SGER: Operator-Cue-Assisted Machine Vision.

*这个奖项，在探索性研究小额拨款模式下，将探索在人类-机器人合作中人类操作员监督和计算机自动化之间的平衡。这项研究将通过寻找方法，将人类的高级视觉感知和任务理解能力与机器人的低级视觉和定位精度相结合，以优化人机团队在视觉和操作过程中的表现。这一初步探索的重点是确定如何将先前的领域知识和模型以及人类操作员的整体视觉和场景感知能力与执行复杂机器人任务的精确和高速的机器操作相结合。这项调查有望确定在合作努力中分配人和机器角色的新方法，这在广泛的新兴应用中将是重要的。*

*** This award, in the Small Grants for Exploratory Research mode, will explore the balance between human operator supervision and computer automation in a human-robot cooperation. The research will do this by finding ways to combine human high-level visual perception and task- understanding capabilities with a robot's low-level vision and positioning precision, to optimize the performance of the human-machine team in vision and manipulation processes. The focus of this initial exploration is to determine ways to combine prior domain knowledge and models, and overall vision and scene perception capabilities of the human operator, with precision and high-speed machine operation in execution of complex robotic tasks. This investigation offers promise of identifying new approaches to allocating human and machine roles in cooperative endeavors, which will be important in a wide range of emerging applications.***