Za spremljanje okolja in krmarjenje po resničnem svetu mora biti robot sposoben pridobiti slike in meritve okolja v različnih svetlobnih pogojih v ozadju. V zadnjih letih si raziskovalci in inženirji po vsem svetu prizadevajo za razvoj vedno bolj naprednih senzorjev za integracijo v robote, nadzorne sisteme ali druge naprave, ki lahko zaznavajo njihovo okolico.
Po poročanju Memes Consulting so raziskovalci s politehnične univerze v Hong Kongu, univerze v Pekingu, univerze Yonsei in univerze Fudan nedavno razvili novo vrsto senzorja bioničnega vida, ki uporablja mehanizem, ki umetno simulira delovanje mrežnice in se lahko uporablja pri različnih zbranih podatkih. pod svetlobnimi pogoji. Ta bionični senzor vida temelji na fototranzistorjih iz molibdenovega disulfida.
Fotografija niza senzorjev biomimetičnega vida (levo); shematska struktura enote vidnega senzorja in slika optičnega mikroskopa (desno)
"Our research team started work on optoelectronic memory five years ago," said Yang Chai, one of the researchers who developed the vision sensor. "This emerging device can output light-dependent and history-dependent signals, enabling image integration. , Weak signal accumulation, spectral analysis and other complex image processing functions, the multi-functional integration of sensing, data storage and data processing into one device."
Leta 2018 so Yang Chai in njegovi sodelavci objavili prvi članek o optoelektronskem pomnilniku, v katerem so predstavili uporovno preklopno pomnilniško napravo, ki lahko izvaja zaznavanje svetlobe in logične operacije. Leto pozneje je ekipa predstavila novo vrsto fotorezistivnega pomnilnika z naključnim dostopom s tremi različnimi funkcijami. Natančneje, nova naprava lahko zaznava okolje, shranjuje informacije v pomnilnik in izvaja nevromorfne vizualne predprocesorske operacije.
"We studied the concepts of near-sensor and in-sensor computing paradigms in 2020 and published our views in the field." Yang Chai continued, "This new research on biomimetic vision sensors builds on our On top of all previous efforts."
The intensity of ambient natural light varies widely, with a total range of 280 dB. When the human retina senses external light signals, it adjusts the light sensitivity of its photoreceptors (i.e., rods and cones) according to the strength of the signal. This ultimately enables the human eye to gradually adapt to varying levels of lighting, allowing it to see clearly in both dark and bright environments, an ability known as "visual adaptation."
"For example, when you enter a dark cinema from a bright hall, you can hardly see anything at first, but after a while in the cinema, it becomes easier to see things," explains Yang Chai. "This phenomenon is called scotopic adaptation. Conversely, if you go from a dark movie theater to a sunny outdoors, you'll feel very dazzled at first, and it takes a while to get used to seeing what's going on around you. The process The opposite of dark adaptation is called photopic adaptation."
The main goal of Yang Chai and his colleagues' recent work is to build a vision sensor inspired by the structure and function of the human retina. To do this, they first started by studying the human retina and then tried to design perceptual strategies that would allow them to artificially simulate visual adaptations.
Najsodobnejši{0}}-- senzorji slik, ki temeljijo na tehnologiji CMOS, imajo običajno omejen dinamični razpon 70 dB. Vendar je ta dinamični razpon veliko ožji od svetlobnega razpona naravnih prizorov (280 dB).
"To achieve visual perception over a wide range of light intensities, researchers have explored the use of controlled optical apertures, liquid lenses, adjustable exposure times, and denoising algorithms in post-processing," said Yang Chai. "However, these Methods often require complex hardware and software resources."
Dark and light adaptation of biomimetic vision sensor arrays. (a) Schematic of the dark adaptation test: recognition of low-light images using an 8 x 8 pixel array in a dark environment. (b) Schematic diagram of light adaptation test: recognition of high-illuminance images using an 8 x 8 pixel array in a bright environment. (c) Dark adaptation process to identify the "8" pattern. (d) The photoadaptation process to identify the "8" pattern.
