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Past Projects

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CBMEN

Content-Based Mobile Edge Networking

The CBMEN program seeks to develop the network services and transport architectures to enable efficient, transparent distribution of content in mobile ad hoc network environments.

Copernicus

Copernicus: Automating Emergence Detection

IARPA’s 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. SRI’s team uses a theory-directed extension of best-of-breed language and network modeling techniques to produce the Copernicus system. SRI’s CSTED leads the theory of emergence task.

MTMMF

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.

Quadri

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.

probes

Behavioral Probes

Activity Recognition in outdoor settings.

TransPAL

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

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.

BL

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

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

Karto Development

The KartoTM 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.

This website does not contain information on all of our past or present projects.
For further information please contact us.

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