Traditional human–robot interfaces usually have limitations in accuracy and/or operational space. This article proposes a natural human–robot interface using an adaptive tracking method, which can effectively expand the operational space while ensuring high accuracy. The natural interface allows the robot to directly reproduce the user's hand movement, making the interaction more intuitive and natural. The leap motion is fixed on the Cartesian platform to capture the movement of the user's hand. Because the Cartesian platform follows the hand and keeps the hand in the center of the detection area, the measurement accuracy is improved and the measurement space can be extended. During the process of acquiring gesture data, the measurement errors were found to increase over time because of the inherent noise of the sensor. To deal with this problem, the unscented Kalman filter is applied to estimate the position of the hand. Moreover, an adaptive velocity control method is proposed to improve the operation accuracy and reduce the task execution time with the consideration of users’ habits and easiness of usage. The effectiveness of this interface is verified by a series of experiments, and the results show that the proposed interface can be used by nonprofessional users for object operation tasks and can provide users with superior interactive experiences.

中文翻译：

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使用带有无迹卡尔曼滤波器的自适应跟踪系统的自然人机界面

传统的人机界面通常在准确性和/或操作空间方面存在限制。本文提出了一种使用自适应跟踪方法的自然人机界面，可以在保证高精度的同时有效扩展操作空间。自然的界面让机器人可以直接再现用户的手部动作，让交互更加直观自然。跳跃运动固定在笛卡尔平台上，捕捉用户手部的运动。由于笛卡尔平台跟随手部，将手部保持在检测区域的中心，提高了测量精度，扩展了测量空间。在获取手势数据的过程中，发现由于传感器的固有噪声，测量误差会随着时间的推移而增加。为了解决这个问题，应用无迹卡尔曼滤波器来估计手的位置。并且，在考虑用户习惯和易用性的情况下，提出了一种自适应速度控制方法，以提高操作精度并减少任务执行时间。通过一系列实验验证了该界面的有效性，结果表明所提出的界面可以被非专业用户用于对象操作任务，并且可以为用户提供卓越的交互体验。