Deep Tactile Sensing in Deep Steppes
Recent news: November, 2022 – Recent Human – Robot Interaction Paper https://authors.elsevier.com/a/1g8pN3HdG3hSDN (free access) and PI is now IEEE Senior Member, “NU works because we do” Tactile lab at NU Open Days; May 2022 – The tactile team meets the President of Kazakhstan (@tengrinews.kz)
Our Instagram page: @tactilelab
1.1. PhotoElasticFinger: Robot Tactile Fingertip Based on Photoelastic Effect
The sensor measures the force based on the PhotoElastic effect observed in the silicone matter. The polarized light within the silicone rubber is subjected to the phase-shift when the silicone is pressed. Force estimated is proportional to the light received by the camera. This paper has been published in Sensors as part of the Special Issue Advances in Bio-Inspired Skin-Like Sensor Technologies, 2022.
3. Vibro-tactile slip, slide, texture detection
Slip detection – oriented research direction that mainly focuses on understanding how to detect and vibrations that appear during mutual movements between the robot end-effector and an object. We created the sensing system described in Vibro-tactile sensor, IEEE SII2019, Paris
3.1 Deep Vibro-Tactile Slip Detection and Texture Identification
The state-of-the-art LSTM, FFN, CNN architectures were applied to detect slippage and identify various textures – journal paper (Massalim et al, mdpi sensors, 2020).
3.2 Tactile Sensor for Contact Detection and Force Sensing via Vibrations
The main idea behind the project is the phenomenon of change in vibration propagation patterns depending on the grip properties. The sensor is used for detecting whether the contact has happened or not. This paper has been published in Sensors as part of the Special Issue Advances in Bio-Inspired Skin-Like Sensor Technologies, 2022.
Soft objects are increasing their attention in manipulation – oriented papers. We developed a pipeline to detect soft and rigid objects using a tactile sensing array – conference IEEE SII2019, Paris.
4.1 Granular Object Recognition
Soft objects can be crunchy inside. In this connection, we can detect various soft objects based on their not only softness but also mechanical vibrations. We applied machine learning methods to detect a foreign body in a soft object (Syrymova et al, AIM2020, Boston).
5. Haptic Illusions
Haptics – oriented research direction, in which we aim in developing new combinations of haptic and visual illusions. We show how pseudoo- and haptic illusions can be used to trick a human brain in perceiving soft objects with different stiffness.
RA-L + ICRA2020, Paris
Submitted to IROS2021
6. Negative Stiffness Structures
Structures design – related research direction that investigates how artificial mezo-structures with negative stiffness properties can be used as active tactile surfaces.
Analytical modelling of a Negative Stiffness Honeycomb is described in IOP Smart Materials and Structures paper.
6.1 Linear Negative Stiffness Honeycomb Actuator with Integrated Force Sensing
Application of Negative Stiffness Structures in actuators is described in our AIM2020, Boston conference paper by Galimzhanov et al.
Robot control design for HRI. This research direction investigates how Robot arms can be used as collaborators.
This work is done in collaboration with Matteo Rubagotti’s RCLlab
8. Augmented Reality and Haptic Teleoperation
This paper was submitted to RA-L, 2021