  In this paper, we present a methodology that uses an optical tactile sensor
for efficient tactile exploration of embedded objects within soft materials.
The methodology consists of an exploration phase, where a probabilistic
estimate of the location of the embedded objects is built using a Bayesian
approach. The exploration phase is then followed by a mapping phase which
exploits the probabilistic map to reconstruct the underlying topography of the
workspace by sampling in more detail regions where there is expected to be
embedded objects. To demonstrate the effectiveness of the method, we tested our
approach on an experimental setup that consists of a series of quartz beads
located underneath a polyethylene foam that prevents direct observation of the
configuration and requires the use of tactile exploration to recover the
location of the beads. We show the performance of our methodology using ten
different configurations of the beads where the proposed approach is able to
approximate the underlying configuration. We benchmark our results against a
random sampling policy.
