Retinomorphic sensor

[1] This is in contrast to conventional optical sensors such as charge coupled device (CCD) or complementary metal oxide semiconductor (CMOS) based sensors, which output a signal that increases with increasing light intensity.

Because they respond to movement only, retinomorphic sensors are hoped to enable faster tracking of moving objects than conventional image sensors, and have potential applications in autonomous vehicles, robotics, and neuromorphic engineering.

[2][3][4][5] The first so-called artificial retina were reported in the late 1980's by Carver Mead and his doctoral students Misha Mahowald, and Tobias Delbrück.

[6][7] These silicon-based sensors were based on small circuits involving differential amplifiers, capacitors, and resistors.

The sensors produced a spike and subsequent decay in output voltage in response to a step-change in illumination intensity.

This response is analogous to that of animal retinal cells, which in the 1920's were observed to fire more frequently when the intensity of light was changed than when it was constant.

[10] The term received wider use by Stanford Professor of Engineering Kwabena Boahen, and has since been applied to a wide range of event-driven sensing strategies.

[11] The word is analogous to neuromorphic, which is applied to hardware elements (such as processors) designed to replicate the way the brain processes information.

The first designs employed a differential amplifier which compared the input signal from of a conventional sensor (e.g. a phototransistor) to a filtered version of the output,[6] resulting in a gradual decay if the input was constant.

[1] A more compact design of retinomorphic sensor consists of just a photosensitive capacitor and a resistor in series.

The photosensitive capacitor is designed to have a capacitance which is a function of incident light intensity.

, is applied across this RC circuit it will act as a passive high-pass filter and all voltage will be dropped across the capacitor (i.e.

The excess charge will be forced to leave the plates, flowing either to ground or the input voltage terminal.

After the charge stops flowing the system returns to steady-state, all the voltage is once again dropped across the capacitor, and

The effective dimensions can be changed by using a bilayer material between the plates, consisting of an insulator and a semiconductor.

For this to be possible, the semiconductor must have a low electrical conductivity in the dark, and have an appropriate band gap to enable charge generation under illumination.

Conventional cameras capture every part of an image, regardless of whether it is relevant to the task.

This limitation could represent a performance bottleneck in the identification of high speed moving objects.

For this reason, retinomorphic sensors are hoped to enable identification of moving objects much more quickly than conventional real-time image analysis strategies.

[4] Retinomorphic sensors are therefore hoped to have applications in autonomous vehicles,[14][15] robotics,[16] and neuromorphic engineering.

[17] Retinomorphic sensor operation can be quantified using similar techniques to simple RC circuits, the only difference being that capacitance is not constant as a function of time in a retinomorphic sensor.

Using the product rule, we get the following general equation of retinomorphic sensor response:

, which increases with a power-law dependence on incident optical power density:

is linearly proportional to charge density, and capacitance is linearly proportional to charges on the plates for a given voltage, the capacitance of a retinomorphic sensor also has a power-law dependence on

is the change in voltage dropped across the capacitor as a result of turning on the light,

are defined as the voltage dropped across the capacitor and the capacitance, respectively, immediately after the light has been turned on.

Assuming the sensor has been held in the dark for sufficiently long before the light is turned on, the change in

With this parameter, the inverse ratio of peak height to input voltage can be written as follows:

This equation provides a simple method for evaluating the retinomorphic figure of merit from experimental data.

, of a retinomorphic sensor in response to a step change in light intensity from 0 to

Top: Step change in light intensity incident on sensor as a function of time. Middle: Form of output from conventional optical sensor as a function of time. Bottom: Form of output from retinomorphic sensor as a function of time.
Illustration of charge on the plates of a photosensitive capacitor in series with a resistor . Before time t 0 , the capacitor is in the dark and the charge on the plates is determined by C dark . At time t ≥ t 0 , the capacitor is under illumination and the capacitance changes to C light , resulting in the charge the plates can accommodate changing. The excess charge then flows on/off of the plates over a period of time determined by the resistor R.
Left: schematic cross-sectional diagram of photosensitive capacitor. Center: circuit diagram of retinomorphic sensor, with photosensitive capacitor at top. Right: Expected transient response of retinomorphic sensor to application of constant illumination.
Top: Illustration of transient response (output voltage as a function of ) of retinomorphic sensor in response to a step change in light intensity from 0 to , for increasing values of . Bottom: Illustration of how one can extract the retinomorphic figure of merit, , from experimental retinomorphic sensor data. By plotting the ratio of on the y-axis against on the x-axis, then fitting with a straight line, the gradient will yield .