Additive Manufacturing (AM) is gaining tremendous interest in the soft robotics field because of the possibility to manufacture i) soft structures, ii) structures with embedded sensors and actuators, and iii) structures made up of several materials characterized by different degrees of stiffness. All these advantages fit very well with soft robotic pillars such as bio-inspiration and design freedom. In the present work, Material Extrusion (MEX) technology, well known for being a low-cost AM technology, has been employed for the fabrication of soft robots with embedded sensors and actuators: a remarkable reduction in assembly tasks, manufacturing steps, manufacturing time, and cost has been achieved. First, 3D printed sensors have been manufactured and characterized: sensors based on piezoresistive and capacitive principle were studied and 3D printed, proving that they can be easily integrated into soft structures. The sensors have been characterized for the force (sensitivity of 0.088 mV/(V∙ g) ), temperature (sensitivity of 0.011 Ω/(°C) ) and liquid sensing (sensitivity of 0.79 pF/mm) showing performances comparable with sensors manufactured in a traditional way. Afterwards, several MEX-based soft robots have been proposed: three major actuation systems have been exploited (pneumatic, shape memory alloys, and electromagnetic) and several studies have been performed to correlate the final soft robot performance to MEX process parameters. A way to improve the adhesion between soft and stiff materials, analyzing several parameters, was discovered: an improvement of 48% in the adhesion (Young’s modulus) was achieved compared to the best result found in scientific literature. Moreover, a custom-made MEX setup for the silicone extrusion was developed and used in conjunction with a custom-made cartesian pick and place robot (CPPR) for the fabrication of silicone skin with embedded SMA actuators. Finally, a multi-material MEX machine was employed for the fabrication of a soft robotic finger equipped with a ...
Additive Manufacturing for soft robotics and sensors
2022-01-01
doi:10.60576/poliba/iris/stano-gianni_phd2022
Theses
Electronic Resource
English