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经桡动脉假体:控制抓握的人工视觉。

Transradial prosthesis: artificial vision for control of prehension.

机构信息

Center for Sensory-Motor Interaction, Aalborg University, Aalborg, Denmark.

出版信息

Artif Organs. 2011 Jan;35(1):37-48. doi: 10.1111/j.1525-1594.2010.01040.x.

Abstract

We present a practical system for controlling the prehension of a transradial prosthesis. The system is mounted on the artificial hand and comprises simple hardware and software that are convenient for real-time implementation. The hardware consists of a standard web camera and an ultrasound distance sensor. The control algorithm mimics biological mechanisms for the control of grasping and uses the measured distance to the target object and the method of computer vision to estimate the object's size and orientation. Based on these estimates, the algorithm outputs the following commands for the control of prehension: (i) the type of grasp and the aperture size appropriate for the target object; and (ii) the angle through which the wrist should be rotated (pronation/supination) in order to properly position the hand for the grasp. We have tested the system's performance with different targets (planar geometric shapes, real-life objects) under static conditions (i.e., when the system is stationary) and dynamic conditions (i.e., when the system moves toward the target). The size estimation was more accurate in the static experiments (error < 36%). Importantly, the system showed to be very robust with respect to the estimation errors, and the correct control commands were generated in most of the tested cases. The presented system is only one component of the hand controller, related strictly to the prehension phase of grasping. The final solution is envisioned as a combination of the presented system, inertial sensors (hand orientation), and a myoelectric control (triggering).

摘要

我们提出了一种实用的桡骨假肢抓握控制系统。该系统安装在人工手上,由简单的硬件和软件组成,便于实时实现。硬件包括标准网络摄像头和超声距离传感器。控制算法模拟了生物控制抓握的机制,使用测量到目标物体的距离和计算机视觉方法来估计物体的大小和方向。基于这些估计,算法输出以下抓握控制命令:(i) 适合目标物体的抓握类型和开口大小;(ii) 为正确定位抓握手,手腕应旋转的角度(旋前/旋后)。我们已经在静态条件(即系统静止时)和动态条件(即系统向目标移动时)下使用不同的目标(平面几何形状、真实物体)测试了系统的性能。在静态实验中,尺寸估计更准确(误差<36%)。重要的是,该系统对估计误差表现出很强的鲁棒性,并且在大多数测试情况下都生成了正确的控制命令。所提出的系统仅是手控器的一个组成部分,与抓握的抓握阶段严格相关。最终的解决方案设想为呈现的系统、惯性传感器(手的方向)和肌电控制(触发)的组合。

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