  Tactile sensing is used by humans when grasping to prevent us dropping
objects. One key facet of tactile sensing is slip detection, which allows a
gripper to know when a grasp is failing and take action to prevent an object
being dropped. This study demonstrates the slip detection capabilities of the
recently developed Tactile Model O (T-MO) by using support vector machines to
detect slip and test multiple slip scenarios including responding to the onset
of slip in real time with eleven different objects in various grasps. We
demonstrate the benefits of slip detection in grasping by testing two
real-world scenarios: adding weight to destabilise a grasp and using slip
detection to lift up objects at the first attempt. The T-MO is able to detect
when an object is slipping, react to stabilise the grasp and be deployed in
real-world scenarios. This shows the T-MO is a suitable platform for autonomous
grasping by using reliable slip detection to ensure a stable grasp in
unstructured environments. Supplementary video: https://youtu.be/wOwFHaiHuKY
