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In Italy, more than 1600 caves are classified as cryo-caves, due to the presence of multiyear snow, firn, or ice. Previous regional studies show that at least 10% of such caves can be included in the ice cave classification, because they have a perennial ice deposit. However, the strong differences in the karstological characteristics of the Italian geology allows having not only caves formed in limestone, dolomite, or marble terrains, in the Alps as well as in the Apennines, but also in lava tubes on the Etna Volcano. Four ice caves are reported here as examples of three different mechanisms of ice cave formation and evolution. From Grigna Settentrionale, central Alps, a vertical shaft ice deposit mainly formed by dripping water was studied by chemical and stable isotope record. Two high altitude ice caves originated by snow accumulation and ice dipping were studied in the Canin massif, southeastern Alps, and a lava tube from Etna volcano was studied for its ice dynamics and air-circulation mechanisms. These four examples provide important data on the evolution of such ice deposits, giving a first clue on their progressive reduction under recent climate forcing.

Starting from the user’s requirements previously defined, a new soft robotics approach was chosen and developed in order to overcome the criticalities arisen in the analysis of the state of the art. One of the key points of soft robotics is biomimicry: in place of heavy, rigid and noisy motors, artificial muscles are in charge of the movement of the soft structure, allowing a number of degrees of freedom unthinkable with traditional mechanics. The shift from hard to soft robotics brings the focus on materials: actuating and sensing devices are embedded in the material itself, which turns out to be smart. In particular, the attention was focused on Electroactive Polymers (EAPs): these polymeric materials work as transducers, converting electrical inputs into mechanical outputs, and vice versa. After an extensive material selection procedure among all the EAPs solutions currently available, Dielectric Elastomers (DEs) emerged as the most suitable materials for the intended application and a mathematical model of their electro-mechanical behavior is presented. The control of the hand exoskeleton is addressed in this section. Its objective is to help the astronaut accomplish the tasks he has to perform. The entire control system is composed of four phases: the recognition of the astronaut’s will (detect and distinguish the different movements), the control strategy, the enhancement of these movements and the measure of the actual position and force. The final measure system was implemented focusing on redundancy, safety control and to assure minimum performances also in off-nominal conditions.