  Endowing robots with tactile capabilities opens up new possibilities for
their interaction with the environment, including the ability to handle fragile
and/or soft objects. In this work, we equip the robot gripper with low-cost
vision-based tactile sensors and propose a manipulation algorithm that adapts
to both rigid and soft objects without requiring any knowledge of their
properties. The algorithm relies on a touch and slip detection method, which
considers the variation in the tactile images with respect to reference ones.
We validate the approach on seven different objects, with different properties
in terms of rigidity and fragility, to perform unplugging and lifting tasks.
Furthermore, to enhance applicability, we combine the manipulation algorithm
with a grasp sampler for the task of finding and picking a grape from a bunch
without damaging~it.
