基于织物拉伸传感器的手势映射系统
发布时间：2018-07-20 14:26
【摘要】：针对人机交互中主从手映射系统反馈信息缺乏、映射精确度及可穿戴性差等存在的缺点,提出一种基于织物可拉伸传感器以及具有反馈机制的主从手映射操控系统。以莱卡织物表面旋涂石墨烯/聚苯胺复合导电材料,有机硅导电银胶作为电极,研制一种全柔性织物可拉伸传感器。同时将该拉伸传感器布置于人手及机械手,构成2×5的拉伸传感阵列。结合主从手拉伸传感信息,通过改进D-H算法,建立手势识别模型。利用BP神经网络对主从手拉伸传感器信息映射进行离线建模,结合在线优化算法,引入拉伸传感器信息反馈机制,实现主从手交互手势的高效、精准映射,建立具有反馈机制的手势映射系统。通过实验分析传感器的拉伸特性,并对有、无反馈机制的手势映射系统的映射精准度进行对比实验。结果表明,所设计的基于柔性织物拉伸传感器、具有反馈机制的主从手映射系统提升了手势映射的精准度,并兼具良好的穿戴性。
[Abstract]:A master-slave mapping control system based on fabric extensible sensor and feedback mechanism is proposed to overcome the shortcomings of lack of feedback information, poor mapping accuracy and wearability in man-machine interaction. A fully flexible fabric tensile sensor was developed using the composite conductive material of graphene / Polyaniline on the surface of Leca fabric and silicone conductive silver glue as the electrode. At the same time, the drawing sensor is arranged on the hand and manipulator to form a 2 脳 5 stretch sensor array. Combined with the sensing information of master and slave hand, a hand gesture recognition model was established by improving D-H algorithm. The information mapping of master-slave hand stretching sensor is modeled offline by BP neural network. Combining with online optimization algorithm, the information feedback mechanism of stretching sensor is introduced to realize the efficient and accurate mapping of master-slave hand gesture. A gesture mapping system with feedback mechanism is established. The stretching characteristics of the sensor are analyzed experimentally, and the mapping accuracy of the gesture mapping system without feedback mechanism is compared. The results show that the master-slave mapping system based on flexible fabric stretch sensor has improved the precision of gesture mapping and has good wearability.
【作者单位】： 合肥工业大学大学电子科学与应用物理学院;
【基金】：国家自然科学基金(61471155,61673369)项目资助
【分类号】：TP212;TP391.41
本文编号：2133830
[Abstract]:A master-slave mapping control system based on fabric extensible sensor and feedback mechanism is proposed to overcome the shortcomings of lack of feedback information, poor mapping accuracy and wearability in man-machine interaction. A fully flexible fabric tensile sensor was developed using the composite conductive material of graphene / Polyaniline on the surface of Leca fabric and silicone conductive silver glue as the electrode. At the same time, the drawing sensor is arranged on the hand and manipulator to form a 2 脳 5 stretch sensor array. Combined with the sensing information of master and slave hand, a hand gesture recognition model was established by improving D-H algorithm. The information mapping of master-slave hand stretching sensor is modeled offline by BP neural network. Combining with online optimization algorithm, the information feedback mechanism of stretching sensor is introduced to realize the efficient and accurate mapping of master-slave hand gesture. A gesture mapping system with feedback mechanism is established. The stretching characteristics of the sensor are analyzed experimentally, and the mapping accuracy of the gesture mapping system without feedback mechanism is compared. The results show that the master-slave mapping system based on flexible fabric stretch sensor has improved the precision of gesture mapping and has good wearability.
【作者单位】： 合肥工业大学大学电子科学与应用物理学院;
【基金】：国家自然科学基金(61471155,61673369)项目资助
【分类号】：TP212;TP391.41
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，本文编号：2133830
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