Adaptive Photoreceptor with Wide Dynamic Range

We describe a photoreceptor circuit that can be used in massively parallel analog VLSI silicon chips, in conjunction with other local circuits, to perform initial analog visual information processing. The receptor provides a continuous-time output that has low gain for static signals (including circuit mismatches), and high gain for transient signals that are centered around the adaptation point. The response is logarithmic, which makes the response to a fixed image contrast invariant to absolute light intensity. The 5-transistor receptor can be fabricated in an area of about 70 μm by 70 μm in a 2-μm single-poly CMOS technology. It has a dynamic range of 1-2 decades at a single adaptation level, and a total dynamic range of more than 6 decades. Several technical improvements in the circuit yield an additional 1-2 decades dynamic range over previous designs without sacrificing signal quality. The lower limit of the dynamic range, defined arbitrarily as the illuminance at which the bandwidth of the receptor is 60 Hz, is at approximately 1 lux, which is the border between rod and cone vision and also the limit of current consumer video cameras. The receptor uses an adaptive element that is resistant to excess minority carrier diffusion. The continuous and logarithmic transduction process makes the bandwidth scale with intensity. As a result, the total A.C. RMS receptor noise is constant, independent of intensity. The spectral density of the noise is within a factor of two of pure photon shot noise and varies inversely with intensity. The connection between shot and thermal noise in a system governed by Boltzman statistics is beautifully illustrated

An on/off spiking photoreceptor for adaptive ultrafast/ultrawide dynamic range vision chips

Published versio

Adaptive ON-OFF spiking photoreceptor

Accepted versio

Exploiting Pull-In/Pull-Out Hysteresis in Electrostatic MEMS Sensor Networks to Realize a Novel Sensing Continuous-Time Recurrent Neural Network

The goal of this paper is to provide a novel computing approach that can be used to reduce the power consumption, size, and cost of wearable electronics. To achieve this goal, the use of microelectromechanical systems (MEMS) sensors for simultaneous sensing and computing is introduced. Specifically, by enabling sensing and computing locally at the MEMS sensor node and utilizing the usually unwanted pull in/out hysteresis, we may eliminate the need for cloud computing and reduce the use of analog-to-digital converters, sampling circuits, and digital processors. As a proof of concept, we show that a simulation model of a network of three commercially available MEMS accelerometers can classify a train of square and triangular acceleration signals inherently using pull-in and release hysteresis. Furthermore, we develop and fabricate a network with finger arrays of parallel plate actuators to facilitate coupling between MEMS devices in the network using actuating assemblies and biasing assemblies, thus bypassing the previously reported coupling challenge in MEMS neural networks

Miniature curved artificial compound eyes.

International audienceIn most animal species, vision is mediated by compound eyes, which offer lower resolution than vertebrate single-lens eyes, but significantly larger fields of view with negligible distortion and spherical aberration, as well as high temporal resolution in a tiny package. Compound eyes are ideally suited for fast panoramic motion perception. Engineering a miniature artificial compound eye is challenging because it requires accurate alignment of photoreceptive and optical components on a curved surface. Here, we describe a unique design method for biomimetic compound eyes featuring a panoramic, undistorted field of view in a very thin package. The design consists of three planar layers of separately produced arrays, namely, a microlens array, a neuromorphic photodetector array, and a flexible printed circuit board that are stacked, cut, and curved to produce a mechanically flexible imager. Following this method, we have prototyped and characterized an artificial compound eye bearing a hemispherical field of view with embedded and programmable low-power signal processing, high temporal resolution, and local adaptation to illumination. The prototyped artificial compound eye possesses several characteristics similar to the eye of the fruit fly Drosophila and other arthropod species. This design method opens up additional vistas for a broad range of applications in which wide field motion detection is at a premium, such as collision-free navigation of terrestrial and aerospace vehicles, and for the experimental testing of insect vision theories

Taking Inspiration from Flying Insects to Navigate inside Buildings

These days, flying insects are seen as genuinely agile micro air vehicles fitted with smart sensors and also parsimonious in their use of brain resources. They are able to visually navigate in unpredictable and GPS-denied environments. Understanding how such tiny animals work would help engineers to figure out different issues relating to drone miniaturization and navigation inside buildings. To turn a drone of ~1 kg into a robot, miniaturized conventional avionics can be employed; however, this results in a loss of their flight autonomy. On the other hand, to turn a drone of a mass between ~1 g (or less) and ~500 g into a robot requires an innovative approach taking inspiration from flying insects both with regard to their flapping wing propulsion system and their sensory system based mainly on motion vision in order to avoid obstacles in three dimensions or to navigate on the basis of visual cues. This chapter will provide a snapshot of the current state of the art in the field of bioinspired optic flow sensors and optic flow-based direct feedback loops applied to micro air vehicles flying inside buildings