The goal of this research is to enhance control and coordination of heterogeneous robots that include both Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles (UAVs), supported by communication of onboard sensor and ancillary information among individual platforms and human users. The research has formulated and experimentally validated robust adaptive algorithms and software codes for decision and control of mobile robotic platforms, as applied to real-time computation and execution of combat mission strategies. These algorithms are executable within a general-purpose programming language environment and make use of the generative power of formal-language-theoretic models instead of ad-hoc rule-based expert systems. Future Plans: (1) Formulation of operational intelligence models in a formal-language-theoretic setting; (2) Algorithm development for intelligent coordination of autonomous agent teams to accomplish complex mission tasks.


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