A tactile sensor for a robot and a gripper, the tactile sensor comprising: an elastically deformable element including an outer impact surface and an undersurface having pins, ridges, or both, each undersurface pin or ridge includes a mark, and the elastically deformable element is attached to the gripper; a camera positioned in a cavity of the gripper to capture images of the marks; a memory having stored data including image data of sets of prelearned positions of marks with corresponding prelearned patterns of forces, each set of prelearned positions of marks corresponds to a prelearned pattern of forces; an image processor operatively connected to the camera and the memory, is configured to: detect positions of the marks in captured images; compare the detected positions of the marks in the captured images to the sets of the prelearned positions of marks, based on a distance function, to determine a quality of match value for each set of the prelearned positions of marks; determine a best quality matched prelearned pattern of forces using a user selected best matching function, that is applied to the determined quality of match values, to calculate a best matching set of the prelearned positions of marks and the corresponding best quality matched prelearned pattern of forces; identify a pattern of forces acting on the elastically deformable element based on the determined best matched prelearned pattern of forces; and output the identified pattern of forces to initiate a gripper action for the gripper based on the identified pattern of forces acting on the deformable element. an elastically deformable element including an outer impact surface and an undersurface having pins, ridges, or both, each undersurface pin or ridge includes a mark, and the elastically deformable element is attached to the gripper; a camera positioned in a cavity of the gripper to capture images of the marks; a memory having stored data including image data of sets of prelearned positions of marks with corresponding prelearned patterns of forces, each set of prelearned positions of marks corresponds to a prelearned pattern of forces; an image processor operatively connected to the camera and the memory, is configured to: detect positions of the marks in captured images; compare the detected positions of the marks in the captured images to the sets of the prelearned positions of marks, based on a distance function, to determine a quality of match value for each set of the prelearned positions of marks; determine a best quality matched prelearned pattern of forces using a user selected best matching function, that is applied to the determined quality of match values, to calculate a best matching set of the prelearned positions of marks and the corresponding best quality matched prelearned pattern of forces; identify a pattern of forces acting on the elastically deformable element based on the determined best matched prelearned pattern of forces; and output the identified pattern of forces to initiate a gripper action for the gripper based on the identified pattern of forces acting on the deformable element. detect positions of the marks in captured images; compare the detected positions of the marks in the captured images to the sets of the prelearned positions of marks, based on a distance function, to determine a quality of match value for each set of the prelearned positions of marks; determine a best quality matched prelearned pattern of forces using a user selected best matching function, that is applied to the determined quality of match values, to calculate a best matching set of the prelearned positions of marks and the corresponding best quality matched prelearned pattern of forces; identify a pattern of forces acting on the elastically deformable element based on the determined best matched prelearned pattern of forces; and output the identified pattern of forces to initiate a gripper action for the gripper based on the identified pattern of forces acting on the deformable element.