Acquiring tactile data for the recognition of planar objects

Model-based recognition of objects by robot systems requires the acquisition of new data when the old data are insufficient in number or quality to uniquely identify the object(s) under investigation. In particular, the initial data set can often be interpreted in several, ambiguous ways. This paper proposes a framework for the acquisition of new data in the tactile domain, concentrating upon the case of two-dimensional objects that are modelled as polygons confined to a plane. A computationally feasible method is presented for finding linear paths for a tactile sensor so that effective data acquisition can occur. Also presented is a representation of the ambiguity present in the data, and how this ambiguity can be reduced and analysed.