Optoelektronske naprave s svetlo-prilagodljivim vidom in širokim razponom zaznavanja na senzoričnih terminalih bi lahko imele zelo dragocene aplikacije. Na primer, lahko pomagajo izboljšati učinkovitost orodij za računalniški vid, zmanjšajo zapletenost strojne opreme, ki je potrebna za izdelavo robotov ali drugih zaznavalnih sistemov, in izboljšajo natančnost sistemov za prepoznavanje slik.
Čeprav so druge raziskovalne skupine v preteklosti razvile optoelektronske naprave, ki se lahko prilagajajo različnim svetlobnim razmeram. Vendar pa lahko večina predhodno dokazanih naprav le posnema mehanizem prilagajanja svetlobi mrežnice. Doslej se je izkazalo, da je proces prilagajanja na temo težje simulirati.
"There is still a long way to go to fully replicate the visual adaptation function of the retina," explains Yang Chai. "To achieve this, we designed a phototransistor-based vision sensor using ultra-thin semiconductors that can The degree of dark adaptation and light adaptation in the same device was controlled by applying different gate voltages. In this way, we simulated photoreceptors and horizontal cells in the retina and successfully achieved a sensing range of 199 dB. Vision-adaptive devices in biomimetic sensors."
Umetna simulacija fotoreceptorjev in horizontalnih celic v mrežnici za vizualno prilagajanje (prilagoditev na temo in prilagajanje svetlobi)
Biomimetični senzor za vid, ki so ga razvili Yang Chai in njegovi sodelavci, temelji na fototranzistorjih, izdelanih iz ultra tankega polprevodniškega materiala, znanega kot molibdenov disulfid. Fototranzistorji, ki so jih uporabili, imajo več stanj lovišča naboja, ki lahko ujamejo ali sprostijo elektrone znotraj kanala pri različnih napetostih vrat.
Ultimately, these states allow researchers to dynamically tune the conductance of their devices. This, in turn, allowed them to artificially simulate the dark- and light-adaptive mechanisms of the human retina, thereby expanding the range of their sensor's perception of different lighting conditions.
"Our bionic vision sensor has several advantages and features," said Yang Chai. "First, the visual adaptation function is implemented in a single device, which greatly reduces the footprint. Second, multiple functions can be implemented on a single device. , including light sensing, memory, and processing. Finally, dark and light adaptation under different light intensities can be achieved by controlling its gate voltage."
Yang Chai in njegovi sodelavci so ocenili bionični senzor vida v seriji testov in ugotovili, da lahko učinkovito posnema delovanje človeške mrežnice in dosega izjemne rezultate tako pri prilagajanju na temo kot na svetlobo. Poleg tega ima bistveno večji zaznavni razpon (199 dB) v primerjavi s prej predlaganimi rešitvami.
"Our vision sensor can enrich machine vision functions, reduce hardware complexity, and achieve high image recognition efficiency," said Yang Chai, "All these advantages are available in areas such as autonomous driving, face recognition, and industrial manufacturing in complex lighting environments. great application prospects."
V prihodnjih študijah nameravajo raziskovalci še izboljšati zmogljivost senzorja vida, hkrati pa ga uporabiti za izdelavo velikih-sistemov, sestavljenih iz nizov senzorjev. V idealnem primeru želijo to vrsto senzorjev zgraditi na fleksibilnem ali hemisferičnem substratu, da bi omogočili širše vidno polje.
"One area that needs improvement is the adaptation time of our vision sensor, as it is still not enough to support machine vision applications." Yang Chai added, "Our goal is to reduce the adaptation time to the microsecond level. In addition, the vision sensor array scale Further improvements are also needed. Our near-term target for array size is greater than 100 x 100 pixels. Finally, the heterogeneous integration of vision sensors and post-processing units, including silicon-based control circuits, is a very important step toward practical applications."
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