High performance 3D sound localization for surveillance applications

One of the key features of the human auditory system, is its nearly constant omni-directional sensitivity, e.g., the system reacts to alerting signals coming from a direction away from the sight of focused visual attention. In many surveillance situations where visual attention completely fails since the robot cameras have no direct line of sight with the sound sources, the ability to estimate the direction of the sources of danger relying on sound becomes extremely important. We present in this paper a novel method for sound localization in azimuth and elevation based on a humanoid head. The method was tested in simulations as well as in a real reverberant environment. Compared to state-of-the-art localization techniques the method is able to localize with high accuracy 3D sound sources even in the presence of reflections and high distortion

Study, Design and Fabrication of an Analogue VLSI Ormia-Ochracea-Inspired Delay Magnification System

This Thesis entails the development of a low-power delay magnification system inspired by the mechanical structure of the ear of the parasitoid fly Ormia Ochracea (O2). The proposed system is suitable as a preprocessing unit for binaural sound localization processors equipped with miniature acoustic sensors. The core of the Thesis involves the study of a delay magnification system based on the O2 sound localization mechanism and the design and testing of a low-power analog integrated circuit based on a proposed, novel delay magnification system inspired by Ormia Ochracea. The study of the delay magnification system based on the O2 sound localization mechanism is divided into two main parts. The first part studies in detail the delay magnification mechanism of the O2 ears. This study sheds light and tries to comprehend what mechanical parameters of the O2 ears are involved in the delay magnification process and how these parameters contribute to the magnification of the delay. The study presents the signal-flow-graph of the O2 system which can be used as a generic delay magnification model for the O2 ears. We also explore the effects of the tuning of the O2 system parameters on the output interaural time difference (ITD). Inspired by the study of the O2 system, in the second part of our study, we modify the O2 system using simpler building blocks and structure which can provide a delay magnification comparable to the original O2 system. We present a new binaural sound localization system suitable for small ITDs which utilizes the new modified O2 system, cochlea filter banks, cross-correlograms and our re-mapping algorithm and show that it can be used to encode very small input delay values that could not be resolved by means of a conventional binaural processor based on the Jeffress’s coincidence detection model. We evaluate the sound localization performance of our new binaural sound localization system for a single sound source and a sound source in the presence of a competing sound source scenario through detailed simulation. The performance of the proposed system is also explored in the presence of filter bandwidth variation and cochlea filter mismatch. After the study of the O2 delay magnification system, we present an analog VLSI chip which morphs the O2 delay magnification system. To determine what topology is the best morphing platform for the O2 system, we present the design and comparative performance of the O2 system when log-domain and gm-C second order weak-inversion filters are employed. The design of the proposed low-power modified O2 system circuit based on translinear loops is detailed. Its performance is evaluated through detailed simulation. Subsequently the Thesis proceeds with the design, fabrication and testing of the new chip based on the modified O2 circuit. The synthesis and testing of the proposed circuit using 0.35μm AMS CMOS process technology parameters is discussed. Detailed measured results confirm the delay magnification ability of the modified O2 circuit and its compliance with theoretical analysis explained earlier in the Thesis. The fabricated system is tuned to operate in the 100Hz to 1kHz frequency range, is able to achieve a delay gain of approximately 3.5 to 9.5 when the input (physical) delay ranges from 0μs to 20μs, and consumes 13.1μW with a 2 V power supply

Neuromorphic auditory computing: towards a digital, event-based implementation of the hearing sense for robotics

