Geometry Optimisation of a Hall-Effect-Based Soft Fingertip for Estimating Orientation of Thin Rectangular Objects
Geometry Optimisation of a Hall-Effect-Based Soft Fingertip for Estimating Orientation of Thin Rectangular Objects
复制标题
DOI：
10.3390/s19184056
复制
发表时间：
2019-09-02
期刊：
影响因子：
3.9
通讯作者：
Hirai, Shinichi
中科院分区：
文献类型：
--
作者：
Rosle, Muhammad Hisyam;Wang, Zhongkui;Hirai, Shinichi
软触觉传感器已被应用于机器人夹具进行装配。利用触觉传感器获取抓取过程中的接触信息和物体方位是一项具有挑战性的任务。目前，设计基于霍尔效应的触觉传感器来执行这些任务是基于试验和错误。提出了一种提高圆柱形软测量灵敏度的优化几何设计方法。在Abaqus中构建了具有两个设计变量的柔性指尖的有限元模型，即，空心半径和磁体位置。然后将模型导入Isight，以磁体位移最大化为目标函数。我们发现，最优设计是在参数设计空间的边界。四个指尖制造一个直观的，一个最佳的，和两个可选的参数集。进行了实验，并通过利用线性近似和机器学习的方法来估计对象的方向。优化和实验之间取得了良好的协议。结果表明，目标定位的估计平均误差降低了优化的指尖设计。此外，可以基于传感器输出成功地估计3轴力。
Soft tactile sensors have been applied to robotic grippers for assembly. It is a challenging task to obtain contact information and object orientation using tactile sensors during grasping. Currently, the design of Hall-effect-based tactile sensors to perform such tasks is based on trial and error. We present a method of investigating the optimal geometrical design of a cylindrical soft sensor to increase its sensitivity. The finite element model of a soft fingertip was constructed in Abaqus with two design variables, i.e., hollow radius and magnet position. Then, the model was imported into Isight, with the maximisation of magnet displacement as the objective function. We found that the optimal design was at the boundary of the parameter design space. Four fingertips were fabricated with one intuitive, one optimal, and two optional sets of parameters. Experiments were performed, and object orientation was estimated by utilising linear approximation and a machine learning approach. Good agreements were achieved between optimisation and experiments. The results revealed that the estimated average error in object orientation was decreased by the optimised fingertip design. Furthermore, the 3-axis forces could successfully be estimated based on sensor outputs.