Learning Latent Space Dynamics for Tactile Servoing

To achieve a dexterous robotic manipulation, we need to endow our robot with tactile feedback capability, i.e. the ability to drive action based on tactile sensing. In this paper, we specifically address the challenge of tactile servoing, i.e. given the current tactile sensing and a target/goal tactile sensing --memorized from a successful task execution in the past-- what is the action that will bring the current tactile sensing to move closer towards the target tactile sensing at the next time step. We develop a data-driven approach to acquire a dynamics model for tactile servoing by learning from demonstration. Moreover, our method represents the tactile sensing information as to lie on a surface --or a 2D manifold-- and perform a manifold learning, making it applicable to any tactile skin geometry. We evaluate our method on a contact point tracking task using a robot equipped with a tactile finger. A video demonstrating our approach can be seen in https://youtu.be/0QK0-Vx7WkIComment: Accepted to be published at the International Conference on Robotics and Automation (ICRA) 2019. The final version for publication at ICRA 2019 is 7 pages (i.e. 6 pages of technical content (including text, figures, tables, acknowledgement, etc.) and 1 page of the Bibliography/References), while this arXiv version is 8 pages (added Appendix and some extra details

Compressed Sensing for Tactile Skins

Whole body tactile perception via tactile skins offers large benefits for robots in unstructured environments. To fully realize this benefit, tactile systems must support real-time data acquisition over a massive number of tactile sensor elements. We present a novel approach for scalable tactile data acquisition using compressed sensing. We first demonstrate that the tactile data is amenable to compressed sensing techniques. We then develop a solution for fast data sampling, compression, and reconstruction that is suited for tactile system hardware and has potential for reducing the wiring complexity. Finally, we evaluate the performance of our technique on simulated tactile sensor networks. Our evaluations show that compressed sensing, with a compression ratio of 3 to 1, can achieve higher signal acquisition accuracy than full data acquisition of noisy sensor data.Comment: 8 pages, 4 figures, submitted to ICRA1

Tactile sensing chips with POSFET array and integrated interface electronics

This work presents the advanced version of novel POSFET (Piezoelectric Oxide Semiconductor Field Effect Transistor) devices based tactile sensing chip. The new version of the tactile sensing chip presented here comprises of a 4 x 4 array of POSFET touch sensing devices and integrated interface electronics (i.e. multiplexers, high compliance current sinks and voltage output buffers). The chip also includes four temperature diodes for the measurement of contact temperature. Various components on the chip have been characterized systematically and the overall operation of the tactile sensing system has been evaluated. With new design the POSFET devices have improved performance (i.e. linear response in the dynamic contact forces range of 0.01–3N and sensitivity (without amplification) of 102.4 mV/N), which is more than twice the performance of their previous implementations. The integrated interface electronics result in reduced interconnections which otherwise would be needed to connect the POSFET array with off-chip interface electronic circuitry. This research paves the way for CMOS (Complementary Metal Oxide Semiconductor) implementation of full on-chip tactile sensing systems based on POSFETs

Tactile sensing means for prosthetic limbs

An improved prosthetic device characterized by a frame and a socket for mounting on the stump of a truncated human appendage is described. Flexible digits extend from the distal end and transducers located within the digits act as sensing devices for detecting tactile stimuli. The transducers are connected through a power circuit with a slave unit supported by a strap and fixed to the stump. The tactile stimuli detected at the sensing devices are reproduced and applied to the skin of the appendage in order to stimulate the sensory organs located therein

GelSlim: A High-Resolution, Compact, Robust, and Calibrated Tactile-sensing Finger

This work describes the development of a high-resolution tactile-sensing finger for robot grasping. This finger, inspired by previous GelSight sensing techniques, features an integration that is slimmer, more robust, and with more homogeneous output than previous vision-based tactile sensors. To achieve a compact integration, we redesign the optical path from illumination source to camera by combining light guides and an arrangement of mirror reflections. We parameterize the optical path with geometric design variables and describe the tradeoffs between the finger thickness, the depth of field of the camera, and the size of the tactile sensing area. The sensor sustains the wear from continuous use -- and abuse -- in grasping tasks by combining tougher materials for the compliant soft gel, a textured fabric skin, a structurally rigid body, and a calibration process that maintains homogeneous illumination and contrast of the tactile images during use. Finally, we evaluate the sensor's durability along four metrics that track the signal quality during more than 3000 grasping experiments.Comment: RA-L Pre-print. 8 page