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Fuzzy Integral-Based Gaze Control of a Robotic Head for Human Robot Interaction

机译:基于模糊积分的人机交互机器人头部视线控制

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During the last few decades, as a part of effort to enhance natural human robot interaction (HRI), considerable research has been carried out to develop human-like gaze control. However, most studies did not consider hardware implementation, real-time processing, and the real environment, factors that should be taken into account to achieve natural HRI. This paper proposes a fuzzy integral-based gaze control algorithm, operating in real-time and the real environment, for a robotic head. We formulate the gaze control as a multicriteria decision making problem and devise seven human gaze-inspired criteria. Partial evaluations of all candidate gaze directions are carried out with respect to the seven criteria defined from perceived visual, auditory, and internal inputs, and fuzzy measures are assigned to a power set of the criteria to reflect the user defined preference. A fuzzy integral of the partial evaluations with respect to the fuzzy measures is employed to make global evaluations of all candidate gaze directions. The global evaluation values are adjusted by applying inhibition of return and are compared with the global evaluation values of the previous gaze directions to decide the final gaze direction. The effectiveness of the proposed algorithm is demonstrated with a robotic head, developed in the Robot Intelligence Technology Laboratory at Korea Advanced Institute of Science and Technology, through three interaction scenarios and three comparison scenarios with another algorithm.
机译:在过去的几十年中,作为增强自然人类机器人交互(HRI)努力的一部分,已经进行了大量研究以开发类似于人的注视控制。但是,大多数研究都没有考虑硬件实现,实时处理和实际环境等因素,因此必须考虑这些因素才能实现自然的HRI。本文提出了一种基于模糊积分的注视控制算法,该算法可以实时,真实地在机器人头上运行。我们将凝视控制公式化为一个多准则决策问题,并设计了七个以人类凝视为灵感的准则。相对于从感知的视觉,听觉和内部输入中定义的七个标准,对所有候选注视方向进行了部分评估,并将模糊度量分配给该标准的一组幂,以反映用户定义的偏好。相对于模糊测度的部分评估的模糊积分用于对所有候选注视方向进行整体评估。通过应用返回抑制来调整整体评估值,并将其与先前注视方向的整体评估值进行比较,以确定最终的注视方向。通过在韩国先进技术学院的机器人智能技术实验室开发的机器人头部,通过三种交互方案和三种与另一种算法的比较方案,证明了该算法的有效性。

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