Smart augmented reality instructional system for mechanical assembly

Quality and efficiency are pivotal indicators of a manufacturing company. Many companies are suffering from shortage of experienced workers across the production line to perform complex assembly tasks such as assembly of an aircraft engine. This could lead to a significant financial loss. In order to further reduce time and error in an assembly, a smart system consisting of multi-modal Augmented Reality (AR) instructions with the support of a deep learning network for tool detection is introduced. The multi-modal smart AR is designed to provide on-site information including various visual renderings with a fine-tuned Region-based Convolutional Neural Network, which is trained on a synthetic tool dataset. The dataset is generated using CAD models of tools augmented onto a 2D scene without the need of manually preparing real tool images. By implementing the system to mechanical assembly of a CNC carving machine, the result has shown that the system is not only able to correctly classify and localize the physical tools but also enables workers to successfully complete the given assembly tasks. With the proposed approaches, an efficiently customizable smart AR instructional system capable of sensing, characterizing the requirements, and enhancing worker\u27s performance effectively has been built and demonstrated --Abstract, page iii

Tangible user interfaces : past, present and future directions

In the last two decades, Tangible User Interfaces (TUIs) have emerged as a new interface type that interlinks the digital and physical worlds. Drawing upon users' knowledge and skills of interaction with the real non-digital world, TUIs show a potential to enhance the way in which people interact with and leverage digital information. However, TUI research is still in its infancy and extensive research is required in or- der to fully understand the implications of tangible user interfaces, to develop technologies that further bridge the digital and the physical, and to guide TUI design with empirical knowledge. This paper examines the existing body of work on Tangible User In- terfaces. We start by sketching the history of tangible user interfaces, examining the intellectual origins of this field. We then present TUIs in a broader context, survey application domains, and review frame- works and taxonomies. We also discuss conceptual foundations of TUIs including perspectives from cognitive sciences, phycology, and philoso- phy. Methods and technologies for designing, building, and evaluating TUIs are also addressed. Finally, we discuss the strengths and limita- tions of TUIs and chart directions for future research

An Intelligent Robot and Augmented Reality Instruction System

Human-Centered Robotics (HCR) is a research area that focuses on how robots can empower people to live safer, simpler, and more independent lives. In this dissertation, I present a combination of two technologies to deliver human-centric solutions to an important population. The first nascent area that I investigate is the creation of an Intelligent Robot Instructor (IRI) as a learning and instruction tool for human pupils. The second technology is the use of augmented reality (AR) to create an Augmented Reality Instruction (ARI) system to provide instruction via a wearable interface. To function in an intelligent and context-aware manner, both systems require the ability to reason about their perception of the environment and make appropriate decisions. In this work, I construct a novel formulation of several education methodologies, particularly those known as response prompting, as part of a cognitive framework to create a system for intelligent instruction, and compare these methodologies in the context of intelligent decision making using both technologies. The IRI system is demonstrated through experiments with a humanoid robot that uses object recognition and localization for perception and interacts with students through speech, gestures, and object interaction. The ARI system uses augmented reality, computer vision, and machine learning methods to create an intelligent, contextually aware instructional system. By using AR to teach prerequisite skills that lend themselves well to visual, augmented reality instruction prior to a robot instructor teaching skills that lend themselves to embodied interaction, I am able to demonstrate the potential of each system independently as well as in combination to facilitate students\u27 learning. I identify people with intellectual and developmental disabilities (I/DD) as a particularly significant use case and show that IRI and ARI systems can help fulfill the compelling need to develop tools and strategies for people with I/DD. I present results that demonstrate both systems can be used independently by students with I/DD to quickly and easily acquire the skills required for performance of relevant vocational tasks. This is the first successful real-world application of response-prompting for decision making in a robotic and augmented reality intelligent instruction system

Precise localization for aerial inspection using augmented reality markers

The final publication is available at link.springer.comThis chapter is devoted to explaining a method for precise localization using augmented reality markers. This method can achieve precision of less of 5 mm in position at a distance of 0.7 m, using a visual mark of 17 mm × 17 mm, and it can be used by controller when the aerial robot is doing a manipulation task. The localization method is based on optimizing the alignment of deformable contours from textureless images working from the raw vertexes of the observed contour. The algorithm optimizes the alignment of the XOR area computed by means of computer graphics clipping techniques. The method can run at 25 frames per second.Peer ReviewedPostprint (author's final draft

Task support system by displaying instructional video onto AR workspace

This paper presents an instructional support system based on aug-mented reality (AR). This system helps a user to work intuitively by overlaying visual information in the same way of a navigation system. In usual AR systems, the contents to be overlaid onto real space are created with 3D Computer Graphics. In most cases, such contents are newly created according to applications. However, there are many 2D videos that show how to take apart or build elec-tric appliances and PCs, how to cook, etc. Therefore, our system employs such existing 2D videos as instructional videos. By trans-forming an instructional video to display, according to the user’s view, and by overlaying the video onto the user’s view space, the proposed system intuitively provides the user with visual guidance. In order to avoid the problem that the display of the instructional video and the user’s view may be visually confused, we add var-ious visual effects to the instructional video, such as transparency and enhancement of contours. By dividing the instructional video into sections according to the operations to be carried out in order to complete a certain task, we ensure that the user can interactively move to the next step in the instructional video after a certain op-eration is completed. Therefore, the user can carry on with the task at his/her own pace. In the usability test, users evaluated the use of the instructional video in our system through two tasks: a task involving building blocks and an origami task. As a result, we found that a user’s visibility improves when the instructional video is transformed to display according to his/her view. Further, for the evaluation of visual effects, we can classify these effects according to the task and obtain the guideline for the use of our system as an instructional support system for performing various other tasks

Assembly Guidance in Augmented Reality Environments Using a Virtual Interactive Tool

The application of augmented reality (AR) technology for assembly guidance is a novel approach in the traditional manufacturing domain. In this paper, we propose an AR approach for assembly guidance using a virtual interactive tool that is intuitive and easy to use. The virtual interactive tool, termed the Virtual Interaction Panel (VirIP), involves two tasks: the design of the VirIPs and the real-time tracking of an interaction pen using a Restricted Coulomb Energy (RCE) neural network. The VirIP includes virtual buttons, which have meaningful assembly information that can be activated by an interaction pen during the assembly process. A visual assembly tree structure (VATS) is used for information management and assembly instructions retrieval in this AR environment. VATS is a hierarchical tree structure that can be easily maintained via a visual interface. This paper describes a typical scenario for assembly guidance using VirIP and VATS. The main characteristic of the proposed AR system is the intuitive way in which an assembly operator can easily step through a pre-defined assembly plan/sequence without the need of any sensor schemes or markers attached on the assembly components.Singapore-MIT Alliance (SMA