Thegeneration of robot motions in the real world is difficult by using conventional controllers alone and requires highly intelligent processing. In this regard, learning-based motion generations are currently being investigated. However, the main issue has been improvements of the adaptability to spatially varying environments, but a variation of the operating speed has not been investigated in detail. In contact-rich tasks, it is especially important to be able to adjust the operating speed because a nonlinear relationship occurs between the operating speed and force (e.g., inertial and frictional forces), and it affects the results of the tasks. Therefore, in this study, we propose a method for generating variable operating speeds while adapting to spatial perturbations in the environment. The proposed method can be adapted to nonlinearities by utilizing a small amount of motion data. We experimentally evaluated the proposed method by erasing a line using an eraser fixed to the tip of the robot as an example of a contact-rich task. Furthermore, the proposed method enables a robot to perform a task faster than a human operator and is capable of operating close to the control bandwidth.

中文翻译：

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用于变速接触运动的模仿学习，以实现控制带宽的操作


单独使用传统控制器很难生成现实世界中的机器人运动，并且需要高度智能的处理。在这方面，目前正在研究基于学习的运动生成。然而，主要问题是提高对空间变化环境的适应性，但尚未详细研究运行速度的变化。在接触丰富的任务中，能够调整运行速度尤为重要，因为运行速度和力（例如惯性力和摩擦力）之间存在非线性关系，并且它会影响任务的结果。因此，在本研究中，我们提出了一种在适应环境中的空间扰动的同时产生可变运行速度的方法。所提出的方法可以通过利用少量的运动数据来适应非线性。我们通过使用固定在机器人尖端的橡皮擦擦除线条作为富含接触任务的示例，对所提出的方法进行了实验评估。此外，所提出的方法使机器人能够比人类操作员更快地执行任务，并且能够在接近控制带宽的情况下运行。