Soft Tactile Sensing for Object Classification and Fine Grasping Adjustment Using a Pneumatic Hand With an Inflatable Palm

作者：Manjia Su, Dongyu Huang, Yisheng Guan, Chaoqun Xiang, Haifei Zhu, Zhi Liu · 发表于：IEEE Transactions on Industrial Electronics · 年份：2023 · DOI：10.1109/tie.2023.3279554 · 被引用次数：20 · 研究领域：Tactile and Sensory Interactions、Robot Manipulation and Learning、Soft Robotics and Applications

Power grasps and fine manipulations with a robotic hand usually require dexterity in the fingers and a rich tactile function. In this article, we propose a novel soft hand with a tactile sensing function and investigate how tactile information can be used to perform object classification and fine grasping adjustments. We first developed a pneumatically driven soft hand with an inflatable palm and bendable fingers, where a TacTip-type sensor and several Flex sensors were integrated. The inflatable palm can not only significantly improve grasping but also object sensing. Based on the perspective projection model of a camera, a 3-D reconstruction algorithm for the deformed surface of a soft palm is presented. A spatial characterization of geometric information regarding objects based on sensing information from the palm and fingers was deduced and analyzed. A classifier was designed for object classification. Finally, a control method for the fine adjustment of grasps based on tactile sensing information was presented and verified using a series of grasps of different objects with a soft hand. The object classification and contact state sensed by the soft tactile sensors can be used for grasp planning and manipulation control with the soft hand.