IEEE Trans Cybern. 2015 Sep;45(9):1769-83. doi: 10.1109/TCYB.2014.2360205. Epub 2014 Oct 8.
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.
在过去的几十年中，作为增强自然人机交互（HRI）努力的一部分，已经进行了大量研究来开发类似人类的注视控制。然而，大多数研究都没有考虑硬件实现、实时处理和真实环境，这些因素对于实现自然的 HRI 是应该考虑的。本文提出了一种基于模糊积分的机器人头部实时、真实环境下的注视控制算法。我们将注视控制表述为多准则决策问题，并设计了七个受人类注视启发的准则。针对从感知视觉、听觉和内部输入中定义的七个准则，对所有候选注视方向进行部分评估，并为准则的幂集分配模糊度量，以反映用户定义的偏好。对模糊度量的部分评估进行模糊积分，以对所有候选注视方向进行全局评估。通过应用返回抑制来调整全局评估值，并与前一个注视方向的全局评估值进行比较，以决定最终的注视方向。通过在韩国先进科学技术研究院的机器人智能技术实验室开发的机器人头部，通过三个交互场景和与另一个算法的三个比较场景，验证了所提出算法的有效性。
