Ergodic tactile estimation of defects

In this work, an algorithm for estimating the position and Gaussian-like shape of an unknown number of defects on a given flat surface is developed. A natural behavior for exploring/exploiting possible defects using the ergodic control theory for trajectory planning has been achieved. Informative tactile measurements along with the end-effector/sensor position related have been used to provide a posterior belief using the Gaussian Mixture Model technique, and a Kullback-Leibler divergence-dependent constraint has been designed to enhance the accuracy of the estimation.