  Traditional methods for achieving high localization accuracy on tactile
sensors usually involve a matrix of miniaturized individual sensors distributed
on the area of interest. This approach usually comes at a price of increased
complexity in fabrication and circuitry, and can be hard to adapt to non-planar
geometries. We propose a method where sensing terminals are embedded in a
volume of soft material. Mechanical strain in this material results in a
measurable signal between any two given terminals. By having multiple terminals
and pairing them against each other in all possible combinations, we obtain a
rich signal set using few wires. We mine this data to learn the mapping between
the signals we extract and the contact parameters of interest. Our approach is
general enough that it can be applied with different transduction methods, and
achieves high accuracy in identifying indentation location and depth. Moreover,
this method lends itself to simple fabrication techniques and makes no
assumption about the underlying geometry, potentially simplifying future
integration in robot hands.
