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The project goal was to design and study engaging and effective augmented reality learning environments using wireless handheld computers equipped with global positioning system (GPS) receivers.
This project will leverage existing capabilities of an augmented reality (AR) sensorimotor assessment tool. Currently, the tool mimics the capabilities of validated 2-dimensional (2D) assessments. While this modality is well-aligned with seated interactions with flight-deck displays, extravehicular activity (EVA) tasks will require full body mobility wherein astronauts reach and bend in a 3-dimensional (3D) space. These types of motions, naturally including head movements, are known to elicit experiences of disorientation. Thus, sensorimotor assessments that include these stimulations and larger movements are important for understanding astronaut readiness prior to initial EVAs. The proposed effort will extend the current 2D eye-hand coordination task in AR to a 3D task designed to evaluate dynamic balance and eye-hand-body coordination. The new module will extend the range of motion and interaction space such that it better aligns with operational task needs for astronaut readiness evaluation.
Initiated in January, 1997, under NASA's Office of Life and Microgravity Sciences and Applications, the Wireless Augmented Reality Prototype (WARP) is a means to leverage recent advances in communications, displays, imaging sensors, biosensors, voice recognition and microelectronics to develop a hands-free, tetherless system capable of real-time personal display and control of computer system resources. Using WARP, an astronaut may efficiently operate and monitor any computer-controllable activity inside or outside the vehicle or station. The WARP concept is a lightweight, unobtrusive heads-up display with a wireless wearable control unit. Connectivity to the external system is achieved through a high-rate radio link from the WARP personal unit to a base station unit installed into any system PC. The radio link has been specially engineered to operate within the high- interference, high-multipath environment of a space shuttle or space station module. Through this virtual terminal, the astronaut will be able to view and manipulate imagery, text or video, using voice commands to control the terminal operations. WARP's hands-free access to computer-based instruction texts, diagrams and checklists replaces juggling manuals and clipboards, and tetherless computer system access allows free motion throughout a cabin while monitoring and operating equipment.
NASA proposed requirements for a digital display for an EVA spacesuit to provide relevant information to the crew member. The Joint Augmented Reality Visual Informatics System (Joint AR) project pursued four years of research and development towards a suit-display system in a near-eye, AR form factor. The project was responsible for developing software (custom graphics engine and core flight software), physical hardware prototyping (controls, projection display optics, suited display platform), virtual prototyping platform (a virtual reality testbed), and human-in-the-loop (HITL) operational testing informed by EVA flight controllers, crew members, and human factors engineers for con-ops definition. This document contains substantial updates to CTSD-ADV-1788 Rev. Basic. This revision was produced by the project to summarize the use-cases and and user experiences developed throughout the project, and refine the Basic revision originally drafted at the beginning of the project life cycle. The primary purpose of this document is to summarize and make available the scenario development efforts that have been pursued and explored within the Joint AR project. This includes descriptions of the scenarios themselves as well as corresponding potential of advanced informatics displays to support those specified scenarios. In doing so, this document provides a variety of approaches to deconstruct and hypothesize how future technological capabilities so that with future EVA work demands can be satisfied within future human planetary spaceflight missions.
The Spacecraft 3D application allows users to learn about and interact with iconic NASA missions in a new and immersive way using common mobile devices. Using Augmented Reality (AR) techniques to project 3D renditions of the mission spacecraft into real-world surroundings, users can interact with and learn about Curiosity, GRAIL, Cassini, and Voyager. Additional updates on future missions, animations, and information will be ongoing. Using a printed AR Target and camera on a mobile device, users can get up close with these robotic explorers, see how some move, and learn about these engineering feats, which are used to expand knowledge and understanding about space. The software receives input from the mobile device's camera to recognize the presence of an AR marker in the camera's field of view. It then displays a 3D rendition of the selected spacecraft in the user's physical surroundings, on the mobile device's screen, while it tracks the device's movement in relation to the physical position of the spacecraft's 3D image on the AR marker.
Firefighters suffer a variety of life-threatening risks, including line-of-duty deaths, injuries, and exposures to hazardous substances. Support for reducing these risks is important. We built a partially occluded object reconstruction method on augmented reality glasses for first responders. We used a deep learning based on conditional generative adversarial networks to train associations between the various images of flammable and hazardous objects and their partially occluded counterparts. Our system then reconstructed an image of a new flammable object. Finally, the reconstructed image was superimposed on the input image to provide "transparency". The system imitates human learning about the laws of physics through experience by learning the shape of flammable objects and the flame characteristics.
