Scalable Tactile Sensing E-Skins Through Spatial Frequency Encoding

Most state-of-the-art tactile sensing arrays are not scalable to large numbers of sensing units due to their raster-scanned readout. This readout scheme results in a high degree of wiring complexity and a tradeoff between spatial and temporal resolution. In this thesis I present the use of spatial frequency encoding to develop asynchronous tactile sensor arrays with single-wire sensor transduction, no per-taxel electronics, and no scanning latency. I demonstrate this through two prototype devices, Neuroskin 1, which is developed using fabric-based e-textile materials, and Neuroskin 2, which is developed using fPCB. Like human skin, Neuroskin has a temporal resolution of 1 kHz and innate data compression where tactile data from an MxN Neuroskin is compressed into M+N values. Neuroskin 2 requires only four interface wires (regardless of its number of sensors) and can be easily scaled up through its development as an fPCB. To demonstrate the utility of the prototypes, Neuroskin was mounted onto a biomimetic robotic finger to palpate different textures and perform a texture discrimination task. Neuroskin 1 and 2 achieved 87% and 76% classification accuracy respectively in the texture discrimination task. Overall, the method of spatial-frequency encoding is theoretically scalable to support sensor arrays with thousands of sensing elements without latency, and the resolution of a Neuroskin array is only limited by the ADC sampling rate. Future tactile sensing systems can utilize the spatial frequency encoding architecture presented here to be dense, numerous, and flexible while retaining excellent temporal resolution

Towards high bandwidth communication systems: from Multi-Gbit/s over SI-POF in home scenarios to 5G cellular networks over SMF

The main objective of the thesis is to study high bandwidth communication systems for different network architectures from the end user at the in-home scenario to the service provider through the mobile cellular front-haul network. This is in parallel with the integration of power over fiber (PoF) technology in these systems.The present work received funds from the following Spanish and international projects: - Spanish Ministerio de Ciencia, Innovación y Universidades, “Tecnologías avanzadas inteligentes basadas en fibras ópticas/Advanced SMART technologies based on Optical Fibers (SMART-OF)”, grant no. RTI2018-094669-B-C32, within the coordinated project “Polymer Optical Fiber Disruptive Technologies (POFTECH)”. - Spanish Ministerio de Ciencia, Innovación y Universidades “LAboratorio de montaje, medida y CAracterización de antenas y dispositivos integrados fotónicos para comunicaciones 5G y de espacio en milimétricas, submilimétricas y THz (hasta 320 GHz) (LACA5G))”, grant no. EQC2018-005152-P. - Comunidad de Madrid “TElealimentación FotovoLtaica por fibra Óptica para medida y coNtrol en entornos extremos (TEFLON-CM)”, grant no. Y2018/EMT-4892. - Comunidad de Madrid “Sensores e Instrumentación en Tecnologías Fotónicas 2 (SINFOTON-2)”, grant no. P2018/NMT-4326, coordinated project with UC3MUPM- UAH-URCJ-CSIC. - H2020 European Union programme Bluespace project “Building the Use of Spatial Multiplexing 5G Networks Infrastructures and Showcasing Advanced Technologies and Networking Capabilities” grant nº.762055.Programa de Doctorado en Ingeniería Eléctrica, Electrónica y Automática por la Universidad Carlos III de MadridPresidente: Beatriz Ortega Tamarit.- Secretario: Guillermo Carpintero del Barrio.- Vocal: Óscar Esteban Martíne