Semantic World Modeling for Robots

The ARL Research Associateship Program (ARL-RAP) opportunity focuses on developing knowledge representation and reasoning methods that enable robots to understand their environment in semantic terms. Semantics may apply to space, time, causality, commonsense knowledge, communication with humans, and more, with a focus on robots in the Army domain. The research explores adapting existing information and knowledge resources, including representation languages, reasoners, existing ontologies, and knowledge bases to Army needs. Research opportunities exist in multiple areas including ontologies for autonomous robots, efficient reasoning algorithms, knowledge acquisition from existing data sources, high-level reasoning under uncertainty, qualitative reasoning for robots, commonsense reasoning for robots, and experimentation and validation methods in robotics. The research is conducted within the Computational and Information Sciences Directorate (CISD), which focuses on achieving the digital battlefield through sensing, distribution, analysis, and display of information. The ARL-RAP is designed to significantly increase the involvement of creative and highly trained scientists and engineers from academia and industry in scientific and technical areas of interest and relevance to the Army. Selected participants work with Army Research Laboratory scientists and engineers to help shape and execute research programs developing technologies that will support Army forces in meeting future operational needs.