深圳大学学报理工版

软体仿人手的感知能力是实现友好交互和灵巧操作的重要条件.柔性的光学弯曲传感器由发光二极管(light emitting diode, LED)、光导纤维和光敏传感器组成,易嵌于软体手指内.经粗糙化的光导纤维可产生光线溢出,通过测量光能损耗量可获得软体手指的弯曲度; 利用归一化标定软体手指初始(伸直)和最大弯曲状态的采样电压值,对归一化后的电压值进行均匀、非均匀和滞环分段,并融合5指弯曲信息实现连续运动检测、动作姿态和物体大小识别.实验结果表明,光学弯曲传感器可检测连续正弦运动状态; 正确识别多种手势和抓握姿态; 也可识别物体大小,结合滞环分段方法,解决单点分类切换存在振荡不足的问题,提高识别率.这种光学式柔性弯曲传感器具有电磁免疫、易于内嵌的优势,在软体手和软体执行器中具有重要应用价值.

The perception capability of soft humanoid hand is very important to the implementation of friendly interactive and dexterous operation. The flexible optical bending sensor which is easy to be embedded into the soft finger is comprised of light emitting diode(LED), optical fiber and photo-sensitive sensor. The roughened optical fibers can generate light overflow. And the bend degree of soft fingers can be obtained by detecting the loss of light energy. The abilities of continuous movement detection, action gestures and object size recognition are implemented according to the following operations: ① calibrating the initial(unbent)and maximum bending statuses of soft fingers with normalization method; ② segmenting the normalized data by uniform, nonuniform and hysteresis segment method; ③ merging together the information of five fingers. The experiment results show that the proposed optical fiber bending sensor is able to detect the continuous sinusoidal movement status, correctly recognize various gestures and grasping postures and the object size. Combining hysteresis subsection method, the shortcoming of single point subsection oscillating near subsection point is overcome, and the recognition rate is improved. This optical flexible bending sensor has the advantages of electromagnetic immunity and easy to be embedded. It has important application value in soft robotic hand or soft actuator.

引言
1 光学弯曲传感器设计
2 弯曲信息处理
3 软体手感知实验
4 结语

图1 光学弯曲传感器的组成<br/>Fig.1 The constitute of the optical fiber bending sensor

图1 光学弯曲传感器的组成
Fig.1 The constitute of the optical fiber bending sensor

图2 光导纤维粗糙化处理<br/>Fig.2 Roughening process of optical fiber

图2 光导纤维粗糙化处理
Fig.2 Roughening process of optical fiber

图3 软体手加工过程<br/>Fig.3 The processing of soft hand

图3 软体手加工过程
Fig.3 The processing of soft hand

图4 光学弯曲传感原理<br/>Fig.4 The principle of optical curvature sensing

图4 光学弯曲传感原理
Fig.4 The principle of optical curvature sensing

图5 滞环分段原理<br/>Fig.5 The principle of hysteresis segmenting

图5 滞环分段原理
Fig.5 The principle of hysteresis segmenting

图6 软件手感知实验平台<br/>Fig.6 Experiment platform for the perception of soft hand

图6 软件手感知实验平台
Fig.6 Experiment platform for the perception of soft hand

图7 软体手指内弯曲传感器的标定数据<br/>Fig.7 The calibration of curvature sensors embedded in soft fingers

图7 软体手指内弯曲传感器的标定数据
Fig.7 The calibration of curvature sensors embedded in soft fingers

图8 手指连续运动的弯曲检测结果<br/>Fig.8 The curvature test result of continuous finger movement

图8 手指连续运动的弯曲检测结果
Fig.8 The curvature test result of continuous finger movement

表1 软体手预设姿态库<br/>Table 1 The preset library of soft hand postures

表1 软体手预设姿态库
Table 1 The preset library of soft hand postures

图9 软体手的动作姿态<br/>Fig.9 Various action postures of soft hand

图9 软体手的动作姿态
Fig.9 Various action postures of soft hand

图10 软体手姿态(手势1)识别结果<br/>Fig.10 The posture recognition result of soft hand: gesture 1

图10 软体手姿态(手势1)识别结果
Fig.10 The posture recognition result of soft hand: gesture 1

图11 软体手抓取不同大小的圆柱体<br/>Fig.11 The soft hand grabbing different sizes of cylinder

图11 软体手抓取不同大小的圆柱体
Fig.11 The soft hand grabbing different sizes of cylinder

图12 物体大小识别结果<br/>Fig.12 The recognizing results of different sizes of object

图12 物体大小识别结果
Fig.12 The recognizing results of different sizes of object

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引言

1 光学弯曲传感器设计

2 弯曲信息处理

3 软体手感知实验

4 结语

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引言