The sense of touch plays an important role in our life lives from perceiving the environment, grasping and manipulating objects to identifying, learning about and interacting with them. Compensating for the lack of touch with other human senses is difficult. For robotic systems that interact with dynamic environments and objects where, it is crucial to identify objects via their physical properties (such as surface texture, stiffness, a center of mass, and thermal conductivity) and to be able to safely operating them. However, these are difficult to achieve even With advanced vision techniques, which are often marred by occlusion, poor lighting situations, and a lack of precision. As an alternative, tactile sensing can simultaneously provide rich and direct feedback to the robotic systems. Moreover,The robots with the sense of touch need to learn continuously and efficiently from tactile experience and update their models of the objects and environment (Tactile Transfer knowledge). This tactile learning strategy keeps a robot stable and adaptable to respond to new stimuli receiving from the surrounding .