In this Summary the social-cognitive network science thrust and the HRI thrust are discussed within the sections below titled “Network Science Enterprise” and “Autonomous Systems,” respectively. Work performed in association with the other thrusts is discussed in this section.

In general, the strongest work in the area of sensory performance is the customer-driven evaluation of equipment. The overall research program in this area has lacked clear direction, although progress is visible. The group is not yet a force in basic or applied research on sensory performance. Recently, a restatement of this area’s vision has appeared under the rubric of “owning the environment.” Under that rubric, the emphasis is on the use of stealth and deception as force multipliers. That work is in an early stage and has not yet given rise to a program of research.

The research on physical and cognitive performance interaction is of generally high technical quality. Its scope has been somewhat limited. However, with the recent development of new facilities, this may be viewed as the start of a successful, coherent program of research. Biomechanics has long been at the core of HRED’s mission, and the directorate has developed a very strong set of facilities for studying soldier performance under various approximations of real-world situations. With these facilities, HRED has identified a niche that it is perhaps uniquely suited to study—the interaction of physical and cognitive stressors on performance.

Supported by a cadre of university experts in a Collaborative Technology Alliance (CTA), the ARL work in translational neuroscience is indicative of high-quality neuroscience research that is routinely validated by its publication in good, peer-reviewed journals. Over the past 5 years, ARL’s neuroscience group has grown into the DoD’s largest internal nonmedical translational neuroscience research effort, and it continues its trajectory toward being a neuroscience laboratory on par with strong university research programs. Work on detection and classification of artifacts in electroencephalogram (EEG) signals is noteworthy.

During the past 2 years, the social-cognitive network science group has worked to refine its vision and to align its work with the network science work in the Computational and Information Sciences Directorate (CISD). The overall quality of the research in this area is uneven. There is some fine work, but also much work that will have low impact, either because it is methodologically weak or because it does not appear to be part of a systematic program of work. Addressing the challenge of network science may be an opportunity to bring in staff with different backgrounds from those of current HRED staff.

HSI represents one of the core HRED competencies: providing the Army with assessments of how humans will work with new systems. Much of the work is very solid, high-quality human factors work, employing a range of tools, including the IMPRINT (Improved Performance Research Integration Tool) model of human performance. IMPRINT is the crown jewel of HRED’s HSI efforts. Its continued development and use represent a strength of the program. It is possible that there is a gap in IMPRINT in the form of inadequate coverage of cognition and perception. If so, given the nature of today’s Army tasks, this gap should be addressed. The use of HRED’s HSI expertise can also be seen in work such as that on progressive insertion of human figure modeling into the acquisition process.

Cases in which no previous research exists for providing a solution to a problem produce the opportunity for research. The HRED “opportunity-driven” research projects presented were generally of high quality. This nicely illustrates the ability of HRED to serve as a problem-solving resource across a wide range of Army problems. Whereas the HSI effort is targeted toward intervening early in the acquisition process, MANPRINT (Manpower and Personnel Integration; the Army’s program for considering manpower and personnel factors during acquisition) equipment design issues can be identified during usability testing or through reports received from the field. This may also be a place where scientific mentoring by senior researchers would be helpful. The data being gathered by the opportunity-driven research represents an opportunity to close the loop between basic and applied research and soldier

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