Controlling gaze with an embodied interactive control architecture
Controlling gaze with an embodied interactive control architecture
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DOI：
10.1007/s10489-009-0180-0
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发表时间：
2010-04-01
影响因子：
5.3
通讯作者：
Nishida, Toyoaki
中科院分区：
文献类型：
--
作者：
Mohammad, Yasser;Nishida, Toyoaki
人机交互（HRI）是一个新兴的研究领域，其目标是开发易于操作、更具吸引力和娱乐性的机器人。自然的类人行为被许多研究者认为是HRI的一个重要目标。人与人之间的交流研究表明，凝视控制是人类在近距离接触中使用的主要互动行为之一。因此，为了与人类伴侣进行自然互动，机器人应该具备的类似人类的凝视控制是重要的行为之一。为了开发类似人类的自然凝视控制，使其易于与机器人的其他行为相结合，需要一种灵活的机器人结构。大多数可用的机器人架构都是在考虑自主机器人的情况下开发的。虽然为HRI开发的机器人通常是自主的，但它们的自主性与交互性相结合，这给支持它们的机器人架构的设计带来了更多挑战。本文报告了两种注视控制器的开发和评估，使用一种新的跨平台机器人架构EICA （Embodied Interactive Control architecture）用于HRI应用，该架构旨在满足这些挑战，强调如何实现低水平的注意力集中和动作集成。对凝视控制者的评估显示，在相互注意、凝视伴侣和相互凝视方面，他们的行为与人类相似。本文还报道了一种新的浮点遗传算法（FPGA），用于学习注视控制器各过程的参数。
Human-Robot Interaction (HRI) is a growing field of research that targets the development of robots which are easy to operate, more engaging and more entertaining. Natural human-like behavior is considered by many researchers as an important target of HRI. Research in Human-Human communications revealed that gaze control is one of the major interactive behaviors used by humans in close encounters. Human-like gaze control is then one of the important behaviors that a robot should have in order to provide natural interactions with human partners. To develop human-like natural gaze control that can integrate easily with other behaviors of the robot, a flexible robotic architecture is needed. Most robotic architectures available were developed with autonomous robots in mind. Although robots developed for HRI are usually autonomous, their autonomy is combined with interactivity, which adds more challenges on the design of the robotic architectures supporting them. This paper reports the development and evaluation of two gaze controllers using a new cross-platform robotic architecture for HRI applications called EICA (The Embodied Interactive Control Architecture), that was designed to meet those challenges emphasizing how low level attention focusing and action integration are implemented. Evaluation of the gaze controllers revealed human-like behavior in terms of mutual attention, gaze toward partner, and mutual gaze. The paper also reports a novel Floating Point Genetic Algorithm (FPGA) for learning the parameters of various processes of the gaze controller.