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Author

Jake Hochstadt

Bio: Jake Hochstadt is an academic researcher from Kennedy Space Center. The author has contributed to research in topics: Wearable computer. The author has an hindex of 1, co-authored 2 publications receiving 1 citations.

Papers
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Proceedings ArticleDOI
12 Sep 2017
TL;DR: The Integrated Display and Environmental Awareness System (IDEAS) as mentioned in this paper is an interdisciplinary team project focusing on the development of a wearable computer and head mounted display (HMD) based on Commercial-Off-The-Shelf (COTS) components for the specific application and needs of NASA technicians, engineers and astronauts.
Abstract: The Integrated Display and Environmental Awareness System (IDEAS) is an interdisciplinary team project focusing on the development of a wearable computer and Head Mounted Display (HMD) based on Commercial-Off-The-Shelf (COTS) components for the specific application and needs of NASA technicians, engineers and astronauts. Wearable computers are on the verge of utilization trials in daily life as well as industrial environments. The first civil and COTS wearable head mounted display systems were introduced just a few years ago and they probed not only technology readiness in terms of performance, endurance, miniaturization, operability and usefulness but also maturity of practice in perspective of a socio-technical context. Although the main technical hurdles such as mass and power were addressed as improvements on the technical side, the usefulness, practicality and social acceptance were often noted on the side of a broad variety of humans' operations. In other words, although the technology made a giant leap, its use and efficiency still looks for the sweet spot. The first IDEAS project started in January 2015 and was concluded in January 2017. The project identified current COTS systems' capability at minimum cost and maximum applicability and brought about important strategic concepts that will serve further IDEAS-like system development.

2 citations


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Proceedings ArticleDOI
20 May 2019
TL;DR: This paper presents a novel method by which an assistive aerial robot can learn the relevant camera views within a task domain through tracking the head motions of a human collaborator.
Abstract: This paper presents a novel method by which an assistive aerial robot can learn the relevant camera views within a task domain through tracking the head motions of a human collaborator. The human’s visual field is modeled as an anisotropic spherical sensor, which decays in acuity towards the periphery, and is integrated in time throughout the domain. This data is resampled and fed into an expectation maximization solver in order to estimate the environment’s visual interest as a mixture of Gaussians. A dynamic coverage control law directs the robot to capture camera views of the peaks of these Gaussians which is broadcast to an augmented reality display worn by the human operator. An experimental study is presented that assesses the influence of the assitive robot on reflex time, head motion, and task completion time.

8 citations

Journal ArticleDOI
TL;DR: A novel method by which an aerial robot can learn sequences of task-relevant camera views within a multitasking environment by tracking the visual gaze of a human collaborator wearing an augmented reality headset is presented.