In this work, it is intended to advance on the development of the neuromorphic audio processing systems in robots through the implementation of an open-source neuromorphic cochlea, event-based models of primary auditory nuclei, and their potential use for real-time robotics applications. First, the main gaps when working with neuromorphic cochleae were identified. Among them, the accessibility and usability of such sensors can be considered as a critical aspect. Silicon cochleae could not be as flexible as desired for some applications. However, FPGA-based sensors can be considered as an alternative for fast prototyping and proof-of-concept applications. Therefore, a software tool was implemented for generating open-source, user-configurable Neuromorphic Auditory Sensor models that can be deployed in any FPGA, removing the aforementioned barriers for the neuromorphic research community. Next, the biological principles of the animals' auditory system were studied with the aim of continuing the development of the Neuromorphic Auditory Sensor. More specifically, the principles of binaural hearing were deeply studied for implementing event-based models to perform real-time sound source localization tasks. Two different approaches were followed to extract inter-aural time differences from event-based auditory signals. On the one hand, a digital, event-based design of the Jeffress model was implemented. On the other hand, a novel digital implementation of the Time Difference Encoder model was designed and implemented on FPGA. Finally, three different robotic platforms were used for evaluating the performance of the proposed real-time neuromorphic audio processing architectures. An audio-guided central pattern generator was used to control a hexapod robot in real-time using spiking neural networks on SpiNNaker. Then, a sensory integration application was implemented combining sound source localization and obstacle avoidance for autonomous robots navigation. Lastly, the Neuromorphic Auditory Sensor was integrated within the iCub robotic platform, being the first time that an event-based cochlea is used in a humanoid robot. Then, the conclusions obtained are presented and new features and improvements are proposed for future works.En este trabajo se pretende avanzar en el desarrollo de los sistemas de procesamiento de audio neuromórficos en robots a través de la implementación de una cóclea neuromórfica de código abierto, modelos basados en eventos de los núcleos auditivos primarios, y su potencial uso para aplicaciones de robótica en tiempo real. En primer lugar, se identificaron los principales problemas a la hora de trabajar con cócleas neuromórficas. Entre ellos, la accesibilidad y usabilidad de dichos sensores puede considerarse un aspecto crítico. Los circuitos integrados analógicos que implementan modelos cocleares pueden no pueden ser tan flexibles como se desea para algunas aplicaciones específicas. Sin embargo, los sensores basados en FPGA pueden considerarse una alternativa para el desarrollo rápido y flexible de prototipos y aplicaciones de prueba de concepto. Por lo tanto, en este trabajo se implementó una herramienta de software para generar modelos de sensores auditivos neuromórficos de código abierto y configurables por el usuario, que pueden desplegarse en cualquier FPGA, eliminando las barreras mencionadas para la comunidad de investigación neuromórfica. A continuación, se estudiaron los principios biológicos del sistema auditivo de los animales con el objetivo de continuar con el desarrollo del Sensor Auditivo Neuromórfico (NAS). Más concretamente, se estudiaron en profundidad los principios de la audición binaural con el fin de implementar modelos basados en eventos para realizar tareas de localización de fuentes sonoras en tiempo real. Se siguieron dos enfoques diferentes para extraer las diferencias temporales interaurales de las señales auditivas basadas en eventos. Por un lado, se implementó un diseño digital basado en eventos del modelo Jeffress. Por otro lado, se diseñó una novedosa implementación digital del modelo de codificador de diferencias temporales y se implementó en FPGA. Por último, se utilizaron tres plataformas robóticas diferentes para evaluar el rendimiento de las arquitecturas de procesamiento de audio neuromórfico en tiempo real propuestas. Se utilizó un generador central de patrones guiado por audio para controlar un robot hexápodo en tiempo real utilizando redes neuronales pulsantes en SpiNNaker. A continuación, se implementó una aplicación de integración sensorial que combina la localización de fuentes de sonido y la evitación de obstáculos para la navegación de robots autónomos. Por último, se integró el Sensor Auditivo Neuromórfico dentro de la plataforma robótica iCub, siendo la primera vez que se utiliza una cóclea basada en eventos en un robot humanoide. Por último, en este trabajo se presentan las conclusiones obtenidas y se proponen nuevas funcionalidades y mejoras para futuros trabajos

Biomimetic Based Applications

The interaction between cells, tissues and biomaterial surfaces are the highlights of the book "Biomimetic Based Applications". In this regard the effect of nanostructures and nanotopographies and their effect on the development of a new generation of biomaterials including advanced multifunctional scaffolds for tissue engineering are discussed. The 2 volumes contain articles that cover a wide spectrum of subject matter such as different aspects of the development of scaffolds and coatings with enhanced performance and bioactivity, including investigations of material surface-cell interactions