent of overall intensity, and that the spatial variation (texture) within the target is easier to detect at 320 Hz that at 40 Hz. The third system developed (again 6 × 4 contactors at 2 mm spacing) was a lightweight modular stimulator developed for fingertip and thumb grasping tasks; furthermore it was integrated with force-feedback on each digit and a complex graphical display, forming a multi-modal Virtual Reality device for the display of virtual textiles. It is capable of broadband stimulation with real-time generated outputs derived from a physical model of the fabric surface. In an evaluation study, virtual textiles generated from physical measurements of real textiles were ranked in categories reflecting key mechanical and textural properties. The results were compared with a similar study performed on the real fabrics from which the virtual textiles had been derived. There was good agreement between the ratings of the virtual textiles and the real textiles, indicating that the virtual textiles are a good representation of the real textiles and that the system is delivering appropriate cues to the user

Visual Representation Learning with Minimal Supervision

Computer vision intends to provide the human abilities of understanding and interpreting the visual surroundings to computers. An essential element to comprehend the environment is to extract relevant information from complex visual data so that the desired task can be solved. For instance, to distinguish cats from dogs the feature 'body shape' is more relevant than 'eye color' or the 'amount of legs'. In traditional computer vision it is conventional to develop handcrafted functions that extract specific low-level features such as edges from visual data. However, in order to solve a particular task satisfactorily we require a combination of several features. Thus, the approach of traditional computer vision has the disadvantage that whenever a new task is addressed, a developer needs to manually specify all the features the computer should look for. For that reason, recent works have primarily focused on developing new algorithms that teach the computer to autonomously detect relevant and task-specific features. Deep learning has been particularly successful for that matter. In deep learning, artificial neural networks automatically learn to extract informative features directly from visual data. The majority of developed deep learning strategies require a dataset with annotations which indicate the solution of the desired task. The main bottleneck is that creating such a dataset is very tedious and time-intensive considering that every sample needs to be annotated manually. This thesis presents new techniques that attempt to keep the amount of human supervision to a minimum while still reaching satisfactory performances on various visual understanding tasks. In particular, this thesis focuses on self-supervised learning algorithms that train a neural network on a surrogate task where no human supervision is required. We create an artificial supervisory signal by breaking the order of visual patterns and asking the network to recover the original structure. Besides demonstrating the abilities of our model on common computer vision tasks such as action recognition, we additionally apply our model to biomedical scenarios. Many research projects in medicine involve profuse manual processes that extend the duration of developing successful treatments. Taking the example of analyzing the motor function of neurologically impaired patients we show that our self-supervised method can help to automate tedious, visually based processes in medical research. In order to perform a detailed analysis of motor behavior and, thus, provide a suitable treatment, it is important to discover and identify the negatively affected movements. Therefore, we propose a magnification tool that can detect and enhance subtle changes in motor function including motor behavior differences across individuals. In this way, our automatic diagnostic system does not only analyze apparent behavior but also facilitates the perception and discovery of impaired movements. Learning a feature representation without requiring annotations significantly reduces human supervision. However, using annotated dataset leads generally to better performances in contrast to self-supervised learning methods. Hence, we additionally examine semi-supervised approaches which efficiently combine few annotated samples with large unlabeled datasets. Consequently, semi-supervised learning represents a good trade-off between annotation time and accuracy

Engineering data compendium. Human perception and performance. User's guide

The concept underlying the Engineering Data Compendium was the product of a research and development program (Integrated Perceptual Information for Designers project) aimed at facilitating the application of basic research findings in human performance to the design and military crew systems. The principal objective was to develop a workable strategy for: (1) identifying and distilling information of potential value to system design from the existing research literature, and (2) presenting this technical information in a way that would aid its accessibility, interpretability, and applicability by systems designers. The present four volumes of the Engineering Data Compendium represent the first implementation of this strategy. This is the first volume, the User's Guide, containing a description of the program and instructions for its use

The Capture of Spring: Hooke’s “Vibrative Pulse Communicated”

In 1678, Robert Hooke published a treatise on his metaphysics of vibration. Lectures de Potentia Restitutiva or Of Spring contains not only experimental and geometrical demonstrations of the spring law (which mutated into Hooke’s law after his time), but also a principle at the heart of his dynamic matter theory – Congruity and Incongruity. Namely, that harmonious and discordant forces unify, shape and separate vibrating matter. This thesis reconstructs Hooke’s production of congruity and incongruity, and the spring law, analysing the inversions, reversals and paradoxes moulding his knowledge-making practices. I argue that artificial instruments and apparatuses capable of magnifying and measuring never-before-seen minute bodies and motions also made the creation of a novel geometry necessary. I attempt to show how Hooke addressed these challenges by reassessing and reconfiguring the role of traditional Euclidean geometry, and reformulating practical-geometrical definitions to create a geometry that could demonstrate the spring law. Specifically, I focus on Hooke’s studies of vibrating bodies and vibrations, and his practical geometry. By investigating Hooke’s studies within the context of his matter theory, I show that, in an epistemological inversion, Hooke used optical instruments to shift frames of reference from the microscopic to the celestial and vice versa for his knowledge production. Further, Hooke’s work is a cohesive whole centred on his studies of the similitudes between vibrating phenomena. Finally, his knowledge-making practices are a conflation of his predominant careers as an experimentalist and geometer. By constructing natural laws from physical reality, thereby implying that nature, artificial instruments, and laws such as the spring law are related, Hooke legitimised the application of instruments and mathematics to the study of nature. This process was far from straightforward or self-evident

Intelligent gripper design and application for automated part recognition and gripping

Intelligent gripping may be achieved through gripper design, automated part recognition, intelligent algorithm for control of the gripper, and on-line decision-making based on sensory data. A generic framework which integrates sensory data, part recognition, decision-making and gripper control to achieve intelligent gripping based on ABB industrial robot is constructed. The three-fingered gripper actuated by a linear servo actuator designed and developed in this project for precise speed and position control is capable of handling a large variety of objects. Generic algorithms for intelligent part recognition are developed. Edge vector representation is discussed. Object geometric features are extracted. Fuzzy logic is successfully utilized to enhance the intelligence of the system. The generic fuzzy logic algorithm, which may also find application in other fields, is presented. Model-based gripping planning algorithm which is capable of extracting object grasp features from its geometric features and reasoning out grasp model for objects with different geometry is proposed. Manipulator trajectory planning solves the problem of generating robot programs automatically. Object-oriented programming technique based on Visual C++ MFC is used to constitute the system software so as to ensure the compatibility, expandability and modular programming design. Hierarchical architecture for intelligent gripping is discussed, which partitions the robot’s functionalities into high-level (modeling, recognizing, planning and perception) layers, and low-level (sensing, interfacing and execute) layers. Individual system modules are integrated seamlessly to constitute the intelligent gripping system