<p dir="ltr">Teletaction, the transmission of tactile feedback or touch, is a crucial aspect in the</p><p dir="ltr">field of teleoperation. High-quality teletaction feedback allows users to remotely manipulate</p><p dir="ltr">objects and increase the quality of the human-machine interface between the operator and</p><p dir="ltr">the robot, making complex manipulation tasks possible. Advances in the field of teletaction</p><p dir="ltr">for teleoperation however, have yet to make full use of the high-resolution 3D data provided</p><p dir="ltr">by modern vision-based tactile sensors. Existing solutions for teletaction lack in one or more</p><p dir="ltr">areas of form or function, such as fidelity or hardware footprint. In this thesis, we showcase</p><p dir="ltr">our research into a low-cost teletaction device for teleoperation that can utilize the real-time</p><p dir="ltr">high-resolution tactile information from vision-based tactile sensors, through both physical</p><p dir="ltr">3D surface reconstruction and shear displacement. We present our device, the Feelit, which</p><p dir="ltr">uses a combination of a pin-based shape display and compliant mechanisms to accomplish</p><p dir="ltr">this task. The pin-based shape display utilizes an array of 24 servomotors with miniature</p><p dir="ltr">Bowden cables, giving the device a resolution of 6x4 pins in a 15x10 mm display footprint.</p><p dir="ltr">Each pin can actuate up to 3 mm in 200 ms, while providing 80 N of force and 3 um of</p><p dir="ltr">depth resolution. Shear displacement and rotation is achieved using a compliant mechanism</p><p dir="ltr">design, allowing a minimum of 1 mm displacement laterally and 10 degrees of rotation. This</p><p dir="ltr">real-time 3D tactile reconstruction is achieved with the use of a vision-based tactile sensor,</p><p dir="ltr">the GelSight, along with an algorithm that samples the depth data and marker tracking to</p><p dir="ltr">generate actuator commands. With our device we perform a series of experiments including</p><p dir="ltr">shape recognition and relative weight identification, showing that our device has the potential</p><p dir="ltr">to expand teletaction capabilities in the teleoperation space.</p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/25727013 |
| Date | 01 May 2024 |
| Creators | Oscar Jia Jun Yu (18391263) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/thesis/TOWARDS_IMPROVING_TELETACTION_IN_TELEOPERATION_TASKS_USING_VISION-BASED_TACTILE_SENSORS/25727013 |
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