CISE Research Instrumentation: Ambiguity Resolution for Intelligent Systems Using a Cognitive Robot

9818341Brown, Frank M.Agah， ArvinUniversity of kansasuniversity使用认知机器人的智能系统歧义解决该研究仪器有助于电子工程与计算机科学，心理学和语音语言与听力部门获得认知机器人（基础系统，手臂和手部操纵器，双目彩色视觉，激光测距，声音接收和解释）。支持以下研究项目：口语理解中的歧义解决、上下文驱动的主动机器人视觉中的歧义解决、记忆系统中的歧义解决以及机器人推理和驱动中的歧义解决。具有视觉、语言、运动和手/手臂操作能力的认知机器人将能够研究多个认知子系统中歧义解决过程之间的合理交互，包括语音和自然语言理解子系统、场景解释子系统、适当记忆上下文检索子系统以及机器人计划和行动执行。研究方法是将这些子系统的各种模糊解决过程的计算模型集成到认知机器人中，并通过观察认知机器人的行为以集成的方式对其进行测试。本研究的意义在于，一个子系统中的歧义往往只能通过其他子系统的歧义解决能力来解决。因此，在使用认知机器人的四个研究项目中，歧义解决的研究将通过与其他歧义解决能力的整合而得到加强。由于人类毫不费力地解决歧义的能力似乎是智能的一个基本方面，因此对这些子系统的歧义解决能力之间的相互作用的解释可能非常重要。

9818341Brown, Frank M.Agah, ArvinUniversity of KansasAmbiguity Resolution for Intelligent Systems Using a Cognitive RobotThis research instrumentation contributes to the acquisition, by the Departments of Electrical Engineering and Computer Science, Psychology, and Speech Language and Hearing, of a Cognitive Robot (base system, arm and hand manipulator, binocular color vision, laser ranger, sound reception and interpretation, and sound generation) enabling research projects in:- Ambiguity Resolution in Spoken Language Understanding,- Ambiguity Resolution in Context Driven Active Robot Vision,- Ambiguity Resolution within the Memory System, and- Ambiguity Resolution in Robot Reasoning and Actuation.The Cognitive Robot, with visual, speech, movement, and hand/arm manipulation capabilities, will enable research plausible interactions among the processes of ambiguity resolution in multiple cognitive subsystems including subsystems for speech and natural language understanding, scene interpretation, the retrieval of appropriate memory context, and robot planning and action execution. The research methodology is to integrate together computational models of these various ambiguity resolution processes of these subsystems into the Cognitive Robot and to test them in an integrated fashion by observing the behavior of the Cognitive Robot. The significance of this research lies in the fact that ambiguity in one subsystem can often only be resolved by the ambiguity resolution capabilities of the other subsystems. Thus, the study of ambiguity resolution in each of the four research projects using the Cognitive Robot will be enhanced by its integration with the ambiguity resolution capabilities of the others. Since the human capability for effortlessly resolving ambiguity seems to be a fundamental aspect of intelligence, an explication of the interactions among the ambiguity resolution capabilities of these subsystems may be highly significant.