Data Integration across Distributed Autonomous Sensor Platforms (DIDASP) Navy SBIR FY2009.1 Sol No.: Navy SBIR FY2009.1 Topic No.: N091-068 Topic Title: Data Integration across Distributed Autonomous Sensor Platforms (DIDASP) Proposal No.: N091-068-0317 Firm: Charles River Analytics Inc. 625 Mount Auburn Street Cambridge, Massachusetts 02138-4555 Contact: Scott Harrison Phone: (617) 491-3474 Web Site: www.cra.com Abstract: Unmanned vehicles have become an increasingly important tool of the U.S. armed forces in recent military conflicts. It is critical that these vehicles be able to fuse data from a variety of heterogeneous, widely dispersed sensor platforms into meaningful information, and share that information in a timely manner among groups of friendly manned and unmanned units. Charles River Analytics proposes an effort to design and demonstrate the feasibility of a system supporting Data Integration over Distributed Autonomous Sensor Platforms (DIDASP). We will construct a system that uses Probabilistic Relational Models to fuse local sensor data on a simulated USV. This data will be shared across a network of simulated USVs, that will be able to incorporate the distributed data into their own fusion efforts in turn, thereby creating a clearer common operational picture for the entire network. Human operators will be able to query the network for specific information about any given sensor contact detected by the USVs. They will also be able to use a rules engine to establish a set of automatic update and alert criteria. Benefits: Technologies developed under DIDASP will enable flexible autonomous and semi-autonomous behavior for a variety of unmanned vehicles, especially those expected to operate as part of a geographically distributed network under low-bandwidth, low-connectivity communications conditions. This work will support commercial development of unmanned vehicles for use in maritime surveillance, exploration, and research markets. Return