Representation for Navigation
ABSTRACT: Matrix Research, Inc. proposes to prototype, test, analyze, and demonstrate novel feature representations in multi-agent simultaneous localization and mapping (MA-SLAM) systems for enhanced navigation accuracy/reliability. The objective of this effort is to develop a framework to integrate data from various air and ground sensor systems employed for exploitation and interdiction tasks, focused on compact, multi-modal feature representations tailored for navigation applications in which low-bandwidth, low-rate communications between agents constrains data throughput. A layered sensing processing framework is needed that combines information, gleans meaning from the collected data, and re-tasks sensor-seekers in a timely manner to garner actionable intelligence and execute a course of action. This is only possible if the platforms have sufficient context and are able to jointly localize and coordinate. Initially, this effort will focus on multi-view descriptors for wide-baseline correspondence. Then it will demonstrate these methods for joint localization and coordination to accomplish an objective. Our thesis is that tightly coupled"vision-based"navigation will provide the necessary foundation, context, and features for MA-SLAM. We have two transition paths lined up to commercialize our results, both of which contribute to the AFRL mission. These will include both indoor and outdoor navigation demonstrations. BENEFIT: The primary benefit of successful completion of this effort is a revolutionary new capability for extracting features for mapping systems. This capability has numerous commercial applications in various business sectors such as defense, search and rescue, mapping, mining, and robotics.
Small Business Information at Submission:
Matrix Research Inc
1300 Research Park Dr Dayton, OH -
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