Robots have several requirements, including environmental adaptability, to operate in the real-world environment. Moreover, the desired success rate for task completion must be achieved. In this regard, end-to-end learning for autonomous operation is currently being investigated. However, the issue of the operating speed has not been investigated in detail. Therefore, in this study, we propose a method for generating variable operating speeds while adapting to perturbations in the environment. When the work speed changes, a nonlinear relationship occurs between the operating speed and force (e.g., inertial and frictional forces). However, 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. Furthermore, the proposed method enables a robot to perform a task faster than a human operator and is capable of operating at the control bandwidth.

翻译：机器人在现实环境中操作有若干要求,包括环境适应性;此外,必须达到完成任务的预期成功率。在这方面,目前正在调查自主操作的端到端学习;然而,操作速度问题尚未详细调查。因此,在本研究中,我们提出一种方法,在适应环境扰动的同时,产生可变操作速度。当工作速度变化时,操作速度和力量(例如惯性力和摩擦力)之间出现非线性关系时,提议的方法可以通过使用少量运动数据来适应非线性。我们实验性地评估了拟议方法,用固定在机器人顶部的橡皮抹除线。此外,拟议方法使机器人能够比人类操作者更快地执行任务,并能在控制带宽下操作。