In this paper, a novel tactile sensing mechanism for soft robotic fingers is proposed. Inspired by the proprioception mechanism found in mammals, the proposed approach infers tactile information from a strain sensor attached on the finger's tendon. We perform experiments to test the tactile sensing capabilities of the proposed structures, and our results indicate this method is capable of palpating texture and stiffness in both abduction and flexion contact. Under systematic cross validation, the proposed system achieved 100% and 99.7% accuracy in texture and stiffness discrimination respectively, which validate the viability of this approach. Furthermore, we use statistics tools to determine the significance of various features extracted for classification.
翻译:在本文中,提出了一个新的软机器人手指触摸机制。在哺乳动物发现自行感知机制的启发下,拟议办法从指角上附着的菌株感应器中推断出触摸信息。我们进行了实验,以测试拟议结构的触摸感应能力,我们的结果表明,这一方法能够在绑架和弹性接触中传递纹理和僵硬性。在系统交叉验证下,拟议办法在纹理和僵硬性歧视方面分别实现了100%和99.7%的准确性,这证实了这一方法的可行性。此外,我们使用统计工具来确定为分类而提取的各种特征的重要性。