Contact modelling and tactile data processing for robot skin
This work addresses computational challenges in tactile sensing for robots interacting with humans or the environment, but appears incremental as it builds on existing methods and datasets.
The paper tackled the problem of extracting contact information from tactile sensing for robot skin by analyzing classical solutions for distributed inverse contact problems, and characterized algorithm performance using a freely available dataset and data from robot skin surfaces.
Tactile sensing is a key enabling technology to develop complex behaviours for robots interacting with humans or the environment. This paper discusses computational aspects playing a significant role when extracting information about contact events. Considering a large-scale, capacitance-based robot skin technology we developed in the past few years, we analyse the classical Boussinesq-Cerruti's solution and the Love's approach for solving a distributed inverse contact problem, both from a qualitative and a computational perspective. Our contribution is the characterisation of algorithms performance using a freely available dataset and data originating from surfaces provided with robot skin.