Numerical Simulation Assisted Design of a Soft-rigid-hybrid Tactile Finger for Surface Recognition
Haptic perception endows human being with the ability to perceive various objects and interact with surrounding environments. Although a variety of embedded-type tactile sensors have been designed, the mechanical characteristics and underlying dynamics behind the contact process is seldom explored, which significantly impairs the sensor's performances. In this work, we proposed a numerical simulation assisted design methodology to develop a soft-rigid-hybrid tactile finger, fully mimicking the structure and appearance of human fingers. The mechanism underlying the dynamic interactions gripping and contact scenarios was analyzed to reveal the stress distribution within the soft-rigid-hybrid finger, based on which the arrangement of sensing elements, i.e., the amount and the position and orientation, was determined. Further, the designed finger was fabricated and extended to construct a tactile gripper, with which robotic exploration on cylindrical objects was implemented. Excellent agreement of the tactile signals was found between simulation and experiment during the manipulation process. When combined with our developed perception model, it achieved an accuracy of 93.64% in the recognition of eight surfaces. In addition to contributing in the novel design of tactile grippers, this work provides a systematic methodology to design tactile sensors from the essential mechanics.
