考虑辅助率的基于中断式直接教学的洗碗冲洗与擦洗行为学习
Behavioral Learning of Dish Rinsing and Scrubbing based on Interruptive Direct Teaching Considering Assistance Rate
AI总结：
本研究提出一种安全灵巧的机器人操作系统，通过中断式直接教学和辅助率学习物体动力学模型，生成减少人类辅助的控制输入，实现对未知盘子的自适应安全冲洗与擦洗。
摘要：
机器人被期望以安全且灵巧的方式操作物体。例如，洗碗是一项灵巧的操作，涉及用海绵擦洗盘子并用水冲洗。必须在不溅水且不掉落盘子的情况下安全地学习该操作。在本研究中，我们提出了一种安全且灵巧的操作系统。当人类通过中断式直接教学纠正机器人手部的初始轨迹后，机器人通过估计物体和机器人本身的状态、控制输入以及所需的人类辅助量（辅助率）来学习物体的动力学模型。通过使用获取的动力学模型，对估计值与参考值之间的误差进行反向传播，机器人能够生成接近参考值的控制输入，例如使得不需要人类辅助且盘子不会过度移动。这使得能够对未知形状和属性的盘子进行自适应冲洗和擦洗。结果，可以生成需要较少人类辅助的安全动作。
英文摘要：
Robots are expected to manipulate objects in a safe and dexterous way. For example, washing dishes is a dexterous operation that involves scrubbing the dishes with a sponge and rinsing them with water. It is necessary to learn it safely without splashing water and without dropping the dishes. In this study, we propose a safe and dexterous manipulation system. The robot learns a dynamics model of the object by estimating the state of the object and the robot itself, the control input, and the amount of human assistance required (assistance rate) after the human corrects the initial trajectory of the robot's hands by interruptive direct teaching. By backpropagating the error between the estimated and the reference value using the acquired dynamics model, the robot can generate a control input that approaches the reference value, for example, so that human assistance is not required and the dish does not move excessively. This allows for adaptive rinsing and scrubbing of dishes with unknown shapes and properties. As a result, it is possible to generate safe actions that require less human assistance.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
