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Mission Control Technology Infusion

Carnegie Mellon University

Alonso Vera (ARC/THI)



Abstract


MER Operations Human factors design depends on accurate models of human task performance, but development of task models is time-consuming and requires special expertise. This research task will develop user-friendly extension of the Apex human-system modeling framework for designing efficient and easy-to-use control systems and data-entry interfaces. Apex is descended from the popular GOMS modeling system, with inclusion of reactive planning. It can represent complex expert performance and can also serve as an intelligent control system.


Task Description


Objective:

This research task, in collaboration with JPL mission system engineers, will demonstrate a range of human-computer interaction models for future NASA mission control centers. CPM-X rapid mathematical analysis of human-computer interaction will provide fast and inexpensive modeling of different levels of expertise or stages of procedural learning by humans, leading to conjoint design and analysis of interfaces and procedures. The task will also provide research on knowledge acquisition and management in the Mars Exploration Rovers (MER) mission.


Applications:

MER operations studies; design of NASA mission control center interfaces and procedures; support for MSL and other missions.


NASA Benefit:

Initial Apex-GOMS extensions produced rapid task-level modeling of human-machine interaction, on the order of 50 times faster than previous methodologies. New work with CPM-X offers even better modeling of human learning and performance for complex tasks, and will aid design of human-friendly interfaces and procedures. Work with JPL is leading toward "control center of the future" concepts, and earth-based demonstrations of Ground Data System (GDS) concepts will be relevant to NASA's new initiative in lunar/planetary exploration.


Keywords:

task learning cognitive modeling, interface procedure design, mission control, HCI, Apex, CPM-X



Research Plan


Prior Technology:

Rules of thumb; design reuse; simulations; field tests.


FY04 Milestone:

CPM-X learning; MER studies; control center concepts



Progress


FY04 Quadchart Slide:

HCC_PGM_Vera_MsnCtl.ppt.


Accomplishments:

Apex-GOMS extensions; rapid task-level modeling of human interaction; MER technology innovations; CPM-X modeling framework.



For More Information


Contacts:

Alonso H. Vera (PI), Ames Research Center (Code THI).



Intelligent Systems | Human-Centered Computing | Decision Systems
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