Toward mobile robots reasoning like humans

Robots are increasingly becoming key players in human-robot teams. To become effective teammates, robots must possess profound understanding of an envi-ronment, be able to reason about the desired commands and goals within a specific context, and be able to com-municate with human teammates in a clear and natural way. To address these challenges, we have developed an intelligence architecture that combines cognitive com-ponents to carry out high-level cognitive tasks, seman-tic perception to label regions in the world, and a natural language component to reason about the command and its relationship to the objects in the world. This paper describes recent developments using this architecture on a fielded mobile robot platform operating in unknown urban environments. We report a summary of extensive outdoor experiments; the results suggest that a multidis-ciplinary approach to robotics has the potential to create competent human-robot teams.

High-resolution observations and modeling of turbulence sources, structures, and intensities in the upper mesosphere

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