In robotic manipulation and grasping tasks, visual sensing is commonly used to gather information about external object properties, including position, shape, and orientation. However, in unstructured environments where occlusions and low visibility may occur, visual information alone is insufficient for providing the necessary tactile feedback. In contrast, tactile sensors offer critical information regarding an object's pose, texture, and force, thereby enhancing a robotic system's ability to grasp and manipulate objects with greater precision. These sensors enable robots to perform tasks such as delicate grasping, shape recognition, and texture detection. This thesis work, developed at the Institute of Robotics and Mechatronics (RMC) of the German Aerospace Center (DLR), addresses the pose estimation problem of both the fingertips of robotic grippers, as well as the objects being grasped.