基于kirigami型压阻传感器的软弯曲执行器端到端姿态感知方法

Jing Shu, Junming Wang, Yujie Su, Honghai Liu, Zheng Li, Raymond K. Tong
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引用次数: 5

摘要

软执行器的姿态感知是实现软机器人闭环控制的关键。提出了一种基于长短期记忆神经网络的软执行器端到端姿态感知方法。提出了一种基于导电硅材料的柔性弯曲传感器,并将其用于姿态传感。该方法还考虑了柔性机器人的磁滞和柔性弯曲传感器的非线性传感信号。通过对传感器输出的一步校正,LSTM网络可以捕获软执行器的姿态。在一个手指大小的单自由度气动纤维增强弯曲驱动器上进行了验证。在致动器的上表面放置了四个基里伽米式柔性压阻式换能器。结果表明,该传感器能够以可接受的精度感知驱动器的姿态。我们相信我们的工作将有助于软机器人的动态姿态感知和闭环控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An End-to-end Posture Perception Method for Soft Bending Actuators Based on Kirigami-inspired Piezoresistive Sensors
Posture sensing of soft actuators is critical for performing closed-loop control of soft robots. This paper presents a novel end-to-end posture perception method for soft actuators by developing long short-term memory (LSTM) neural networks. A novel flexible bending sensor developed from off-the-shelf conductive silicon material was proposed and used for posture sensing. In the proposed method, the hysteresis of the soft robot and non-linear sensing signals from the flexible bending sensors have also been considered. With one-step calibration from the sensor output, the posture of the soft actuator could be captured by the LSTM network. The method was validated on a finger-size one DOF pneumatic fiber-reinforced bending actuator. Four kirigami-inspired flexible piezoresistive transducers were placed on the top surface of the actuator. Results show that the transducers could sense the posture of the actuator with acceptable accuracy. We believe our work could benefit soft robot dynamic posture perception and closed-loop control.
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