This book introduces the challenges of robotic tactile perception and task understanding and
describes an advanced approach based on machine learning and sparse coding techniques. Further
a set of structured sparse coding models is developed to address the issues of dynamic tactile
sensing. The book then proves that the proposed framework is effective in solving the problems
of multi-finger tactile object recognition multi-label tactile adjective recognition and
multi-category material analysis which are all challenging practical problems in the fields of
robotics and automation. The proposed sparse coding model can be used to tackle the challenging
visual-tactile fusion recognition problem and the book develops a series of efficient
optimization algorithms to implement the model. It is suitable as a reference book for graduate
students with a basic knowledge of machine learning as well as professional researchers
interested in robotic tactile perception and understanding and machine learning.
