  This paper presents a novel framework for integration of vision and tactile
sensing by localizing tactile readings in a visual object map. Intuitively,
there are some correspondences, e.g., prominent features, between visual and
tactile object identification. To apply it in robotics, we propose to localize
tactile readings in visual images by sharing same sets of feature descriptors
through two sensing modalities. It is then treated as a probabilistic
estimation problem solved in a framework of recursive Bayesian filtering.
Feature-based measurement model and Gaussian based motion model are thus built.
In our tests, a tactile array sensor is utilized to generate tactile images
during interaction with objects and the results have proven the feasibility of
our proposed framework.
