3D Printed Proprioceptive Soft Fluidic Actuators with graded porosity

Integration of both actuation and proprioception into the robot body enables sensorized soft actuators that can operate in a closed loop. An interesting class of actuators for this purpose are graded porous actuators, which can be mechanically programmed by their porosity (gradient) and sensorized by using a smart material. Three types of such actuators were 3D printed, namely: a bending finger, contractor, and a three DoF bending segment. Piezoresistive sensing was embedded by printing with a conductive thermoplastic elastomer. A challenge with piezoresistive sensors is to relate the change in resistance to deformation due to their inherent hysteresis and nonlinearity. In this work, an (estimated) Wiener-Hammerstein (WH) model was used to predict the deformation. The bending and contracting actuators showed that the linear and WH models could reach 70+% and 80+% fits, respectively. Thereby indicating that the deformation of the printed actuators could be estimated quite well. Similarly, the 3DoF bending segment showed similar values with the WH model reducing both the fitting and RMS error on average with 20+%. These results indicate that sensorized actuators based on 3D-printed soft structures with a porosity gradient can be mechanically programmed whereas strain estimation can be done using identified Wiener-Hammerstein models.