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Spatial language for route-based humanoid robot navigation

机译:基于路线的类人机器人导航的空间语言

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A more natural interaction between humans and mobilerobots can be achieved if they have a common ground(Kiesler 2005). Natural language interfaces support suc-cessful styles of interaction between robots and users.Typical scenarios include the user who instructs a robot toperform actions in an environment, such as moving tolocations or manipulating objects. Thus, route descriptions,which are used to guide robots in executing navigationtasks in their surrounding environment, are important forrealizing effective human–robot interaction. To provide theroute in an effective way, the rules and sequences ofcommands should be expressed in a very concise way.Natural language uses symbols and syntactic rules tointeract with the robots, which possess knowledge repre-sentations at the symbolic level. On the other hand, spatialreasoning concerning verbal route descriptions is essentialfor humans as well as for mobile robots which navigate inunstructured environments. Such reasoning gives robotsthe ability to comprehend human-like spatial language,which provides the human users with an intuitive interfacethat is consistent with their innate spatial cognition (Lauriaet al. 2001). It can also provide an accelerated learning byusing symbolic communication, which was proven byCangelosi and Hamad 2001.
机译:如果人类和移动机器人有一个共同点,他们之间就可以实现更自然的互动(Kiesler 2005)。自然语言界面支持机器人与用户之间成功的交互样式。典型的场景包括指示机器人在环境中执行动作(例如,移动位置或操纵对象)的用户。因此,用于指导机器人在其周围环境中执行导航任务的路线描述对于实现有效的人机交互至关重要。为了有效地提供路线,命令的规则和顺序应该非常简洁。自然语言使用符号和句法规则与机器人进行交互,这些机器人在符号级别具有知识表示。另一方面,关于语言路线描述的空间推理对于人类以及在非结构化环境中导航的移动机器人都是必不可少的。这种推理使机器人能够理解类似于人类的空间语言,从而为人类用户提供了一个直观的界面,与他们固有的空间认知相一致(Lauriaet等,2001)。它也可以通过使用符号通信来提供加速的学习,这已由Cangelosi和Hamad 2001证明。

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