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Teaching robots to cooperate with humans in dynamic manipulation tasks based on multi-modal human-in-the-loop approach

机译:基于多模式人在回路方法的教学机器人在动态操纵任务中与人合作

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摘要

We propose an approach to efficiently teach robots how to perform dynamic manipulation tasks in cooperation with a human partner. The approach utilises human sensorimotor learning ability where the human tutor controls the robot through a multi-modal interface to make it perform the desired task. During the tutoring, the robot simultaneously learns the action policy of the tutor and through time gains full autonomy. We demonstrate our approach by an experiment where we taught a robot how to perform a wood sawing task with a human partner using a two-person cross-cut saw. The challenge of this experiment is that it requires precise coordination of the robot's motion and compliance according to the partner's actions. To transfer the sawing skill from the tutor to the robot we used Locally Weighted Regression for trajectory generalisation, and adaptive oscillators for adaptation of the robot to the partner's motion.
机译:我们提出一种有效地教机器人如何与人类伙伴合作执行动态操纵任务的方法。该方法利用了人类的感觉运动学习能力,其中人类导师通过多模式界面控制机器人以使其执行所需的任务。在辅导期间,机器人会同时学习辅导者的行动策略,并随着时间的流逝获得完全的自主权。我们通过一个实验演示了我们的方法,在该实验中,我们教机器人如何使用两人横切锯与人类伙伴一起执行木锯任务。此实验的挑战在于,它需要根据合作伙伴的动作精确协调机器人的运动和顺应性。为了将锯切技能从导师转移到机器人,我们使用了局部加权回归进行轨迹概括,并使用了自适应振荡器来使机器人适应伙伴的运动。

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