  Telerobotics enables humans to overcome spatial constraints and allows them
to physically interact with the environment in remote locations. However, the
sensory feedback provided by the system to the operator is often purely visual,
limiting the operator's dexterity in manipulation tasks. In this work, we
address this issue by equipping the robot's end-effector with high-resolution
visuotactile GelSight sensors. Using low-cost MANUS-Gloves, we provide the
operator with haptic feedback about forces acting at the points of contact in
the form of vibration signals. We propose two different methods for estimating
these forces; one based on estimating the movement of markers on the sensor
surface and one deep-learning approach. Additionally, we integrate our system
into a virtual-reality teleoperation pipeline in which a human operator
controls both arms of a Tiago robot while receiving visual and haptic feedback.
We believe that integrating haptic feedback is a crucial step for dexterous
manipulation in teleoperated robotic systems.
