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Operator Engagement Detection for Robot Behavior Adaptation

机译:机器人行为适应的操作员参与度检测

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It has been shown that in human-robot interaction, the effectiveness of a robot varies inversely with the operator engagement in the task. Given the importance of maintaining optimal task engagement when working with a robot, it would be immensely useful to have a robotic system that can detect the level of operator engagement and modify its behavior if required. This paper presents a framework for human-robot interaction that allows inference of operator's engagement level through the analysis of his/her physiological signals, and adaptation of robot behavior as a function of the operator's engagement level. Peripheral physiological signals were measured through wearable biofeedback sensors and a control architecture inspired by Riley's original information-flow model was developed to implement such human-robot interaction. The results from affect-elicitation tasks for human participants showed that it was possible to detect engagement through physiological sensing in real-time. An open-loop teleoperatio...
机译:已经表明,在人机交互中,机器人的有效性与操作员参与任务的能力成反比。考虑到与机器人一起工作时保持最佳任务参与的重要性,拥有一种能够检测操作员参与程度并在需要时更改其行为的机器人系统将非常有用。本文提出了一种人机交互的框架,该框架允许通过分析操作员的生理信号来推断操作员的参与程度,并根据操作员的参与程度来调整机器人的行为。通过可穿戴的生物反馈传感器测量周围的生理信号,并开发了受赖利(Riley)原始信息流模型启发的控制架构来实现这种人机交互。来自人类参与者的情感启发任务的结果表明,可以通过生理感应实时检测参与。开环远程操作...

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