All Projects

Displaying 1 to 10 (out of 84)

	Copernicus: Automating Emergence Detection IARPAÂs Foresight and Understanding from Scientific Exposition (FUSE) Program seeks to develop automated methods that aid in the systematic, continuous, and comprehensive assessment of technical emergence using publicly available information found in published scientific, technical and patent literature. SRIÂs team uses a theory-directed extension of best-of-breed language and network modeling techniques to produce the Copernicus system. SRIÂs CSTED leads the theory of emergence task.
	DoVETAIL: Domain Vocabulary Extraction and Transduction, and Auto-Induction of Layout The ability to quickly produce actionable intelligence from unanticipated, multiple, varied data sets require research advances in two key areas: (1) alignment of data models; and (2) advanced analytic algorithms. Making advances in these two research areas, and fully characterizing the performance of the research results, is the focus of this project, which is part of the IARPA Knowledge Discovery and Dissemination (KDD) Program.
	Multi-Threaded Missions and Means Framework This project explores the utilization of a multiagent modeling and simulation environment where multiple military domains or threads (e.g. Logistics, Transportation, Combat Operations, Intelligence, Engineering) can be described in terms of tasking and capabilities and their mission interactions simulated over some mission scenario time horizon.
	Intelligent Question Answering in the HIV Domain Natural language technology and deductive inference are applied to allow a researcher to access online HIV databases through English queries.
	Behavioral Probes Activity Recognition in outdoor settings.
	TransPAL: Transitioning PAL Technologies The TransPAL project is transitioning a number of technologies developed on the DARPA PAL program for use by various members of the Armed Services.
	FAUST (Flexible Acquisition and Understanding System for Text) SRI is developing an automated reading system that makes the information in text accessible to a range of formal reasoning systems.
	Bootstrapped Learning Currently, fielded software systems can only be modified by sending them "back to the shop" for expensive, time-consuming reprogramming. The goal of Bootstrapped Learning is to let end users rapidly modify system by instructing them in correct behavior, similar to how they would teach a person.
	Leaving Flatland: Fast Autonomous Navigation For UGVs in Challenging Terrain We envision a new research program on autonomous modeling and navigation, with the goal of enabling small unmanned ground vehicles (UGVs) to move alongside their human counterparts through virtually any environment. Such UGVs will operate indoor and outdoor, with no distinction, and at a speed compatible with human motion. This is a joint project with Stanford University and Boston Dynamics.
	Karto Development The Karto^TM SDK leverages three decades of leading edge research by SRI International to provide high accuracy navigation, mapping, and exploration functionality across a broad range of mobile robot platforms.

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