Ka Hyun W, Chung Cheng-Shiu, Ding Dan, James Khara, Cooper Rory
a Department of Veterans Affairs , Human Engineering Research Laboratories , Pittsburgh , PA , USA.
b Department of Rehabilitation Science and Technology , University of Pittsburgh , Pittsburgh , PA , USA.
Disabil Rehabil Assist Technol. 2018 Feb;13(2):140-145. doi: 10.1080/17483107.2017.1299804. Epub 2017 Mar 22.
We developed a 3D vision-based semi-autonomous control interface for assistive robotic manipulators. It was implemented based on one of the most popular commercially available assistive robotic manipulator combined with a low-cost depth-sensing camera mounted on the robot base. To perform a manipulation task with the 3D vision-based semi-autonomous control interface, a user starts operating with a manual control method available to him/her. When detecting objects within a set range, the control interface automatically stops the robot, and provides the user with possible manipulation options through audible text output, based on the detected object characteristics. Then, the system waits until the user states a voice command. Once the user command is given, the control interface drives the robot autonomously until the given command is completed. In the empirical evaluations conducted with human subjects from two different groups, it was shown that the semi-autonomous control can be used as an alternative control method to enable individuals with impaired motor control to more efficiently operate the robot arms by facilitating their fine motion control. The advantage of semi-autonomous control was not so obvious for the simple tasks. But, for the relatively complex real-life tasks, the 3D vision-based semi-autonomous control showed significantly faster performance. Implications for Rehabilitation A 3D vision-based semi-autonomous control interface will improve clinical practice by providing an alternative control method that is less demanding physically as well cognitively. A 3D vision-based semi-autonomous control provides the user with task specific intelligent semiautonomous manipulation assistances. A 3D vision-based semi-autonomous control gives the user the feeling that he or she is still in control at any moment. A 3D vision-based semi-autonomous control is compatible with different types of new and existing manual control methods for ARMs.
我们为辅助机器人操纵器开发了一种基于3D视觉的半自动控制界面。它是基于一种最流行的商用辅助机器人操纵器之一，并结合安装在机器人基座上的低成本深度感应相机实现的。要使用基于3D视觉的半自动控制界面执行操纵任务，用户首先使用其可用的手动控制方法进行操作。当在设定范围内检测到物体时，控制界面会自动停止机器人，并根据检测到的物体特征通过语音文本输出为用户提供可能的操纵选项。然后，系统等待直到用户说出语音命令。一旦给出用户命令，控制界面就会自主驱动机器人，直到完成给定命令。在对来自两个不同组的人类受试者进行的实证评估中，结果表明，半自动控制可以用作一种替代控制方法，通过促进精细运动控制，使运动控制受损的个体能够更有效地操作机器人手臂。对于简单任务，半自动控制的优势并不明显。但是，对于相对复杂的现实生活任务，基于3D视觉的半自动控制表现出明显更快的性能。对康复的意义 基于3D视觉的半自动控制界面将通过提供一种对身体和认知要求较低的替代控制方法来改善临床实践。基于3D视觉的半自动控制为用户提供特定任务的智能半自动操纵辅助。基于3D视觉的半自动控制让用户感觉自己在任何时候都仍在掌控之中。基于3D视觉的半自动控制与不同类型的用于手臂的新的和现有的手动控制方法兼容。
