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The Gestural Joystick and the Efficacy of the Path Tortuosity Metric for Human/Robot Interaction

机译:手势操纵杆和人与机器人交互路径曲折度量的功效

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This paper describes the design and evaluation of the "gestural joystick," a wearable 2-D pointing controller for mobile robots in hazardous environments that uses hand gestures. Hazardous environments, such as that of a collapsed building search, require operators to wear a significant amount of protective clothing. This protective clothing, which may include hard hats, suits, gloves, goggles, etc., reduces comfort, mobility, dexterity, load capacity, and ability to interact with conventional computer input devices. The gestural joystick, which is embedded in protective clothing, mitigates some of these impacts, but at the cost of lesser familiarity for the user and, therefore, potentially lesser performance. Effective performance metrics are required to evaluate this interface mechanism. Path tortuosity has been proposed as a performance metric for the evaluation of teleoperation of a robot, but has not been proven to be distinct from time-to-complete metrics. By injecting controlled uncertainty between the user and robot, we show, for the first time, that path tortuosity is a useful and distinct metric for the evaluation of robot teleoperation.
机译:本文介绍了“手势操纵杆”的设计和评估,“手势操纵杆”是一种在危险环境中使用手势的移动机器人的可穿戴式2-D指向控制器。危险环境(例如倒塌的建筑物搜索)要求操作员穿着大量防护服。这种防护服可能包括安全帽,西装,手套,护目镜等,从而降低了舒适度,移动性,灵巧性,负载能力以及与常规计算机输入设备进行交互的能力。内置在防护服中的手势操纵杆可减轻其中的一些影响,但会给用户带来较少的熟悉度,因此可能会降低性能。需要有效的性能指标来评估此接口机制。路径曲折度已被提出作为评估机器人遥距操作的性能指标,但尚未证明与完成时间指标有区别。通过在用户和机器人之间注入可控制的不确定性,我们首次展示了路径曲折度是评估机器人远程操作的有用且独特的指标。

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