Visual pointing gestures for bi-directional human robot interaction in a pick-and-place task

C. P. Quintero, R. T. Fomena, Mona Gridseth, Martin Jägersand
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引用次数: 28

Abstract

This paper explores visual pointing gestures for two-way nonverbal communication for interacting with a robot arm. Such non-verbal instruction is common when humans communicate spatial directions and actions while collaboratively performing manipulation tasks. Using 3D RGBD we compare human-human and human-robot interaction for solving a pick-and-place task. In the human-human interaction we study both pointing and other types of gestures, performed by humans in a collaborative task. For the human-robot interaction we design a system that allows the user to interact with a 7DOF robot arm using gestures for selecting, picking and dropping objects at different locations. Bi-directional confirmation gestures allow the robot (or human) to verify that the right object is selected. We perform experiments where 8 human subjects collaborate with the robot to manipulate ordinary household objects on a tabletop. Without confirmation feedback selection accuracy was 70-90% for both humans and the robot. With feedback through confirmation gestures both humans and our vision-robotic system could perform the task accurately every time (100%). Finally to illustrate our gesture interface in a real application, we let a human instruct our robot to make a pizza by selecting different ingredients.
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在拾取和放置任务中双向人机交互的视觉指向手势
本文探讨了与机械臂交互的双向非语言交流的视觉指向手势。当人类在协作执行操作任务时交流空间方向和动作时,这种非语言指令很常见。使用3D RGBD,我们比较了解决拾取任务的人机交互和人机交互。在人与人之间的互动中,我们研究了人类在协作任务中所做的指向和其他类型的手势。对于人机交互,我们设计了一个系统,允许用户使用手势与7DOF机械臂进行交互,以在不同位置选择,拾取和丢弃物体。双向确认手势允许机器人(或人类)验证是否选择了正确的对象。我们进行了实验,8名人类受试者与机器人合作,在桌面上操作普通的家用物品。在没有确认的情况下,人类和机器人的反馈选择准确率都是70-90%。通过确认手势的反馈,人类和我们的视觉机器人系统每次都能准确地执行任务(100%)。最后,为了在实际应用中说明我们的手势界面,我们让一个人指导我们的机器人通过选择不同的原料来制作披萨。
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