Fireballs in the Sky is an innovative Australian citizen science program that connects the public with the research of the Desert Fireball Network (DFN). This research aims to understand the early workings of the solar system, and Fireballs in the Sky invites people around the world to learn about this science, contributing fireball sightings via a user-friendly augmented reality mobile app. Tens of thousands of people have downloaded the app world-wide and participated in the science of meteoritics. The Fireballs in the Sky app allows users to get involved with the Desert Fireball Network research, supplementing DFN observations and providing enhanced coverage by reporting their own meteor sightings to DFN scientists. Fireballs in the Sky reports are used to track the trajectories of meteors - from their orbit in space to where they might have landed on Earth. Led by Phil Bland at Curtin University in Australia, the Desert Fireball Network (DFN) uses automated observatories across Australia to triangulate trajectories of meteorites entering the atmosphere, determine pre-entry orbits, and pinpoint their fall positions. Each observatory is an autonomous intelligent imaging system, taking 1000 by 36 megapixel all-sky images throughout the night, using neural network algorithms to recognize events. They are capable of operating for 12 months in a harsh environment, and store all imagery collected. We developed a completely automated software pipeline for data reduction, and built a supercomputer database for storage, allowing us to process our entire archive. The DFN currently stands at 50 stations distributed across the Australian continent, covering an area of 2.5 million square kilometers. Working with DFN's partners at NASA's Solar System Exploration Research Virtual Institute, the team is expanding the network beyond Australia to locations around the world. Fireballs in the Sky allows a growing public base to learn about and participate in this exciting research.
One of the major challenges in deep learning is retrieving sufficiently large labeled training datasets, which can become expensive and time consuming to collect. A unique approach to training segmentation is to use Deep Neural Network (DNN) models with a minimal amount of initial labeled training samples. The procedure involves creating synthetic data and using image registration to calculate affine transformations to apply to the synthetic data. The method takes a small dataset and generates a highquality augmented reality synthetic dataset with strong variance while maintaining consistency with real cases. Results illustrate segmentation improvements in various target features and increased average target confidence.
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The Special Purpose Dexterous Manipulator (SPDM) is a two-armed robot that functions as an extension to the end effector of the Space Station Robotics Manipulator System (SSRMS), currently in use on the International Space Station (ISS). Crew training for the SPDM is accomplished using a robotic hardware simulator, which performs most of SPDM functions under normal static Earth gravitational forces. Both the simulator and SPDM are controlled from a standard robotic workstation using a laptop for the user interface and three monitors for camera views. Most operations anticipated for the SPDM involve the manipulation, insertion, and removal of any of several types of Orbital Replaceable Unit (ORU), modules which control various ISS functions. Alignment tolerances for insertion of the ORU into its receptacle are 0.25 inch and 0.5 degree from nominal values. The pre-insertion alignment task must be performed within these tolerances by using available video camera views of the intrinsic features of the ORU and receptacle, without special registration markings. Since optimum camera views may not be available, and dynamic orbital lighting conditions may limit periods of viewing, a successful ORU insertion operation may require an extended period of time. This study explored the feasibility of using augmented reality (AR) to assist SPDM operations. Geometric graphical symbols were overlaid on one of the workstation monitors to afford cues to assist the operator in attaining adequate pre-insertion ORU alignment. Twelve skilled subjects performed eight ORU insertion tasks using the simulator with and without the AR symbols in a repeated measures experimental design. Results indicated that using the AR symbols reduced pre-insertion alignment error for all subjects and reduced the time to complete pre-insertion alignment for most subjects.
One of the most versatile tools designed for use on the International Space Station (ISS) is the Special Purpose Dexterous Manipulator (SPDM) robot. Operators for this system are trained at NASA Johnson Space Center (JSC) using a robotic simulator, the Dexterous Manipulator Trainer (DMT), which performs most SPDM functions under normal static Earth gravitational forces. The SPDM is controlled from a standard Robotic Workstation. A key feature of the SPDM and DMT is the Force/Moment Accommodation (FMA) system, which limits the contact forces and moments acting on the robot components, on its payload, an Orbital Replaceable Unit (ORU), and on the receptacle for the ORU. The FMA system helps to automatically alleviate any binding of the ORU as it is inserted or withdrawn from a receptacle, but it is limited in its correction capability. A successful ORU insertion generally requires that the reference axes of the ORU and receptacle be aligned to within approximately 0.25 inch and 0.5 degree of nominal values. The only guides available for the operator to achieve these alignment tolerances are views from any available video cameras. No special registration markings are provided on the ORU or receptacle, so the operator must use their intrinsic features in the video display to perform the pre-insertion alignment task. Since optimum camera views may not be available, and dynamic orbital lighting conditions may limit viewing periods, long times are anticipated for performing some ORU insertion or extraction operations. This study explored the feasibility of using augmented reality (AR) to assist with SPDM operations. Geometric graphical symbols were overlaid on the end effector (EE) camera view to afford cues to assist the operator in attaining adequate pre-insertion ORU alignment.
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The system of the present invention is a highly integrated radio communication system with a multimedia co-processor which allows true two-way multimedia (video, audio, data) access as well as real-time biomedical monitoring in a pager-sized portable access unit. The system is integrated in a network structure including one or more general purpose nodes for providing a wireless-to-wired interface. The network architecture allows video, audio and data (including biomedical data) streams to be connected directly to external users and devices. The portable access units may also be mated to various non-personal devices such as cameras or environmental sensors for providing a method for setting up wireless sensor nets from which reported data may be accessed through the portable access unit. The reported data may alternatively be automatically logged at a remote computer for access and viewing through a portable access unit, including the user's own.