Nowadays, there is an urgent need for humanoid robots
containing
human finger-like electronic skins with mechanical endurance and tactile
perception. This study reports the development of an ionotronic skin-based
humanoid robot hand that can recognize objects precisely through finger
tapping or touching. The ionotronic skin is composed of a cytoskeleton-like
filament network structure and possesses mechanical properties highly
akin to human skins, including softness (Young’s modulus of
51 ± 15 MPa), toughness (1.6 ± 0.7 MJ m–3), and antifatigue-fracture ability. In addition, the i-skin functions
as a triboelectric nanogenerator with the ability to perceive the
triboelectric signals of an object when in contact with it. By combining
triboelectric sensing information, machine learning, and Internet
of Things techniques, the humanoid robot hand can accurately recognize
different materials among a diverse set of spherical objects and further
deliver them to the designated location. The high sorting success
rate of 97.2% in 600 tests of recognizing five types of spherical
objects, together with the outstanding mechanical and environmental
tolerance, allow such humanoid robot hands to be used for intelligent
sorting, automatic operation, and assembly in unmanned factories,
as well as for the classification of garbage and hazardous materials.