  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.
