Objective: Assistive technology for cognition (ATC) is reviewed and 2 case studies presented. Participants: Study 1, a 19-year-old man, with topographical disorientation after traumatic brain injury (TBI); Study 2, a 71-year-old woman with cognitive declines associated with TBI and a pre-injury history of chronic ischemic changes. Design and Interventions: To assess ATC intervention, Study 1 used an ABAЈ design for a navigation task; Study 2 used a modified ABAB design for setting an alarm clock. Main Outcome Measures: Study 1, average errors per route; Study 2, average errors per task substep and number of substeps attempted. Results: For Study 1, navigation errors reduced with ATC; without ATC, partial improvement was maintained, with greater intertrial variability. For Study 2, performance errors reduced with ATC and all substeps were completed; without ATC, errors persisted, but declined across trials, suggesting learning. Conclusions: ATC interventions can facilitate functional performance and contribute to learning of specific adaptive skills. Wireless, interactive, Web-based interventions appear particularly suited to tasks in the home and community, permitting remote intervention and monitoring of task status.
Since 2004, NASA has been working to return to the Moon. In contrast to the Apollo missions, two key objectives of the current exploration program is to establish significant infrastructure and an outpost. Achieving these objectives will enable long-duration stays and long-distance exploration of the Moon. To do this, robotic systems will be needed to perform tasks which cannot, or should not, be performed by crew alone. In this paper, we summarize our work to develop "utility robots" for lunar surface operations, present results and lessons learned from field testing, and discuss directions for future research.
Future manned space operations will include a greater use of automation than we currently see. 1 For example, semiautonomous robots and software agents will perform difficult tasks while operating unattended most of the time. As these automated agents become more prevalent, human contact with them will occur more often and become more routine, so designing these automated agents according to the principles of human-centered computing is important.In this article, we describe two cases of semiautonomous control software developed and fielded in test environments at the NASA Johnson Space Center. This software operated continuously at the JSC and interacted closely with humans for months at a time. Our approachFor the past seven years, we've worked on developing intelligent software for the control of advanced life support systems. We fielded this control software in an operational environment in which test engineers manually controlled and continuously monitored all life support systems from a console in a test control room. Such operations required the engineers to spend considerable time on routine data monitoring and lowlevel commanding. Our biggest challenges initially were to prove that automated control software was reliable enough to be useful and that automating routine control tasks would be worthwhile.Thus, from the beginning, we had the goal of using automation to reduce the engineer's workload. However, our objective was not to replace humans in operations but to free them from routine tasks (such as vigilant monitoring), thereby enabling them to concentrate on activities that capitalize on human strengths (such as supervisory monitoring). To perform these new tasks, humans still must interact with the control automation. In fact, human interaction becomes more challenging because the human is less involved in routine day-to-day operations and, as a result, might be less aware of the ongoing control situation and could lose anomaly response skills through lack of practice. This is a critical consideration for the human centering of semi-autonomous control systems.We also recognized that the change in test operations resulting from the use of automated control would be fundamental. The human role changes to one of supervisory monitoring with occasional intervention when operations cannot be automated or when exceptional situations occur. During normal operations, engineers supporting these tests will spend most of their time doing activities unrelated to control but will need to be on call should the automation or life support hardware experience problems. In addition, humans will need to supervise and command these continuously operating systems from remote locations (such as their offices) with only infrequent (and possibly asynchronous) interaction. For such operations, human supervisors must be able to quickly form an integrated view of distributed control without having to continuously monitor control data.This concept of test operations, however, represented too radical a change to be quickly acc...
Robotic reconnaissance ("recon") has the potential to significantly improve scientific and technical return from lunar surface exploration. In particular, robotic recon can be used to improve traverse planning, reduce operational risk, and increase crew productivity. To study how robotic recon can benefit human exploration, we recently conducted a field experiment at Black Point Lava Flow (BPLF), Arizona. In our experiment, a simulated ground control team at NASA Ames teleoperated a planetary rover to scout geology traverses at BPLF. The recon data was then used to plan revised traverses. Two-man crews subsequently performed both types of traverses using the NASA "Lunar Electric Rover" (LER) and simulated extra-vehicular activity (EVA) suits. This paper describes the design of our experiment, presents our preliminary results and discusses directions for future research.
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