TOWARDS IMPROVING TELETACTION IN TELEOPERATION TASKS USING VISION-BASED TACTILE SENSORS

Teletaction, the transmission of tactile feedback or touch, is a crucial aspect in the

field of teleoperation. High-quality teletaction feedback allows users to remotely manipulate

objects and increase the quality of the human-machine interface between the operator and

the robot, making complex manipulation tasks possible. Advances in the field of teletaction

for teleoperation however, have yet to make full use of the high-resolution 3D data provided

by modern vision-based tactile sensors. Existing solutions for teletaction lack in one or more

areas of form or function, such as fidelity or hardware footprint. In this thesis, we showcase

our research into a low-cost teletaction device for teleoperation that can utilize the real-time

high-resolution tactile information from vision-based tactile sensors, through both physical

3D surface reconstruction and shear displacement. We present our device, the Feelit, which

uses a combination of a pin-based shape display and compliant mechanisms to accomplish

this task. The pin-based shape display utilizes an array of 24 servomotors with miniature

Bowden cables, giving the device a resolution of 6x4 pins in a 15x10 mm display footprint.

Each pin can actuate up to 3 mm in 200 ms, while providing 80 N of force and 3 um of

depth resolution. Shear displacement and rotation is achieved using a compliant mechanism

design, allowing a minimum of 1 mm displacement laterally and 10 degrees of rotation. This

real-time 3D tactile reconstruction is achieved with the use of a vision-based tactile sensor,

the GelSight, along with an algorithm that samples the depth data and marker tracking to

generate actuator commands. With our device we perform a series of experiments including

shape recognition and relative weight identification, showing that our device has the potential

to expand teletaction capabilities in the teleoperation space.