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Creating a human-robot interface is a daunting experience. Capabilities and functionalities of the interface are dependent on the robustness of many different sensor and input modalities. For example, object recognition poses problems for state-of-the-art vision systems. Speech recognition in noisy environments remains problematic for acoustic systems. Natural language understanding and dialog are often limited to specific domains and baffled by ambiguous or novel utterances. Plans based on domain-specific tasks limit the applicability of dialog managers. The types of sensors used limit spatial knowledge and understanding, and constrain cognitive issues, such as perspective-taking.In this research, we are integrating several modalities, such as vision, audition, and natural language understanding to leverage the existing strengths of each modality and overcome individual weaknesses. We are using visual …