Integrating Visuo-tactile Sensing with Haptic Feedback for Teleoperated Robot Manipulation

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.