四肢瘫痪患者辅助机械臂的半自主舌头控制

Max Hildebrand, Frederik Bonde, Rasmus Vedel Nonboe Kobborg, C. Andersen, Andreas Flem Norman, M. Thøgersen, S. Bengtson, S. Došen, L. Struijk
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引用次数: 8

摘要

四肢瘫痪患者可以通过使用辅助机械臂(ARM)来提高独立性。然而,由于它们的残疾,可用于操作此类设备的接口变得有限。由于舌头通常不会残疾,以前已经为这一用户群体开发了一种多功能的口内舌头控制界面(ITCI)。先前的一项研究表明,由于提供了大量输入,ITCI可以直接连续控制ARM的6-7个自由度(DoF)(18)。在目前的试点研究中,我们调查了半自动化是否可以进一步提高ITCI在控制ARM时的效率。这是通过在ARM的末端执行器上增加一个摄像头,并使用计算机视觉算法引导ARM抓取目标物体来实现的。对三种ITCI和一种操纵杆控制方案进行了测试和比较:1)带有基架参考点的手动笛卡尔控制,2)带有末端执行器参考点的手动笛卡尔控制,3)带有末端执行器参考点和自主抓取功能的手动笛卡尔控制,4)常规JACO2操纵杆控制。结果表明,末端执行器控制在总任务时间、发出指令数量和路径效率方面优于基架控制。自动抓取功能的加入并没有提高抓取性能,但却减少了抓取时目标物体的碰撞/位移。
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Semi-Autonomous Tongue Control of an Assistive Robotic Arm for Individuals with Quadriplegia
Individuals suffering from quadriplegia can achieve increased independence by using an assistive robotic manipulator (ARM). However, due to their disability, the interfaces that can be used to operate such devices become limited. A versatile intraoral tongue control interface (ITCI) has previously been develop for this user group, as the tongue is usually spared from disability. A previous study has shown that the ITCI can provide direct and continuous control of 6-7 degrees of freedom (DoF) of an ARM, due to a high number of provided inputs (18). In the present pilot study we investigated whether semi-automation might further improve the efficiency of the ITCI, when controlling an ARM. This was achieved by adding a camera to the end effector of the ARM and using computer vision algorithms to guide the ARM to grasp a target object. Three ITCI and one joystick control scheme were tested and compared: 1) manual Cartesian control with a base frame reference point, 2) manual Cartesian control with an end effector reference point 3) manual Cartesian control with an end effector reference point and an autonomous grasp function 4) regular JACO2 joystick control. The results indicated that end effector control was superior to the base frame control in total task time, number of commands issued and path efficiency. The addition of the automatic grasp function did not improve the performance, but resulted in fewer collisions/displacements of the target object when grasping.
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